Quantitative Comparison of Open-Source Data for Fine-Grain Mapping of Land Use
作者： Shawn Newsam , Xueqing Deng
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摘要: This paper performs a quantitative comparison of open-source data available on the Internet for fine-grain mapping land use. Three points interest (POI) sources--Google Places, Bing Maps, and Yellow Pages--and one volunteered geographic information source--Open Street Map (OSM)--are compared with each other at parcel level San Francisco respect to proposed land-use taxonomy. The sources are also coarse-grain authoritative which we consider be ground truth. Results show limited agreement among as well accuracy even coarse class granularity. We conclude that POI OSM do not appear sufficient alone mapping.
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