Modelling of land use and land cover changes and prediction using CA-Markov and Random Forest
نویسندگان
چکیده
We used the Cellular Automata Markov (CA-Markov) integrated technique to study land use and cover (LULC) changes in Cholistan Thal deserts Punjab, Pakistan. plotted distribution of LULC throughout desert terrain for years 1990, 2006 2022. The Random Forest methodology was utilized classify data obtained from Landsat 5 (TM), 7 (ETM+) 8 (OLI/TIRS), as well ancillary data. maps generated using this method have an overall accuracy more than 87%. CA-Markov forecast usage 2022, were projected 2038 by extending patterns seen A CA-Markov-Chain developed simulating long-term landscape at 16-year time steps 2022 2038. Analysis urban sprawl carried out (RF). Through Chain analysis, we can expect that high density low-density residential areas will grow 8.12 12.26 km2 18.10 28.45 2038, inferred occurred 1990 showed there would be increased urbanization terrain, with probable development croplands westward northward, growth centers. findings potentially assist management operations geared towards conservation wildlife eco-system region. This also a reference other studies try project arid are undergoing land-use comparable those study.
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ژورنال
عنوان ژورنال: Geocarto International
سال: 2023
ISSN: ['1010-6049', '1752-0762']
DOI: https://doi.org/10.1080/10106049.2023.2210532