Jotisankasa, A.; Torsri, K.; Supavetch, S.; Sirirodwattanakool, K.; Thonglert, N.; Sawangwattanaphaibun, R.; Faikrua, A.; Peangta, P.; Akaranee, J. Investigating Correlations and the Validation of SMAP-Sentinel L2 and In Situ Soil Moisture in Thailand. Sensors2023, 23, 8828.
Jotisankasa, A.; Torsri, K.; Supavetch, S.; Sirirodwattanakool, K.; Thonglert, N.; Sawangwattanaphaibun, R.; Faikrua, A.; Peangta, P.; Akaranee, J. Investigating Correlations and the Validation of SMAP-Sentinel L2 and In Situ Soil Moisture in Thailand. Sensors 2023, 23, 8828.
Jotisankasa, A.; Torsri, K.; Supavetch, S.; Sirirodwattanakool, K.; Thonglert, N.; Sawangwattanaphaibun, R.; Faikrua, A.; Peangta, P.; Akaranee, J. Investigating Correlations and the Validation of SMAP-Sentinel L2 and In Situ Soil Moisture in Thailand. Sensors2023, 23, 8828.
Jotisankasa, A.; Torsri, K.; Supavetch, S.; Sirirodwattanakool, K.; Thonglert, N.; Sawangwattanaphaibun, R.; Faikrua, A.; Peangta, P.; Akaranee, J. Investigating Correlations and the Validation of SMAP-Sentinel L2 and In Situ Soil Moisture in Thailand. Sensors 2023, 23, 8828.
Abstract
Soil moisture plays a crucial role in various hydrological processes and energy partitioning of the global surface. The Soil Moisture Active Passive-Sentinel (SMAP-Sentinel) remote sensing technology has demonstrated a great potential in monitoring soil moisture at a scale greater than 1 km. This capability can be applied to improve weather forecast accuracy, enhance water management for agriculture, and climate-related disasters. Despite the techniques increasing used worldwide, its accuracy still requires field validation in specific regions like Thailand. In this paper, we report on extensive in-situ monitoring of soil moisture (from surface up to 1 m depth) at 10 stations across Thailand spanning the years 2021 to 2023. The aim was to validate SMAP surface soil moisture (SSM) Level 2 product over a period of two years. Using one month averaging approach, the study revealed linear relationships between the two measurement types, with the coefficient of determination (R-squared) varying from 0.13 to 0.58. Notably, areas with more uniform land use and topography such as croplands tended to have a better coefficient of determination. We also conducted detailed soil core characterization, including soil-water retention curves, permeability, porosity, and other physics properties. These soil properties were then used for estimating the correlation constants between SMAP and in-situ soil moistures using multiple linear regression. The results demonstrated R-squared values between 0.933 and 0.847. An upscaling approach of SMAP was proposed which showed a promising results when using 3-month average of all measurements in cropland together. The finding also suggest that the SMAP-Sentinel remote sensing technology exhibits significant potential for accurate soil moisture monitoring in diverse applications. Further validation efforts and research, particularly in terms of root zone depths and area-based assessments, especially in the agricultural sector, can greatly improve the technology’s effectiveness and usefulness in the region.
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.
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