Near-Infrared and Short-Wavelength Infrared-Based Indices to Monitor Soil Moisture from a Satellite: A Comparative Analysis

Abstract

Soil Moisture (SM) is a key parameter in several research and application fields, from climate studies to farming, from natural disaster prediction to land management. In this respect, Earth Observation (EO) images have been widely recognized as a useful tool able to provide information on a large scale. In the last few decades, several near-infrared (NIR) and short-wavelength-infrared (SWIR) indices have been proposed for SM monitoring. Nonetheless, the number of EO studies addressing real, heterogeneous scenarios is very limited. In this paper, we present the results of a comparative analysis conducted on a multi-temporal sequence of optical EO images by computing a set of NIR-SWIR-based indices in order to assess their performances for SM monitoring. The studied area was a highly heterogeneous farming area featuring bare soil, cultivated areas and forests. The outcomes highlighted an overall good performance for some indices despite the effects of some environmental parameters.

Keywords

• soil moisture
• Landsat-OLI
• GLDAS
• optical satellite data
• multispectral indexes
• Earth observation