It is essential to monitor urban evolution at spatial and temporal scales to improve our understanding of the changes in cities and their impact on natural resources and environmental systems. Various aspects of remote sensing are routinely used to detect and map features and changes on land and sea surfaces, and in the atmosphere that affect urban sustainability. We provide a critical and comprehensive review of the characteristics of remote sensing systems, and in particular the trade-offs between various system parameters, as well as their use in two key research areas: (a) issues resulting from the expansion of urban environments, and (b) sustainable urban development. The analysis identifies three key trends in the existing literature: (a) the integration of heterogeneous remote sensing data, primarily for investigating or modelling urban environments as a complex system, (b) the development of new algorithms for effective extraction of urban features, and (c) the improvement in the accuracy of traditional spectral-based classification algorithms for addressing the spectral heterogeneity within urban areas. Growing interests in renewable energy have also resulted in the increased use of remote sensing-for planning, operation, and maintenance of energy infrastructures, in particular the ones with spatial variability, such as solar, wind, and geothermal energy. The proliferation of sustainability thinking in all facets of urban development and management also acts as a catalyst for the increased use of, and advances in, remote sensing for urban applications.

Building height is a key geometric attribute for generating 3-D 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, 2-D 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 predefined 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, U.K. with various levels of morphological complexity. Our method outperforms the past attempts, and the mean error is reduced by at least 21%.

ABSTRACT:Very-High-Resolution (VHR) satellite imagery is a powerful source of data for detecting and extracting information about urban constructions. Shadow in the VHR satellite imageries provides vital information on urban construction forms, illumination direction, and the spatial distribution of the objects that can help to further understanding of the built environment. However, to extract shadows, the automated detection of shadows from images must be accurate. This paper reviews current automatic approaches that have been used for shadow detection from VHR satellite images and comprises two main parts. In the first part, shadow concepts are presented in terms of shadow appearance in the VHR satellite imageries, current shadow detection methods, and the usefulness of shadow detection in urban environments. In the second part, we adopted two approaches which are considered current state-of-theart shadow detection, and segmentation algorithms using WorldView-3 and Quickbird images. In the first approach, the ratios between the NIR and visible bands were computed on a pixel-by-pixel basis, which allows for disambiguation between shadows and dark objects. To obtain an accurate shadow candidate map, we further refine the shadow map after applying the ratio algorithm on the Quickbird image. The second selected approach is the GrabCut segmentation approach for examining its performance in detecting the shadow regions of urban objects using the true colour image from WorldView-3. Further refinement was applied to attain a segmented shadow map. Although the detection of shadow regions is a very difficult task when they are derived from a VHR satellite image that comprises a visible spectrum range (RGB true colour), the results demonstrate that the detection of shadow regions in the WorldView-3 image is a reasonable separation from other objects by applying the GrabCut algorithm. In addition, the derived shadow map from the Quickbird image indicates significant performance of the ratio algorithm. The differences in the characteristics of the two satellite imageries in terms of spatial and spectral resolution can play an important role in the estimation and detection of the shadow of urban objects.

The digital 3D models of the buildings based on laser-scanning data become a vital source of data and information repository to the Architecture, Construction, Engineering and Facilities Management (AEC & FM) sectors. A major advantage of the points cloud data captured by laser-scanning technology is its ability to the representation of the details of the three-dimensional models to exemplify the as-is conditions of buildings. However, the creation process of 3D models from the dense coloured 3D points provided by laser scanners has a significant impact on the quality of that produced models including building edges, walls, doors and windows. In particular, much uncertainty still exists about the compatibilities between the points cloud data formats and software extensions for the creation of as-is Building Information Modelling (BIM) models of the buildings. This paper presents a new framework for the creation of a 3D building model by transferring laser-scanning data into BIM software, such as Autodesk Revit. In our framework, an adopted link between software extensions was established in creating an accurate 3D building model. This framework is a road map of the required steps for investing the points cloud data relevant to BIM modelling. The promising results of the new approach illustrate to extract the 3D models of the buildings can reduce time-consuming, cost and efforts in dealing with or transferring laser-scanning data into Autodesk Revit for BIM models.

Abstract. Building performance and condition assessment necessitate the integration of a variety of data sources, including building features, element/system properties, and supporting documentation. Previous research has concentrated on locating these data and establishing a building performance analytical framework using various techniques. However, due to challenges with traditional methods in monitoring the performance of a building within the default life of its construction, the maintenance procedure takes time and effort. This issue reflects the widespread omission of the appearance and progression of structural and non-structural faults in buildings, as well as a lack of methods for radical and speedy treatment. To overcome this issue, this research proposes a technique for integrating BIM and GIS data for building performance assessment. This will enable better-informed judgments about how to accelerate and optimise in-service asset operations and maintenance. The findings are also important for the advancement of GIS and BIM linked structural integrity evaluation solutions in the future. There are some important conclusions to be derived, as well as some possible future research subjects.

Abstract. A major topic that is focused on the potential difficulties and safety considerations associated with adding an additional storey is the effect of a building's dead loads on its foundations. It is important to take into account the constraints imposed by the current building loads as well as any dangers or concerns related to structural integrity when deciding whether or not such an expansion is practical or allowed. However, if an interactive map displaying the weights of the walls and their computations is provided, stakeholders and decision-makers will decide correctly to add another level to the building. Therefore, with the advancement of technology and the demands of modern living, an interactive maps app for showing building loads and its capability to rapidly and precisely visualise spatial data linked to structural stress, safety concerns, and capacity usage has become essential. The objective of this study is to develop an immediate app that allows viewers to explore more details about calculating the dead loads of the building and their impacts on its structure. Our new approach shows a detailed map of the various load values together with supplementary text that offers further information. The loads-interactive App can also help in surfing map layers so that users can examine and better understand the computation of the building's dead loads. The outputs of our promising method illustrate the importance of interactive map applications in facilitating accurate calculations of building loads.

No abstract

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: PDF