Comprehensive spatial mapping of metals and metalloids in the Peruvian Mantaro Valley using advanced geospatial data Integration
The quality and safety of soil are crucial for ensuring social and economic development and providing contaminant-free food. The availability and quality of soil data, particularly for multiple metals and metalloids, are often insufficient for comprehensive analysis. Soil formation and the distribut...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Artículo |
| Published: |
Elsevier
2025
|
| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.12955/2697 https://doi.org/10.1016/j.geoderma.2024.117138 |
| _version_ | 1855490416546152448 |
|---|---|
| author | Pizarro Carcausto, Samuel Edwin Pricope , Narcisa G. Vera Vilchez, Jesús Emilio Cruz Luis, Juancarlos Alejandro Lastra Paucar, Sphyros Roomel Solórzano Acosta, Richard Andi Verástegui Martínez, Patricia |
| author_browse | Cruz Luis, Juancarlos Alejandro Lastra Paucar, Sphyros Roomel Pizarro Carcausto, Samuel Edwin Pricope , Narcisa G. Solórzano Acosta, Richard Andi Vera Vilchez, Jesús Emilio Verástegui Martínez, Patricia |
| author_facet | Pizarro Carcausto, Samuel Edwin Pricope , Narcisa G. Vera Vilchez, Jesús Emilio Cruz Luis, Juancarlos Alejandro Lastra Paucar, Sphyros Roomel Solórzano Acosta, Richard Andi Verástegui Martínez, Patricia |
| author_sort | Pizarro Carcausto, Samuel Edwin |
| collection | Repositorio INIA |
| description | The quality and safety of soil are crucial for ensuring social and economic development and providing contaminant-free food. The availability and quality of soil data, particularly for multiple metals and metalloids, are often insufficient for comprehensive analysis. Soil formation and the distribution of metals are shaped by various factors such as geology, climate, topography, and human activities, making accurate modeling highly challenging. Additionally, agricultural intensification, urban expansion, road construction, and mining activities frequently result in soil pollution, posing serious risks to ecosystems and human health. This study aims to integrate diverse geospatial datasets with machine learning for high resolution soil contamination mapping (10 m spatial resolution) in a major agricultural region of Peruvian highlands. This study mapped 25 elements (Ca, Mg, Sr, Ba, Be, K, Na, As, Sb, Se, Tl, Cd, Zn, Al, Pb, Hg, Cr, Ni, Cu, Mo, Ag, Fe, Co, Mn, V) in the Peruvian Mantaro Valley using a training dataset of 109 topsoil samples combined with various geospatial datasets (remote sensing, climate, topography, soil data, and distance). The model provided satisfactory results in predicting the spatial distribution of the selected elements, with R² values ranging from 0.6 to 0.9 for most elements. Edaphic, climate, and topographic covariates were the most significant predictors, particularly for croplands near rivers, whereas spectral variables were less important. The results reveal As, Pb, and Cd concentrations significantly above permissible limits, highlighting urgent health risks. These findings suggest that it is feasible to identify polluted soils and improve regulations based on widely available geospatial datasets with minimal training data. The study contributes to the development of models to assess the impact of pollutants on environmental and human health in the short-to-medium term, emphasizing the need for further research on the translocation of toxic metals into food crops and the implications for public health. |
| format | Artículo |
| id | INIA2697 |
| institution | Institucional Nacional de Innovación Agraria |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | Elsevier |
| publisherStr | Elsevier |
| record_format | dspace |
| spelling | INIA26972025-04-01T20:37:17Z Comprehensive spatial mapping of metals and metalloids in the Peruvian Mantaro Valley using advanced geospatial data Integration Pizarro Carcausto, Samuel Edwin Pricope , Narcisa G. Vera Vilchez, Jesús Emilio Cruz Luis, Juancarlos Alejandro Lastra Paucar, Sphyros Roomel Solórzano Acosta, Richard Andi Verástegui Martínez, Patricia Random forest Soil mapping Google earth engine Machine learning Cloud computing https://purl.org/pe-repo/ocde/ford#4.01.04 Materia orgánica del suelo; Mapeo de suelos; Elementos traza; Metales; Valles; Perú The quality and safety of soil are crucial for ensuring social and economic development and providing contaminant-free food. The availability and quality of soil data, particularly for multiple metals and metalloids, are often insufficient for comprehensive analysis. Soil formation and the distribution of metals are shaped by various factors such as geology, climate, topography, and human activities, making accurate modeling highly challenging. Additionally, agricultural intensification, urban expansion, road construction, and mining activities frequently result in soil pollution, posing serious risks to ecosystems and human health. This study aims to integrate diverse geospatial datasets with machine learning for high resolution soil contamination mapping (10 m spatial resolution) in a major agricultural region of Peruvian highlands. This study mapped 25 elements (Ca, Mg, Sr, Ba, Be, K, Na, As, Sb, Se, Tl, Cd, Zn, Al, Pb, Hg, Cr, Ni, Cu, Mo, Ag, Fe, Co, Mn, V) in the Peruvian Mantaro Valley using a training dataset of 109 topsoil samples combined with various geospatial datasets (remote sensing, climate, topography, soil data, and distance). The model provided satisfactory results in predicting the spatial distribution of the selected elements, with R² values ranging from 0.6 to 0.9 for most elements. Edaphic, climate, and topographic covariates were the most significant predictors, particularly for croplands near rivers, whereas spectral variables were less important. The results reveal As, Pb, and Cd concentrations significantly above permissible limits, highlighting urgent health risks. These findings suggest that it is feasible to identify polluted soils and improve regulations based on widely available geospatial datasets with minimal training data. The study contributes to the development of models to assess the impact of pollutants on environmental and human health in the short-to-medium term, emphasizing the need for further research on the translocation of toxic metals into food crops and the implications for public health. This research was funded by the INIA project "Mejoramiento de los servicios de investigación y transferencia tecnológica en el manejo y recuperación de suelos agrícolas degradados y aguas para riego en la pequeña y mediana agricultura en los departamentos de Lima, Áncash, San Martín, Cajamarca, Lambayeque, Junín, Ayacucho, Arequipa, Puno y Ucayali" CUI 2487112, of the Ministry of Agrarian Development and Irrigation (MIDAGRI) of the Peruvian Government. 2025-04-01T20:37:16Z 2025-04-01T20:37:16Z 2024-12-12 info:eu-repo/semantics/article Pizarro et al., Comprehensive spatial mapping of metals and metalloids in the Peruvian Mantaro Valley using advanced geospatial data Integration, Geoderma 453 (2025) 117138 http://hdl.handle.net/20.500.12955/2697 https://doi.org/10.1016/j.geoderma.2024.117138 0016-7061 Geoderma info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/ application/pdf application/pdf Elsevier NL Instituto Nacional de Innovación Agraria Repositorio Institucional - INIA |
| spellingShingle | Random forest Soil mapping Google earth engine Machine learning Cloud computing https://purl.org/pe-repo/ocde/ford#4.01.04 Materia orgánica del suelo; Mapeo de suelos; Elementos traza; Metales; Valles; Perú Pizarro Carcausto, Samuel Edwin Pricope , Narcisa G. Vera Vilchez, Jesús Emilio Cruz Luis, Juancarlos Alejandro Lastra Paucar, Sphyros Roomel Solórzano Acosta, Richard Andi Verástegui Martínez, Patricia Comprehensive spatial mapping of metals and metalloids in the Peruvian Mantaro Valley using advanced geospatial data Integration |
| title | Comprehensive spatial mapping of metals and metalloids in the Peruvian Mantaro Valley using advanced geospatial data Integration |
| title_full | Comprehensive spatial mapping of metals and metalloids in the Peruvian Mantaro Valley using advanced geospatial data Integration |
| title_fullStr | Comprehensive spatial mapping of metals and metalloids in the Peruvian Mantaro Valley using advanced geospatial data Integration |
| title_full_unstemmed | Comprehensive spatial mapping of metals and metalloids in the Peruvian Mantaro Valley using advanced geospatial data Integration |
| title_short | Comprehensive spatial mapping of metals and metalloids in the Peruvian Mantaro Valley using advanced geospatial data Integration |
| title_sort | comprehensive spatial mapping of metals and metalloids in the peruvian mantaro valley using advanced geospatial data integration |
| topic | Random forest Soil mapping Google earth engine Machine learning Cloud computing https://purl.org/pe-repo/ocde/ford#4.01.04 Materia orgánica del suelo; Mapeo de suelos; Elementos traza; Metales; Valles; Perú |
| url | http://hdl.handle.net/20.500.12955/2697 https://doi.org/10.1016/j.geoderma.2024.117138 |
| work_keys_str_mv | AT pizarrocarcaustosamueledwin comprehensivespatialmappingofmetalsandmetalloidsintheperuvianmantarovalleyusingadvancedgeospatialdataintegration AT pricopenarcisag comprehensivespatialmappingofmetalsandmetalloidsintheperuvianmantarovalleyusingadvancedgeospatialdataintegration AT veravilchezjesusemilio comprehensivespatialmappingofmetalsandmetalloidsintheperuvianmantarovalleyusingadvancedgeospatialdataintegration AT cruzluisjuancarlosalejandro comprehensivespatialmappingofmetalsandmetalloidsintheperuvianmantarovalleyusingadvancedgeospatialdataintegration AT lastrapaucarsphyrosroomel comprehensivespatialmappingofmetalsandmetalloidsintheperuvianmantarovalleyusingadvancedgeospatialdataintegration AT solorzanoacostarichardandi comprehensivespatialmappingofmetalsandmetalloidsintheperuvianmantarovalleyusingadvancedgeospatialdataintegration AT verasteguimartinezpatricia comprehensivespatialmappingofmetalsandmetalloidsintheperuvianmantarovalleyusingadvancedgeospatialdataintegration |