期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2010
卷号：XXXVIII Part 4
出版社：Copernicus Publications
摘要：The high frequency and scope of spatial changes in cities demands ways of expediting the production and updating of large-scalegeographic information. For that purpose, current and future very high spatial resolution satellite imagery (VHR) and semiautomatedobject-based image analysis methods may be an advantageous alternative to classical data sources and methods, i.e.,aerial photography and photogrammetry. At the same time, the urban environment is becoming more complex and heterogeneous,possibly turning the feature extraction process more challenging. While much research has focused on developing, adapting andapplying these approaches, less attention has been devoted to the interplay of data source (imagery), feature extraction methods, andgeographic characteristics of the area under analysis. Lisbon, Portugal, is both a historical and modern city having a dynamiclandscape, where increasingly diverse urban forms and materials coexist. This complex reality is possibly causing the featureextraction process from imagery to become more challenging. This study tests the semi-automated extraction of buildings from aQuickBird image in several urban study areas in Lisbon having different characteristics, and explores the impact of theheterogeneity of these features in the extraction process. Spatial metrics and spectral response are used to characterize types ofbuildings present in the study areas. Results show that the study areas display different levels of heterogeneity even for the sametype of building and suggest that the quality of the extraction is affected by more factors than the complex variations in color/tone,composition and spatial configuration of target features
