Land Suitability Modeling for gram crop using remote sensing and GIS: A case study of Seonath basin, India

  • Sk Mustak
  • N K Baghmar
  • Sudhir Kumar Singh


Land suitability analysis is a model initiatives decision
support system, which standardized in spatial
framework within digital environment. Healthy gram
crop farming is primarily depends on combination of
favourable environmental factors, which are complex in
nature. In this article, these complex environmental factors
purified in mathematical and technological environments
for selecting condition, which is good, or bad
for gram crop farming. Analytical Hierarchical Program
(AHP), Remote Sensing and GIS are such tools and techniques,
which provide better solution. The degree of
suitability of classes has been classified according to the
standard framework of FAO (1976) such as, highly suitable,
moderately suitable, marginally suitable, currently
not suitable and permanently unsuitable and assigns
code as S1, S2, S3, N1 and N2. In the study area, the degree
of land suitability namely S1, S2, S3, N1 and N2 are
distributed as 22.94%, 20.21%, 17.70%, 22.68%, 16.47%
of the total cropland and 15.39%, 13.56%, 11.87%,
15.22% and 11.05% of total geographical area. This land
suitability has been delineated based on present spatial
distribution of favourable environmental conditions
but others factors like cropping process, technological
innovation and land use management policy can also
change the magnitude of land suitability. As the land
use is a dynamic and complex phenomena and trajectory
in nature so the amount of land suitability can be
varied in future land use planning for gram farming.
The outcome of this study will be useful to agriculture
land use planners and policy makers for the benefits of
farmers and the national economy.

How to Cite
MUSTAK, Sk; BAGHMAR, N K; SINGH, Sudhir Kumar. Land Suitability Modeling for gram crop using remote sensing and GIS: A case study of Seonath basin, India. Bulletin of Environmental and Scientific Research, [S.l.], v. 4, n. 3, p. 6-17, oct. 2015. ISSN 2278-5205. Available at: <>. Date accessed: 17 sep. 2019.