A comparative Digital Soil Mapping (DSM) study using a non-supervised clustering analysis and an expert knowledge based model - A case study from Ahuachapán, El Salvador

DSM is the inference of spatial and temporal soil property variations using mathematical models based on quantitative relationships between environmental information and soil measurements. The quality of DSM information depends on the method and environmental covariates used for its estimations. We...

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Autores principales: Martin López, Javier Mauricio, Silva, Mayesse Aparecida da, Valencia Gómez, Jefferson, Quintero, Marcela, Keough, Adam, Casares, Francisco
Formato: Póster
Lenguaje:Inglés
Publicado: International Center for Tropical Agriculture 2019
Materias:
Acceso en línea:https://hdl.handle.net/10568/106786
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author Martin López, Javier Mauricio
Silva, Mayesse Aparecida da
Valencia Gómez, Jefferson
Quintero, Marcela
Keough, Adam
Casares, Francisco
author_browse Casares, Francisco
Keough, Adam
Martin López, Javier Mauricio
Quintero, Marcela
Silva, Mayesse Aparecida da
Valencia Gómez, Jefferson
author_facet Martin López, Javier Mauricio
Silva, Mayesse Aparecida da
Valencia Gómez, Jefferson
Quintero, Marcela
Keough, Adam
Casares, Francisco
author_sort Martin López, Javier Mauricio
collection Repository of Agricultural Research Outputs (CGSpace)
description DSM is the inference of spatial and temporal soil property variations using mathematical models based on quantitative relationships between environmental information and soil measurements. The quality of DSM information depends on the method and environmental covariates used for its estimations. We compared two DSM methods to predict soil properties such as Organic Matter “MO” (%), Sand (%), Clay (%), pH (H2O), Phosphorus (mg/kg), Effective Cationic Exchange Capacity “CICE” (cmol/L), Potassium (cmol/L) and Water Holding Capacity (mm/m) for the department of Ahuachapán in El Salvador to support the activities of the Agriculture Landscape Restoration Initiative (ALRI) in the country
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publisherStr International Center for Tropical Agriculture
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spelling CGSpace1067862025-11-05T16:17:55Z A comparative Digital Soil Mapping (DSM) study using a non-supervised clustering analysis and an expert knowledge based model - A case study from Ahuachapán, El Salvador Martin López, Javier Mauricio Silva, Mayesse Aparecida da Valencia Gómez, Jefferson Quintero, Marcela Keough, Adam Casares, Francisco soil soil properties models DSM is the inference of spatial and temporal soil property variations using mathematical models based on quantitative relationships between environmental information and soil measurements. The quality of DSM information depends on the method and environmental covariates used for its estimations. We compared two DSM methods to predict soil properties such as Organic Matter “MO” (%), Sand (%), Clay (%), pH (H2O), Phosphorus (mg/kg), Effective Cationic Exchange Capacity “CICE” (cmol/L), Potassium (cmol/L) and Water Holding Capacity (mm/m) for the department of Ahuachapán in El Salvador to support the activities of the Agriculture Landscape Restoration Initiative (ALRI) in the country 2019 2020-01-29T13:19:43Z 2020-01-29T13:19:43Z Poster https://hdl.handle.net/10568/106786 en Open Access application/pdf International Center for Tropical Agriculture Martín-López, Javier M.; da Silva Mayesse; Valencia, Jefferson; Quintero, Marcela; Keough, Adam & Casares, Francisco (2019). A comparative Digital Soil Mapping (DSM) study using a non-supervised clustering analysis and an expert knowledge based model - A case study from Ahuachapán, El Salvador.Presented at:Joint Workshop for Digital Soil Mapping and Global Soil Map March 12-16 2019. 1 p.
spellingShingle soil
soil properties
models
Martin López, Javier Mauricio
Silva, Mayesse Aparecida da
Valencia Gómez, Jefferson
Quintero, Marcela
Keough, Adam
Casares, Francisco
A comparative Digital Soil Mapping (DSM) study using a non-supervised clustering analysis and an expert knowledge based model - A case study from Ahuachapán, El Salvador
title A comparative Digital Soil Mapping (DSM) study using a non-supervised clustering analysis and an expert knowledge based model - A case study from Ahuachapán, El Salvador
title_full A comparative Digital Soil Mapping (DSM) study using a non-supervised clustering analysis and an expert knowledge based model - A case study from Ahuachapán, El Salvador
title_fullStr A comparative Digital Soil Mapping (DSM) study using a non-supervised clustering analysis and an expert knowledge based model - A case study from Ahuachapán, El Salvador
title_full_unstemmed A comparative Digital Soil Mapping (DSM) study using a non-supervised clustering analysis and an expert knowledge based model - A case study from Ahuachapán, El Salvador
title_short A comparative Digital Soil Mapping (DSM) study using a non-supervised clustering analysis and an expert knowledge based model - A case study from Ahuachapán, El Salvador
title_sort comparative digital soil mapping dsm study using a non supervised clustering analysis and an expert knowledge based model a case study from ahuachapan el salvador
topic soil
soil properties
models
url https://hdl.handle.net/10568/106786
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