Fig 2 - uploaded by Sébastien Lefèvre
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Sample DSM image of 4000 × 4000 pixels (left) and corresponding classification map (right) obtained with the proposed method on a sample DSM from the Vaihingen dataset. The color correspondence table is the following: roads (yellow/orange), buildings (blue), steeples (red), cars (cyan), trees (green). Each shade corresponds to a set of selection criteria.
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Citations
... Moreover, an increasing number of methods for the detection of building information are based on high-resolution digital surface models (DSMs) generated from satellite images (Lafarge, Descombes, Zerubia, & Pierrot-Deseilligny, 2010;Merciol & J o u r n a l P r e -p r o o f Lefèvre, 2015;Davydova, Cui, & Reinartz, 2016). However, the accuracy and the universality of the applicability of satellite image-based methods have been limited by the cost or accessibility of high-spatial-resolution remotely sensed data (Weidner & Förstner, 1995). ...
... Moreover, an increasing number of methods for the detection of building information are based on high-resolution digital surface models (DSMs) generated from satellite images (Lafarge, Descombes, Zerubia, & Pierrot-Deseilligny, 2010;Merciol & J o u r n a l P r e -p r o o f Lefèvre, 2015;Davydova, Cui, & Reinartz, 2016). However, the accuracy and the universality of the applicability of satellite image-based methods have been limited by the cost or accessibility of high-spatial-resolution remotely sensed data (Weidner & Förstner, 1995). ...
Available and accessible three-dimensional (3D) urban morphology data have become essential for extensive academic research on built-up environments and urban climates. A rapid and consistent methodology for extracting urban morphology information is urgently needed for sustainable urban development in global cities, particularly given future trends of rapid urbanization. However, there is still a lack of generally applicable methods that use open-source data in this context. In this study, we developed a simple and highly efficient method for acquiring 3D urban morphology information using open-source data. Building footprints were acquired from the Maps Static application programming interface. Building heights were extracted from an open digital surface model, i.e., the ALOS World 3D model with a resolution of 30 m (AW3D30). Thereafter, urban morphological parameters, including the sky view factor, building coverage ratio, building volume density, and frontal area density, were calculated based on the retrieved building footprints and building heights. The proposed method was applied to extract the 3D urban morphology of Hong Kong, a city with a complex urban environment and a highly mixed geographical context. The results show a usable accuracy and wide applicability for the newly proposed method.
... In this paper, we propose a methodological framework to utilize the NDVI attribute for high-resolution urban image classification by incorporating the multi-level spatial contextual information from the NDVI attribute. The multi-level characterization of the NDVI attribute is generated by means of Similarly, the incorporation of the spatial contextual information from the DSM or nDSM might be required to achieve the expected improvement in the classification accuracy (Merciol and Lefèvre, 2015). Recently, the attribute profiles were generated from the DSM derived by lidar data (Pedergnana et al., 2012;Khodadadzadeh et al., 2015;Liao et al., 2016), and they have shown the ability of attribute profiles to improve the classification accuracy. ...
This research deals with the automatic generation of 2D land cover maps of urban areas using very high resolution multispectral aerial imagery. The appropriate selection of classifier and attributes is important to achieve high thematic accuracies. In this paper, new attributes are generated to increase the discriminative power of auxiliary information provided by remote sensing images. The generated attributes are derived from the vegetation index and elevation information using morphological attribute profiles. The extended experimental evaluation and comparison of attribute profile-based mapping solutions is conducted to derive the optimal combinations of attributes required for classification and to understand the genericity of attributes on a range of classifiers, i.e., various combinations of attributes and classifiers. Experimental results with two high resolution images show that the proposed attributes derived on auxiliary information outperform the existing attribute profiles computed on original image and its principal components.
The theory of hierarchical image representations has been well-established in Mathematical Morphology, and provides a suitable framework to handle images through objects or regions taking into account their scale. Such approaches have increased in popularity and been favourably compared to treating individual image elements in various domains and applications. This survey paper presents the development of hierarchical image representations over the last
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