Automating land parcel classification for neighborhood-scale urban analysis

Abstract

Homeowners’ Associations (HOAs) dictate landscape structure and management through legally enforceable land covenants at the neighborhood scale in the USA. Determining the location and spatial extent of HOAs is critical for examining its influence. However, such analysis is confounded by the lack of spatial data at the appropriate unit for such analysis. The purpose of this paper is to develop and realize an open source implementation to automate land parcel classification, which is an initial step towards the goal of determining the impact of HOAs on urban land management. Using Maricopa County, Arizona as a testbed, we found that parcel merging processes reduce the number of subdivisions from 26,042 to 17,269, such that boundaries better align with neighborhood units to which rule sets like land covenants apply. Moreover, after an initial training period, this process was completed in just over 7 hours. This research is an important first step in enabling a number of analysis including determining the location and spatial extent of HOAs regionally and, eventually, nationally and determining proposed links between HOAs and land management outcomes.

Keywords

• land management
• land parcel classification
• open source
• neighborhood-scale urban analysis