Version 1
: Received: 16 July 2024 / Approved: 16 July 2024 / Online: 16 July 2024 (10:39:27 CEST)
How to cite:
Sun, J.; Tang, C.; Mu, K.; Li, Y.; Zheng, X.; Zou, T. Tidal Flat Extraction and Analysis in China Based on Multi-source Remote Sensing Image Collection and MSIC-OA Algorithm. Preprints2024, 2024071304. https://doi.org/10.20944/preprints202407.1304.v1
Sun, J.; Tang, C.; Mu, K.; Li, Y.; Zheng, X.; Zou, T. Tidal Flat Extraction and Analysis in China Based on Multi-source Remote Sensing Image Collection and MSIC-OA Algorithm. Preprints 2024, 2024071304. https://doi.org/10.20944/preprints202407.1304.v1
Sun, J.; Tang, C.; Mu, K.; Li, Y.; Zheng, X.; Zou, T. Tidal Flat Extraction and Analysis in China Based on Multi-source Remote Sensing Image Collection and MSIC-OA Algorithm. Preprints2024, 2024071304. https://doi.org/10.20944/preprints202407.1304.v1
APA Style
Sun, J., Tang, C., Mu, K., Li, Y., Zheng, X., & Zou, T. (2024). Tidal Flat Extraction and Analysis in China Based on Multi-source Remote Sensing Image Collection and MSIC-OA Algorithm. Preprints. https://doi.org/10.20944/preprints202407.1304.v1
Chicago/Turabian Style
Sun, J., Xiangyang Zheng and Tao Zou. 2024 "Tidal Flat Extraction and Analysis in China Based on Multi-source Remote Sensing Image Collection and MSIC-OA Algorithm" Preprints. https://doi.org/10.20944/preprints202407.1304.v1
Abstract
As an important part of coastal wetlands, tidal flats provide unique ecosystem services and functions. China's tidal flats are significantly threatened by industrialization, urbanization, aquaculture expansion and coastline reconstruction, and there is an urgent need for sustainable strategies to balance the protection and utilization of tidal flats. Remote sensing technology can realize large-scale spatiotemporal research of tidal flats, comprehensively improve the ecological environment of coastal zones, and help achieve the overall planning goals of major projects for the protection and restoration of important ecosystems in China. In this study, based on GEE (Google Earth Engine) platform, Sentinel-2 (MSI), Landsat 8 (OLI) and Landsat 9 (OLI-2) remote sensing images were used to construct multi-source intensive time series remote sensing image collection, combined with MSIC-OA algorithm. The tidal flat data of China in 2018 and 2023 are extracted and analyzed. The results show as follows: 1) The overall classification accuracy of the tidal flat in 2023 is 95.19%, and the Kappa coefficient is 0.89; In 2018, they were 92.77% and 0.83 respectively. 2) The total tidal flat area in 2018 and 2023 is 8300.34km2 and 8151.54km2, respectively, a decrease of 148.80km2; 3) In 2023, estuarine and bay tidal flats will account for 54.88% of the total area, and most of the tidal flats will be distributed near river inlets and bays; 4) In 2023, the total length of the coastline adjacent to the tidal flat is 10196.17km, of which the artificial shoreline accounts for 67.06%, and the development degree of the tidal flat is 2.04, indicating that most of the tidal flat has been developed and utilized. The research results provide valuable reference for the scientific planning and rational utilization of tidal flat resources in China.
Keywords
remote sensing; Google Earth Engine; MSIC-OA; tidal flat resources; shoreline
Subject
Environmental and Earth Sciences, Remote Sensing
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
