An Assessment of the Seasonal Uncertainty of Microwave L-Band Satellite Soil Moisture Products in Jiangsu Province, China DOI Creative Commons

Chuanxiang Yi,

Xiaojun Li,

Zanpin Xing

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(22), P. 4235 - 4235

Published: Nov. 14, 2024

Accurate surface soil moisture (SM) data are crucial for agricultural management in Jiangsu Province, one of the major regions China. However, seasonal performance different SM products is still unknown. To address this, this study aims to evaluate applicability four L-band microwave remotely sensed products, namely, Soil Moisture Active Passive Single-Channel Algorithm at Vertical Polarization Level 3 (SMAP SCA-V L3, hereafter SMAP-L3), SMOS-SMAP-INRAE-BORDEAUX (SMOSMAP-IB), and Ocean Salinity version IC (SMOS-IC), SMAP-INRAE-BORDEAUX (SMAP-IB) scale. In addition, effects dynamic environmental variables such as leaf vegetation index (LAI), mean temperature (MSST), wetness (MSSM) on above investigated. The results indicate that all exhibit significant differences when evaluated against situ observations between 2016 2022, with most achieving their highest correlation (R) unbiased root-mean-square difference (ubRMSD) scores during autumn. Conversely, significantly deteriorates summer, ubRMSD values exceeding 0.06 m3/m3. SMOS-IC generally achieves better R across seasons but has limited temporal availability, while SMAP-IB typically lowest values, even reaching 0.03 m3/m3 morning observation winter. Additionally, sensitivity products’ skill metrics factors varies seasons. For ubRMSD, SMAP-L3 shows a general increase LAI seasons, exhibits notable becomes wetter summer. wet conditions notably reduce autumn products. These findings expected offer valuable insights appropriate selection enhancement retrieval algorithms.

Language: Английский

From theory to hydrological practice: Leveraging CYGNSS data over seven years for advanced soil moisture monitoring DOI
Hoang Hai Nguyen, Hyunglok Kim, Wade T. Crow

et al.

Remote Sensing of Environment, Journal Year: 2024, Volume and Issue: 316, P. 114509 - 114509

Published: Nov. 16, 2024

Language: Английский

Citations

2
An Assessment of the Seasonal Uncertainty of Microwave L-Band Satellite Soil Moisture Products in Jiangsu Province, China DOI Creative Commons

Chuanxiang Yi,

Xiaojun Li,

Zanpin Xing

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(22), P. 4235 - 4235

Published: Nov. 14, 2024

Accurate surface soil moisture (SM) data are crucial for agricultural management in Jiangsu Province, one of the major regions China. However, seasonal performance different SM products is still unknown. To address this, this study aims to evaluate applicability four L-band microwave remotely sensed products, namely, Soil Moisture Active Passive Single-Channel Algorithm at Vertical Polarization Level 3 (SMAP SCA-V L3, hereafter SMAP-L3), SMOS-SMAP-INRAE-BORDEAUX (SMOSMAP-IB), and Ocean Salinity version IC (SMOS-IC), SMAP-INRAE-BORDEAUX (SMAP-IB) scale. In addition, effects dynamic environmental variables such as leaf vegetation index (LAI), mean temperature (MSST), wetness (MSSM) on above investigated. The results indicate that all exhibit significant differences when evaluated against situ observations between 2016 2022, with most achieving their highest correlation (R) unbiased root-mean-square difference (ubRMSD) scores during autumn. Conversely, significantly deteriorates summer, ubRMSD values exceeding 0.06 m3/m3. SMOS-IC generally achieves better R across seasons but has limited temporal availability, while SMAP-IB typically lowest values, even reaching 0.03 m3/m3 morning observation winter. Additionally, sensitivity products’ skill metrics factors varies seasons. For ubRMSD, SMAP-L3 shows a general increase LAI seasons, exhibits notable becomes wetter summer. wet conditions notably reduce autumn products. These findings expected offer valuable insights appropriate selection enhancement retrieval algorithms.

Language: Английский

Citations

0