Incorporating road and parcel data for object-based classification of detailed urban land covers from NAIP images

Xiaomin Qiu, Missouri State University
Shuo-Sheng Wu, Missouri State University
Xin Miao, Missouri State University


A map showing various urban features, such as buildings, roads, and vegetation, is useful for a variety of urban planning applications. The objective of this study was to incorporate road and parcel GIS data as well as relevant expert knowledge to classify different urban land covers from 1-meter, 4-band NAIP images. Based on a hybrid simultaneous-classification and one-by-one-classification approach, a total of 14 urban classes are classified. The classification map has an overall accuracy of 90%, demonstrating a noticeable improvement over past comparable studies on detailed urban land cover classification.