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## Introduction Information of different LULC, extracted from satellite data, is useful for the policy makers in understanding the dynamics of environment (Gashu and Gebre-Egziabher, 2018) to ensure the sustainable development (Nwokoro and Dekolo, 2012). Therefore, identification of the LULC types in any region has become an important area of research nowadays (Zhang et al., 2006). Satellite data are very good data source to derive information regarding LULC. In an urban context when remotely sensed multiband satellite data is used, sometimes the correlation, spectral confusion, and redundancy between different bands may be high. Due to this, all of the features, present in an urban area, may not be distinguished properly (Mwakapuja et al., 2013). In urban areas, assessment and quantification of LULCC is a challenging task as these areas have large spatio-temporal variations and activities of diversified nature take place (Faridatul and Wu, 2018). Thus, a more precise image classification methodology for LULC mapping is needed (Sinha et al., 2015). The spectral characteristics of built-up area and bare soil are quite similar; thereby, it causes confusion and misclassification among

Author

Atul Kant Piyoosh; Sanjay Kumar Ghosh

Publisher

Elsevier - Health Sciences Division

Published

2023

Language

EN

ISBN

9780443186417

Subjects

Science, Social Science, Anthropology