DOI: 10.1016/j.jag.2017.07.014
Scopus记录号: 2-s2.0-85032466874
论文题名: Open land cover from OpenStreetMap and remote sensing
作者: Schultz M ; , Voss J ; , Auer M ; , Carter S ; , Zipf A
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2017
卷: 63 起始页码: 206
结束页码: 213
语种: 英语
英文关键词: Land cover
; OpenStreetMap
; Random forest
; Remote sensing
; Tag based
Scopus关键词: accuracy assessment
; land classification
; land cover
; remote sensing
; thematic mapping
; Baden-Wurttemberg
; Germany
; Heidelberg
英文摘要: OpenStreetMap (OSM) tags were used to produce a global Open Land Cover (OLC) product with fractional data gaps available at osmlanduse.org. Data gaps in the global OLC map were filled for a case study in Heidelberg, Germany using free remote sensing data, which resulted in a land cover (LC) prototype with complete coverage in this area. Sixty tags in the OSM were used to allocate a Corine Land Cover (CLC) level 2 land use classification to 91.8% of the study area, and the remaining gaps were filled with remote sensing data. For this case study, complete are coverage OLC overall accuracy was estimated 87%, which performed better than the CLC product (81% overall accuracy) of 2012. Spatial thematic overlap for the two products was 84%. OLC was in large parts found to be more detailed than CLC, particularly when LC patterns were heterogeneous, and outperformed CLC in the classification of 12 of the 14 classes. Our OLC product represented data created in different periods; 53% of the area was 2011–2016, and 46% of the area was representative of 2016–2017. © 2017 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79974
Appears in Collections: 气候变化事实与影响
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作者单位: GI-Science, Heidelberg University, Im Neuenheimer Feld 348 Room 19, Germany; Laboratory of Geo-Information Science and Remote Sensing, Wageningen University, Droevendaalsesteeg 3, Wageningen, Netherlands
Recommended Citation:
Schultz M,, Voss J,, Auer M,et al. Open land cover from OpenStreetMap and remote sensing[J]. International Journal of Applied Earth Observation and Geoinformation,2017-01-01,63