Soil Order-Land Use Index Using Field-Satellite Spectroradiometry in the Ecuadorian Andean Territory for Modeling Soil Quality

Susana Arciniegas-Ortega, Iñigo Molina and Cesar Garcia-Aranda
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Susana Arciniegas-Ortega: Department of Land Surveying and Cartography Engineering, Universidad Politécnica de Madrid, 28040 Madrid, Spain
Iñigo Molina: Department of Land Surveying and Cartography Engineering, Universidad Politécnica de Madrid, 28040 Madrid, Spain
Cesar Garcia-Aranda: Department of Land Surveying and Cartography Engineering, Universidad Politécnica de Madrid, 28040 Madrid, Spain

Sustainability, 2022, vol. 14, issue 12, 1-28

Abstract: Land use conversion is the main cause for soil degradation, influencing the sustainability of agricultural activities in the Ecuadorian Andean region. The possibility to identify the quality based on the spectral properties allows remote sensing methods to offer an alternative form of monitoring the environment. This study used laboratory spectroscopy and multi-spectral images (Sentinel 2) with environmental covariates (physicochemical parameters) to find an affordable method that can be used to present spatial prediction models as a tool for the evaluation of the quality of Andean soils. The models were developed using statistical techniques of logistic regression and linear discriminant analysis to generate an index based on soil order and three indexes based on the combination of soil order and land use. This combined approach offers an effective method, relative to traditional laboratory methods, to derive estimates of the content and composition of soil constituents, such as electrical conductivity (CE), organic matter (OM), pH, and soil moisture (HU). For Mollisol index.3 with Páramo land use, a value of organic matter (OM) ≥8.6% was obtained, whereas for Mollisol index.4 with Shrub land use, OM was ≥6.1%. These results reveal good predictive (estimation) capabilities for these soil order–land use groups. This provides a new way to monitor soil quality using remote sensing techniques, opening promising prospects for operational applications in land use planning.

Keywords: remote sensing; soil quality; soil properties; indices; Andean region (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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