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

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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Bibliographic Details
Main Authors: Marcelo Bueno, Carlos Baca García, Nilton Montoya, Pedro Rau, Hildo Loayza
Format: Article
Language:English
Published: Universidad Nacional de Trujillo 2024-03-01
Series:Scientia Agropecuaria
Subjects:
soil moisture
remote sensing
machine learning
random forest
downscaling
Online Access:https://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/5434
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