Spatiotemporal changes of impervious surface areas in Great Mekong Subregion from 1992 to 2019

被引:1
|
作者
He, Li [1 ]
Shi, Zhengtao [1 ]
机构
[1] Yunnan Normal Univ, Fac Geog, Kunming, Yunnan, Peoples R China
基金
中国国家自然科学基金;
关键词
impervious surface area; remote sensing; Great Mekong Subregion; GOOGLE EARTH ENGINE; SPECTRAL MIXTURE ANALYSIS; ANNUAL URBAN-DYNAMICS; BIG DATA APPLICATIONS; TIME-SERIES; NIGHTTIME LIGHT; INDEX; SEGMENTATION; DATASETS; ACCURACY;
D O I
10.1117/1.JRS.15.048506
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
As one of the fastest growing economies in the world, the Great Mekong Subregion (GMS) has experienced dramatic changes in impervious surface areas (ISA) during the last few decades, which have a profound impact on human society and ecosystems. To quantify the impacts of rapid urbanization, it is essential to examine spatial distribution and dynamic change of ISA in the GMS. Thus we the applied object-based image analysis (OBIA) method to map ISA in the GMS from 1992 to 2019 using nighttime light data and Landsat images. Meanwhile, spatiotemporal changes of ISA across the GMS during the study period were analyzed. Our results show that (1) the OBIA algorithm was effective for mapping ISA in the GMS, with the overall accuracy reaching 92.28%. (2) The ISA in the GMS reached 17671.47 km(2) in 2019, which is 4.36 times more than that in 1992. (3) The increase of ISA in the GMS mainly occurred in 10 metropolitan cities with the highest population densities, accounting for similar to 93% of the GMS's total in 2019. There are different possible major driving factors for each city and member state. Monitoring the spatiotemporal changes of ISA in rapidly urbanized areas is crucial for promoting sustainable urban development and reducing the impact of urbanization. (C) 2021 Society of Photo-Optical Instrumentation Engineers (SPIE)
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页数:19
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