Publications by authors named "Deepanshu Parashar"
Article Synopsis
- The study addresses urbanization challenges in developing countries, focusing on improved Land Use Land Cover (LULC) classification mapping to tackle issues like traffic congestion and slum development.
- It explores the use of machine learning algorithms, specifically Random Forest (RF) and Support Vector Machine (SVM), to enhance LULC classification, particularly in mountainous terrains where classification is more complex.
- The research utilized Google Earth Engine to create four different classification models based on Sentinel 2B satellite imagery, achieving accuracies of 82% and 86% for standard models and 87.17% and 87.2% for models incorporating additional indices.
There are several causes for the increasing rate of deglaciation, such as global warming, increase in the concentration of black carbon, and extensive use of fossil fuels which causes the change in the overall climate system and shifting glacier ecosystem. This study was conducted on Pindari valley glaciers part of lesser Himalaya in Uttarakhand. This study investigates to (1) monitor and map change in the frontal length or the snout region of a glacier that can be studied with the help of remote sensing techniques and (2) evaluate the decadal and annual retreat rate of the glacier from 1972 to 2018.
View Article and Find Full Text PDFVegetation dynamics is an important aspect for determining climate change trends. The present study delineates to examine spatiotemporal changes of vegetation cover in Pindari valley (Kumaun Himalaya) from the 1972 to 2018 timeline. The study includes the calculation of vegetation spectral indices of normalized vegetation index (NDVI), extraction of different vegetation classes, and statistical analysis of the Mann-Kendall (MK) test on historical metrological data (especially precipitation and temperature) of the study site.
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