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.
