Application of artificial neural network algorithms to estimate spatial soil organic carbon stock in Prairie lands from remote sensing and soil data pool

Estimating soil organic carbon stock (SOCS), the largest terrestrial carbon reservoir at the ecosystem level, is essential for identifying land management practices that support climate resilience. Remote sensing (RS) enables affordable analysis of SOCS, but lack of high-resolution RS data on biotic...

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Principais autores:	Reshmi Sarkar, Ram L. Ray
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Taylor & Francis Group 2025-12-01
Colecção:	Geocarto International
Assuntos:	Machine learning soil organic carbon stock deep learning Sentinel 2A Normalized Difference Vegetation Index cropping-grazing-wetlands agroecosystems
Acesso em linha:	https://www.tandfonline.com/doi/10.1080/10106049.2025.2597423
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