Surface Soil Moisture Evaluated from Satellite Multispectral Optical Data Through Visible and Shortwave Drought Index and Its Comparison with Microwave-Based Soil Moisture Products

Soil moisture is a key parameter in several applications, from land management to emergency response. Microwave-based soil moisture products are already provided daily, yet at 1 km resolution. Optical remote sensing could be a complementary source of information at higher spatial resolution (10–100 m), but most studies have been limited to highly homogeneous scenarios. In this paper, the potential of optical images to assess soil moisture in a highly fragmented scenario is investigated. Landsat-8 optical data were processed to retrieve the Visible and Shortwave Drought Index (VSDI) over an area with heterogeneous land cover. Results were compared with the Copernicus Soil Water Index (SWI) product, showing a moderate correlation (Pearson coefficient equal to 0.402) that however increased to 0.668 if only bare soil pixels were selected.

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Published
2025-09-12
DOI
https://doi.org/10.3390/proceedings2025129029
Primary Topic
Soil Moisture and Remote Sensing
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article
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article

Surface Soil Moisture Evaluated from Satellite Multispectral Optical Data Through Visible and Shortwave Drought Index and Its Comparison with Microwave-Based Soil Moisture Products

Valentina Raimondi, Stefano Baronti, Roberto Carlà
Soil Moisture and Remote Sensing
article

Surface Soil Moisture Evaluated from Satellite Multispectral Optical Data Through Visible and Shortwave Drought Index and Its Comparison with Microwave-Based Soil Moisture Products

Valentina Raimondi, Stefano Baronti, Roberto Carlà
article en

Abstract

Soil moisture is a key parameter in several applications, from land management to emergency response. Microwave-based soil moisture products are already provided daily, yet at 1 km resolution. Optical remote sensing could be a complementary source of information at higher spatial resolution (10–100 m), but most studies have been limited to highly homogeneous scenarios. In this paper, the potential of optical images to assess soil moisture in a highly fragmented scenario is investigated. Landsat-8 optical data were processed to retrieve the Visible and Shortwave Drought Index (VSDI) over an area with heterogeneous land cover. Results were compared with the Copernicus Soil Water Index (SWI) product, showing a moderate correlation (Pearson coefficient equal to 0.402) that however increased to 0.668 if only bare soil pixels were selected.

Nello Carrara Institute of Applied Physics (IT)
Openalex Percentile: Top 77%
Soil Moisture and Remote Sensing
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