Land use Mapping of Yamuna river Flood Plain in Delhi using K-Mean and spectral angle image classification algorithms Ahmad Nehal1, Ahsan Naved2, Said Saif3 1Department of Civil Engineering, Aliah University, Kolkata, India 2Department of Civil Engineering, Jamia Milia Islamia, New Delhi, India 3Department of Civil Engineering, Aligarh Muslim University, India Online published on 7 September, 2019. Abstract This study intends to analyze the land use mapping within the Yamuna river flood plain in Delhi by USGS-LULC level II category classification system using K-Mean and Spectral Angle algorithm. ERDAS imagine 9.2 were used for Image processing and land use assessment. The Landsat 8 (2018) and TM (2000) images were acquired for assessing the classification algorithms. LULC classification was achieved with overall accuracies of 86.00%, 86.00%, 94.00% and 96.00% for the year of assessment 2000 and 2018 by K-Mean and Spectral Angle algorithm respectively. The kappa coefficient was achieved as 0.76, 0.69, 0.88 and 0.9 for the year of assessment 2000 and 2018 by K-Mean and Spectral Angle algorithm respectively. For the year of assessment 2000, the maximum and minimum land use was 40% and 4% for Agriculture and barren land respectively where as for the year of assessment 2018, the maximum and minimum land use was 30% and 6% for Forest and barren land respectively. During the assessment period 2000 to 2018, the maximum gain and loss recorded for forest and agriculture respectively. The results of this study can be significantly used for land use planning and management of the Yamuna River Flood Plain. Top Keywords Classification algorithm, Land use mapping, Remote Sensing and GIS, Yamuna River. Top |