Content area

Abstract

Using more than three million Landsat satellite images, this research developed the first global impervious surface area (GISA) dataset from 1972 to 2019. Based on 120,777 independent and random reference sites from 270 cities all over the world, the omission error, commission error, and F-score of GISA are 5.16%, 0.82%, and 0.954, respectively. Compared to the existing global datasets, the merits of GISA include: (1) It provided the global ISA maps before the year of 1985, and showed the longest time span (1972–2019) and the highest accuracy (in terms of a large number of randomly selected and third-party validation sample sets); (2) it presented a new global ISA mapping method including a semi-automatic global sample collection, a locally adaptive classification strategy, and a spatio-temporal post-processing procedure; and (3) it extracted ISA from the whole global land area (not from an urban mask) and hence reduced the underestimation. Moreover, on the basis of GISA, the long time series global urban expansion pattern (GUEP) has been calculated for the first time, and the pattern of continents and representative countries were analyzed. The two new datasets (GISA and GUEP) produced in this study can contribute to further understanding on the human’s utilization and reformation to nature during the past half century, and can be freely download from http://irsip.whu.edu.cn/resources/dataweb.php.

Details

Title
30 m global impervious surface area dynamics and urban expansion pattern observed by Landsat satellites: From 1972 to 2019
Author
Huang, Xin 1 ; Li, Jiayi 2 ; Yang, Jie 2 ; Zhang, Zhen 2 ; Li, Dongrui 2 ; Liu, Xiaoping 3 

 Wuhan University, School of Remote Sensing and Information Engineering, Wuhan, China (GRID:grid.49470.3e) (ISNI:0000 0001 2331 6153); Wuhan University, State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan, China (GRID:grid.49470.3e) (ISNI:0000 0001 2331 6153) 
 Wuhan University, School of Remote Sensing and Information Engineering, Wuhan, China (GRID:grid.49470.3e) (ISNI:0000 0001 2331 6153) 
 Sun Yat-Sen University, Guangdong Key Laboratory for Urbanization and Geo-simulation, School of Geography and Planning, Guangzhou, China (GRID:grid.12981.33) (ISNI:0000 0001 2360 039X) 
Pages
1922-1933
Publication year
2021
Publication date
Nov 2021
Publisher
Springer Nature B.V.
ISSN
16747313
e-ISSN
18691897
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2590784081
Copyright
© Science China Press and Springer-Verlag GmbH Germany, part of Springer Nature 2021.