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

Environmental Research Letters · 2020 · Vol. 15(9) · pp. 094044–094044
Xuecao LiPeng GongYuyu ZhouJie WangYuqi BaiБин ЧэнTengyun HuYixiong XiaoBing XuJun YangXiaoping LiuWenjia CaiHuabing HuangTinghai WuXi WangPeng LinXun LiJin ChenChunyang HeXia LiLe YuNicholas ClintonZhiliang Zhu

Abstract

Abstract 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 km 2 , is 809 664 km 2 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 m 2 ) 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 .

Land Use and Ecosystem ServicesImpact of Light on Environment and HealthUrban Green Space and HealthImpervious surfaceBoundary (topology)Urban planningRemote sensingUrban areaScale (ratio)GeographyKernel density estimationCartographyEnvironmental science

Funding

  • Iowa State University
  • Tsinghua University
Citations
706
FWCI
27.50
field-weighted impact
References
59
Percentile
100%
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Citations per year
References
A new urban landscape in East–Southeast Asia, 2000–2010
Environmental Research Letters · 2015 · 449 citations
Global Consequences of Land Use
Science · 2005 · 12,734 citations
Google Earth Engine: Planetary-scale geospatial analysis for everyone
Remote Sensing of Environment · 2017 · 13,362 citations
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