Large-Scale Soil Resource Mapping Using IRS-P6 LISS-IV and Cartosat-1 DEM in Basaltic Terrain of Central India View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2016-10

AUTHORS

Nisha Sahu, S. K. Singh, G. P. Obi Reddy, Nirmal Kumar, M. S. S. Nagaraju, Rajeev Srivastava

ABSTRACT

In the present study, an attempt has been made to describe the technique for large-scale soil mapping using remote sensing data. Based on erosional and depositional processes, seven major landforms namely plateau top, scarp slopes, plateau spurs, pediment, undulating plain, valley and floodplain have been delineated using Cartosat-1 DEM (10 m), contour (10 m) and hillshade. Using two seasons high-resolution IRS-P6 LISS-IV data, six land use/land cover classes namely double crop, single crop, orchard, wasteland with and without scrub and degraded forest have been identified using visual interpretation. A detailed slope map has been generated from Cartosat-1 DEM and reclassified into seven classes. On the basis of landform, slope, land use/land cover and ground truth, 37 Physiography-Landuse Units (PLU) were identified and described. PLU-soil relationship was developed by correlating soil-site characteristics and physical and chemical properties of soils. Six soil series were identified in major landforms and soil map depicting phases of soil series was developed. The study revealed that the combined use of Cartosat-1 DEM (10 m) and high-resolution IRS-P6 LISS-IV data will be of immense help in identifying soil patterns for large-scale soil resource inventory useful for village-level agricultural planning. More... »

PAGES

811-819

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s12524-015-0540-7

DOI

http://dx.doi.org/10.1007/s12524-015-0540-7

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1042384204


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