Abstract

  The study was conducted using existing soil data from Nawagaon and Maskara Rao watershed boundary in Shaharanpur district, India to assess land capability classes using Remote Sensing and GIS approach. Land sat image was integrated with SRTM DEM for delineation of landforms and analysis of land use/land cover data. The filled SRTM DEM of the study area was extracted at 30 m resolution to extract terrain parameters such as elevation, slope and aspect. SRTM DEM was visually interpreted. Three major landforms were identified, namely, 3 landforms – hills, piedmont plains and alluvia plains. These were further delineated according to slope and finally according to vegetation cover to give eight physiographic units. The slope map and aspect map were produced using filed Dem and were classified into nine and two classes respectively. Land use/land cover map was also generated using satellite image for the study area in India. The dominant land use was: dense forest, degraded forest, crop land I, crop land II, scrub/barren, settlement, river, canal and road.

  Based on the slope map, land characteristics of each physiographic unit and land capability criteria for land qualities, land capability classes were assigned and were translated into a land capability map. The soils were placed in seven classes (I, II, III, IV, VI, VII and VIII). Both the GIS approach and LCC evaluation using criteria rating of FAO gave the same classes for the mapped soil. The study revealed that soils from the study areas varied with different physiographic unit, therefore soils of the hilly areas should be put to use for nature conservation other than arable production while the lower portion should be cultivated with intensive care for arable crops.

Keywords: SRTM DEM; Landsat; Physiography; Land Use/Land Cover; Land Evaluation

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Citation

Citation: Adegbenro RO., et al. “Land Evaluation for Land Use Planning Using Remote Sensing and GIS - A Case Study of Nawagaon Maskara Rao Watershed, Saharanpur, India" . Acta Scientific Agriculture 4.2 (2020): 130-138.

Copyright

Copyright: © 2020 Adegbenro RO., et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.