Assessment of Classification and Accuracy of Land Use/Land Cover in Jabalpur District, Madhya Pradesh, India: An Analysis by Remote Sensing and GIS Application

Abstract

The main purpose of remote sensing is to prepare land use/ land cover (LULC) thematic maps through satellite image classification. So many researchers worked on various image classification techniques and accuracy assessment. LUCC change is posing a serious problem to earth’s ecosystems. One estimate puts the safe upper boundary for global cropland area to 15% of the total terrestrial area, a level that is only about three percentage point higher than current cropland area, which account for 12% of global land area (Anonymus, 2012).  Objective of this study is to use remote sensing and GIS to prepare LULC map for the year 2016 in the Jabalpur district, Madhya Pradesh and to assess the accuracy of classified image. A multivariate rule is applied to carry out supervised classification. Five classes of LULC has been chosen to prepare the LULC map and areas coming under these classes are agriculture (59.26%), forest (18.28%) open/barren/wasteland (18.08%), waterbodies (2.68%) and built-up (1.70%). Overall classification accuracy of satellite image obtained in present study was 88.52 percent and kappa coefficient 0.80.