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Research Article

Vol. 42 Núm. 3 (2025): Vol. 42 Núm. 3 (2025): Revista de Ciencias Agrícolas - Septiembre - Diciembre 2025

Soil sealing vulnerability in high-value agricultural land: A multicriteria GIS-based approach

DOI
https://doi.org/10.22267/rcia.20254203.277
Enviado
julio 16, 2025
Publicado
2025-12-22

Resumen

Soil sealing remains an under-addressed threat to agricultural sustainability, particularly in rapidly urbanizing rural-urban interfaces. To address this challenge, a spatially explicit Soil Sealing Vulnerability Index (SSVI) was developed for 126,734.87 hectares of agricultural land in the Guachal and Amaime watersheds (GAWs), Valle del Cauca, Colombia. The SSVI integrates seven spatially referenced biophysical and institutional parameters—terrain slope, parcel size, road proximity, proximity to surface water bodies, agrological soil class, urban growth trends (2000–2024), and municipal land-use designations—using a multi-criteria analysis structured by expert consensus through the Analytic Hierarchy Process. With strong internal consistency, demonstrated by a Consistency Ratio (CR) of 2.51% that confirms the logical stability of expert judgments, the SSVI provides spatial support for decision-making in municipal land-use planning. Independent validation is deferred until sealing datasets become available, using a replicable concordance workflow. Results indicate that 42.54% of the GAWs area presents moderate vulnerability, 19.01% low vulnerability, 1.00% (1,270.1 ha) high vulnerability, and 37.44% corresponds to exclusion zones (e.g., urban cores and protected areas). Importantly, 938.7 ha of environmentally restricted soils and 228.8 ha of Mollisols fall within high-vulnerability zones, highlighting the model’s ability to identify policy-relevant risks. This study introduces the first spatially resolved SSVI tailored to Colombia’s regulatory landscape, demonstrating that vulnerability is more strongly influenced by institutional planning than by natural land constraints. Although technically replicable, effective application requires high-resolution spatial datasets and local expert participation. Integration into municipal planning instruments is essential to translate technical findings into policy action.

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