Validation of the NISAR Multi-Scale Soil Moisture Retrieval Algorithm across Various Spatial Resolutions and Landcovers Using the ALOS-2 SAR Data
High-resolution soil moisture data are essential for numerous geophysical applications, enabling improved decision-making in environmental and resource management. However, current satellite-derived global soil moisture products suffer from coarse spatial resolution, limiting their utility. The upco...
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American Association for the Advancement of Science (AAAS)
2025-01-01
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| Series: | Journal of Remote Sensing |
| Online Access: | https://spj.science.org/doi/10.34133/remotesensing.0729 |
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| author | Preet Lal Gurjeet Singh Narendra N. Das Rowena B. Lohman |
| author_facet | Preet Lal Gurjeet Singh Narendra N. Das Rowena B. Lohman |
| author_sort | Preet Lal |
| collection | DOAJ |
| description | High-resolution soil moisture data are essential for numerous geophysical applications, enabling improved decision-making in environmental and resource management. However, current satellite-derived global soil moisture products suffer from coarse spatial resolution, limiting their utility. The upcoming NASA-ISRO SAR (NISAR) mission, set for launch in July 2025, aims to overcome this limitation by providing high-resolution soil moisture data at 200 [m]. One of the mission’s key approaches is the multi-scale algorithm, which enhances coarse-resolution data by incorporating fine-scale synthetic aperture radar (SAR) observations. While initial validation of this algorithm has been conducted over cropland, a broader evaluation is needed across various land covers and climates to ensure its robustness. This study investigates the performance of soil moisture retrieval across 5 diverse test sites, covering forest, shrubland, cropland, and grassland environments, as well as hydrometeorological conditions ranging from arid to polar. The algorithm was assessed at 100 [m] and 200 [m] resolutions, revealing consistent moisture patterns, with the finer resolution offering greater detail. Validation using in situ measurements showed that the unbiased root mean square error was less than 0.06 [m3/m3] for most sites, matching NISAR’s accuracy requirements. A wet bias was observed, and challenges emerged at a polar site due to organic soil. A minimum performance test was conducted to evaluate the impact of SAR backscatter measurements. The results demonstrate that these measurements contribute to improving the accuracy of high-resolution soil moisture retrieval using a multi-scale algorithm. Overall, the study highlights the algorithm’s capability to retrieve soil moisture at high resolution, reinforcing its suitability for the NISAR mission. |
| format | Article |
| id | doaj-art-3b8a3d56c4c343debbc68150230b7659 |
| institution | Kabale University |
| issn | 2694-1589 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | American Association for the Advancement of Science (AAAS) |
| record_format | Article |
| series | Journal of Remote Sensing |
| spelling | doaj-art-3b8a3d56c4c343debbc68150230b76592025-08-20T03:30:39ZengAmerican Association for the Advancement of Science (AAAS)Journal of Remote Sensing2694-15892025-01-01510.34133/remotesensing.0729Validation of the NISAR Multi-Scale Soil Moisture Retrieval Algorithm across Various Spatial Resolutions and Landcovers Using the ALOS-2 SAR DataPreet Lal0Gurjeet Singh1Narendra N. Das2Rowena B. Lohman3Department of Civil and Environmental Engineering, Michigan State University, East Lansing, MI, USA.Department of Civil and Environmental Engineering, Michigan State University, East Lansing, MI, USA.Department of Civil and Environmental Engineering, Michigan State University, East Lansing, MI, USA.Department of Earth and Atmospheric Science, Cornell University, Ithaca, NY, USA.High-resolution soil moisture data are essential for numerous geophysical applications, enabling improved decision-making in environmental and resource management. However, current satellite-derived global soil moisture products suffer from coarse spatial resolution, limiting their utility. The upcoming NASA-ISRO SAR (NISAR) mission, set for launch in July 2025, aims to overcome this limitation by providing high-resolution soil moisture data at 200 [m]. One of the mission’s key approaches is the multi-scale algorithm, which enhances coarse-resolution data by incorporating fine-scale synthetic aperture radar (SAR) observations. While initial validation of this algorithm has been conducted over cropland, a broader evaluation is needed across various land covers and climates to ensure its robustness. This study investigates the performance of soil moisture retrieval across 5 diverse test sites, covering forest, shrubland, cropland, and grassland environments, as well as hydrometeorological conditions ranging from arid to polar. The algorithm was assessed at 100 [m] and 200 [m] resolutions, revealing consistent moisture patterns, with the finer resolution offering greater detail. Validation using in situ measurements showed that the unbiased root mean square error was less than 0.06 [m3/m3] for most sites, matching NISAR’s accuracy requirements. A wet bias was observed, and challenges emerged at a polar site due to organic soil. A minimum performance test was conducted to evaluate the impact of SAR backscatter measurements. The results demonstrate that these measurements contribute to improving the accuracy of high-resolution soil moisture retrieval using a multi-scale algorithm. Overall, the study highlights the algorithm’s capability to retrieve soil moisture at high resolution, reinforcing its suitability for the NISAR mission.https://spj.science.org/doi/10.34133/remotesensing.0729 |
| spellingShingle | Preet Lal Gurjeet Singh Narendra N. Das Rowena B. Lohman Validation of the NISAR Multi-Scale Soil Moisture Retrieval Algorithm across Various Spatial Resolutions and Landcovers Using the ALOS-2 SAR Data Journal of Remote Sensing |
| title | Validation of the NISAR Multi-Scale Soil Moisture Retrieval Algorithm across Various Spatial Resolutions and Landcovers Using the ALOS-2 SAR Data |
| title_full | Validation of the NISAR Multi-Scale Soil Moisture Retrieval Algorithm across Various Spatial Resolutions and Landcovers Using the ALOS-2 SAR Data |
| title_fullStr | Validation of the NISAR Multi-Scale Soil Moisture Retrieval Algorithm across Various Spatial Resolutions and Landcovers Using the ALOS-2 SAR Data |
| title_full_unstemmed | Validation of the NISAR Multi-Scale Soil Moisture Retrieval Algorithm across Various Spatial Resolutions and Landcovers Using the ALOS-2 SAR Data |
| title_short | Validation of the NISAR Multi-Scale Soil Moisture Retrieval Algorithm across Various Spatial Resolutions and Landcovers Using the ALOS-2 SAR Data |
| title_sort | validation of the nisar multi scale soil moisture retrieval algorithm across various spatial resolutions and landcovers using the alos 2 sar data |
| url | https://spj.science.org/doi/10.34133/remotesensing.0729 |
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