A novel hybrid approach using SVM and spectral indices for enhanced land use land cover mapping of coastal urban plains

Abstract

In present study, Landsat images of years 2001, 2009 and 2018 are used for LUC mapping of a coastal-urban-floodplain wherein built-up and coastal-barren classes have been identified to be the most confusing classes for interpretation. Otsu’s thresholding techniques have been used for mapping of waterbodies, built-up, and coastal-barren lands. The performance of most commonly used built-up indices have been assessed, among which BCI performed best for the study area. A new index, called Coastal-Barren-Index (CBI), has been developed using the spectral characteristics of SWIR1 and green spectral reflectance bands. A critical comparison of SVM and RFC classifiers are reported, and, finally, a hybrid approach is proposed as a combination MNDWI-CBI-SVM for mapping of the study area with Overall Accuracy 90.5% and Kappa value 0.87. The proposed approach is validated for an independent site, and, can be considered as generic in nature for LUC mapping of coastal urban plains.