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Automated identification and characterization of parcels with OpenStreetMap and points of interest

机译:使用OpenStreetMap和兴趣点自动识别和表征包裹

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Against the paucity of information on urban parcels in China, we propose a method to automatically identify and characterize parcels using OpenStreetMap (OSM) and points of interest (POI) data. Parcels are the basic spatial units for fine-scale urban modeling, urban studies, and spatial planning. Conventional methods for 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 China. Against this backdrop, we employ OSM road networks to identify parcel geometries and POI data to infer parcel characteristics. A vector-based cellular automata 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 can produce a reasonably good approximation of parcels identified using conventional methods, thus it has the potential to become a useful tool.
机译:针对中国城市地块信息匮乏的情况,我们提出了一种使用OpenStreetMap(OSM)和兴趣点(POI)数据自动识别和表征地块的方法。宗地是用于精细规模城市建模,城市研究和空间规划的基本空间单位。用于识别和表征包裹的常规方法依赖于遥感和现场调查,这需要大量的劳力和资源。数字基础设施发展欠佳,资源有限以及体制障碍,都阻碍了中国包裹数据的收集和应用。在这种背景下,我们采用OSM道路网络来识别宗地几何形状和POI数据以推断宗地特性。采用基于向量的元胞自动机模型选择城市地块。该方法适用于整个中国,可识别297个城市的82645个城市地块。尽管公开和/或众包数据的所有注意事项,我们的方法仍可以使用传统方法对包裹进行合理合理的近似估计,因此它有可能成为有用的工具。

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