NISAR Time-Series Ratio Algorithm for Soil Moisture Retrieval: Prelaunch Evaluation With SMAPVEX12 Field Campaign Data
| Autor: | Jeonghwan Park, Rajat Bindlish, Alexandra Bringer, Dustin Horton, Joel T. Johnson |
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| Jazyk: | angličtina |
| Rok vydání: | 2024 |
| Předmět: | |
| Zdroj: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 12959-12968 (2024) |
| Druh dokumentu: | article |
| ISSN: | 1939-1404 2151-1535 |
| DOI: | 10.1109/JSTARS.2024.3422071 |
| Popis: | The NASA ISRO synthetic aperture radar (NISAR) mission scheduled for launch in 2024 will provide global L-band radar observations that can be applied to estimate land surface soil moisture. The mission's soil moisture product will be provided at 200-m resolution with a global revisit frequency of 12 days (or 6 days when considering both ascending and descending observations). A time-series ratio algorithm for soil moisture retrieval has been applied to NISAR simulated datasets from airborne UAVSAR measurements in the SMAPVEX12 field campaign. Soil moisture retrieval performance using the algorithm is encouraging, with a correlation coefficient between retrievals and in situ observations greater than 0.7 and an unbiased root-mean-squared Error (RMSE) of 0.05 ${{{\bm{m}}}^3}/{{{\bm{m}}}^3}$. The results suggest that the time-series ratio algorithm will provide soil moisture products that meet an accuracy goal of 0.06 ${{{\bm{m}}}^3}/{{{\bm{m}}}^3}$ unbiased RMSE. |
| Databáze: | Directory of Open Access Journals |
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