Conventional soil resources information in the Philippines, primarily comprising legacy soil maps, requires modernization to meet the demands of contemporary environmental and agricultural planning. This study developed and validated a robust, scalable framework for updating the national soil information system by integrating legacy pedological data with advanced digital geospatial processing techniques. The methodology leveraged high-resolution (5-meter) Digital Elevation Models (DEMs) and a quantitative landform classification approach based on the Topographic Position Index (TPI) to generate preliminary soil mapping units with significantly improved spatial accuracy and objectivity over analog methods. Legacy soil datasets, containing soil properties and characteristics up to the Soil Series level of the USDA Soil Taxonomy, were synthesized into soil-landscape relationship conceptual models to guide the correlation of soil classes with the digitally derived landform units. The resulting detailed, large-scale (up to 1:20,000) provisional maps were rigorously validated through stratified field verification and laboratory analysis of key soil physicochemical properties, culminating in the compilation of enhanced, GIS-ready soil maps and associated geodatabases. This hybrid approach effectively bridges the gap between conventional soil survey and digital soil mapping, providing a critical geospatial infrastructure to support science-driven decision-making for sustainable agriculture and environmental management in the Philippines.
Keywords: conventional soil maps, Digital Elevation Model, Geographic Information Systems, landform classification approach, soil-landscape relationship, Topographic Position Index, Digital Soil Mapping
Conventional soil resources information in the Philippines, primarily comprising legacy soil maps, requires modernization to meet the demands of contemporary environmental and agricultural planning. This study developed and validated a robust, scalable framework for updating the national soil information system by integrating legacy pedological data with advanced digital geospatial processing techniques. The methodology leveraged high-resolution (5-meter) Digital Elevation Models (DEMs) and a quantitative landform classification approach based on the Topographic Position Index (TPI) to generate preliminary soil mapping units with significantly improved spatial accuracy and objectivity over analog methods. Legacy soil datasets, containing soil properties and characteristics up to the Soil Series level of the USDA Soil Taxonomy, were synthesized into soil-landscape relationship conceptual models to guide the correlation of soil classes with the digitally derived landform units. The resulting detailed, large-scale (up to 1:20,000) provisional maps were rigorously validated through stratified field verification and laboratory analysis of key soil physicochemical properties, culminating in the compilation of enhanced, GIS-ready soil maps and associated geodatabases. This hybrid approach effectively bridges the gap between conventional soil survey and digital soil mapping, providing a critical geospatial infrastructure to support science-driven decision-making for sustainable agriculture and environmental management in the Philippines.
Keywords: conventional soil maps, Digital Elevation Model, Geographic Information Systems, landform classification approach, soil-landscape relationship, Topographic Position Index, Digital Soil Mapping