Aeolian sand affected wasteland monitoring using multi-temporal remotely sensed imagery: A case study of Sirsa district of Haryana, India

Evaluation of integrated classification data for glacier terrain mapping using the Maximum likelihood classifier (MLC) approach: A case study of Kolahoi Glacier in Jammu & Kashmir

“…According to Negi et al (2021), statistical analysis was conducted using polynomial regression and non-linear regression, and data-driven models for a mountainous catchment were created using fuzzy logic (FL) and advances tool artificial neural networks (ANN). In numerous areas of a few Indian states, including Haryana, Rajasthan, and Punjab, fast deforestation, changes in land use/land cover (LULC), intensive agriculture, and urbanization have had a significant negative impact on desertification, according to a statement made by Rawat et al 2022. Therefore, in the present study, data from various ancillary sources have been integrated with the spectral data, and a integrated classification classification approach has been adopted to map nine different classes in a glacierized terrain located in and around the Kolahoi glacier. The main aim of the present study is to perform a integrated classification classification for the mapping of various glacier terrain classes (snow, ice, debris, water, periglacial debris, supraglacial debris, valley rock, shadow, and vegetation) using remote sensing and other ancillary data.…”