4.5 Article

Land change modeler and CA-Markov chain analysis for land use land cover change using satellite data of Peshawar, Pakistan

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PHYSICS AND CHEMISTRY OF THE EARTH
卷 128, 期 -, 页码 -

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PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.pce.2022.103286

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Urbanization; Urban sprawl; GIS; Remote sensing; Land change modeler; CA-Markov chain model

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Urbanization is a global phenomenon that leads to dramatic changes in land use and land cover in many regions, particularly due to urban sprawl and its consequences. This study assesses and predicts the urban growth and land use and land cover changes in Peshawar city using the Cellular-Automata-Markov-Chain model. The results show significant expansion in built-up areas and vegetation, replacing bare lands. The model predicts further growth in built-up areas and vegetation in the future.
Urbanization is a global phenomenon that caused many regions worldwide to face dramatic Land Use Land Cover (LULC) changes associated with urban sprawl and significant consequences. This research aims to assess and predict the urban growth of Peshawar city as well as LULC with a Cellular-Automata-Markov-Chain (CA-Markov-Chain). LULC distributions were mapped using Landsat (5, 7, and 8) data from 1998, 2003, 2008, 2013 and 2018. Long-term changes to the landscape were simulated using a CA-Markov model at 10-year intervals from 2018, 2028 and 2038. Finally, the overall accuracy and kappa coefficient were used to validate the models and LULC maps accuracies. Results indicate a substantial expansion in built-up area and vegetation class for Peshawar city replacing bare land. As a result of our research, the total built-up area was increased in 2018 was 272 km(2). Peshawar's vegetation cover has increased by 25.6% throughout the study period, especially 12.7% under the billion-tree project (from 2013 to 2018). According to CA-Markov Chain analysis, we can predict the growth of built-up area and vegetation area from 299.75 km(2) (23.71%) to 318.92 km(2) (25.23%) and 701.38 km(2) (55.48%) to 748.69 km(2) (59.23%) between 2028 and 2038, based on the development from 1998 to 2018. This study is very significant for the urban designing, urban development, policy makers and law enforcement departments.

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