EXTRACTIO OF BUILDI GS FROM QUICKBIRD IMAGERY FOR MU ICIPAL PLA I G PURPOSES: QUALITY ASSESSME T CO SIDERI G EXISTI G MAPPI G STA DARDS

Many municipal activities require updated large-scale maps that include both topographic and thematic information. For this purpose, the efficient use of very high spatial resolution (VHR) satellite imagery suggests the development of approaches that enable a timely discrimination, counting and delineation of urban elements according to legal technical specifications and quality standards. Therefore, the nature of this data source and expanding range of applications calls for additional methods and metrics to assess the quality of the extracted information which go beyond traditional thematic accuracy alone. The present work concerns the feasibility of VHR satellite imagery as an alternative source of geospatial information for large scale mapping to assist urban planning in Portugal. Feature extraction software was employed to map buildings present in a pansharpened QuickBird image of Lisbon. Quality assessment was exhaustive and involved comparisons of extracted features against a reference dataset, introducing cartographic constraints from scales 1:1000, 1:5000, and 1:10000. The spatial data quality elements subject to evaluation were: thematic (attribute) accuracy, completeness, and geometric quality based on planimetric deviation from the reference. Tests were developed and metrics analyzed considering thresholds and standards for the different mapping scales most used by municipalities. Results show that values for completeness varied with mapping scales and results were only slightly better for scale 1:10000. Concerning the geometric quality, a large percentage of extracted features met the strict topographic standards of planimetric deviation for scale 1:10000, while no buildings were compliant with the specification for scale 1:1000. * Corresponding author. 1. I TRODUCTIO A spatial component is associated with the majority of municipal activities, namely in urban planning and management. At this level, decision-making is supported by large-scale spatial data that include both topographic and thematic information, but which frequently become outdated due to the dynamics of the urban environment. Very high spatial resolution (VHR) satellite imagery can be used for faster updating of municipal spatial databases, but the nature of this recent data source and target features, the object-based image analysis, and expanding range of applications call for additional methods and metrics to assess the quality of the extracted spatial information (see Zhan et al., 2005). These go beyond traditional pixel-based thematic accuracy alone, requiring the assessment of discrimination/classification, detection/counting, and delineation of features of interest. Also, an efficient operational use of VHR satellite imagery suggests the development of approaches for mapping urban features that conforms to legal technical specifications and quality standards. Meeting all these requirements may change quality assessment from a generic process to one specific for each feature type. Buildings are a major urban element and one of the main feature classes of interest for a municipality, whose ‘correct’ semiautomatic extraction from imagery remains a challenging task. To obtain a cartographic product, most of the challenge results from the interplay of several factors, namely the object and its context, nature of imagery, and mapping requirements and constraints. Despite the many methodologies proposed for feature extraction, none has so far proved to be effective in all conditions and for all types of data (Salah et al., 2009). For the image analyst / map producer the challenge may be limited to handling the necessary stages of image preprocessing, image segmentation, and generalization of features to produce a map. In the present context, the very quality assessment of extracted buildings is a complex endeavour for which there is no consensual or standard approach. Van Coillie et al. (2008) presented a methodology for a supervised, objective evaluation of segmentation quality based on quantitative similarity measures. The methods were tested on a single house, and its manual digitizing used as reference. Eight quality measures were tested to compare different segmentations layers with the reference one. The discrepancy quality measures included the number of segments that have their centroid in the reference polygon, difference in total area and total perimeter, difference in shape complexity, average distance between edge pixels and cumulative distance from the reference. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XXXVIII-4/C7 Regarding polygon generalization, despite being the subject of significant research, there is still a need for comprehensive investigation (Podolskaya et al., 2007). Khoshelham et al. (2009) have conducted a detailed comparative analysis of five automated methods for building detection, but used pixel-based metrics for accuracy assessment. Accuracy assessment of thematic maps, based on map comparison, has often neglected cartometric quantities (Dungan, 2006). In the case of buildings, topographic maps represent the building footprint according to scale-dependent constraints. Vu et al. (2009) propose a multi-scale solution based on mathematical morphology for building extraction using LiDAR and image data. This approach allows extraction of complex buildings as scale-dependent multi-part objects and to capture building footprint. Introducing mapping specifications in quality assessment of extracted features, Gianinetto (2008) tested roads and buildings extracted from pansharpened QuickBird imagery for updating large-scale topographic databases of urban areas. Results showed that updating of 1:10000 scale was always compliant with standards, while updating of scale 1:5000 was only possible in certain situations. However, test features were manually digitized. The GeoSat research project, which involves the Lisbon City Hall, aims at developing methods to expedite the production of geographic information for municipal planning and land monitoring, and investigates the potential of VHR satellite imagery and Geographic Object-Based Image Analysis (GEOBIA) (Hay and Castilla, 2008) for detection and mapping of urban features and their integration into operational urban planning and management activities. Previous work (Santos et al., 2009) has explored and proposed detailed vector-based metrics for accuracy assessment of QuickBird-derived buildings, but without taking map standards into account. The goal of the present research is to introduce existing scalebased mapping constraints from official specifications in the process of quality assessment of features extracted from QuickBird imagery. The motivation is to evaluate the feasibility of features extracted from Very-High Resolution (VHR) imagery by semi-automatic methods to readily integrate a municipal GIS database. First, buildings were extracted from the image using feature extraction software and ancillary data. The second part included the development and testing of quality assessment procedures considering thresholds and standards for the different mapping scales used by municipalities, analysis of metrics, and discussion of results. 2. STUDY AREA A D DATA