Cadastral-level soil mapping in basaltic terrain using Cartosat-1-derived products

Abstract

Lack of topographic details in cadastral maps and limited terrain information in coarse-resolution digital elevation models (DEMs) are limitations in understanding the soil–environment relationship, identification of soil patterns, and their boundaries. The present study describes the technique of cadastral-level soil mapping using Cartosat-1-derived products. A high-resolution DEM with a posting of 10 m generated from a Cartosat-1 stereo pair was used to derive terrain attributes. Based on erosional and depositional processes, five major landforms, namely plateau top, escarpment, pediment (erosional), alluvial plain, and narrow valley (depositional), have been delineated using 3D perspective viewing of the landscape and 10 m contours generated from the DEM. The pediments and alluvial plain were further divided into upper and lower pediments and alluvial plain based on elevation. A detailed slope map has been generated from the DEM and reclassified into seven slope classes, namely nearly level (0–1%), very gently sloping (1–3%), gently sloping (3–5%), moderately sloping (5–10%), strongly sloping (10–15%), moderately steep to steep (15–25%), and steep to very steep (25–50%). Five land-use/land-cover classes, namely single crop, double crop, wasteland with and without scrub, and degraded forest have been delineated using Cartosat-1-sharpened IRS-P6 LISS-IV data. The landforms, slope, and land-use/land-cover maps were integrated in a GIS framework and 45 precise physiography–land-use (PLU) units were derived. Nine soil series were identified in major landforms. Soils of plateau top, escarpment, and pediment associated with a low weathering front are very shallow to shallow in depth, have moderate to severe erosion, slight stoniness, and clay texture, whereas soils of alluvial plain, developed in Deccan basaltic alluvium, are deep to very deep (>150 cm), fine textured with shrink–swell potential, and calcareous in nature. Different phases of soil series were identified based on tone, texture, and pattern variations in the satellite image. A detailed soil map has been developed from the PLU map using soil series information and augur observations through the PLU–soil relationship. The combined use of the high-resolution DEM and satellite data has immensely helped in understanding the soil-forming environment, identification of soil patterns, and their boundaries for precise and faster mapping compared to conventional soil mapping.