  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.
