Examining the effects of vented dams on land use and land cover in the Shambhavi Catchment: a multitemporal sentinel imagery analysis
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Date
2024
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier Ltd
Abstract
The rapid expansion of the global economy has given rise to concerning ecological consequences, notably a dramatic increase in land cover change (LCC). This section presents how to use the Google Earth Engine (GEE) cloud platform to explore the administrative divisions of the Southern Indian Dakshina Kannada (DK) district, which were chosen for their LCC susceptibility. Leveraging GEE, we generated a time series dataset tracking LCC over a 4-year period (2019–22). Our findings demonstrate an impressive overall accuracy (OA) of 96.30% for 2019 and 95.47% for 2022. A significant revelation in our study is the 13.64% reduction in forested areas, accompanied by a 0.68% increase in urban development within the district. This research attempt offers vital insights into the impact of dam construction on LCC, aiding informed decisions on water resource management. This research promotes a sustainable and ecologically conscious approach to holistic development in the study region and beyond. © 2024 Elsevier B.V.
Description
Keywords
change detection, environmental management, geomatics, Google Earth Engine, hydrology, impact assessment, India, Karnataka, land use land cover, machine learning, multitemporal, natural resource management, random forest, Sentinel-2, supervised classification, surface water, Vented dams
Citation
Developments in Environmental Science, 2024, Vol.16, , p. 431-454
