Detailed intra-urban mapping through transferable OBIA rule sets using WorldView-2 very-high-resolution satellite images

Abstract

A detailed knowledge of the types and coverage of intra-urban features is helpful for different applications, such as roof run-off approximation and urban micro-climate studies. Previous studies have applied object-based image analysis (OBIA) to explore the detailed urban characterization on a single image of satellite sensors with very-high- resolution. The automated and transferable detection of intra-urban features is challenging because of variations of the spatial and spectral characteristics. This study utilizes the rule-based structure of OBIA to investigate the transferability of the OBIA rule sets on three subsets of a WorldView-2 (WV-2) image. Spatial, spectral, and textural features as well as several spectral indices are incorporated in these rule sets. The rule sets are developed on the first study site and reused in the second and third images. This OBIA framework provides a transferable process of detecting the intra-urban features without manually adjusting the rule set parameters and thresholds. Overall accuracies of 88%, 88%, and 86% are obtained for the first, second, and third images, respectively. The rule sets used in this study can be applied to other study areas or temporal WV-2 images for accurate detection of the intra-urban land-cover classes.