Resultado de búsqueda
Soil organic carbon stock. SoilGrids250m 2.0 - A system for digital soil mapping based on global compilation of soil profile data and environmental layers.
SoilGrids TM (hereafter SoilGrids) is a system for global digital soil mapping that uses state-of-the-art machine learning methods to map the spatial distribution of soil properties across the globe.
14 de jun. de 2021 · SoilGrids produces maps of soil properties for the entire globe at medium spatial resolution (250 m cell size) using state-of-the-art machine learning methods to generate the necessary models. It takes as inputs soil observations from about 240 000 locations worldwide and over 400 global environmental covariates describing vegetation ...
SoilGrids is a collections of soil property maps for the world produced using machine learning at 250 m resolution. Predictions are made at six standard depths. SoilGrids uses global models that are calibrated using all available input observations and globally available environmental covariates.
16 de feb. de 2017 · SoilGrids provides global predictions for standard numeric soil properties (organic carbon, bulk density, Cation Exchange Capacity (CEC), pH, soil texture fractions and coarse fragments) at seven standard depths (0, 5, 15, 30, 60, 100 and 200 cm), in addition to predictions of depth to bedrock and distribution of soil classes based ...
20 de oct. de 2020 · SoilGrids is a project of ISRIC – World Soil Information which aims to provide a globally consistent, data-driven system that predicts soil properties and classes using global covariates and globally fitted models with a digital soil mapping approach based on Quantile Random Forest.
16 de feb. de 2017 · SoilGrids provides global predictions for standard numeric soil properties (organic carbon, bulk density, Cation Exchange Capacity (CEC), pH, soil texture fractions and coarse fragments) at seven standard depths (0, 5, 15, 30, 60, 100 and 200 cm), in addition to predictions of depth to bedrock and distribution of soil classes based ...
