Per-field urban land use classification based on tax parcel boundaries

The objective of this study is to test a per-field approach for classifying detailed urban land use, such as single-family, multi-family, industrial and commercial. Tax parcel boundaries are used as the field boundaries for classification. Twelve attributes of parcels, such as parcel sizes, parcel shape, building counts and building heights, are used as the discriminant factors between different land use types. For our study area that consists of 33 025 parcels, we first derived parcel attributes from geographic information system (GIS) and remote sensing data. We then converted the parcel vector data to an image of 12 bands with pixel values from parcel attributes. After that, we performed a standard supervised classification to classify the image into nine land use types. The best classification result with a decision tree classifier had an overall accuracy of 93.53% and a Kappa Coefficient of 0.7023. This study shows the feasibility of applying a perfield approach based on tax parcel boundaries to classify detailed urban land use.