Utilizing LANDSAT data and the Maximum Likelihood Classifier for Analysing Land Use Patterns in Shimoga, Karnataka

Abstract

Abstract The loss of natural resources has been linked to rapid and invasive urbanization, which in turn worsens the local environment’s scenery and conditions. Preparation of a land use land cover(LULC) map is one of the methods to observe the changes in the geological structure of the study area. The LULU map gives an idea of changes that are occurring during the specified period which will in turn helps in suggesting the measures to be taken to prevent the chances of natural disasters that might occur because of these changes. This study uses a collection of LANDSAT images to evaluate changes in LULC in the Shimoga district for the years 2010, 2015, and 2020. For the classification and creation of LULC maps for the chosen periods, a supervised technique using a Maximum Likelihood Classifier(MLC) has been used. Waterbodies, urban areas, forest areas, and agricultural land have been recognized as the main classes of LULC. The overall accuracy of these maps has been evaluated while taking into account ground facts from Google Earth Pro. The overall accuracy for classification obtained is 85.03% for 2010, 85.27% for 2015, and 85.61% for 2020. The classifier created using LANDSAT scenes and the MLC approach performs well for the research area, as seen by the Kappa index values of 0.8, 0.8, and 0.81 for the years 2010, 2015, and 2020, respectively. The study’s findings indicate that over ten years, the proportion of built-up areas has expanded from 2.8% to 5.4%. When a 2.49% increase occurs in just 10 years, it is necessary to be concerned given the rise of only 1.6% over the previous 40 years. It can also be observed that the proportion of agricultural land has expanded while the fraction of forests has diminished in the study area. The findings of this study are useful in determining that LULC changes are one of the causes of natural disasters including landslides, floods, and forest fires.