High Spatial Resolution Soil Moisture Mapping over Agricultural Field Integrating SMAP, IMERG, and Sentinel-1 Data in Machine Learning Models

High Spatial Resolution Soil Moisture Mapping over Agricultural Field Integrating SMAP, IMERG, and Sentinel-1 Data in Machine Learning Models

Soil moisture content (SMC) is a critical parameter for agricultural productivity, particularly in semi-arid regions, where irrigation practices are extensively used to offset water deficits and ensure decent yields. Yet, the socio-economic and remote context of these regions prevents sufficiently d...

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Bibliographic Details
Main Authors: Diego Tola, Lautaro Bustillos, Fanny Arragan, Rene Chipana, Renaud Hostache, Eléonore Resongles, Raúl Espinoza-Villar, Ramiro Pillco Zolá, Elvis Uscamayta, Mayra Perez-Flores, Frédéric Satgé
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Remote Sensing
Subjects:
sentinel-1
SMAP
high spatial resolution
soil moisture content
machine learning
Online Access:https://www.mdpi.com/2072-4292/17/13/2129
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