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Spatiotemporal evolution of impervious surface and the driving factors in Chenggong District, Kunming City.
- Source :
- Remote Sensing for Natural Resources; Jun2022, Vol. 34 Issue 2, p136-143, 8p
- Publication Year :
- 2022
-
Abstract
- Impervious surface is a key factor to measure the urban ecological environment. It is of great significance for urban development planning to grasp the dynamic changes of impervious surfaces timely and accurately. Taking the Chenggong District of Kunming City as an example' based on the Landsat images in 2007' 2011' 2015' and 2019' the comparative study of normalized difference impervious surface index ( NDISI) and modified soil adjusted vegetation index ( MSAVI) was carried out to analyze the spatial and temporal evolution characteristics of impervious surface. The results showed that: !As the extraction accuracy and Kappa coefficient of NDISI were 87. 01% and 0. 81' respectively' which were beUer than MSAVI's 81. 78% and 0. 75 ' this paper selected the NDISI method to extract impervious surfaces in the Chenggong District the impervious surface area extracted in this paper increased from 46. 12 km2 in 2007 to 72. 64 km2 in 2011' 146. 94 km2 in 2015 and 164. 42 km2 in 2019' especially from 2011 to 2015' the impervious surface area had the fastest growth rate and nearly doubled. The changes to the impervious surface in Chenggong District are mainly influenced by such factors as national policies' urban planning' topographic factors' and traffic development. The impervious surface area along the Dianchi Lake in the west of Chenggong District and several administrative regions in the middle of Chenggong District developed rapidly' which brings certain preesure on the prevention and control of waterlogging in urban areas and the Dianchi Lake area. In the process of future urban planning' the expansion scope and speed of impervious surfaces should be wen controlled to avoid ecological and environmental problems caused by the unreasonable spatial patterns of impervious sur&aces. [ABSTRACT FROM AUTHOR]
Details
- Language :
- Chinese
- ISSN :
- 2097034X
- Volume :
- 34
- Issue :
- 2
- Database :
- Complementary Index
- Journal :
- Remote Sensing for Natural Resources
- Publication Type :
- Academic Journal
- Accession number :
- 157743010
- Full Text :
- https://doi.org/10.6046/zrzyg.2021187