Spatiotemporal analysis of urban sprawl using a multi-technique approach and remote sensing satellite imagery from 1990 to 2020: Kerman/Iran

被引:15
作者
Mohimi, Amirmohim [1 ]
Esmaeily, Ali [2 ]
机构
[1] Res Inst Cultural Heritage & Tourism, Tehran, Iran
[2] Grad Univ Adv Technol, Kerman, Iran
关键词
Dynamic sprawl; Machine learning; Support vector machine (SVM); Remote sensing; Static sprawl; Urban growth; LAND-COVER; GROWTH; GIS; METRICS; AREA;
D O I
10.1007/s10668-023-03378-8
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In this research, remote sensing satellite imagery has been applied to assess dynamic and static sprawl measured simultaneously via a multi-technique approach. The first technique, which evaluates dynamic sprawl, essentially measures the "magnitude" and "direction". The second technique, which evaluates static sprawl, measures the "magnitude" and "pattern". The dynamic sprawl used in this study, shows in which "direction", in what "period" and to what "extent" Kerman had sprawl. In the static sprawl, the most sprawled pattern that the city of Kerman follows is Area-Edge, followed by Aggregation, Shape and Diversity, respectively.
引用
收藏
页码:18033 / 18068
页数:36
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