Watershed scale soil moisture estimation model using machine learning and remote sensing in a data-scarce context

Soil moisture content can be used to predict drought impact on agricultural yield better than precipitation. Remote sensing is viable source of soil moisture data in instrument-scarce areas. However, space-based soil moisture estimates lack suitability for daily and high-resolution agricultural, hyd...

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Detalles Bibliográficos
Autores principales:	Bueno, M., Baca García, C., Montoya, N., Rau, P., Loayza, H.
Formato:	Journal Article
Lenguaje:	Inglés
Publicado:	Scientia Agropecuaria 2024
Materias:	soil water content remote sensing machine learning drought
Acceso en línea:	https://hdl.handle.net/10568/131095

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