文章基本信息

标题：A national dataset of 30m annual urban extent dynamics (1985–2015) in the conterminous United States
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作者：Li, Xuecao ; Zhou, Yuyu ; Zhu, Zhengyuan 等
期刊名称：Earth System Science Data Discussions
电子版ISSN：1866-3591
出版年度：2020
卷号：12
期号：1
页码：357-371
DOI：10.5194/essd-12-357-2020
语种：English
出版社：Copernicus Publications
摘要：Dynamics of the urban extent at fine spatial and temporalresolutions over large areas are crucial for developing urban growth modelsand achieving sustainable development goals. However, there are limitedpractices of mapping urban dynamics with these two merits combined. In thisstudy, we proposed a new method to map urban dynamics from Landsat timeseries data using the Google Earth Engine (GEE) platform and developed anational dataset of annual urban extent (1985–2015) at a fine spatialresolution (30 m) in the conterminous United States (US). First, we derivedthe change information of urbanized years in four periods that weredetermined from the National Land Cover Database (NLCD), using a temporalsegmentation approach. Then, we classified urban extents in the beginning (1985) and ending (2015) years at the cluster level through the implementation of achange vector analysis (CVA)-based approach. We also developed ahierarchical strategy to apply the CVA-based approach due to the spatiallyexplicit urban sprawl over large areas. The overall accuracy of mappedurbanized years is around 90 % with the 1-year tolerance strategy. Themapped urbanized areas in the beginning and ending years are reliable, withoverall accuracies of 96 % and 88 %, respectively. Our results revealthat the total urban area increased by about 20 % during the periodof 1985–2015 in the US, and the annual urban area growth is not linear over the years. Overall, the growth pattern of urban extent in most coastal states isplateaued over the past three decades while the states in the Midwestern USshow an accelerated growth pattern. The derived annual urban extents are ofgreat use for relevant urban studies such as urban area projection and urbansprawl modeling over large areas. Moreover, the proposed mapping frameworkis transferable for developing annual dynamics of urban extent in otherregions and even globally. The data are available at https://doi.org/10.6084/m9.figshare.8190920.v2 (Li et al.,2019c).