globalchange  > 气候变化事实与影响
DOI: 10.1016/j.jag.2014.09.005
Scopus记录号: 2-s2.0-84924366937
论文题名:
Multitemporal settlement and population mapping from landsatusing google earth engine
作者: Patela N; N; , Angiuli E; , Gamba P; , Gaughan A; , Lisini G; , Stevens F; R; , Tatem A; J; , Trianni G
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2015
卷: 35, 期:PB
起始页码: 199
结束页码: 208
语种: 英语
英文关键词: Google earth engine ; Landsat ; Multitemporal ; Population mapping ; Settlement mapping ; Spatial demography ; Urbanization
Scopus关键词: demographic transition ; Landsat ; mapping ; population dynamics ; satellite imagery ; settlement pattern ; urbanization ; World Wide Web ; Greater Sunda Islands ; Indonesia ; Java ; Sunda Isles
英文摘要: As countries become increasingly urbanized, understanding how urban areas are changing within thelandscape becomes increasingly important. Urbanized areas are often the strongest indicators of humaninteraction with the environment, and understanding how urban areas develop through remotely senseddata allows for more sustainable practices. The Google Earth Engine (GEE) leverages cloud computingservices to provide analysis capabilities on over 40 years of Landsat data. As a remote sensing platform, its ability to analyze global data rapidly lends itself to being an invaluable tool for studying the growthof urban areas. Here we present (i) An approach for the automated extraction of urban areas from Land-sat imagery using GEE, validated using higher resolution images, (ii) a novel method of validation ofthe extracted urban extents using changes in the statistical performance of a high resolution populationmapping method. Temporally distinct urban extractions were classified from the GEE catalog of Landsat5 and 7 data over the Indonesian island of Java by using a Normalized Difference Spectral Vector (NDSV)method. Statistical evaluation of all of the tests was performed, and the value of population mappingmethods in validating these urban extents was also examined. Results showed that the automated clas-sification from GEE produced accurate urban extent maps, and that the integration of GEE-derived urbanextents also improved the quality of the population mapping outputs. © 2014 Elsevier B.V.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79554
Appears in Collections:气候变化事实与影响

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作者单位: Department of Geography and Geoinformation Science, George Mason University, 4400 University Drive, MS 6C3, Fairfax, VA, United States; Department of Electrical, Biomedical and Computer Engineering, University of Pavia, Italy; Department of Geography and Geosciences, University of Louisville, 213 Lutz Hall, Louisville, KY, United States; Department of Geography and Environment, University of Southampton, Highfield, Southampton, United Kingdom; Fogarty International Center, National Institutes of Health, Bethesda, MD, United States; Flowminder Foundation, Stockholm, Sweden

Recommended Citation:
Patela N,N,, Angiuli E,et al. Multitemporal settlement and population mapping from landsatusing google earth engine[J]. International Journal of Applied Earth Observation and Geoinformation,2015-01-01,35(PB)
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