skip to main content
Language:
Search Limited to: Search Limited to: Resource type Show Results with: Show Results with: Search type Index

Mapping global urban boundaries from the global artificial impervious area (GAIA) data

Environmental research letters, 2020-09, Vol.15 (9), p.94044 [Peer Reviewed Journal]

2020 The Author(s). Published by IOP Publishing Ltd ;Copyright IOP Publishing Sep 2020 ;ISSN: 1748-9326 ;EISSN: 1748-9326 ;DOI: 10.1088/1748-9326/ab9be3 ;CODEN: ERLNAL

Full text available

Citations Cited by
  • Title:
    Mapping global urban boundaries from the global artificial impervious area (GAIA) data
  • Author: Li, Xuecao ; Gong, Peng ; Zhou, Yuyu ; Wang, Jie ; Bai, Yuqi ; Chen, Bin ; Hu, Tengyun ; Xiao, Yixiong ; Xu, Bing ; Yang, Jun ; Liu, Xiaoping ; Cai, Wenjia ; Huang, Huabing ; Wu, Tinghai ; Wang, Xi ; Lin, Peng ; Li, Xun ; Chen, Jin ; He, Chunyang ; Li, Xia ; Yu, Le ; Clinton, Nicholas ; Zhu, Zhiliang
  • Subjects: Biodiversity ; Boundaries ; Cellular automata ; Climate change ; Datasets ; Delineation ; Food security ; GEE ; Image resolution ; kernel density ; multi-temporal ; nighttime light ; Satellite imagery ; Satellites ; Urban areas ; urban clusters ; Urban development ; Urban sprawl ; Urbanization
  • Is Part Of: Environmental research letters, 2020-09, Vol.15 (9), p.94044
  • Description: Urban boundaries, an essential property of cities, are widely used in many urban studies. However, extracting urban boundaries from satellite images is still a great challenge, especially at a global scale and a fine resolution. In this study, we developed an automatic delineation framework to generate a multi-temporal dataset of global urban boundaries (GUB) using 30 m global artificial impervious area (GAIA) data. First, we delineated an initial urban boundary by filling inner non-urban areas of each city. A kernel density estimation approach and cellular-automata based urban growth modeling were jointly used in this step. Second, we improved the initial urban boundaries around urban fringe areas, using a morphological approach by dilating and eroding the derived urban extent. We implemented this delineation on the Google Earth Engine platform and generated a 30 m resolution global urban boundary dataset in seven representative years (i.e. 1990, 1995, 2000, 2005, 2010, 2015, and 2018). Our extracted urban boundaries show a good agreement with results derived from nighttime light data and human interpretation, and they can well delineate the urban extent of cities when compared with high-resolution Google Earth images. The total area of 65 582 GUBs, each of which exceeds 1 km2, is 809 664 km2 in 2018. The impervious surface areas account for approximately 60% of the total. From 1990 to 2018, the proportion of impervious areas in delineated boundaries increased from 53% to 60%, suggesting a compact urban growth over the past decades. We found that the United States has the highest per capita urban area (i.e. more than 900 m2) among the top 10 most urbanized nations in 2018. This dataset provides a physical boundary of urban areas that can be used to study the impact of urbanization on food security, biodiversity, climate change, and urban health. The GUB dataset can be accessed from http://data.ess.tsinghua.edu.cn.
  • Publisher: Bristol: IOP Publishing
  • Language: English
  • Identifier: ISSN: 1748-9326
    EISSN: 1748-9326
    DOI: 10.1088/1748-9326/ab9be3
    CODEN: ERLNAL
  • Source: DOAJ Directory of Open Access Journals
    Geneva Foundation Free Medical Journals at publisher websites
    IOP Publishing (Open access)
    AUTh Library subscriptions: ProQuest Central
    IOPscience (Open Access)
    ROAD: Directory of Open Access Scholarly Resources
Back to results list
INSPIRE LIBRARY - TON DUC THANG UNIVERSITY (84-028) 37 755 057 Feedback
19 Nguyen Huu Tho St. Dist.7, HCM thuvien@tdtu.edu.vn

Copyright © 2017 INSPIRE LIBRARY - TON DUC THANG UNIVERSITY

Searching Remote Databases, Please Wait