Hybrid learning model for analysing the Uppal earth region, in Telangana state, using multispectral Landsat-8 OLI images

Abstract

Remote Sensing (RS) and Geographical Information Systems (GIS) are being widely used to carry out analysis of the Earth's surface. In this paper, a hybrid learning model is proposed for the classification and analysis of the Uppal earth region, located nearby Hyderabad in Telangana state. In the hybrid learning model, the ISODATA clustering algorithm is combined with the Normalised Vegetation Index (NDVI) and K-means learning model. In this proposal, the spectral features of the Uppal region are extracted from the satellite images and used for further analysis. The obtained accuracy of the proposed Merged-ISODATA algorithm is 74.33% and the Kappa value is 0.64. The obtained accuracy and Kappa value for existing ISODATA clustering and K-Means algorithm are 71.5% and 0.58. These values imply that the obtained results of the proposed algorithm are better than the results obtained in existing approaches.