A shadow–overlapping algorithm for estimating building heights from VHR satellite images

Building height is a key geometric attribute for generating 3D building models. We propose a novel four-stage approach for automated estimation of building heights from their shadows in very-high-resolution (VHR) multispectral images. First, a building’s actual shadow regions are detected by applying ratio-band algorithm to the VHR image. Second, 2D building footprint geometries are identified using graph theory and morphological fuzzy processing techniques. Third, artificial shadow regions are simulated using the identified building footprint and solar information in the image metadata at pre-defined height increments. Finally, the difference between the actual and simulated shadow regions at every height increment is computed using Jaccard similarity coefficient. The estimated building height corresponds to the height of the simulated shadow region that resulted in the maximum value for Jaccard index. The algorithm is tested on seven urban sites in Cardiff, UK with various levels of morphological complexity. Our method outperforms the past attempts, and mean error is reduced by at least 21%

BUILDING ASSESSMENT USING SHADOW ANALYSIS FOR THE ARCHITECTURAL DOCUMENTATION

One essential approach in preserving architectural heritage is the documentation of building geometries and their sites are thoroughly photographed of existing buildings. For instance, an automated detection of the locations and the extraction of geometry information of the buildings are intrinsic attributes of the architectural design of building interiors and exteriors in cultural heritage documentation and preservation. In this study, contributions of remotely sensed images to detect the sites and shapes of the buildings based on shadow analysis were evaluated. The aim of this paper is to develop an approach to assist in recording and documenting the external geometry of historic buildings and their real location supplying much ease and time-saving in protection projects of cultural heritage. A distinctive merit of the proposed approach is its ability to document the spatial distribution of the detecting buildings by extracting the graphic coordinates of their corners without any additional data. Our experiments demonstrate the efficiency of the proposed approach on two cases, including the architectural documentation of external edges, shape, size, site, orientation, and coordinates. Thus, our new approach offers a tool to document architectural and cultural heritage which can help in capturing and recording all the relevant data and information, both in visual and written format

Urban Landscape Fragmentation as an Indicator of Urban Expansion Using Sentinel-2 Imageries

Rapid urbanization in some cities has led to the emergence of numerous subsidiary settlements around their primary cities. Due to this rapid urbanization and growth, there is a great demand for urban land, mostly for commercial, industrial, and residential uses. Urban green spaces and vegetation are at risk due to a large amount of urban land, as seen by a decline in connectivity and increased fragmentation, especially due to land conversion. However, the identification of the spatial and momentary variability in the clustering and fragmentation of vegetation patterns in urban settings has not made full use of local indicators of spatial distribution measurements, such as Baqubah, a city in Iraq. Since it is essential to measure the degree of fragmentation and evaluate urban expansion trajectories consistently, this study proposes a new approach to assessing the anticipated direction of urban extension, using the fragmentation indicator of built-up patterns in urban areas. Sentinel-2 data was used to map the fragmented urban centres and their future extent in the city at a single time point. The proposed method employs indices to capture the initial distribution of spatial patterns of vegetation cover and built-up areas. The main extracted land cover classes, landscape fragmentation performance, and surface density analysis were accomplished in ArcGIS. The results indicate that the entire built-up area in Baqubah has a high degree of fragmentation at 75%, and about 23% of the open space within the urban extent of the city. Two predicted trajectories of urban expansion were also revealed: one may follow the external road direction, while the other is multi-directional, commencing from the edges of the built-up area. The study concludes that the new method is useful for comprehending and assessing urban landscape fragmentation, as well as anticipating its path. This integrated approach to remote sensing and GIS can sufficiently and effectively determine priority urban regions for successful planning and management. In addition, our study's findings highlight the potential of the suggested strategy as a useful spatially explicit method for determining the spatial clustering and fragmentation of urban landscape patterns. Doi: 10.28991/CEJ-2022-08-09-04 Full Text: PD