Soil erosion is one of the most important environmental problems which can have various negative consequences, such as land degradation affecting the sustainable development and the agricultural production, especially for developing countries like Tunisia. Moreover, soil erosion is a major problem around the world because of its effects on soil fertility by nutriment loss and siltation in water bodies. Apart from this, soil erosion by water is the most serious type of land loss in several regions both locally and globally. This study evaluated regional soil erosion risk through the derivation of appropriate factors, using the Revised Universal Soil Loss Equation (RUSLE), which was applied to establish a soil erosion risk map of the whole Tunisian territory and to identify the vulnerable areas of the country. RUSLE model take into account all the factors playing a major role in erosion processes, namely the erodibility of soils, topography, land use, rainfall erosivity and anti-erosion farming practices. The equation is thus implemented under Geographic Information System (GIS) “Arc GIS Desktop”. The results indicated that Tunisia has a serious risk of soil water erosion, showing that 6.43% of the total area of the country is affected by a very high soil loss rate estimated at more than 30 t/ha/year and 4.20% are affected by high mean annual soil loss ranging from 20 to 30 t/ha/year. The most eroded areas were identified in west southern, central and western parts of the country. The spatial erosion map can be used as a decision support document to guide decision-makers towards better land management and provide the opportunity to develop management strategies for soil erosion prevention and control in the global scale of Tunisia.

Habitat quality has great significance for regional ecological conservation and human welfare. In this study, we evaluated the spatial and temporal characteristics of land use and habitat quality in the temperate desert sub-region of Ordos Plateau using patch-generating land use simulation (PLUS) and integrated valuation of ecosystem services and trade-offs (InVEST) models. From 2000 to 2020, the areas of grassland, cropland, and unused land in the study area increased significantly; the areas of water bodies and woodland increased slightly; and the area of wasteland decreased significantly. Moreover, the habitat quality in the temperate desert subzone of the Ordos Plateau showed a trend of increasing and then decreasing from 2000 to 2020. The areas of lower and low habitat quality first decreased and then increased, and the overall area decreased over time. Conversely, the areas of high and higher habitat quality initially increased and then decreased, and the overall area increased over time. The area of medium habitat quality first decreased and then increased, although the overall change was minimal. Based on the PLUS model, the habitat quality of the study area in 2025 predicted under the natural development scenario was compared with that predicted under the ecological conservation scenario, showing higher habitat quality and lower habitat degradation under the ecological conservation development scenario. These results can be used to provide a scientific basis and decision reference for the sustainable use of land resources and high-quality socio-economic development in the temperate desert sub-region of the Ordos Plateau.

Japan Aerospace Exploration Agency (JAXA) is going to launch Advanced Land Observing Satellite 3 (ALOS-3) after 2022. ALOS-3 satellite is capable of observing global land areas with wide swath (4000 km along-track direction and 70 km cross-track direction) at high spatial resolution (panchromatic: 0.8m, multispectral: 3.2m). Maintenance and updating of land cover and vegetation information at national level is one of the major goals of the ALOS-3 mission. This paper presents the potential of simulated ALOS-3 images for the classification and mapping of land cover and vegetation types at Genus-Physiognomy-Ecosystem (GPE) level. We acquired and simulated WorldView-3 images according to the configuration of the ALOS-3 satellite sensor and the simulated ALOS-3 images were utilized for the classification and mapping of land cover and vegetation types in three sites (Hakkoda, Zao, and Shiranuka) in northern Japan. This research dealt with 17 land cover and vegetation types in Hakkoda site, 25 land cover and vegetation types in Zao site, and 12 land cover and vegetation types in Shiranuka site. Ground truth data were newly collected in three sites, and we employed eXtreme Gradient Boosting (XGBoost) classifier with the implementation of 10-fold cross-validation method for assessing the potential of ALOS-3S images. The classification accuracies obtained in Hakkoda, Zao, and Shiranuka sites in terms of f1-score were 0.810, 0.729, and 0.805 respectively. The fine scale (3.2m) land cover and vegetation maps produced in the study sites showed clear and detailed view of the distribution of plant communities. Regardless of the limited number of the temporal images, ALOS-3S images showed high potential (at least 0.729 F1-score) for the land cover and vegetation classification in all three sites. The availability of more cloud free temporal scenes is expected for improved classification and mapping in the future.

The impact of ponds on basins has recently started to receive its well–deserved scientific attention. In this study, pond–induced impacts on soil erosion and sediment transport were investigated at the scale of the French Claise basin. In order to determine erosion and sediment transport patterns under current conditions, the CORINE erosion and SWAT models were used. The impact of ponds on the studied processes was revealed by means of land cover change scenarios, using ponded versus pondless inputs. Results show that under current conditions (pond presence), 12.48% of the basin corresponds to no–erosion risk zones (attributed to the dense pond network), while 65.66% corresponds to low–erosion risk, 21.68% to moderate–erosion risk and only 0.18% to high–erosion risk zones. The SWAT model revealed that ponded sub–basins correspond to low sediment yields areas, in contrast to the pondless sub–basins, which yield appreciably higher erosion rates. Under the alternative scenario, erosion risks shifted to 1.12%, 0.52%, 76.8% and 21.56% for no, low, moderate and high–erosion risks, respectively, while the sediment transport pattern of the Claise completely shifted to higher sediment yield zones. This approach solidifies ponds as powerful man–induced modifications to hydro/sedimentary processes.

Reaching the land-related UN-Sustainable Development Goals (SDGs) and similar goals articulated by the EU-Green Deal (GD) by 2030 presents a major challenge and requires a pragmatic approach to be focused on joint learning by land users (mostly farmers), researchers and other stakeholders in “Living Labs” and system experiments at experimental farms of research organizations. Defining specific indicators and thresholds for ecosystem services in line with land-related SDGs, are crucial to establish: “Lighthouses” that can act as inspiring examples if they meet the various thresholds. This exploratory paper discusses indicators and thresholds for an arable farm operating on marine, calcareous light clay soils in the Netherlands. Studies of a system experiment are used to discuss and test operational methodology to be widely applied when characterizing many “Living Labs” in future as planned by the European Union. The important role of soils, contributing to ecosystem services, is discussed in terms of soil health. Recommendations are made for innovative methodology to be associated with all land-related SDGs. Satisfying thresholds of ecosystem services, that will vary by soil type, region and farm-type, can be the basis for farm subsidies such as the Common Agricultural Policy (CAP). Research on Living Labs and in system experiments has to be judged by different criteria than those associated with traditional linear research. Important contributions by soils to achieve ecosystem services are framed in terms of soil health and are the most effective way to promote soil science in a by now widely desired inter- and transdisciplinary context.

In the context of the energy transition, the integration of land use considerations into energy planning is increasingly vital, especially in scenarios where land availability is a constraint. This study addresses the challenge of incorporating land-use aspects into Energy System Optimization Models (ESOMs), with a focus on the unique context of Pantelleria Island. It aims to bridge the gap in methodologies for renewable energy potential assessment and model integration, considering the critical role of land pricing and availability. It combines geospatial data aggregation with model adaptation to include detailed land use aspects. Findings highlight the substantial impact of land costs on renewable energy planning, with land pricing significantly altering model outcomes. This research offers key insights for sustainable energy planning and underscores the importance of considering land use in energy transition strategies.

Land cover mapping provides spatial information on the physical properties of the Earth’s surface, for various classes of wetlands, artificial surface and constructions, vineyards, water bodies, etc. Having reliable information on land cover is crucial to developing solutions to a variety of environmental problems such as destruction of important wetlands/forests, and loss of fish and wildlife habitats. This has made land cover mapping one of the most widespread application areas in remote sensing computational imaging. However, due to the differences between modalities in terms of resolutions, content, and sensors, integrating complementary information that multi-modal remote sensing imagery exhibits into a robust and accurate system still remains challenging, and classical segmentation approaches generally do not give satisfactory results for land cover mapping. In this paper, we propose a novel dynamic deep network architecture, AMM-FuseNet, that promotes the use of multi-modal remote sensing images for the purpose of land cover mapping. The proposed network exploits the hybrid approach of the Channel Attention mechanism and Densely Connected Atrous Spatial Pyramid Pooling (DenseASPP). In the experimental analysis, in order to to verify the validity of the proposed method, we test AMM-FuseNet applied to four datasets whilst comparing it to the 6 state-of-the-art models of DeepLabV3+, PSPNet, UNet, SegNet, DenseASPP, and DANet. In addition, we also demonstrate the capability of AMM-FuseNet under minimal training supervision (reduced number of training samples) compared to the state-of-the-art, achieving less accuracy loss even for the case with 1/20 of the training samples.

The desert locust remains a major threat to global food security. Control operations are a crucial tool to manage crisis; this research investigated the nature of control operations conducted between 2019-2021. Historical data on desert locust and control operations were obtained from the survey reports at the FAO Locust Hub and analysed with respect to survey reports, land cover types, cropland/rangeland extent and crop productivity data. We found that 16.1% of the grid cells with locust presence and 14.9% of the grid cells with control operations had a proportion of rangeland higher than 0.75; while 13.3% of the grid cells with locust presence and 13.2% of the grid cells with control operations had a proportion of croplands higher than 0.75, highlighting that locust presence and control operations were reported in both rangeland and cropland. Control operations continue to be used both to reduce overall locust numbers and to protect crops. Furthermore, through identifying which crops were most at risk, our analyses indicate that wheat production was under the highest strain during periods of increased locust infestations.

While the scientific community has focused on documenting environmental degradation and developing scenarios that help identify the operational margins for system Earth, less attention has been given to the mental models of decision-makers that underpin environmental policies. We suggest that global efforts to stop deforestation and biodiversity loss are failing in part due to a critical blind spot in the analysis—human agency. To address this weakness, we propose to formulate mental models and translate them into strategy games. This will increase the representation of agency in scenario development and create spaces for deliberation between different worldviews. We claim that personal transformation can be achieved through transparent democratic dialogues that identify, challenge, and respond to the human and social limitations inherent to decision-making and we present empirical examples that validate that claim. Their transformation through gaming gives decision-makers access to the experience of consciousness: “what is it like being a stakeholder?”. Such experience will help to break free of established norms in science and political processes.

The coordination planning between land use and transportation system is an important premise of solving urban transportation problems and realizing land use integration. This study investigates the interactive and feedback relationship between land use and transportation system from the perspective of access management. By integrating the land use and traffic data from Las Vegas Metropolitan area with the system dynamics model, the causal relationship and causal loop diagrams (CLDs) are introduced to analyze the cause-and-effect relationship and quantitative relationship between the factors of the combined system of land use and transportation, and then sub-models partition and system simulation are performed. The systems dynamics model is established by analyzing the relationship between a series of access management techniques, traffic characteristics, and land use features. The results show that system dynamics model can be used as an effective alternative to model the symbiosis relationship of land use and transportation system for urban planning and construction.

Pekalongan is one of several cities that lies in the northern coast of Java island which is often flooded due to sea level rise. This condition impacted its urban development characteristic and increase in the future. In this research both Geographical Information System based and Spatial Metric approach are used. The spatial pattern is analyzed by using spatial metric based on the exploration of land use change that occurred. In this research, the spatial pattern is focused on aggregation pattern and diversity in coastal area. The result shows that the land use of coastal area are dominated with swamp, then followed by settlement and fishpond. It is also shown that the greatest land use change occurred on paddy field and swamp areas. Based on the spatial metric calculation, the aggregation level of land use decrease periodically and has a small growth level. It is indicated from its metric value aggregation and diversity from two periods: 2003-2009 and 2009-2016. Overall the land use of Pekalongan experienced large dynamics, especially in its coastal area. The spatial pattern trend in those area tend to be more sprawl as defined by the decrease of aggregation pattern and low level of land use growth pattern.

Pekalongan is one of several cities that lies in the northern coast of Java island which is often flooded due to sea level rise. This condition impacted its urban development characteristic and increase in the future. In this research both Geographical Information System based and Spatial Metric approach are used. The spatial pattern is analyzed by using spatial metric based on the exploration of land use change that occurred. In this research, the spatial pattern is focused on aggregation pattern and diversity in coastal area. The result shows that the land use of coastal area are dominated with swamp, then followed by settlement and fishpond. It is also shown that the greatest land use change occurred on paddy field and swamp areas. Based on the spatial metric calculation, the aggregation level of land use decrease periodically and has a small growth level. It is indicated from its metric value aggregation and diversity from two periods: 2003-2009 and 2009-2016. Overall the land use of Pekalongan experienced large dynamics, especially in its coastal area. The spatial pattern trend in those area tend to be more sprawl as defined by the decrease of aggregation pattern and low level of land use growth pattern.

The watershed hydrologic conditions in the Madre de Dios (MDD) basin in the Peruvian Amazon have been irreversibly impacted by deforestation and changes in land use cover. These changes have also had detrimental effects on the geomorphology, water quality, and aquatic habitat within the basin. However, there is a scarcity of hydrological modeling studies in this area primarily due to the limited availability of hydrometeorological data. The primary objective of this study was to examine how deforestation impacts the hydrological conditions in the MDD basin. By implementing the Soil and Water Assessment Tool (SWAT) model, this study determined that replacing 12% of the evergreen broadleaf forest area with bare land resulted in an significant increase in surface runoff by 38% monthly, a reduction of evapotranspiration by 1% annually, and an average monthly streamflow increase of 12%. Changes in spatial patterns reveal that the primary impacted watershed is the Inambari River subbasin, a significant tributary of the Madre de Dios River. This area experiences an annual average surge of 187% in surface runoff generation while witnessing an annual average reduction of 8% in evapotranspiration.These findings have important implications, as they can contribute to instances of flooding and extreme inundation events, which have already occurred in the MDD region.

Rapid peri-urbanization has resulted in increasing demand for and pressure on peri-urban lands at the expense of agricultural lands. Households’ decision to convert from agricultural land uses to residential and commercial land uses is driven by a myriad of factors, ranging from social to economic, in the Asante-Akim South district of the Asante region, Ghana. The paper examined the effects of agricultural land use trade-off on food production in the district. Using a triangulation of qualitative and quantitative methods, 115 household respondents were proportionately sampled from three selected communities in the district, for the collection of data through the administration of questionnaires. The data were subjected to the Pearson’s chi-square, embedded in the SPSS V.16, to test for association among the variables. We report that the increasing rate of agricultural land uses conversions was as a result of increasing demand for residential and commercial land usage at the expense of agricultural land uses. Converting prime agricultural lands into other land uses was seen as profitable to agricultural expansion. A re-examination of the district land use plans by the Ghanaian Physical (Town and Country) Planning Department in tandem with the Lands Commission is therefore recommended.

The article describes the results of comparison of occurence of buildings (and address points) in Poland with delimitations of land use belonging to particular classes in the CORINE Land Cover (CLC) 2018 dataset. Large discrepancies have been identified, which reach on average approx. 34% of addresses and 35% of buildings located outside class 1 (artificial surfaces), mainly on terrains of class 2 (agricultural areas). Among single-family buildings it was 37% and among new addresses (forecasted or ‘under construction’ buildings) – as much as 50%. This puts a question mark over the possibility of using CLC data with resolution of 25 ha for monitoring of spatial planning and development in Poland for purposes of the diagnosis and assessment of the scale of dispersion of built-up areas. It is worth carrying out similar analyses in other countries, known for the deconcentration processes and a relatively large share of dispersed settlement e.g. other CEE countries, Spain, Portugal, Italy.

The mantle mass flow interconnected with the process of Glacial Isostatic Adjustment (GIA) and the reformation of the Earth’s crust constantly perturbs the observed gravity field towards a hypothetic isostatic state. We analyse the temporal changes of the gravity field from the GRACE data, using different mathematical and/or statistical methods to detect the GIA amidst other gravity signals. A number of gravimetric post-glacial land uplift rate (LUR) modelling methods are investigated and compared with the data from a total number of 515 GPS stations and preferred GIA forward models in Fennoscandia and North America. We investigate three mathematical methods, namely regression, principal component, and independent component analysis (ICA) to extracting the GIA signal from the GRACE monthly geoid heights. We use some regularization techniques to exploit the GRACE monthly data to their maximum spatial resolution and to increase the Signal to Noise Ratio of their short wavelengths. Near the centres of the study areas the gravimetric LUR model using the fast-ICA algorithm of Hyvärinen and Oja (2000) is shown to be in a complete agreement with the GPS data and the predictions of the GIA forward models, and for the whole areas, subject to epeirogeny movement of the two regions, their discrepancies reach to the extrema at -1.8 and +3.3, and -4.5 and +7.5 mm/a, respectively. We show that the largest discrepancies between the gravimetric model using the ICA method and the GIA forward model, occur for the sub-regions likely collocated with strong ice mass change signals.

Background: There are major air pollution monitoring gaps in sub-Saharan Africa. Developing capacity in the region to conduct air monitoring in the region can help estimate exposure to air pollution for epidemiology research. The purpose of our study is to develop a land use regression (LUR) model using low-cost air quality sensors developed by a research group in Uganda (AirQo). Methods: Using these low-cost sensors, we collected continuous measurements of fine particulate matter (PM2.5) between May 1, 2019 and February 29, 2020 at 22 monitoring sites across urban municipalities of Uganda. We compared average monthly PM2.5 concentrations from the AirQo sensors with measurements from a BAM-1020 reference monitor operated at the US Embassy in Kampala. Monthly PM2.5 concentrations were used for LUR modeling. We used eight Machine Learning (ML) algorithms and ensemble modeling; using 10-fold cross validation and root mean squared error (RMSE) to evaluate model performance. Results: Monthly PM2.5 concentration was 60.2 µg/m³ (IQR: 45.4-73.0 µg/m³; median= 57.5 µg/m³). For the ML LUR models, RMSE values ranged between 5.43 µg/m³ - 15.43 µg/m³ and explained between 28% and 92% of monthly PM2.5 variability. Generalized additive models explained the largest amount of PM2.5 variability (R²=0.92) and produced the lowest RMSE (5.43 µg/m³) in the held-out test set. The most important predictors of monthly PM2.5 concentrations included monthly precipitation, major roadway density, population density, latitude, greenness, and percentage of households using solid fuels. Conclusion: To our knowledge, ours is the first study to model the spatial distribution of urban air pollution in sub-Saharan Africa using air monitors developed from the region itself. Non-parametric ML for LUR modeling performed with high accuracy for prediction of monthly PM2.5 levels. Our analysis suggests that locally produced low-cost air quality sensors can help build capacity to conduct air pollution epidemiology research in the region.

The Southwest Alpine Canyon Area of China was one of the regions in the world that suffered from severe soil erosion. The focus of this research was to understand the response of land use change on soil loss by water erosion in alpine canyon on Southeast Tibet, we analyzed the characteristics of temporal and spatial dynamics of land use in the Niyang River Basin from 1990 to 2020 using GIS and statistical methods, assessed the spatial and temporal change characteristics of soil erosion in the Niyang River Basin using RUSLE model. For this purpose, the meteorological, soil, topographic, remote sensing data were collected. The results showed the area of cropland and construction land in the Niyang River Basin increased to 2.4 and 6.1 times the original from 1990 to 2020, respectively, the area of forest and water continued to decrease. Grassland, unused land and forest have always been the dominant land types in the Niyang River Basin. Tolerable soil erosion was distributed in the flat areas of the valley terraces in the main stream and its tributaries, slight soil erosion was mainly distributed in the flat areas at high altitudes, and moderate, severe, very severe and destructive soil erosion was sporadically distributed in the Niyang River Basin. The areas of tolerable and slight soil erosion exceeded 82% of the total area, The area of severe, very severe and destructive soil erosion was less than 6%, but the total soil loss amount of severe, very severe and destructive erosion was more than 27%. From 1990 to 2020, the soil erosion area decreased from 9219.34 km2 to 8,090.84 km2 in Niyang River Basin, more than 85% of the soil erosion class has not changed, and the change of total soil loss amount also shows a significant reduction trend as a whole. 99% of the total soil loss amount in the Niyang River basin is generated by grassland, forest and unused land. The conversion of various land use types to cropland will cause the enhancement in soil erosion grade. We recommend that the focus of soil erosion control in the Niyang River Basin is to protect grassland, forest and carry out scientific farming.

A land cover map of two arctic catchments, nearby the Abisko Scientific Research Station, was obtained from a classification of a Sentinel-2 satellite image and a ground survey performed in July 2022. The two contiguous catchments, Miellajokka and Stordalen, are covered by various ecotypes, from boreal forest to alpine tundra and peatland. The random forests algorithm correctly identified 88% of polygon pixels reserved for testing. The developed workflow relied solely on open source software and acquired ground observations. Space organization was directed by the altitude as demonstrated by the intersection of the land cover with the topography. Comparison between this new land cover map and previous ones based on data acquired between 2008 and 2011 shows some trends of vegetation cover evolution in response to climate change in the considered area.

Classification and mapping of plant communities is an essential step for conservation and management of ecosystems and biodiversity. We adopt the Genus-Physiognomy-Ecosystem (GPE) system developed in previous study for satellite-based classification of plant communities. This paper assesses the potential of multi-spectral and multi-temporal images collected by Sentinel-2 satellites. This research was conducted in five representative study sites in a temperate region. It consists of 44 types of plant communities including a few land cover types as well. The plant community types were enumerated in the study sites and ground truth data were prepared with reference to extant vegetation surveys, visual interpretation of high-resolution images, and onsite field observations. We acquired all Sentinel-2 Level-1C product images available for the study sites between 2017-2019 and generated monthly median composite images consisting of ten spectral and twelve spectral-indices. Gradient Boosting Decision Trees (GBDT) classifier was employed as an efficient and distributed gradient boosting technique for the supervised classification of big datasets involved in the research. The cross-validation accuracy in terms of kappa coefficient varied from 87% in Oze site with 41 land cover and plant community types to 95% in Hakkoda site with 19 land cover and plant community types; with average performance of 91% across all sites. In addition, the resulting maps demonstrated a clear distribution of plant community types involved in all sites, highlighting the potential of Sentinel-2 multi-spectral and multi-temporal images with GPE classification system for operational and broad-scale mapping of land cover and plant communities.

To ensure sustainable production and consumption in the agricultural sector, it is necessary to assess the contribution of each element of the nexus in the agricultural production chain. The aim of this study is to make a quantitative and qualitative analysis of the contributions of each element of the energy, water, waste and land nexus to agricultural products. A composite method approach combining aspects based on input-output model, Location Quotient (LQ) as well as competitive position is adopted. A database of nexus elements over a period from 2009 to 2018 is used for Cameroon, with ten regions considered. The results show proportions of around 0.42% energy, 67.88% water withdrawal, 11.91% harvested area, 97.81% waste for agricultural products. The geolocation of harvested areas shows that the largest portion is in the far north (1,373,829 ha) and the smallest in Adamawa (224,038 ha). Maximum production is in the central region (4,334,095 tons) and minimum in the Adamawa region (915,841 tons). The central, littoral and west regions are more representative of agricultural products. The analysis of the competitive position of agricultural products contributes to a better orientation of national strategies for agricultural sustainability according to existing potentials.

One of the issues facing modern society, whatever the socio-economic level of the communities involved, is the development of sustainable strategies in the management of sludge/biosolids. Today, it is imperative to replace solutions aimed at simply “disposing of” with those oriented towards “maximizing recovery benefits”. It is desirable that agricultural use remains the main option in sludge/biosolids management, but to ensure effective and safe agronomic benefits, correctly fulfill the legal requirements, and build stakeholder and public confidence, rigorous and sustainable procedures need to be estab-lished. The development of realistic and enforceable regulation is crucial as it represents the right bal-ance between the different aspects of a coordinated and effective management. Furthermore, it is to recognize that regulation needs to be supported by standardized character-ization procedures and guidelines of good practices, because well-defined procedures allow le-gal requirements to be correctly and uniformly met, thus ensuring reliable comparison of re-sults obtained under different conditions. In this article, main aspects to consider for a sustainable application of this management practice are discussed, together with the parameters that need to be evaluated for the characterization of sludge/biosolids, according to the various aspects related to the agricultural use.

Due to the increasing global importance of decarbonizing human activities, especially the production of electricity, the optimal deployment of renewable energy technologies will play a crucial role in future energy systems. To accomplish this, particular attention must be accorded to the geospatial and temporal distribution of variable renewable energy sources (VRES) such as wind and solar radiation in order to match electricity supply and demand. This study presents a techno-economical assessment of four energy technologies in the hypothetical context of Mexico in 2050, namely: onshore and offshore wind turbines, and open-field and rooftop photovoltaics. A land eligibility analysis incorporating physical, environmental, and socio-political eligibility constraints and individual turbine and photovoltaic park simulations, drawing on 39 years of climate data, is performed for individual sites across the country in an effort to determine the installable potential and the associated levelized costs of electricity. The results reveal that up to 54 PWh of renewable electricity can be produced as a cost of less than 70 EUR/MWh. Around 91% (49 PWh) of this would originate from 23 TW of open-field photovoltaic parks that could occupy up to 578,000 km2 of eligible land across the country. The remaining 9% (4.8 PWh) could be produced by 1.9 TW of onshore wind installations allocated to approximately 68,500 km2 of eligible land that is almost fully adjacent to three mountainous zones. The combination of rooftop photovoltaic and offshore wind turbines account for a very small share of less than 0.03% of the overall techno-economical potential.

Abstract:The ecological protection of cultivated land is crucial for advancing high-quality agricultural development. This study analyzes the impact of agricultural socialization services on the ecological conservation of farmland, focusing on the reduction of chemical fertilizers and pesticides among rice farmers in the Jianghan Plain area. Utilizing data from 743 farmer household surveys conducted in 2023, the findings reveal that agricultural socialization services significantly encourage farmers to reduce chemical input usage. Specifically, a 1% increase in the level of agricultural socialization services correlates with a 14% decrease in chemical fertilizers and a 16.4% decrease in pesticides per mu. The study identifies scale operation, factor substitution, and alleviation of capital constraints as mediating factors enhancing the efficacy of these services. Furthermore, heterogeneity analysis indicates that these services are more effective in reducing chemical inputs among large-scale and newer-generation farmers compared to their small-scale and older counterparts. Additionally, technology-intensive socialized services exhibit a stronger impact on reducing chemical inputs than labor-intensive services.

Tesso Nilo National Park is one of the protected areas designated as KPA by the Decree of the Minister of Forestry No.225/Menhut-II/2004 dated July 19, 2004 covering an area of ​​38,576 ha, then expanded again through the Decree of the Minister of Forestry No.663/Menhut/2009 dated 19 October 2009 with an area of ​​± 83,068 ha. The Tesso Nilo National Park area is experiencing the dynamics of land cover changes, namely the conversion of forest land which causes the forest area to become increasingly narrow in this area. With the reduction in forest area in this area, it causes a decrease in ecosystem network connectivity due to forest fragmentation that occurs, so that forests are separated and further apart. This study aims to analyze changes in land cover in the Tesso Nilo National Park area to find out information on changes in habitat ecosystems in the last 20 years. the observations were made using satellite images in 1999, 2010 and 2019. so that it can be seen the effect of forest fragmentation on ecosystems in the Tesso Nilo National Park area. From the results of the analysis, it was found that the area of ​​forest cover in the Tesso Nilo National Park decreased from 1999 to 2019 and caused changes in the connectivity network of forest ecosystems, which was found in the study, the weakest connectivity separated forest fragments as far as 17394.47 meters due to forest cover fragmentation.

In order to alleviate the conflict between populations and land-resource, Tianjin has adopted multi-phase reclamation projects to formed large-scale artificial reclamation land. However, the reclamation areas are susceptible to subsidence, which demonstrate a serious threat to infrastructure and people’s lives and property. The SBAS-InSAR was used to acquired surface deformation of Tianjin Binhai New Area from January 2017 year to December 2022 year, analyzed in depth the response relationship between land subsidence and reclamation projects time as well as the land use type. The results show that the Lingang Industrial Zone was the earliest to be reclaimed, with extensive reclamation completed by 2016 year, while Nangang Industrial Zone and Hangu Port started reclamation projects in 2009 year, some areas are still currently under construction. There is a strong correlation between surface deformation and reclamation time, the severe land subsidence occurred over newly reclaimed areas. Surface deformation gradually intensifies from west to east, the maximum surface settlement in Nangang Industrial Zone, Lingang Industrial Zone from the west to the east has changed from -50 mm to -890 mm,45 mm to -580 mm, respectively, reclamation area of Hangu Port with maximum surface deformation is -250 mm. Significant differences deformation among different land use types, which reclamation projects completed in the same time. Subsidence is positively correlated with surface load, in areas with higher surface loads, the surface settlement is also severer,the average surface settlement for the heavy shipyard, 67 grain storage tanks, 27 grain storage tanks, road, and bare land are -201 mm, -166 mm, -107 mm, -64 mm, and -43 mm, respectively. This study reveals significant differences of surface deformation in the reclamation completed at different times and the load is the main driving factor of settlement difference in the reclamation land completed at the same time. Which has important guiding significance for preventing and controlling geological disasters in the reclamation area and later development planning.

Conventional methods of crop mapping need ground truth information to train the classifier. Thanks to the frequent acquisition allowed by recent satellite missions (Sentinel 2), we can identify temporal patterns that depend on both phenology and crop management. Some of these patterns are specific to a given crop and thus can be used to map it. Thus, we can substitute ground truth information used in conventional methods with agronomic knowledge. This approach was applied to identify irrigated permanent grasslands (IPG) in the Crau area (Southern France) which play a crucial role in groundwater recharge. The grassland is managed by making three mows during the May-October period which leads to a specific temporal pattern of leaf area index (LAI). The mowing detection algorithm was designed using the temporal LAI signal derived from Sentinel 2 observations. The algorithm includes some filtering to remove noise in the signal that might lead to false mowing detection. A pixel is considered a grassland if the number of detected mows is greater than 1. A data set covering five years (2016-2020) was used. The detection mowing number was done at the pixel level and then results are aggregated at the plot level. A validation data set including 780 plots was used to assess the performances of the classification. We obtained a Kappa index ranging between 0.94-0.99 according to the year. These results were better than other supervised classification methods that include training data sets. The analysis of land-use changes shows that misclassified plots concern grasslands managed less intensively with strong intra-parcel heterogeneity due to irrigation defects or year-round grazing. Time series analysis, therefore, allows us to understand different management practices. Real land-use change in use can be observed, but long time series are needed to confirm the change and remove ambiguities with heterogeneous grasslands.

The meaning of a good social outcome in land use transport policy/planning has been relatively underdeveloped, compared to economic and environmental sustainability goals, but this is now changing. Cities are increasingly prioritizing reducing social exclusion, with the allied intent of providing all residents with equitable access to the benefits of their city. However, in jurisdictions that use cost-benefit analysis to guide government decision-making, this poses a challenge: monetization of the benefits of reducing social exclusion is poorly developed. An evaluation gap thus confronts benefit-cost based assessment of initiatives intended to reduce social exclusion, compared to initiatives directed towards societal economic and environmental goals. This is a particular problem for public transport services that primarily enable people at risk of mobility-related social exclusion to access more opportunities in their society (social transit). The benefits of reducing social exclusion associated with these services have not been monetized, so social transit initiatives are poorly placed to argue their merits against competing initiatives where benefit monetization is more advanced (e.g., mass public transport and roads). The paper summarizes Australian research that has developed monetized measures for the value of increased trip making, bridging/bonding social capital, sense of community and several conceptions of wellbeing, and of reducing neighbourhood disadvantage, as these contribute to reducing social exclusion. New Singaporean research on the value of trip making to support reduced exclusion is also presented, affirming the Australian trip values. Trip values are then used in case study examples to show they can make a material difference to the societal worth of initiatives intended to reduce exclusion. Using these trip values, and other pathway values linked to reducing social exclusion, closes or at least substantially reduces the evaluation gap confronting social goal achievement in land use transport policy and planning, strengthening the case for reducing exclusion. These values will assist jurisdictions that are seeking to provide their residents with more equitable access to the benefits of their city.

Wetland ecosystems provide valuable services to human beings, but they are also among the most threatened ecosystems in the world (1). Sixteen ecosystem services are identified through the South African Water Research Commission's Wet-Health Tool (2). This study sought to establish which of these ecosystem services are highly ranked/rated by the community members living in the Soutpansberg area in South Africa. This area is a strategic water source/watershed. The area is rich in biodiversity and is also experiencing competing administrative jurisdictions: the local traditional leadership and the municipal council. This study also sought to determine the influence of age, education status, employment status, and family income, among other demographic factors, on how people view the importance of services derived from wetlands. It also sought to establish whether people in urban settings view the ecosys-tem services obtained from wetlands similarly to people in rural settings. A literature review was conducted to understand the wetland ecosystem services and how communities benefit from these services. A close-ended questionnaire was used to collect data for the current study, which was circulated among the villagers around the wetlands, particularly those living close to the wetlands. One hundred and sixteen responses from the study were recorded. Food for livestock was ranked the greatest benefit or service derived from the wetlands rated by 82% of the participants, followed by the provision of cultivated foods at 60%, provision of water for human use at 58%, provision of harvestable resources at 42% and erosion control at 38% completes the top 5 ranked ecosystem services in the area. The study concluded that the participants living in rural areas had greater awareness of wetlands' ecosystem services than their urban counterparts.

Image classification in Remote Sensing and Geographic Information Systems (GIS) containing various land-cover classes is essential for efficient and sustainable land-use estimation, and other tasks like object detection, localization and segmentation. Deep Learning (DL) techniques have shown a tremendous potential in the GIS domain. While Convolutional Neural Networks (CNN) have dominated most of the image analysis domain, a new architecture called transformers have proved to be a unifying solution for several AI-based processing pipelines. Vision Transformers (ViT), a variant of transformers can have comparable and in some cases better accuracy than a CNN. However, they suffer from a significant drawback associated with an excessive use of training parameters. In this research we explore several modifications in the vision transformer architectures, especially MobileViT that can be optimized while boosting accuracy. To verify our proposed approach these new architectures are trained on four land-cover datasets AID, EuroSAT, UC-Merced, and WHU-RS19. Experiments reveal that combination of lightweight convolutional layers including ShuffleNet along with depthwise separable convolutions and average pooling can reduce the trainable parameters by 17.85% and yet achieve higher accuracy than the base MobileViT. It is also observed that utilizing a combination of convolution layers along with multi-headed self attention layers in MobileViT variants provide better performance in capturing local and global features unlike the standalone ViT architecture that utilizes almost 95% more parameters than the proposed MobileViT variant.

Large-scale land cover plays a crucial role in global resource monitoring and management, as well as research on sustainable development. However, the complexity of the mapping process, coupled with significant computational and data storage requirements, often leads to delays between data processing and product publication, creating challenges for dynamic monitoring of large-scale land cover. Therefore, improving the efficiency of each stage in large-scale land cover mapping and automating the mapping process is currently an urgent and critical issue that needs to be addressed. We propose a high-performance automated large-scale land cover mapping framework(HALF) that introduces high-performance computing technology to the field of land cover production. HALF optimizes key processes, such as automated sample point extraction, sample-remote sensing image matching, and large-scale classification result mosaic and update. We selected several 10°×10° regions globally and the research makes several significant contributions:(1)We design HALF for land cover mapping based on docker and CWL-Airflow, which solves the heterogeneity of models between complex processes in land cover mapping and simplifies the model deployment process. By introducing workflow organization, this method achieves a high degree of decoupling between the production models of each stage and the overall process, enhancing the scalability of the framework. (2)HALF propose an automatic sample points method that generates a large number of samples by overlaying and analyzing multiple prior products, thus saving the cost of manual sample selection. Using high-performance computing technology improved the computational efficiency of sample-image matching and feature extraction phase, with 10 times faster than traditional matching methods.(3)HALF propose a high-performance classification result mosaic method based on the idea of grid division. By quickly establishing the spatial relationship between the image and the product and performing parallel computing, the efficiency of the mosaicking in large areas is significantly improved. The average processing time for a single image is around 6.5 seconds.

Agricultural land fires have been linked to various and adverse impacts on ecosystems, food security and the agriculture sector. Understanding the patterns and drivers of agricultural land fires is essential for effective agricultural land fire management. The key objectives of this study were to (1) analyze the temporal and spatial patterns of agricultural land fires using satellite remote sensed data, (2) assess a range of environmental conditions that could drive the occurrence of agricultural land fires, (3) determine the best model for predicting agricultural land fires and (4) determine the relative contribution of each environmental condition variable on the best predictive model. We used both univariate and multivariate regressions for the fire prediction capability of four independent environmental conditions (fuel, weather, topographic and anthropogenic). Analysis of historical satellite data revealed that agricultural land fires were more frequent than forested land fires. Our analyses also revealed that fuel condition was the most important variable for predicting agricultural land fires followed by weather, topographic and anthropogenic conditions. This study provides a novel multivariate model for predicting agricultural land fires that harbors the potential to improve agricultural land fire management and reduce fire risk within the agricultural sector.

Woody vegetation in farmland acts as a carbon sink and provides ecosystem services for local people, but no macro-scale assessments of the impact of management and climate on woody cover exists for drylands. Here we make use of very high spatial resolution satellite imagery to derive wall-to-wall woody cover patterns in tropical West African drylands. In arid and semi-arid Sahel, areas of more people are associated with more trees: mean woody cover is greater in farmlands (12%) than in savannas (6%), and likewise it is higher close to villages than further away. In sub-humid savannas of West Africa, woody cover is generally above 20% and decreases with increasing population density, but remains around 15% in farmlands, independent of rainfall. In the region as a whole, rainfall, terrain and soil are the most important (80%) determinants of woody cover, while management factors play a smaller (20%) role. We conclude that agricultural expansion cannot generally be claimed to cause woody cover losses, and that observations in Sahel contradict simplistic ideas of a high negative correlation between population density and woody cover.

The composition and pattern of ecosystems are important factors determining the overall status and spatial differences of ecosystem service functions. However, under the background of differential land policies and ecological protection policies, research on the trend of ecological system pattern changes in the Fenhe River Basin is insufficient. Taking the upper and middle reaches of the Fenhe River Basin as the study area, based on long-term NDVI index and multi-period LUCC remote sensing images, this study used spatial statistics and time trend analysis methods to analyze the spatio-temporal dynamic changes of vegetation, land use, landscape pattern, and explored the impact of major driving factors on ecosystem changes. The results show that: (1) From 2010 to 2020, the vegetation cover in the upper and middle reaches of the Fenhe River Basin increased, with an annual NDVI increment of 0.003 (P<0.001). NDVI showed an increasing trend spatially, with significant statistics (P<0.001) and significant changes (P<0.05) in vegetation in high-altitude mountain areas, and the vegetation cover was mostly forests or grasslands. There was no significant change in vegetation cover in the low-lying urban agglomeration area. (2) From 2010 to 2020, the area of water bodies or wetlands in the study area significantly decreased, with 51.3% converted to arable land and 33.9% transferred to construction land, while only 2.2% remained as water bodies or wetlands. From 2015 to 2020, the trend of water body changes slowed down, with the proportions of conversion to arable land and construction land being 44.0% and 18.4% respectively, while the area of wetlands or water bodies remained at 16.3%. During the period of 2015-2020, the area of water bodies or wetlands converted to other land types increased by more than 14% compared to 2010-2015. This proportion reached more than 30% compared to the 13th Five-year Plan Period. (3) From 2010 to 2020, the spatial changes of landscape diversity (SHDI) and evenness (SHEI) of LUCC showed heterogeneous characteristics. In the high-altitude areas near the river basin boundary, the values of SHDI and SHEI were below 1.0. While in the low-altitude plain areas and urban areas with relatively frequent human activities, the values of SHDI and SHEI were above 1.0, and the values in urban areas could reach above 1.5. The evolution of ecosystem patterns in the upper and middle reaches of the Fenhe River Basin in the past decade has been clarified, providing a scientific basis for the construction and management of ecological environment governance and restoration projects in the Fenhe River Basin, and providing practical references for ecological protection and high-quality development practice in the Yellow River Basin.

Biodiversity conservation planning is highly important in the current context of global change. Biodiversity conservation can be achieved by understanding changes in land use at the landscape scale. Such understanding is needed to reverse the unprecedented pressure on natural resources that has been reported by many studies conducted on biodiversity conservation within the Oti-Keran-Mandouri protected areas. Land cover maps reflecting different dates (1987, 2000, and 2013) and depicting different management systems, with overall accuracy ranging from 73% to 79%, were analyzed to understand the processes that lead to habitat degradation within these protected areas. The nature of change, within a given land cover class, was determined by comparing land cover maps on different dates using a decision tree algorithm that compares the number of patches, their areas, and their perimeters at different time periods (T₁ and T₂). Specifically, two time-periods were considered for this analysis: 1987–2000 and 2000–2013. Croplands and settlements increased at an average of 108.13% and 5.45%, respectively, from 1987 to 2000. From 2000 to 2013, croplands gained from all other land categories and continued to increase at a rate of 11.77% per year, whereas forests and savannas decreased at an annual average rate by 5.79% and 2.32%, respectively. The dominant processes of habitat change from 1987 to 2000 were the creation of forests, dissection of savannas, attrition of wetlands, and creation of croplands. Meanwhile, from 2000 to 2013, there was attrition of forests, as well as attrition of savannas, dissection of wetlands, and aggregation of croplands. In general, from 1987 to 2013, natural habitats regressed and were replaced by croplands; forests, savannas, and wetlands decreased at an average annual percentage 5.74%, 3.94%, and 2.02%, respectively, whereas croplands increased at an average annual rate of 285.39% of their own area. Aggregation, attrition, dissection, and creation were the main habitat change processes identified for the overall period from 1987 to 2013. There was habitat loss in forests and savannas and habitat fragmentation in wetland due to attrition and dissection, respectively. Identifying and understanding habitat change processes would enable the taking of appropriate biodiversity conservation actions.

Climate change is expected to result in rising temperatures, leading to increased occurrences of extreme weather events like heat waves and cold spells. Urban planning responses are crucial for improving the adaptive capacity of cities and communities in dealing with significant temperature variations across seasons. This study aims to investigate the relationship between urban temperature fluctuations and urban morphology throughout the four seasons. Through quadrant and statistical analyses, the study identifies built-environment factors that contribute to moderate seasonal land surface temperatures (LST). The research focuses on Seoul, South Korea as a case study and calculates seasonal LST values at both the grid level (100m×100m) and street-block level, incorporating factors such as vegetation density, land use patterns, albedo, two- and three-dimensional building forms, and gravity indices for natural reserves. The quadrant analysis reveals spatial segregation between areas demonstrating high LST adaptability (cooler summers and warmer winters) and those displaying LST vulnerability (hotter summers and colder winters), with significant differences in vegetation and building forms. The spatial regression analysis demonstrates that higher vegetation density and proximity to water bodies play key roles in moderating LST, leading to cooler summers and warmer winters. Building characteristics have an invariant impact on LST across all seasons, where horizontal expansion contributes to higher LST, while vertical expansion reduces LST. These findings are consistent for both grid- and block-level analyses. The study emphasizes the flexible role of the natural environment in moderating temperatures.

The eutrophication caused by excessive total nitrogen(TN) and total phosphorus(TP) emissions has been widely concerned by the whole society. Studies have revealed the relationship between land use and TN and TP, but the relationship between land use compound topographic position and TP and TN was seldom studied. Therefore, Spearman correlation and redundancy analyses were used to reveal the relationship between land use compound topographic position and TN and TP based on the monthly data of 28 water quality sampling sites and the land use data of 2013 and 2016 in the lakes of Guizhou Plateau. The results show that the nutritional state of the HBA watershed is medium. The trophic level index (TLI) value and TN concentration were high during flood, while TP concentration was high in dry period. The TN concentration in the tributaries was higher than that in the reservoir area. Construction and valley were the sources of the pollution, whereas forest land and gentle slope were the sink. According to the”source-sink”effect, the optimal zoning of land use was completed, and the urban land pollution govern area should be strengthened firstly. This paper can provide decision support for water environment management and sustainable development decision-making.

Damage to crops from wildlife interference is a common threat to food security among rural communities in or near Game Management Areas (GMAs) in Zambia. This study uses a two-stage econometric model and cross-sectional data from a survey of 2,769 households to determine the impact of land use planning on the probability and extent of wildlife-inflicted crop damage. The results show that crop damage is higher in GMAs as compared to non-GMAs, and that land use planning could be an effective tool to significantly reduce the likelihood of such damage. These findings suggest that there is merit in the current drive to develop and implement land use plans as means to minimize human-wildlife conflict such as crop damage. This is especially critical as Zambian conservation policies do not have an explicit provision for compensation in the event of damage from wildlife.

Anthropogenic disturbances interacting with natural disturbances, ecological and socio-economic factors can provoke forest degradation and modulate ecosystem resilience. In Haiti, protected areas recently created to reduce forest loss, require studies about forest dynamics and land use to assure the development of sustainable management policies. We combine field interview with Landsat satellite images of the Macaya National Park collected between 1985 and 2021 to investigate: 1) how much of the original forest area has been converted into agricultural or logged area since 1985; and 2) how do elevation and slope influence the expansion of human-induced land-use changes. Our results indicate an increase of 11.36% in forest cover and a reduction of 75.34% in agriculture class cover, despite the passage of seven hurricanes in the region. Forest recovery was apparently unrelated to elevation and slope, and likely reflected the implementation of new environmental laws and policies with the creation of the Macaya National Park in 1983. Restoration and protection programs contributed to ensure access to financial resources, technical assistance and new technology, thus promoting a shift into a more resilient forest system. This study brings hope for forest conservation in Haiti by showing that positive results can be achieved through inclusive collaboration.

Current species’ range displacements are mostly triggered by climate change but European landscapes are largely dominated by human activities. In this study we identify the most promising spatial adaptive trajectories (SATs) for the thirty most threatened non volant mammal species in Europe up to 2080 (under three climate and land change scenarios) and where/when SATs of each species synchronically converge. We found large contrasts on the persistence of species in SATs, with some species largely reliant on the functionality of areas where many SATs converge. Overall, SATs and convergence centers are not adequately covered by existing conservation areas and coincide with crop and arable lands, compromising species persistence. It is important to invest in the protection of SATs and convergence centers through a mix of conventional instruments and new collaborative forms with the socio-economy. Anticipative plans at long-term coupled with risk analysis offer decision–makers templates to prevent negative surprises.

This investigation delves into the profound interplay between the e-commerce environment and the agricultural system, while scrutinizing the intricate human-land coupling dynamics engen-dered by transformations within the agricultural domain. Focusing on the expansion of orchards in Pinghe County, a pivotal epicenter for Chinese sweet pomelo production, this study eluci-dates the reverberations of Rural E-commerce Environment Development on Orchard Expansion through the lens of Tele-coupling. In doing so, it unveils the nuanced tapestry of the human-land coupling associations latent within the evolutionary trajectory of the agricultural system amidst the blossoming information society. The findings underscore a symbiotic relationship between the augmentation of orchard acreage and the burgeoning rural e-commerce landscape, effec-tively propelling the economic prosperity of the agricultural system. Moreover, a tele-coupling phenomenon has emerged, underscoring the intricate web of interconnections binding the mat-uration of the rural e-commerce ecosystem with the proliferation of orchards. The research illu-minates that the transformation of land utilization, imbricated within the agricultural system, manifests as a distinctive form of tele-coupling intricately woven into the fabric of urbanization and information technology advancements. Consequently, adopting a comprehensive theoreti-cal perspective, amalgamating disparate domains across distinct geographic realms, becomes imperative for discerning the intricate nuances of the human-land coupling nexus within these multifaceted, open systems.

The seasonal and vertical spatial variation characteristics of total N, NH4+—N and NO3-—N in the soil in Picea mongolica forest at different stand ages were studied. The results showed that: (1) NH4+ —N in the soil in Picea mongolica forest was positively correlated with sample date, soil NO3-—N and forest age (P <0.05), and negatively correlated with soil depth (P < 0.01). NO3-—N in the soil in Picea mongolica forest was negatively correlated with sample date and forest age (P < 0.05), and significantly negatively correlated with soil depth (P < 0.01); (2) the content of NH4+—N is greater than that of NO3-—N in each soil layer of Picea mongolica forest at three forest ages. The correlation analysis showed which had an impact on the content of NH4+—N and NO3-—N in the soil in Picea mongolica forest. The content was lower in February and November, and higher in May and August；(3) The contents of total N, NH4+—N and NO3-—N in the soil of Picea mongolica forest in the three forest ages increased with the depth of soil layer (0-50cm), and showed an overall downward trend. The contents of NH4+—N in the soil layer of young forest (0-10cm, 10-20cm and 20-30cm, 30-40cm and 40-50cm) were significantly different (P＜0.05), and the contents of NO3-—N were also significantly different (P＜0.05), while their contents of middle-aged forest and near mature forest increased with the depth of soil layer, There was no significant difference in the content of NH4+—N; (4) The content of NH4+—N in the soil in Picea mongolica forest generally showed the following change trend near mature forest > middle-aged forest > young forest. The change trend of soil NO3-—N content is consistent with that of the content of NH4+—N in the soil in Picea mongolica forest.

An investigation studied the impact of various solid waste types on Helianthus plant growth, encompassing both Helianthus annuus and Helianthus giant. Common sunflowers (Helianthus) were cultivated to assess the influence of soil substrates with differing compositions and solid waste concentrations on plant growth and morphology. Materials included fireplace ash, oil burner dust, forge dust, land of Milos (pozzolan), and land of Milos mixed with olive core. The aim was to determine if Helianthus could remediate soil contaminated by these wastes. Results re-vealed plant growth relied on substrate quality and quantity. High concentrations of fireplace ash and oil burner dust were detrimental, while forge dust, land of Milos, and olive core combinations supported satisfactory growth and improved resistance. Generally, Helianthus annuus outper-formed Helianthus giant. These findings highlight Helianthus' potential for soil restoration and decontamination under specific substrate conditions concerning solid waste type and concentration.

Recent Socio-economic changes resulted to mass abandonment of agricultural lands in Central-Eastern Europe. This leads to landscapes homogenisation, especially the disappearance of semi-open habitats of the farmland-woodland interface. The information on potentials of transforming feral, abandoned landscapes to wood-pastures is limited. We studied the ecological features and silvopastoral benefits of a landscape subjected to intensive cattle grazing after ~20 years of abandonment, i.e. the mosaic of habitats, cattle’s preference for habitats and for arboreal forages. The nutritional characteristics of arboreal forage and herbaceous forage were compared. After the initial increase in the landscape’s woodland share, cattle grazing halted further woody succession and stabilised the landscape structure, with treeless grassland occupying 49% of the landscape (most preferred by cattle with regard to the time spent), followed by treed grassland (19%), pioneering birch/alder groves (13%), riparian vegetation (12%, least preferred by cattle), and close-canopy woods (6%). The consumption intensity of arboreal forages was on about 4.5 folds higher than that of herbaceous forage. Our study proved that the grazing herd of arobust cattle breed can turn a feral, post-agricultural land into a working wood pasture, consisting of interconnected open grasslands and various facets of woodland, which seldom occur in contemporary high forests. We advocate for the transition management of abandoned farmlands towards integrated silvopastoral landscapes for sustainable provision of multiple ecosystem services that cannot be provided by segregated agriculture and forestry.

As a rapidly growing coastal megacity, Shanghai is continuously threatened with land subsidence issues since 1920s. Land subsidence was controlled in 1960s, however in 1990s, unconscious and dangerous urban underground space (UUS) exploration and tunneling development are causing further land subsidence. It is imperative to study previous relations towards future adaptive and resilient scenario modelling and planning. There are multiple cause-effect factors determined in the urban built environment of Shanghai megacity. This paper presents the current evidence based on the relations of the multifactor of the spectrum. Methods consist of understanding the cause-effect relations and spatiotemporal from the crucial period of 1960-2020. Data are collected secondarily from multiple open sourced databases. The results determine Shanghai are highly influenced by the UUS development induced-subsidence, tunneling leakage and weak spatial modelling. Spatiotemporal pattern has shown a mixed positive-negative impact: population, land subsidence is growing in parallel distribution (positive) with tunneling leakage, construction of tunneling, metro system, UUS development, building price, reconstruction area, GDP growth, land price, arable land decrease and further tunnel settlement in Urban City Centre, Pudong New Area, Minhang, Baoshan and Songjiang districts. These results are useful for further adaptive and resilient scenario modelling and spatial planning.

The way people in many countries eat today is disconnected to the resources and land locally available. In Europe, for instance, too much meat is eaten, but often cannot be fed by local resources. The percentage of non-local and non-seasonal food is tremendous, exploiting other regions and their water reservoirs. Current diets harm eco systems and people’s health. (Re-)regionalising food systems and aligning diets to planetary boundaries could be one way to reconnect people to the food they eat. Before demanding the (re-)regionalisation of food, it should be analysed whether current consumption patterns can be met at all with the regionally available agricultural land. We looked at the region Hesse in Central Germany, calculated and compared land consumption of current diets with the consumption as recommended by the Planetary Health Diet. Our focus is on livestock because land consumption to produce meat, dairy and eggs is relatively high. Our results show that the region is far from being able to feed the current livestock population, that it does not have the land to support the livestock needed to meet current consumption patterns, but that it could support a smaller livestock population according to the Planetary Health Diet, especially if farmers adopt crop rotation systems and extensive husbandry.

In recent years, land supply in Hong Kong has fallen sharply and fails to keep pace with the growth of population and number of households. Land shortage becomes urgent and dire. With the inadequate provision of residential land, housing supply is also adversely affected.Insufficient housing supply leads to surging property and rental price in the private market. According to the Rating and Valuation Department (RVD), the overall private domestic price index peaked in June 2017 at 336.1. Keen housing demand is also observed in the private rental market. RVD statistics showed that the domestic rental index also reached the peak at 183.6 in June 2017 and the vacancy rate of about 3.8% as at the end-2016, which is much lower than the average vacancy rate of 5% from 1996 to 2015 (Development Bureau, 2017).In addition, there is soaring housing demand in public housing. As at the end-December 2021, the average waiting time for general applicants was 5.7 years, which is nearly double of the Housing Authority’s target for providing the first flat offer to general applicants at around three years on average (Housing Authority, 2021). Identifying and securing sufficient land to meet both current and anticipated pressing housing demand becomes a key challenge of the government. In the light of this, the government has established a dedicated task force (Task Force on Land Supply) in September 2017 and appointed 30 professionals from different disciplines, such as planning, engineering, academia and think tank, to take a Marco-review on the land supply sources, look for feasible options as well as consider the pros and cons of various options. 18 land supply options were worked out for the public to make choices in the public engagement exercise. Among the 18 choices, the development area on the Periphery of Country Parks was regarded as one of the land supplies sources. This option does not only include the Hong Kong Housing Society’s studies on developing Two Pilot Areas on the Periphery of Tai Lam and Man On Shan Country Parks, but also include developing more areas on the periphery of Country Parks. The proposed option received overwhelming attention from the public and aroused debates in various perspectives. Its ecological value, recreational value, financial viability and even legitimacy were discussed. However, spatial analysis on the suitability of having residential development in Country Parks has not been conducted. Therefore, in this study, multi criteria GIS analysis is conducted to evaluate the geographic suitability of Hong Kong Country Parks for residential purpose with the consideration of various criteria.

The integration of nature-based solutions into land use optimization has emerged as a focal point of current research, primarily due to its efficacy in mitigating flooding impacts and fostering sus-tainable development in both urban and rural areas. Utilizing Shanghai Pujiang Country Park as a case study, this paper conducts a simulation analysis to assess the flood mitigation effectiveness of three distinct land use patterns (Natural scenario, Scenario N; Complete urbanization scenario, Scenario U; Country Park Planning scenario, Scenario P) under five stormwater scenarios with re-turn periods of 2, 5, 10, 20, and 50 years. The findings reveal that Scenario P exhibits superior flood mitigation performance, particularly under stormwater scenarios with a return period of less than 50 years. Building upon these results, the paper proposes recommendations for optimizing land use with a focus on mitigating the impact of flooding. This study is crucial for comprehending the mechanisms involved in urban stormwater logging mitigation through land use methods and holds significance for decision-making in land use and planning at the micro level.

Urban sprawl propelled by rapid population growth leads to the shrinkage of productive agricultural lands and pristine forests in the suburban areas and, in turn, substantially alters ecosystem services. Hence, the quantification of urban sprawl is crucial for effective urban planning, and environmental and ecosystem management. Like many megacities in fast growing developing countries, Chennai, the capital of Tamilnadu and one of the business hubs in India, has experienced extensive urban sprawl triggered by the doubling of total population over the past three decades. We employed the Random Forest (RF) classification on Landsat imageries from 1991, 2003, and 2016, and computed spatial metrics to quantify the extent of urban sprawl within a 10km suburban buffer of Chennai. The rate of urban sprawl was quantified using Renyi’s entropy, and the urban extent was predicted for 2027 using land-use and land-cover change modeling. A 70.35% increase in urban areas was observed for the suburban periphery of Chennai between 1991 and 2016. The Renyi’s entropy value for year 2016 was ≥ 0.9, exhibiting a two-fold rate of urban sprawl. The spatial metrics values indicate that the existing urban areas of Chennai became denser and the suburban agricultural, forests and barren lands were transformed into fragmented urban settlements. The forecasted urban growth for 2027 predicts a conversion of 13670.33ha (16.57 % of the total landscape) of existing forests and agricultural lands into urban areas with an associated increase in the entropy value of 1.7. Our findings are relevant for urban planning and environmental management in Chennai and provide quantitative measures for addressing the social-ecological consequences of urban sprawl and the protection of ecosystem services.

Integrated landscape approaches (ILA) aim to reconcile multiple, often competing, interests across agriculture, nature conservation, and other land uses. Recognized ILA design principles provide guidance for their implementation, yet application remains challenging, and a strong performance evidence-base is yet to be formed. A comprehensive literature review and focus group discussions with practitioners identified considerable diversity of ILA in actors, temporal, and spatial scales, inter alia. This diversity hampers learning from and steering these integrated planning approaches because of its intractable nature. Therefore, we developed a tool—an ‘ILA mixing board’—to structure the complexity of ILA into selectable and scalable attributes in a replicable way to allow planning, diagnostics, and comparative assessment of ILA. The ILA mixing board tool presents seven qualifiers, each representing a key attribute of ILA design and performance such as project flexibility, inclusiveness of the dialogue, and the centrality of the power distribution. Each qualifier has five (non-normative) outcome indicators that can be registered as present or absent. This process in turn guides planners, evaluators and other participating stakeholders involved in landscape management to diagnose the ILA type, and or its performance. We apply the ILA mixing board as a diagnostic tool to three ILA cases in Nicaragua, Madagascar, and the Congo Basin to show some of the many possible configurations of qualifiers on the mixing board. Overall, the tool allows comparative analyses of the complexity of ILA in a structured and manageable way.

In the Brazilian Amazon, rural settlements are increasingly isolated by large-scale production farms, jeopardizing their sustainability and the good living of family farmers. Works were carried out in settlements to measure sustainability. However, the majority does not consider the participation and the collectively of those involved. In this way, we propose to evaluate, in a collective and participatory way, the sustainability and good living of the SDP São Paulo Rural Settlement, of the northern Amazon of Mato Grosso. We used the didactic-pedagogical method Circle of Sustainability, developed from five points: 1st - circle of investigation of generating themes; 2nd - circle of the history of the subject world; 3rd - circle of diagnosis of rural settlements; 4th - circle of exchange of knowledge; and 5th - circle of sustainable perceptions and narratives. The historical, socioeconomic and cultural characterization of the settlement allowed us to understand how sustainability and good living are being built in the settlement history process. Sustainability and good living are dialectical processes, are under construction, in movement.

Observation of the ambient aerosol surface area concentrations is important to understand the aerosol toxicity because an increased surface area may be able to act as an enhanced reaction interface for certain reactions between aerosol particles and biological cells, as well as an augmented carrier surface for co-pollutants. In this study, the concentration of aerosol surface area was measured from April 2015 to March 2016 in Fukuoka, Japan. We investigated the monthly and diurnal variations in the correlations between the aerosol surface area and black carbon (BC) and sulfate concentrations. Throughout the year, aerosol surface area concentration was strongly correlated with the concentrations of BC, which has relatively large surface area since BC particles are usually submicron agglomerates consisting of much smaller (tens of nanometers) sized primary soot particles. The slopes of the regression between the aerosol surface area and BC concentrations was highest in August and September 2015. This appears to have been the results of an increase in the proportion of the airmass that originated on the main islands of Japan. This may enhance the introduction of the BC from the main islands of Japan that is relatively fresh (or “uncoated”), thereby maintaining its larger surface area.

The eco-efficiency of cultivated land use (ECLU) is an important indicator for the construction of ecological civilization in China. Exploring the spatiotemporal dynamic evolution of the ECLU is helpful for sustainable use of arable land, ensuring food security and ecological security. However, previous studies have mostly focused on the use of a slacks-based measure (SBM) model for ECLU measurement, ignoring the more accurate epsilon-based measure (EBM) model. Therefore, in this study, firstly, we explored the conceptual framework of ECLU, and then, based on the panel data of the counties in the region around Beijing and Tianjin from 2005 to 2020, we investigated the spatial and temporal evolution of ECLU by using the Super-EBM model, kernel density estimation method, and spatial Markov chain model. Results displayed: (1) From 2005 to 2020, the ECLU in the region around Beijing and Tianjin displayed an increasing state, but the average value was only 0.55. (2) The time evolution of the ECLU has gradually polarized, the internal gap has widened, but it tends to stabilize. (3) The ECLU in the region around Beijing-Tianjin was more inclined to keep it the same and there was a "club convergence" phenomenon, which was meaningfully affected by the background of neighboring areas. In the light of local conditions, the government should reasonably formulate the path to optimize the ECLU, strengthen the linkage with the surrounding cities, and bring into play the positive spillover effect.

This paper compares the Medieval (ca. 400–1500 CE) dynamics of forests from low-mountain (Montcortès; ca. 1000 m a.s.l.) and high-mountain (Sant Maurici; 1900 m a.s.l.) areas of the Iberian Pyrenees, both of which experienced similar climatic forcing but different anthropogenic pressures. The main aim is to identify forest changes over time and associate them with the corresponding climatic and anthropogenic drivers (or synergies among them) to test how different forests at different elevations respond to external forcings. This could be useful to evaluate the hypothesis of general Pyrenean deforestation during the Middle Ages leading to present-day landscapes and to improve the background for forest conservation. The study uses palynological analysis of lake sediments, historical documents and paleoecological reconstructions based on pollen-independent proxies. The two sites studied showed different forest trajectories. The Montcortès area was subjected to intense human pressure during regional deforestation up to a maximum of ca. 1000 CE. Further forest recovery took place until the end of the Middle Ages due to a change in forest management, including the abandonment of slash-and-burn practices. Climatic shifts indirectly influenced forest trends by regulating human migrations and the resulting shifts in the type and intensity of forest exploitation. The highland Sant Maurici forests exhibited a remarkably long-standing constancy and an exceptional resilience to climatic shifts, which were unable to affect forest extension and composition, and to local human pressure, from which they rapidly recovered. The Montcortès and Sant Maurici records did not follow the rule of an irreversible forest clearing during the Middle Ages leading to present-day landscapes. The present Montcortès landscape was shaped after a Medieval forest recovery, a new Modern-Age deforestation and a further forest recovery during the last centuries. The Sant Maurici forests remained apparently untouched since the Bronze Age and were never cleared during the Middle Ages. The relevance of these findings for forest conservation is briefly addressed, and the need for the development of more high-resolution studies on Pyrenean forest dynamics is highlighted.

Strip-mined land (SML) disturbed by coal-mining is the non-crop land resource that can be utilized to cultivate high-yielding energy crops such as miscanthus for bioenergy applications. However, the biomass yield potential, annual availability and environmental impacts on growing energy crops in SML are less understood. In this study, we estimated the yield potential of miscanthus (Miscanthus sinensis) in SML and its environmental impacts on local streams using the Soil and Water Assessment Tool (SWAT). After calibration and validation of the SWAT model, the results demonstrated that miscanthus yield potentials were 2.6 (0.8−5.53), 10.0 (1.3−16.0) and 16.0 (1.34−26.0) Mg ha^-1 with the fertilizer application rate of 0, 100, and 200 kg-N ha^-1 respectively. Furthermore, cultivation of miscanthus in the SML has the potential to reduce sediment (~20%) and nitrate (2.5%−10.0 %) loads reaching to water streams with a marginal increase in phosphorus load. The available SML in the United States could produce about 10 to 16 dry Tg of biomass per year without negatively impacting the water quality. In conclusion, SML can provide a unique opportunity to produce biomass for bioenergy applications, while improving stream water quality in highly dense mining area (the Appalachian region) in the United States.

Can investing in women’s agriculture increase productivity? This paper argues that it can. We assess climate impacts and gender bias on women’s production in the global South and North and challenge the male model of agricultural development to argue further that women’s farming approaches can be more sustainable. Level-based analysis (global, regional, local) draws on literature review, including authors’ published longitudinal field research in Ghana and the United States. Women farmers are shown to be undervalued and to work harder, with fewer resources, for less compensation; gender bias challenges are shared globally while economic disparities differentiate; breaches of distributive, gender, and intergenerational justices as well as compromise of food sovereignty affect women everywhere. We conclude that investing in women’s agriculture needs more than standard approaches of capital and technology investment. Effective ‘investment’ would include systemic interventions into agricultural policy, governance, education, and industry; be directed at men as well as women; and use gender metrics, e.g. quotas, budgets, vulnerability and impacts assessments, to generate assessment reports and track gender parity in agriculture. Increasing women’s access, capacity, and productivity cannot succeed without men’s awareness and proactivity. Systemic change can increase productivity and sustainability.

We estimate general public’s willingness to pay (WTP) for agricultural soil quality protection and improvement in Spain (n=1000) and the UK (n=984) using data from a cross-sectional survey via Qualtrics panels in March-April 2021. We use a double bound dichotomous choice contingent valuation approach to elicit the individuals’ WTP. We investigate the effect of uncertainty on the success of policies aiming at achieving soil protection. In addition, to understand the heterogeneity in individuals’ WTP for agricultural soil quality protection and improvement we model individuals’ WTP through individual’s awareness and attitudes toward agricultural soil quality protection and the environment, trust in institutions; risk and time preferences; pro-social behavior and socio-demographics in Spain and the UK. We found that there is significant public support for agricultural soil quality protection and improvement in Spain and the UK. We also found that the support does not vary significantly under uncertainty of success of policies aiming at achieving soil protection. However the individual’s reasons for supporting agricultural soil quality protection and improvement are found to depend on the level of uncertainty and country. Hence, promoting public support for soil protection needs to be tailored according to the level of general public’s perceived uncertainty and geographic location.

Land surface temperature (LST) is a critical parameter for the dynamic simulation of land surface processes and for analyzing variations on regional or global scales. Obtaining LST with high spatiotemporal resolution is a subject of intensive and ongoing research. This study proposes a pixel-wise temporal alignment iterative linear regression model for downscaling based on MODIS LST products. This approach allows us to address the problem of high temporal resolution but low spatial resolution of the ERA5 reanalysis LST product, while remaining immune to pixel loss caused by clouds. The hourly ERA5 LST of the study area for 2012–2021 was downscaled to 1000 m resolution, and its accuracy was verified by comparison with measured data from meteorological stations. The downscaled LST offers intricate details and is faithful to the LST characteristics of distinct land-cover categories. In comparison with other downscaling techniques, the proposed technique is more stable and preserves the spatial distribution of ERA5 LST with minimal missing pixels. The pixel-wise average R-squared and mean absolute error for MODIS view times are 0.87 and 2.7 K, respectively, for cloud-free conditions at a 1000 m scale. Accuracy verification using data from meteorological stations indicates that the overall error is lower during cloudless periods rather than during overcast periods, during the night rather than during the day, and at MODIS view times rather than at non-view times. The maximum and minimum mean errors are 0.13 K for cloud-free periods and −0.98 K for cloudy periods, indicating a slight underestimation and overestimation, respectively. Conversely, the maximum and minimum mean absolute errors are 2.01 K for the daytime and 0.85 K for the nighttime. Therefore, the model ensures higher accuracy during cloudy periods with only clear sky LST as input data, making it suitable for long-term, all-weather ERA5 LST downscaling.

Accurate seasonal weather forecasts are vital across a broad spectrum of applications, bearing significant environmental and socioeconomic implications. This importance renders the subject a matter of primary interest to a wide range of stakeholders, including the general public, agricultural sector, emergency responders, financial institutions, and policy strategists. The need for precision in long-term predictive models necessitates the development of innovative methodologies. These methodologies should be capable of deciphering atmospheric patterns and mechanisms with detail, especially at a local level, without the resource constraints that dynamical downscaling imposes. In response to this expanding demand, this study presents a novel solution, combining a stochastic deep learning methodology, specifically Generative Adversarial Networks (GANs), with a Digital Elevation Model (DEM). The cornerstone of the proposed model is the enhancement of gridded temperature fields from seasonal forecasts. The area of focus was the Hellenic region, wherein the spatial resolution is amplified from a coarse 1° x 1° grid to an impressively detailed 0.1° x 0.1° grid. This offers a transformative perspective for interpreting and employing this crucial meteorological data. The results suggest that the downscaled fields adequately approximate the actual spatial distribution, although the predicted values tend to slightly overestimate and in some cases underestimate the original ones. This study underlines the potential of this approach to significantly enhance the resolution and utility of weather forecasts, thereby contributing to a variety of sectors dependent on reliable meteorological data.

In its Nationally Determined Contribution (NDC) to the United Nations Framework Convention on Climate Change, Brazil committed to reducing greenhouse gas emissions and restoring its forests. This study examines the challenges of fulfilling these commitments in Brazilian Amazonia. We carry out a detailed assessment of the current status of land tenure in the region and its relation to deforestation. After dealing with conflicts and overlaps between data from various sources, we produce a new map of public and private land tenure in Amazonia. Combining this map with Brazil's official data on deforestation, we find out how much natural vegetation has been preserved in each public or private area. The result is used to estimate how much deforestation is illegal. We also establish how much deforestation is associated with each land tenure type. Our results show that most deforestation inside rural properties is done by a few landowners, a finding that has important consequences for law enforcement. We then assess the challenges for reforestation in detail. To do so, we consider how much forest needs to be rehabilitated according to Brazil's Forest Code. Our analysis provides a comprehensive appraisal of the potential opportunity costs for forest restoration in the biome, considering farm size and land use. This analysis provides insights into targeted land use policies that can meet Brazil’s forest restoration goals.

Land resources have been under tremendous anthropogenic pressure with the consequence of their degradation. It is therefore necessary that the land resources must be managed effectively for sustainable development. Different from the developed countries, carbon inventories and data bank to monitor carbon sequestration potential of different ecosystems are unavailable in India. Micro-level studies are essential for sustainable land use management for a land scarce nation like India. To achieve the desirable goal of the present study, a total of 33 tree-based land uses were identified from forested and agricultural landscapes. Of these total land uses, five were in forest landscapes and rest in agricultural landscapes categorized into forest tree plantations (8 land uses), agroforestry (nine land uses), commercial crop plantations (six land uses) and fruit orchards (five land uses). A stratified random nested quadrate sampling method was adopted for vegetation analysis of the different land uses. The SOC, biomass and carbon accumulation in the tree-based land uses were significantly different from each other. Mixed forest soil had the highest amount of SOC, primary nutrients, standing biomass carbon, and ecosystem carbon. Positive correlations were observed between SOC, total standing biomass, litter production, and ecosystem carbon. The sequence of best tree based land uses in terms of total SOC (up to 60 cm depth), total plant biomass, total plant biomass carbon and ecosystem carbon was mixed species forest (126.67, 781.21, 390.61 and 517.27) > sole tree species stands in forest landscape (109.71, 192.56, 96.28 and 205.98) > tea plantations (103.19, 77.07, 38.54 and 141.74) > homegardens (90.34, 97.38, 48.69 and 139.02) > mixed plantation of Anthocephalus cadamba + Swietenia macrophylla (60.07, 111.86, 55.93 and 116.02) > Swietenia macrophylla based agroforestry (62.49, 83.82, 41.91 and 104.40) > mixed plantation of Tectona grandis + Milvus migrans (60.0, 85.97, 42.99 and 102.90). Similarly, the order of the major land uses was forest > commercial crop plantation > forest tree plantations > agroforestry > fruit orchards. The overall average ecosystem carbon accumulation in forests was 3.24 times more than the land uses in agricultural landscapes. The ecosystem carbon accumulation in the tree-based land uses in both forest and agricultural landscape was highly variable and was significantly different from each other. Land use conversion from forest to agriculture can reduce more than half of the carbon stock, but converting into homegardens, tree plantations or agroforestry enhanced carbon storage of the land use systems. The present findings can be used as baseline information for developing prediction models for probable effects of different land use, future intervention and sustainable management of land use systems.

Farm fragmentation is the occurrence of numerous and often discontinuous land parcels associated with a single farm. Farm fragmentation is considered to be a defining feature of Northern Ireland’s (NI) agricultural landscape, influencing agricultural efficiency, productivity, and the spread of livestock diseases. Despite this, the full extent of farm fragmentation in cattle farms is not well understood, and little is known of how farm fragmentation either influences, or is influenced by, different animal production types. This study describes and quantifies farm fragmentation metrics for cattle enterprises in NI, presented separately for dairy and non-dairy production types. We find that 35% of farms consist of five or more fragments, with larger farms associated with greater levels of farm fragmentation, fragment dispersal and contact with contiguous farms. Moreover, this was particularly evident in dairy farms, which were over twice the size of farms associated with non-dairy production types, with twice as many individual land parcels and twice as many fragments. We hypothesise that the difference in farm fragmentation and farm size between dairy and non-dairy production types is associated with the recent expansion of dairy farms after the abolition of the milk quota system in 2015, which may have driven the expansion of dairy farms via the acquisition of land. The high levels of land fragmentation, fragment dispersal and contiguous contact observed in NI cattle farms may also have important implications for agricultural productivity and epidemiology alike. Whilst highly connected pastures could facilitate the dissemination of disease, highly fragmented and parcellised land could also hamper productivity via diseconomies of scale, such as preventing the increase of herd sizes or additionally, adding to farm costs by increasing the complexity of herd management.

Land degradation is a critical issue globally putting our future generations at risk. The decrease in farm productivity over the years is evidence of land degradation severity in Nepal. Among the many strategies in place, agroforestry, which is an integrated tree-based farming, is widely recommended to address this productivity issue. This paper thoroughly examines what influences the choice of agroforestry adoption by farmers and what discourages the adoption. For this, a total of 288 households were surveyed using a structured questionnaire. Two agroforestry practices were compared with conventional agriculture with the help of the Multinomial Logistic Regression (MNL) model. The likelihood of adoption was found to be influenced by gender; the male-headed households were more likely to adopt the tree-based farming practice. Having a source of off-farm income was positively associated with the adoption decision of farmers. Area of farmland was found being the major constraint to agroforestry adoption for smallholder farmers. Some other variables that affected positively included livestock herd size, provision of extension service, home-to- forest distance, farmers’ group membership and awareness of farmers about environmental benefits of agroforestry. Irrigation was another adoption constraint that the study area farmers were faced with. The households with means of transport and with larger family (household) size were found to be reluctant towards agroforestry adoption. A collective farming practice could be a strategy to engage the smallholder farmers in agroforestry.

An all-weather land surface temperature (LST) product derived at the Satellite Application Facility on Land Surface Analysis (LSA-SAF) is presented. The product is based on clear-sky LST retrieved from MSG/SEVIRI infrared (IR) measurements, complemented by LST estimated with a land surface energy balance (EB) model to fill gaps caused by clouds. The EB model solves the surface energy balance mostly using products derived at LSA-SAF. The new product is compared with in situ observations made at 3 dedicated validation stations, and with a Microwave (MW) based LST product derived from AMSR-E measurements. The validation against in-situ LST indicates an accuracy of the new product between -0.8 K and 1.1 K and a precision between 1.0 K and 1.4 K, generally showing a better performance than the MW product. The EB model shows some limitations concerning the representation of the LST diurnal cycle. Comparisons with MW LST generally show higher LST of the new product over desert areas, and lower LST over tropical regions. Several other imagers provide suitable measurements for implementing the proposed methodology, which offers the potential to obtain a global, nearly gap-free LST product.

Droughts occurring more and more frequently in recent years are usually associated with progressive climate changes. Modern monitoring methods is mainly associated with agricultural use due to the high market demand for services protecting against agricultural losses. In natural wetland ecosystem this problem is neglected which is probably due to fact that this are ecosystems rich in water by definition. Nevertheless this droughts might become a problem of wetlands, whose good condition depends on adequate hydration. Therefore this study focused on determination Crop Water Stress Index (CWSI) for natural heterogeneous wetland habitats. CWSI based on remotely sensed land surface temperature and associated basic meteorological (air temperature and humidity) measurements. CWSI was calculated based on high resolution LST measurements from UAV platform and compare with on ground measurements of soil moisture, CCI, fAPAR and meteorological conditions. Results shows that CWSI properly shows water condition of plants in measured habitats and revels high importance of metrological conditions during data acquisition.

Abstract: The air pollution dispersion modelling via spatial analyses (Land Use Regression – LUR) is an alternative approach to the air quality assessment to the standard air pollution dispersion modelling techniques. Its advantages are mainly much simpler mathematical apparatus, quicker and simpler calculations and a possibility to incorporate other factors affecting pollutant’s concentration. The goal of the study was to model the PM10 particles dispersion modelling via spatial analyses v in Czech-Polish border area of Upper Silesian industrial agglomeration and compare results with results of the standard Gaussian dispersion model SYMOS’97. Results show that standard Gaussian model with the same data as the LUR model gives better results (determination coefficient 71% for Gaussian model to 48% for LUR model). When factors of the land cover and were included into the LUR model, the LUR model results were significantly improved (65% determination coefficient) to the level comparable with Gaussian model. The hybrid approach combining the Gaussian model with the LUR gives superior quality of results (65% determination coefficient).

Abstract: rainfall is the main driver of soil erosion. With the daily rainfall, riverine flow discharge and sediment load in the upper Lianjiang River watershed from 1990 to 2020, extreme rainfall events were defined by the 95th percentile method and minimum event interval time (MIT), change trends and mutations of yearly rainfall, riverine flow discharge and sediment load were identified using the Mann-Kendall test, then the optimum lag response time and antecedent rainfall were investigated with the multiple linear regression. The results showed that (1) the sediment changed significantly and abruptly in 1995 due to the expansion of the garden land. (2) Compared with ordinary rainfall, extreme rainfall events explained more variations of riverine flow and sediment with a higher degree, and had a more significant effect on the lag time of runoff and sediment. (3) Garden land expansion in extreme rainfall scenarios resulted in longer lag times for runoff and sediment and decreased demand for antecedent rainfall with more pre-event time. Therefore, taking the rainfall event as a breakthrough, analyzing the antecedent rainfall and the lag response of riverine flow discharge and sediment load is conducive to revealing the response mechanism of riverine flow discharge and sediment load and improving the simulation accuracy of riverine flow and sediment under extreme rainfall condition, thus help for the soil erosion control under extreme rainfall.

In order to explore the grassland ecosystem productivity and landscape ecological patterns of main pastoral grasslands in China, it provides a theoretical basis for the efficient implementation of ecological engineering and rational management of grassland resources in the region. This study analyzed the changes in grassland area, landscape index (LSI), and net primary productivity (NPP) in seven major pastoral areas in China in 1985, 1995, 2005, and 2015. Results showed that (1) the sizes of the grassland study area in 1985, 1995, 2005, and 2015 were 248.34, 243.93, 245.80, and 244.660 km2 respectively. (2) The dominance of grassland in the landscape pattern increased from 2005 to 2015 as compared with that in 1985–1995 and 1995–2005. The degrees of spatial heterogeneity were reduced. (3) The grassland NPP showed spatial and temporal differences. The average NPP of grassland increased by 21.30%, 16.47%, and 36.17% during 1985–1995, 2005–2015, and 1985–2015, respectively. From 1995 to 2005, the average NPP decreased by 5.05 gC/m2, which is equivalent to -3.61% of the average NPP in 1995. The total amount of grassland NPP in the study area was the greatest in 2015, showing increments of 36.37% and 16.61% compared with those in 1985 and 2005, respectively.

The rural population percentage decreased from 82.7% to 68.9% in 2011, even though there is an increase in the total rural population, which stands at 833.7 million, and the rural population were now more than three times compared to the population seven decades ago. Another observation is the decrease in cultivators percentage from 71.9% to 45.1 %, while agriculture labour increase from 28.1% to 54.9% during the same period. Despite the increase in irrigated land and net area sown, the average holdings' size under the farmers is continuously decreasing, and it requires a study to look into the reasons. The research probes the role of Minimum Support Price (MSP) in supporting farmers and measuring market price above MSP needed to help marginal and small farmers remain above the poverty level. It explains how different market rates above MSP have a different impact on different categories of agriculture landholding. The study works on developing a common model that relates the impact of MSP on different farmers categories. The model can be generalized to all crops and regions and useful in designing policies that focus on uplifting the income of agricultural farmers.

The Arctic freshwater budget is critical for understanding the climate in the northern regions. However, the hydrology of the Arctic circumpolar tundra region (ACTR) and the largest pan-Arctic rivers are still not well understood. In the present paper, we analyze the spatiotemporal variations in terrestrial water storage (TWS) of the ACTR, including three of its largest pan-Arctic river basins (Lena, Mackenzie, Yukon), using monthly Gravity Recovery and Climate Experiment (GRACE) data from 2002 to 2016. Together with global land reanalysis, river runoff, and inundation extent area (IEA) data, we identify declining TWS trends throughout the ACTR that we attribute largely to increasing evapotranspiration driven by increasing summer air temperatures. In terms of regional changes, large and significant negative trends in TWS are observed mainly over the North American continent. At basin scale, we show that, in the Lena River basin, the autumnal TWS signal persists until the winter of the following year, while in the Mackenzie River basin, the TWS levels in the autumn and winter has no significant impact on the following year. As global warming is expected to be particularly significant in the northern regions, our results are important for understanding future TWS trends, with possible further decline.

Interdisciplinary STEM and STEAM education give us an opportunity for creativity and educational innovation in a world scenario that needs training in which students can achieve all educational objectives and are prepared to achieve sustainable development. The rural environment with its land is a scenario that provides us with a range of educational resources for the development of STEM and STEAM projects in which students who are better trained and prepared for the needs of today's world are developed, as well as students who are more linked and sensitized to the environment, with the rural environment and its land, so important in our time.  In this article, we will collect examples from Latin America; STEM projects are being developed in which young people establish links with their environment, territory, and the local environment surrounding them. We must look carefully at projects and works in which students' ties with their land and environment are valued through the STEM and STEAM education necessary today. In this scenario, a comparison has been made between Latin American countries and Spain.

This study has simulated the typical rainstorm on 20 July 2021 over central east China by using the first-generation Chinese Reanalysis datasets and Global Land Data Assimilation System datasets, and the Noah land surface model coupled with the advanced weather research and forecasting model. Based on this, the gridded planetary boundary layer (PBL) profiles and ensemble states within soil perturbations are collected to investigate the main land-atmosphere coupling characteristics during this modeled rainstorm by using various local coupling metrics and the introduced ensemble statistical metrics. Results have shown that (1) except for the stratospheric thermodynamics and surface thermal over mountain areas, the main characteristics of mid-low layers and surface have been well documented in this modeled rainstorm; (2) the typical coupling intensity is characterized by the dominant morning moistening, early noon weak PBL warming around 2, noontime buoyant mixing temperature deficit around 274 K, daytime PBL and surface latent flux contribution around 100 and 280 W/m2 respectively, and significant afternoon soil-surface latent flux coupling; (3) moist static energy is more significant than PBL height during the relation chains, which is consistent with the significance of surface moistening indicated by local coupling metrics. In general, wet soil contributes greatly to daytime moisture evaporation, which then increases the early noon PBL warming and enhances the noontime buoyant mixing within weak flux contribution. However, this has been suppressed by large-scale forcing such as the upper southwestern inflows of rainstorms, which has further significantly shaped the spatial distribution of statistical metrics in contrast. These quantitatively described local couplings have highlighted both the convection potential diagnoses usage for the local weather application and more applicable coupling threshold diagnoses within the finer spatial investigation.

Land and property development process include a series of multifaceted activities ranging from purchasing to converting it for development purposes and everything in between. The process itself encompasses multiple stakeholders, drivers, and contributions from diversified public and private actors and transaction cost arises out of their complex interaction. Transaction costs incurred during any kind of human interactions (i.e. transactions). Every actor involved in the process wishes to maximize his achievement under various constraints and hence institutional arrangement (i.e. set of humanly devised rules to administer the constraints) is necessary for efficient management of the development process. Therefore, to devise an optimum outcome out of economic and social transactions in the property development process, cooperative and competitive relationships between individuals should be understood from a broader socio-political and governance structure. In this research, it is critically argued that land and property development process should implicate a multifaceted set of formal and informal rules or institutional arrangement to govern the intrinsic interaction, action and thereby reducing the related transaction cost. The argument is further reproachfully evaluated and implicated in the urban development process through the myopic lens of Transit-oriented development (TOD) pathway. A vigilant combination of descriptive and explanatory research approach is adopted to analyze the connection between theory and practice.

Threats to natural ecosystems are closely linked to human development, and the lack, insufficiency or inefficiency of public policies are some of the most important drivers of negative effects on the environment. The contribution of the IUCN’s Red List of Ecosystems (RLE) to conservation topics has been discussed in previous studies; however, to date its implications for conservation in public policies have not been addressed. This perspective discusses how the RLE may support the improvement and development of these policies, specifically through the implications for public policy of each of the criteria that substantiate the threat status of ecosystems. We aim to provide a plausible baseline to the operationalization of RLE in public and conservation policy, facilitating the work of governments, practitioners and decision makers. Finally, we provide recommendations and examples as to how to proceed in creating and modifying different public policy instruments, such as land-use planning, spatial zoning, tax reduction, compensation schemes, climate change adaptation plans, management of introduced species, development offsets and restoration investment. This perspective contributes to implement RLE into public policy and to improve ecosystem conservation by expanding the current scope of RLE into practical and political dimensions through plausible actions, policies and strategies.

In an era of rapid technological improvements, state-of-the-art methodologies and tools dedicated to protecting and promoting our cultural heritage should be developed and extensively employed in the contemporary built environment and lifestyle. At the same time, sustainability principles underline the importance of the continuous use of historic or vernacular buildings as part of the building stock of our society. Adopting a holistic, integrated, multi-disciplinary strategy can bridge technological innovation with conserving and restoring heritage buildings. The paper presents ongoing research and results of the application of Machine Learning methods for the remote monitoring of the built environment of the historic cluster in Cypriot cities. This study is part of an integrated, multi-scale, and multi-discipline study of heritage buildings towards the creation of an online HBIM platform for urban monitoring.

The development of dispersed urbanism in Spain ran parallel to the real estate boom and consolidated a new model of city sprawl based on the expansion of suburban areas. This process, which started in the mid 1980s, came to a halt with the onset of the economic crisis in 2007. With it, construction stopped, mobility fell and urban growth came to a standstill. The purpose of this article is to carry out an analysis of the recent evolution and chronology of the expansion of dispersed urbanism in the Barcelona Metropolitan Region (BMR) in order to gain an insight into some of the explanatory factors of such expansion and to deal with the future prospects of middle-term development of dispersed urbanism in the BMR and in Spain. To do this, we examine the trends in the housing market, in residential mobility and we take stock of the impact of business cycles. The conclusion is that dispersed areas retain their appeal in the stages of creation and expansion of households. For this reason, an effective economic recovery and a renewed rise in the price of housing in denser cities may contribute to an upturn in the popularity of the dispersed residential model, which nowadays could be considered to be in a ‘lethargic’ stage, waiting for certain factors to coincide and re-activate its expansion.

To investigate the dynamics of land surface temperature (LST) in Afghanistan in the period 2000-2021 and to assess the impact of such factors as soil moisture, precipitation, and vegetation coverage on it, remotely sensed soil moisture data from Land Data Assimilation System (FLDAS), precipitation data from Climate Hazards Group Infra-Red Precipitation with Station (CHIRPS), and NDVI and LST from Moderate Resolution Imaging Spectroradiometer (MODIS) were downloaded and correlations between them were analyzed using the regression method. The result shows that the LST in Afghanistan has a slightly decreasing, but insignificant trend during the study period (R=0.2, p-value=0.25), while vegetation coverage, precipitation, and soil moisture had an increasing trend. It was revealed that soil moisture has the highest impact on LST (R=0.7, p-value=0.0007), and the soil moisture, precipitation, and vegetation coverage explain almost 80% of spring (R2=0.73) and summer (R2=0.76) LST variability in Afghanistan. The LST variability analysis done separately for Afghanistan’s rivers subbasins shows that the LST of the Amu Darya subbasin had an upward trend in the study period, while for the Kabul subbasin the trend was downward.

Canada has committed to reducing greenhouse gas (GHG) emissions by increasing the non-emitting share of electricity generation to 90% by 2030. As solar energy costs have plummeted, agrivoltaics (co-development of solar photovoltaic (PV) systems and agriculture) provide an economic path to these goals. This study quantifies agrivoltaic potential in Canada by province using geographical information system analysis of agricultural areas and numerical simulations. Systems modeled would enable conventional farming of field crops to continue (and potentially increase yield) by using bifacial PV for single-axis tracking and vertical system configurations. Between a quarter (vertical) to more than one third (single axis tracking) of Canada’s electrical energy needs can be provided solely by agrivoltaics using only 1% of current agricultural lands. These results show that agrivoltaics could be a major contributor to sustainable electricity generation and provide the ability for Canada to render the power generation sector net zero/GHG emission free. It is clear that the potential of agrivoltaic-based solar energy production in Canada far outstrips current electric demand and can thus be used to electrify and decarbonize transportation, heating, expand economic opportunities by powering the burgeoning computing sector, and export green electricity to the U.S. to help eliminate their dependence on fossil fuels.

Understanding how industrial agglomeration affects agricultural green production efficiency is essential for green agricultural development. This study uses the super-efficient EBM-GML to measure and analyze the spatial and temporal evolution characteristics and core sources of dynamics of agricultural green production efficiency in China by using panel data from 30 Chinese provinces from 2006 to 2020. It also empirically investigates the relationships between industrial agglomeration, land transfer, and agricultural production efficiency. By using fixed, intermediary, and threshold effects models, the internal links between the industrial agglomeration, land transfer, and agricultural green production efficiency are examined. The findings indicate that the green production efficiency of Chinese agriculture exhibits the regional characteristics of being “high in the west and low in the east, high in the south and low in the north” in terms of space; in terms of time series, the overall trend is that of growing, with an average annual growth rate of 11.45%, and the growth primarily depends on the “single-track drive” of green technological progress. By promoting land transfer, industrial agglomeration can increase the agricultural green production efficiency and decomposition index. Land transfer has a double-threshold effect on the influence of industrial agglomeration on agricultural green production efficiency. As a result, this study suggests adhering to the idea of synergistic development, promoting agricultural green development, strengthening the development of industrial agglomerations, promoting the quality and efficiency of industry, improving land-transfer mechanisms, and placing a focus on resource efficiency improvements, as well as other policy recommendations.

The notion that ‘Stock-G’ humpback whales off western South America are primarily deep oceanic migrators is poorly supported. We documented 66 land-based sightings from Pucusana, Lima Sur: 18 incidental (2002–2023) and 48 dedicated sightings during the northbound winter migration (June-July 2023), covering respectively 38 and 105 individual whales, despite a mean daily observer effort of only 58.7 min. Estimated distances from shore ranged 20–7,000 m (mean= 2,729 m) at depths 25–99 m, while 50% migrated at < 2,500 m (median) from shore. Several groups skirted the coastline from headland to headland. Of five southbound migrating groups, four included an adult with neonate; no northbound groups enclosed a neonate. Two cases of single juvenile/subadult whales moving multidirectionally and closely associated with large seabird feeding frenzies, were considered foraging also. In 2023, 94% of all northbound nearshore sightings occurred from 14 June-11 July, signalling the maximum threat period for interactions with coastal fisheries off metropolitan Lima. If migration is temporally and spatially predictable, effective mitigating measures should be feasible.

Over the last several decades, large wildfires are increasingly common across the United States causing disproportionate impact on forest health and function, human well-being, and economy. Here, we examine the severity of large wildfires across the Contiguous United States over the past decade (2011-2020) using a wide array of meteorological, vegetational, and topographical features in the Deep Neural Network model. A total of 4,538 wildfire incidents were used in the analysis covering 87,305 square miles of burned area. We observed the highest number of large wildfires in California, Texas, and Idaho, with lightning causing 43 % of these incidents. Importantly, results indicate that the severity of wildfire occurrences is highly correlated with the climatological forcings, land cover, location, and elevation of the ecosystem. Overall, results may serve useful guide in managing landscapes under changing climate and disturbance regimes.

Water scarcity is a key challenge to global development. In Brazil, the Sao Francisco River Basin (SFB) has experienced water scarcity problems because of decreasing streamflow and increasing demands from multiple sectors. However, the drivers of decreased streamflow, particularly the potential role of surface-groundwater interaction, have not been yet investigated. Here, we assess long-term trends in baseflow, quickflow, and streamflow of the SFB during 1980–2015 and constrain the most likely drivers of observed decreases through trend analysis of precipitation (P), evapotranspiration (ET), and terrestrial water storage change (TWS). We found that over 82% of the observed decrease in streamflow can be attributed to a significant decreasing baseflow trend (< -20 m3 s-1 y-1) along the SFR with spatial agreement between decreased baseflow, increased ET, and irrigated agricultural land. We also noted a decrease in TWS across the SFB with trends exceeding -20 mm y-1. Overall, our findings indicate that decreasing groundwater contributions (i.e., baseflow) is providing the observed reduction in total SFR flow. A lack of significant P trends indicates that only P variability likely has not caused the observed baseflow reduction, mainly in the Middle and Sub-middle SFB. Therefore, groundwater and surface withdrawals may be likely a driver of water scarcity over the SFB.

As the EU is moving towards a low carbon economy and seeks to further develop its renewable energy policy, this paper quantitatively investigates the impact of plausible energy market reforms from the perspective of bio-renewables. Employing a state-of-the-art biobased variant of a computable general equilibrium model, this study assesses the perceived medium-term benefits, risks and trade-offs which arise from an advanced biofuels plan, two exploratory scenarios of a more 'sustainable' conventional biofuels plan and a 'no-mandate' scenario. Consistent with more recent studies, none of the scenarios considered present significant challenges to EU food-security or agricultural land usage. An illustrative advanced biofuels plan simulation requires non-trivial public support to implement whilst a degree of competition for biomass with (high-value) advanced biomass material industries is observed. On the other hand, it significantly alleviates land use pressures, whilst lignocellulose biomass prices are not expected to increase to unsustainable levels. Clearly, these observations are subject to assumptions on technological change, sustainable biomass limits, expected trends in fossil fuel prices and EU access to third-country trade. With these same caveats in mind, the switch to increased bioethanol production does not result in significant market tensions in biomass markets.

Economic valuations of ecosystem services often transfer previously estimated global unit values to the geographical setting of interest. While this approach produces quick results, its reliability depends on how representative the large-scale average unit values are for the given local context. Here, we estimate the values of three ecosystem services (ES) – water filtration, nutrient cycling and carbon sequestration – in the Grand River watershed (GRW) of southern Ontario, Canada. The watershed covers nearly 7000 km2, has a humid continental climate and a population of close to one million people. Land cover is dominated by agriculture. We compare ES valuations using locally derived (i.e., GRW-specific) unit values to valuations based on unit values from a regional database and those compiled in the global Ecosystem Services Valuation Database (ESVD). The regional database includes mean unit values from three case studies within southern Ontario and one boreal watershed in British Columbia. As expected, the regional database yields average monetary values for the three ES that are close to those obtained with the local unit values but with larger associated uncertainties. Using the ESVD, however, results in significantly higher monetary values for the ES. For water filtration, the ESVD value is more than five times higher than the regional and local estimates. We further illustrate the effect of the extent of aggregation of forested and agricultural land categories on the ES values. For example, by subdividing the forest category into three sub-categories (deciduous, coniferous, and mixed forest), the estimated value of the carbon sequestration ES of forested areas within the GRW increases by 15%. Overall, our results emphasize the importance of critically assessing the origin of unit values and the land cover resolution in ES valuation, especially when the latter is used as a policy-guiding tool.

Section 25(2) of the Constitution of South Africa protects property rights and the White Paper on Land Reform demonstrate tolerance and wisdom in the application of land reform policies. The central argument to this research was whether amendment of Section 25 (2) of the constitution to allow expropriation of land without compensation redresses redistribution of land for social cohesion and political stability. The researcher argues that, currently, Section 25 of the constitution provides for expropriation without compensation but at the same time protects property rights reducing the pace of redistribution. Hence, an amendment of section 25 (2) may remove the property right clause and accelerate expropriation without compensation. But whether the removal of the property right clause and acceleration of the process of expropriation without compensation will result to equitable and fair distribution of land to the majority of landless South Africans is not certain. The study concludes that, amendment of Section 25(2) is a justifiable process and priorities must be given to equity in redistribution to the majority landless at the margins of communities and not elites. If the amendment of Section 25 (2) cannot guarantee equity in redistribution for all ill respective of race, social cohesion, political stability and economic growth, intra-racial tensions may emerge. Such tensions may further compound the land question and affects investors’ confidence in South Africa.

The foundation for accurately understanding regional land-use structures and pursuing the coordination of human–land relations is the scientific identification and simulation of temporal and spatial evolution patterns of land-use spatial conflict (LUSC). Taking the Yimengshan Geopark (YG) as an example, based on the productional–living–ecological space (PLES) perspective, which constructs a land-use spatial conflict identification and intensity diagnosis model (LUCSII) using the landscape ecology index. We apply geographic information system (GIS) and other methods to achieve the spatial pattern of LUSC over the last 20 years, and we use the GMOP–Markov–PLUS model to simulate the evolution of LUSC in the future under various scenarios. From 2000 to 2020, the LUSC values in the YG were mainly stable and controllable, with mild conflict, while the areas of severe conflict were mainly concentrated in the central urban area of Mengyin County and in low and flat terrain areas such as southern Bailin Town. The LUSC in the YG showed a significant positive spatial correlation, and spatial agglomeration is gradually strengthening. The high–high clusters are found in contiguous areas at the junction of Changlu Town, Gaodu Town, and Mengyin Street, as well as in the southern hilly areas. The low–low clusters were concentrated in Yedian Town, Daigu Town inarea north of the study, and areas surrounding Yunmeng Lake Wetland Park. In the next ten years, the ecological priority scenario (EPD) and sustainable development scenario (ESD) will both be reasonable options for easing and controlling LUSC in YG. Local governments and park management bureaus should determine the three lines and three zones based on the needs of social and economic development, particularly the boundary red line for construction land growth, and plan production and living spaces to alleviate land-use conflicts and stabilize the land-use system. Regional ecological security can be maintained, and future deterioration of the park’s ecological environment avoided, by performing well in terms of ecological isolation.

Abstract: Spatially explicit, fine-grained datasets describing historical urban extents are rarely available prior to the era of operational remote sensing. However, such data are necessary to better understand long-term urbanization and land development processes and for the assessment of coupled nature-human systems, e.g., the dynamics of the wildland-urban interface. Herein, we propose a framework that jointly uses remote sensing derived human settlement data (i.e., the Global Human Settlement Layer, GHSL) and scanned, georeferenced historical maps to automatically generate historical urban extents for the early 20th century. By applying unsupervised color segmentation to the historical maps, spatially constrained to the urban extents derived from the GHSL, our approach generates historical settlement extents for seamless integration with the multi-temporal GHSL. We apply our method to study areas in countries across four continents, and evaluate our approach for two U.S. study sites against historical settlement extents derived from the Historical Settlement Data Compilation for the US, HISDAC-US, achieving Area-under-the-Curve values >0.9. Our results are largely in agreement with model-based urban areas from the HYDE database, and demonstrate that the integration of remote sensing derived observations and historical cartographic data sources opens up new, promising avenues for assessing urbanization, and long-term land cover change in countries where historical maps are available.

A land cover map of two arctic catchments, nearby the Abisko Scientific Research Station, was obtained from a classification of a Sentinel-2 satellite image and a ground survey performed in July 2022. The two contiguous catchments, Miellajokka and Stordalen, are covered by various ecotypes, from boreal forest to alpine tundra and peatland. Two classification algorithms, support vector machine and random forest, were tested and gave very similar results. The percentage of correctly classified pixels was over 88% in both cases. The developed workflow relies solely on open source software and acquired ground observations. Space organization was directed by the altitude as demonstrated by the intersection of the land cover with the topography. Comparison between this new land cover map and previous ones based on data acquired between 2008 and 2011 shows some trends of vegetation cover evolution in response to climate change in the considered area. This land cover map is key input data for permafrost modeling, and hence for the quantification of climate change impacts in the studied area.

Decision tables have been used for many years in data processing and business applications to simulate complex rule sets. Several computer languages have been developed based on rule systems and they are easily programmed in several current languages. Land management and river-reservoir models simulate complex land management operations and reservoir management in highly regulated river systems. Decision tables are a precise yet compact way to model the rule sets and corresponding actions found in these models. In this study, we discuss the suitability of decision tables to simulate management in the river basin scale Soil and Water Assessment Tool (SWAT+) model. Decision tables are developed to simulate automated irrigation and reservoir releases. A simple auto irrigation application of decision tables was developed using plant water stress as a condition for irrigating corn in Texas. Sensitivity of the water stress trigger and irrigation application amounts were shown on soil moisture and corn yields. In addition, the Grapevine Reservoir near Dallas, Texas was used to illustrate the use of decision tables to simulate reservoir releases. The releases were conditioned on reservoir volumes and flood season. The release rules as implemented by the decision table realistically simulated flood releases as evidenced by a daily NSE (Nash-Sutcliffe Efficiency) of 0.52 and a percent bias of -1.1%. Using decision tables to simulate management in land, river and reservoir models was shown to have several advantages over current approaches including: 1) mature technology with considerable literature and applications, 2) ability to accurately represent complex, real world decision making, 3) code that is efficient, modular and easy to maintain, and 4) tables that are easy to maintain, support, and modify.

Multiple social and environmental justice concerns are linked to urban form such as the distribution of socioeconomic class populations, healthcare spending, air pollution exposure, and human mobility. This study used 1m resolved LIDAR data to characterize land use in Salt Lake County, Utah and associate it with sociodemographic and air quality data at the census block group and zip code levels. We found that increasing tree cover was associated with higher per capita income and lower minority populations while increasing built cover was linked to lower per capita income and higher minority populations. Air quality showed less strong correlations, however, decreased non irrigated cover, increased built cover, and higher amounts of households living under poverty was related to higher long-term PM2.5 exposure. Several policy efforts have been undertaken to improve air quality and reduce negative health outcomes in Utah which are being informed by regulatory and research grade air quality sensors.

The key to simulating soil erosion is to calculate the vegetation cover (C) factor. Methods that apply remote sensing to calculate C factor at regional scale cannot directly use the C factor formula. That is because the C factor formula is obtained by experiment, and needs the coverage ratio data of croplands, woodlands and grasslands at standard plot scale. In this paper, we present a C factor conversion method from a standard plot to a km-sized grid based on large sample theory and multi-scale remote sensing. Results show that: 1) Compared with the existing C factor formula, our method is based on the coverage ratio of croplands, woodlands and grasslands on a km-sized grid, takes the C factor formula obtained from the standard plot experiment and applies it to regional scale. This method improves the applicability of the C factor formula, and can satisfy the need to simulate soil erosion in large areas. 2) The vegetation coverage obtained by remote sensing interpretation is significantly consistent (paired samples t-test, t = −0.03, df = 0.12, 2-tail significance p < 0.05) and significantly correlated with the measured vegetation coverage. 3) The C factor of the study area is smaller in the middle, southern and northern regions, and larger in the eastern and western regions. The main reason for that is the distribution of woodlands, the Hunshandake and Horqin sandy lands and the valleys affected by human activities. 4) The method presented in this paper is more meticulous than the C factor method based on the vegetation index, improves the applicability of the C factor formula, and can be used to simulate soil erosion on large scale and provide strong support for regional soil and water conservation planning.

With the pressure of the increasing density of urban areas, some public infrastructures are moving to the underground to free up space above, such as utility lines, rail lines and roads. In the big data era, the three dimensional (3D) data can be beneficial to understand the complex urban area. Comparing to spatial data and information of the above ground, we lack of the precise and detailed information about underground infrastructures, such as the spatial information of underground infrastructure, the ownership of underground objects and the interdependence of infrastructures in the above and below ground. How to map reliable 3D underground utility networks and use it in the land administration? First, to explain the importance of this work and find a possible solution, this paper observes the current issues of the existing underground utility database in Singapore. A framework for utility data governance is proposed to manage the work process from the underground utility data capture to data usage. This is the backbone to support the coordination of different roles in the utility data governance and usage. Then, an initial design of the 3D underground utility data model is introduced to describe the 3D geometric and spatial information about underground utility data and connect it to the cadastral parcel for land administration. In the case study, the newly collected data from mobile Ground Penetrating Radar is integrated with the existing utility data for 3D modelling. It is expected to explore the integration of new collected 3D data, the existing 2D data and cadastral information for land administration of underground utilities.

Small-scale fisheries are significant sources of nutrition and livelihood globally. However, increasing anthropogenic activities in coastal areas of developing countries have threatened the sustainability of artisanal fisheries and species. Fisheries of Sardinella maderensis (Lowe, 1838), to which Nigeria contributes 9% of the global stock and is a significant livelihood source in the coastal communities of Ibeju-Lekki, Lagos, face sustainability threats. This research investigated the effects of anthropogenic activities on S. maderensis fishery in the coastal areas of Ibeju-Lekki, Lagos, Nigeria. The study adopted a mixed-method approach involving qualitative and quantitative research methods. These include species identification, water quality analysis, land use change analysis, field surveys, focus group discussions and interviews. Results show genetic analysis of the fish samples from six stations revealed that the species had a mean of 98% similarity to Sardinella maderensis in NCBI. Multiple linear regression indicates that anthropogenic variables explained approximately 4.62% of the variance in the fish catch (p &lt; .001, R2 = .05). Water samples showed heavy metal levels were above international limits, high total petroleum hydrocarbon (TPH) pollution in all stations (27.56 mg/L- 3985.40 mg/L). Physiochemical analysis of water samples indicated TDS higher than acceptable limits (Mean = 24971.1 mg/L) and inadequate chlorophyll-a level (Mean = 0.01 µg/L). Hence, urgent strategies are required to mitigate anthropogenic threats through inclusive coastal management policies supporting resilient artisanal fisheries and marine spatial planning.

Mining for resources extraction may lead to several geological and associated environmental changes due to ground movements, collision with mining cavities and deformation of aquifers. Geological changes may continue in a reclaimed mine area, and the deformed aquifers may entail a breakdown of substrates and an increase in ground water tables, which may cause surface area inundation. Consequently, a reclaimed mine area may experience surface area collapse, i.e. subsidence, and degradation of vegetation health. Thus, monitoring short-term landscape dynamics in a reclaimed mine area may provide important information on the long-term geological and environmental impacts of mining activities. We studied landscape dynamics in Kirchheller Heide, Germany, which experienced extensive soil movement due to longwall mining without stowing, using Landsat imageries between 2013 and 2016. A Random Forest image classification technique was applied to analyse land-use and land-cover dynamics and the growth of wetland areas was assessed using a Spectral Mixture Analysis (SMA). We also analyzed the changes in vegetation health using a Normalized Difference Vegetation Index (NDVI). We observed a 19.9% growth of wetland area within the four years with 87.2% of growth in the coverage of two major waterbodies in the reclaimed mine area. NDVI values indicate that 66.5% of the vegetation of the study area was degraded due to changes in ground water tables and surface flooding. Our results inform environmental management and mining reclamation authorities about the subsidence spots and priority mitigation areas from land surface and vegetation degradation in Kirchheller Heide.

Japan has the world’s largest old population ratio, and aging is an urgent societal issue. As global trends seem to be following Japan’s social changes, there is an emphasis on municipalities becoming more age-friendly. Hence, we examine the age-friendliness of 135 Japanese municipalities, selecting 240 resident architectural designers and constructors to assess their municipalities, using the Age-Friendly Cities and Communities Questionnaire (AFCCQ). The findings indicate that Japan lacks “outdoor spaces and buildings.” Additionally, the evaluation of “housing,” “community support and health services,” and “transportation” in populated municipalities in the past five years is significantly higher than those in depopulated ones. Age-friendliness is significantly affected in the AFCCQ total score (hereafter, Score) based on “housing,” “social participation,” “community support and health services,” “transportation” and “financial situation” evaluations. High specificity (0.939) was found when the Score was treated as a marker of depopulation and, therefore, an age-friendly approach is a necessary condition to prevent depopulation. Furthermore, a lack of “communication and information” is observed in municipalities with a higher rate of single-person households aged 65 years and above. Therefore, resident architectural designers’ and constructors’ assessments, combined with the AFCCQ can be a powerful tool in evaluating the age-friendliness of municipalities.

Pollinators are being threatened globally by urbanisation and agricultural intensification, driv-en by a growing human population. Understanding these impacts on landscapes and pollinators is critical to ensuring a robust pollination system. Remote sensing data on land use attributes have previously linked honeybee nutrition to land use in the Western Honeybee (Apis mellifera L.). Here, we instead focus on the less commonly studied Apis cerana japonica – the Japanese Honeybee. Our study presents preliminary data comparing forage (honey and pollen) with land use across a rural-urban gradient from 22 sites in Kyushu, southern Japan. Honey samples were collected from hives between June 2018 and August 2019. Pollen were collected and biotyped from hives in urban and rural locations (n = 4). Previous studies of honey show substantial vari-ation in monosaccharide content. Our analysis of A. cerana japonica honey found very little varia-tion in glucose and fructose (which accounted for 97% of monosaccharides), despite substantial differences in surrounding forage composition. As expected, we observed temporal variation in pollen foraged by A. cerana japonica, likely dependent on flowering phenology. These prelimi-nary results suggest that the forage and nutrition of A. cerana japonica may not be negatively af-fected by urban land use. This highlights the need for further comparative studies between A. cerana japonica and A. mellifera as it could suggest a resilience in pollinators foraging in their na-tive range.

The land-surface developments of the European Centre for Medium-range Weather Forecasts (ECMWF) are based on the Carbon-Hydrology Tiled Scheme for Surface Exchanges over Land (CHTESSEL) and form an integral part of the Integrated Forecasting System (IFS), supporting a wide range of global weather, climate and environmental applications. In order to structure, coordinate and focus future developments and benefit from international collaboration in new areas, a flexible system named ECLand which would facilitates modular extensions to support numerical weather prediction (NWP) and society-relevant operational services, e.g. Copernicus, is presented . This paper introduces recent examples of novel ECLand developments on (i) vegetation, (ii) snow, (iii) soil, (iv) open water/lake (v) river/inundation, and (vi) urban areas. The developments are evaluated separately with long-range, atmosphere-forced surface offline simulations, and coupled land-atmosphere-ocean experiments. This illustrates the benchmark criteria for assessing both, process fidelity with regards to land surface fluxes and reservoirs of the water-energy-carbon exchange on the one hand, and on the other hand the requirements of ECMWF’s NWP, climate and atmospheric composition monitoring services using an Earth system assimilation prediction framework.

Surface urban heat island (SUHI) depicts the deteriorating thermal environment in high-density cities and local climate zone (LCZ) classification provides a universal protocol for SUHI identification. In this study, taking the central urbanized area of Guangzhou in the humid subtropical region of China as the study area, the maps or images of LCZ, land surface temperature (LST), SUHI and urban design factors were achieved by using Landsat satellite data, GIS database and a series of retrieval and classification algorithms, and the urban design factors influencing SUHI were investigated based on 625 samples of LCZs. The results show that in the summer daytime under the clear sky condition, the LST varied greatly from 26 °C to 40 °C and the SUHI changed in a wide range of -6 °C to 8 °C in the LCZs of the study area. Seven and five urban design factors influencing the summer daytime SUHI were identified for the two dominant LCZ of LCZs 1-5 (LCZ 1 to LCZ 5) and the mixed LCZ (containing at least three types of LCZs), respectively. The summer daytime SUHI prediction models were obtained by using the step-wise multiple linear regression, with the performance of R2 of 0.697, RMSE of 1.21 °C, and the d value of 0.81 for the model of LCZs 1-5, and the values of 0.666, 1.66 °C, and 0.76 for the model of the mixed LCZ, indicating that the models can predict the changes of SUHI with LCZs to a large and satisfactory extent. This study presents a methodology to efficiently achieve a large sample of SUHI and urban design factors of LCZs in the largely urbanized cities, and provides information beneficial to the urban designs and regenerations in the humid subtropical region.

The research carried out concerned the laboratory assessment of the applicability of the Crop Water Stress Index (CWSI) as a practical tool for assessing the risk of desiccation for selected wetland habitats: transition mires and quaking bogs as well as alkaline fens. The analysis was carried out on 3 soil samples with a vegetation cover (with the dimensions of 40×40×30 cm) collected during the full vegetation season for each mentioned habitat, with a characteristic species composition. Experimental research was carried out between 17^th May 2018 and 19^th June 2018. Thermal, RGB and multispectral images, chlorophyll content, volumetric soil moisture, air temperature and relative humidity measurements were taken for each sample every two days. The obtained results clearly indicate the dependence between CWSI and plant condition parameters in the first phase of desiccation. At the same time, as a result of the observations taken, thresholds have been set, indicating different desiccation phases.

Land cover change detection (LCCD) based on bi-temporal remote sensing images plays an important role in the inventory of land cover change. Due to the benefit of having spatial dependency properties within the image space while using remote sensing images for detecting land cover change, many contextual information based change detection methods have been proposed during past decades. However, there is still a space for improvement in accuracies and usability of LCCD. In this paper, a LCCD method based on adaptive contextual information is proposed. First, an adaptive region is constructed by gradually detecting the spectral similarity surrounding a central pixel. Second, the Euclidean distance between pairwise extended regions is calculated to measure the change magnitude between the pairwise central pixels of bi-temporal images. While the whole bi-temporal images are scanned pixel-by-pixel, the change magnitude image (CMI) can be generated. Then, the Otsu or a manual threshold is employed to acquire the binary change detection map (BCDM). The detection accuracies of the proposed approach are investigated by two land cover change cases with Landsat bi-temporal remote sensing images. In comparison to several widely used change detection methods, the proposed approach can achieve a land cover change inventory map with a competitive accuracy.