A scalable framework for soil property mapping tested across a highly diverse tropical data-scarce regionZENODO

A scalable framework for soil property mapping tested across a highly diverse tropical data-scarce regionZENODO

Reliable soil property maps are essential for environmental modeling, yet conventional mapping methods remain costly and time-consuming. We developed a machine learning framework that integrates the Soil-Landscape Estimation and Evaluation Program (SLEEP) with gradient boosting to predict soil prope...

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Bibliographic Details
Main Authors: Rodrigo de Q. Miranda, Rodolfo L.B. Nóbrega, Anne Verhoef, Estevão L.R. da Silva, Jadson F. da Silva, José C. de Araújo Filho, Magna S.B. de Moura, Alexandre H.C. Barros, Alzira G.S.S. Souza, Wanhong Yang, Hui Shao, Raghavan Srinivasan, Feras Ziadat, Suzana M.G.L. Montenegro, Maria do S.B. Araújo, Josiclêda D. Galvíncio
Format: Article
Language:English
Published: Elsevier 2025-12-01
Series:Soil Advances
Subjects:
Digital Soil Mapping
Tropical Soil Properties
Gradient Boosting Model
SLEEP
Pernambuco
Northeast region
Online Access:http://www.sciencedirect.com/science/article/pii/S2950289625000326
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