4.5 Article

Assessment and prediction of urban growth for a mega-city using CA-Markov model

期刊

GEOCARTO INTERNATIONAL
卷 36, 期 17, 页码 1960-1992

出版社

TAYLOR & FRANCIS LTD
DOI: 10.1080/10106049.2019.1690054

关键词

Urban Growth; spatio-temporal LULC change; land use dynamic degree; transition potential modeling; CA-Markov modeling

向作者/读者索取更多资源

This study assessed the land use and land cover changes in Chennai using temporal Landsat data and various analytical methods to study the impact of urbanization. The results showed a growing trend in the urban area of Chennai, with the prediction model indicating that vegetation and barren land will continue to be converted into urban land in the coming decades.
Most of World's mega-cities are facing high population growth. To accommodate the increased population, new built-up areas are emerging at the periphery or fringe area of cities. New urbanisation has an adverse impact on the existing Land Use Land Cover (LULC). To monitor and analyse the impact of urbanisation, LULC change analysis has become the primary concern for LULC monitoring agencies. In this study, LULC change of Chennai has been assessed during 1981-2011 using temporal Landsat data. All the dataset has been classified using Maximum Likelihood Classifier (MLC). Quantitative change in LULC has been carried out using Pearson's Correlation Coefficient, Transition Potential Matrix, Land Use Dynamic Degree and MLC. Further, spatio-temporal change analysis has been performed using Post-classification comparison technique. Cellular Automata-Markov (CA-Markov) Model used for LULC prediction for 2021-2051. The urban area of Chennai has increased from 40.74 to 103.52 km(2) during 1981-2011. Further, LULC prediction using the CA-Markov model shows that the urban area of Chennai district may increase from 103.52 to 140.79 km(2) during 2011-2051. During the period 1981-2051, the prediction model indicates that mostly vegetation and barren land will be converted into urban land class.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.5
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据