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Landcover is the easiest detectable indicator of human interventions on land. Urban and peri-urban areas present a complex\udcombination of landcover, which makes classification challenging. This paper assesses the different methods of classifying landcover\udusing dual polarimetric Sentinel-1 data collected during monsoon (July) and winter (December) months of 2015. Four broad\udlandcover classes such as built up areas, water bodies and wetlands, vegetation and open spaces of Kolkata and its surrounding\udregions were identified. Polarimetric analyses were conducted on Single Look Complex (SLC) data of the region while ground range\uddetected (GRD) data were used for spectral and spatial classification. Unsupervised classification by means of K-Means clustering\udused backscatter values and was able to identify homogenous landcovers over the study area. The results produced an overall\udaccuracy of less than 50% for both the seasons. Higher classification accuracy (around 70%) was achieved by adding texture\udvariables as inputs along with the backscatter values. However, the accuracy of classification increased significantly with\udpolarimetric analyses. The overall accuracy was around 80% in Wishart H-A-Alpha unsupervised classification. The method was\uduseful in identifying urban areas due to their double-bounce scattering and vegetated areas, which have more random scattering.\udNormalized Difference Built-up index (NDBI) and Normalized Difference Vegetation Index (NDVI) obtained from Landsat 8 data\udover the study area were used to verify vegetation and urban classes. The study compares the accuracies of different methods of\udclassifying landcover using medium resolution SAR data in a complex urban area and suggests that polarimetric analyses present the\udmost accurate results for urban and suburban areas

the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences

COMPARISON BETWEEN SPECTRAL, SPATIAL AND POLARIMETRIC CLASSIFICATION OF URBAN AND PERIURBAN LANDCOVER USING TEMPORAL SENTINEL – 1 IMAGES