Identification of land cover changes in the coastal area of Dakshina Kannada district, South India during the year 2004–2008

Abstract

This study investigates land cover (LC) changes in the coastal area of Dakshina Kannada district in the state of Karnataka, South India, during the years 2004–2008 as a case study. IRS P-6, Linear Imaging Self Scanning sensor (LISS-IV) satellite images were used in the present work. Classification was carried out using artificial bee colony algorithm and support vector machine (SVM) which gave a better result compared to other traditional classification techniques. The best overall classification accuracy for the study area was achieved with an ABC classifier with an OCA of 80.35% for 2004 year data and OCA of 80.40% for 2008 year data, whereas the OCA in SVM, for the same training set is 71.42% for 2004 data and 71.38% for 2008 data on study area 1 and the results were optimised with respect to multispectral data. In study area 2, ABC algorithm achieved an OCA of 78.17% and MLC of 62.63% which was used to check the universality of the classifier. The classification results with post-classification technique for study area 1 indicate that urbanisation in the study area has almost increased twice. During the same time there is an increase in the forest plantation, agricultural plantation and a decrease in crop land and land without scrubs, indicates rapid changes in the coastal environment.