Digital soil mapping of metals and metalloids in croplands using multiple geospatial data and machine learning, implemented in GEE, for the Peruvian Mantaro Valley
Quality and safety of the soil are essential to ensure social and economic development and provides the supply of contaminant free food. With agriculture intensification, expansion of urban zones, construction of roads, and mining, some agricultural soils sites become polluted increasing environment...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Artículo preliminar |
| Language: | Inglés |
| Published: |
Elsevier
2024
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/20.500.12955/2537 http://dx.doi.org/10.2139/ssrn.4777607 |
Similar Items: Digital soil mapping of metals and metalloids in croplands using multiple geospatial data and machine learning, implemented in GEE, for the Peruvian Mantaro Valley
- Comprehensive spatial mapping of metals and metalloids in the Peruvian Mantaro Valley using advanced geospatial data Integration
- Imputación de genotipos faltantes mediante algoritmos de machine learning = Imputation of missing genotypes using machine learning algorithms
- Implementing cloud computing for the digital mapping of agricultural soil properties from high resolution UAV multispectral imagery
- Which machine learning algorithm is best suited for estimating reference evapotranspiration in humid subtropical climate?
- Machine learning algorithms identified relevant SNPs for milk fat content in cattle
- INFINITy : A fast machine learning-based application for human influenza A and B virus subtyping