Expansion of Impervious Surfaces and Their Driving Forces in Highly Urbanized Cities in Kyrgyzstan.

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ID: 82392
2020
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Ranked #463 of 862 articles by views in International journal of environmental research and public health

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Abstract
The expansion of urban areas due to population increase and economic expansion creates demand and depletes natural resources, thereby causing land use changes in the main cities. This study focuses on land cover datasets to characterize impervious surface (urban area) expansion in select cities from 1993 to 2017, using supervised classification maximum likelihood techniques and by quantifying impervious surfaces. The results indicate an increasing trend in the impervious surface area by 35% in Bishkek, 75% in Osh, and 15% in Jalal-Abad. The overall accuracy (OA) for the image classification of two different datasets for the three cities was between 82% and 93%, and the kappa coefficients (KCs) were approximately 77% and 91%. The Landsat images with other supplementary data showed positive urban growth in all of the cities. The GDP, industrial growth, and urban population growth were driving factors of impervious surface sprawl in these cities from 1993 to 2017.Landscape Expansion Index (LEI) results also provided good evidence for the change of impervious surfaces during the study period. The results emphasize the idea of applying future planning and sustainable urban development procedures for sustainable use of natural resources and their management, which will increase life quality in urban areas and environments.
Reference Key
omurakunova2020expansioninternational Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Omurakunova, Gulkaiyr;Bao, Anming;Xu, Wenqiang;Duulatov, Eldiiar;Jiang, Liangliang;Cai, Peng;Abdullaev, Farkhod;Nzabarinda, Vincent;Durdiev, Khaydar;Baiseitova, Makhabat;
Journal International journal of environmental research and public health
Year 2020
DOI
E362
URL
Keywords
urban driving factors impervious surfaces landscape expansion index supervised classification

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