DOI: 10.1016/j.jag.2016.04.002
Scopus记录号: 2-s2.0-84997482096
论文题名: Urban land cover thematic disaggregation, employing datasets from multiple sources and RandomForests modeling
作者: Gounaridis D ; , Koukoulas S
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2016
卷: 51 起始页码: 1
结束页码: 10
语种: 英语
英文关键词: Landsat
; RandomForests
; Thematic disaggregation
; Urban atlas
; Urban land cover
英文摘要: Urban land cover mapping has lately attracted a vast amount of attention as it closely relates to a broad scope of scientific and management applications. Late methodological and technological advancements facilitate the development of datasets with improved accuracy. However, thematic resolution of urban land cover has received much less attention so far, a fact that hampers the produced datasets utility. This paper seeks to provide insights towards the improvement of thematic resolution of urban land cover classification. We integrate existing, readily available and with acceptable accuracies datasets from multiple sources, with remote sensing techniques. The study site is Greece and the urban land cover is classified nationwide into five classes, using the RandomForests algorithm. Results allowed us to quantify, for the first time with a good accuracy, the proportion that is occupied by each different urban land cover class. The total area covered by urban land cover is 2280 km2 (1.76% of total terrestrial area), the dominant class is discontinuous dense urban fabric (50.71% of urban land cover) and the least occurring class is discontinuous very low density urban fabric (2.06% of urban land cover). © 2016 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/80068
Appears in Collections: 气候变化事实与影响
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作者单位: SAGISRS Lab, Department of Geography, University of the Aegean, Mytilene, Lesvos, Greece
Recommended Citation:
Gounaridis D,, Koukoulas S. Urban land cover thematic disaggregation, employing datasets from multiple sources and RandomForests modeling[J]. International Journal of Applied Earth Observation and Geoinformation,2016-01-01,51