Publication

Abstract : Chennai is a metropolitan city in India. It has many lakes and reservoirs which are changing due to urbanization. Remote sensing and GIS techniques are widely used for water body extraction and water body change detection. This study evaluates water body extraction from satellite images of Chennai city using machine learning methods. Many classifiers are trained to extract water bodies from satellite images. Landsat 5 images of Chennai were taken from USGS Earth Explorer for the year 2009. The study aims to compare the classification results of different machine learning algorithms such as J48 decision tree, naive Bayes, multilayer perceptron, k-nearest neighbor, iso-cluster and random forest in extracting the water bodies. The tools used are ArcGIS for geospatial analysis, Weka tool for classification and R for the visual interpretation of the results. The results illustrate that naive Bayes classifier is able to identify lake regions better when compared to all other classifiers.