Automated identification and characterization of parcels (AICP) with OpenStreetMap and Points of Interest
Automated identification and characterization of parcels (AICP) with OpenStreetMap and Points of Interest
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发表时间：
2013-11
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通讯作者：
Ying Long;Xingjian Liu
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作者：
Ying Long;Xingjian Liu
针对中国城市地块数量稀少的现状，本文提出了一种基于OpenStreetMap （OSM）和兴趣点（POI）数据的地块自动识别和特征化方法。地块是精细尺度城市建模、城市研究和空间规划的基本空间单元。传统的包裹识别和表征方法依赖于遥感和实地调查，这是劳动密集型和资源消耗。不发达的数字基础设施、有限的资源和制度障碍都阻碍了发展中国家包裹数据的收集和应用。在此背景下，我们使用OSM道路网络来识别包裹几何形状，并使用POI数据来推断包裹特征。采用基于向量的CA模型对城市地块进行选择。该方法适用于整个中国，在297个城市中识别出82645个城市地块。尽管有公开和/或众包数据的所有警告，但我们的方法可以产生与传统方法识别的包裹相当好的近似，因此有可能成为有用的补充。
Against the paucity of urban parcels in China, this paper proposes a method to automatically identify and characterize parcels (AICP) with OpenStreetMap (OSM) and Points of Interest (POI) data. Parcels are the basic spatial units for fine-scale urban modeling, urban studies, as well as spatial planning. Conventional ways of identification and characterization of parcels rely on remote sensing and field surveys, which are labor intensive and resource-consuming. Poorly developed digital infrastructure, limited resources, and institutional barriers have all hampered the gathering and application of parcel data in developing countries. Against this backdrop, we employ OSM road networks to identify parcel geometries and POI data to infer parcel characteristics. A vector-based CA model is adopted to select urban parcels. The method is applied to the entire state of China and identifies 82,645 urban parcels in 297 cities. Notwithstanding all the caveats of open and/or crowd-sourced data, our approach could produce reasonably good approximation of parcels identified from conventional methods, thus having the potential to become a useful supplement.