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%

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

Automatic extraction of urban structures based on shadow information from satellite imagery

The geometric visualisation of the buildings as the 3D solid structures can provide a comprehensive vision in terms of the assessment and simulation of solar exposed surfaces, which includes rooftops and facades. However, the main issue in the simulation a genuine data source that presents the real characteristics of buildings. This research aims to extract the 3D model as the solid boxes of urban structures automatically from Quickbird satellite image with 0.6 m GSD for assessing the solar energy potential. The results illustrate that the 3D model of building presents spatial visualisation of solar radiation for the entire building surface in a different direction

Advances in remote sensing applications for urban sustainability

Abstract: 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

Creating 3D city models from satellite imagery for integrated assessment and forecasting of solar energy

Buildings are the most prominent component in the urban environment. The geometric identification of urban buildings plays an important role in a range of urban applications, including 3D representations of buildings, energy consumption analysis, sustainable development, urban planning, risk assessment, and change detection. In particular, 3D building models can provide a comprehensive assessment of surfaces exposed to solar radiation. However, the identification of the available surfaces on urban structures and the actual locations which receive a sufficient amount of sunlight to increase installed power capacity (e.g. Photovoltaic systems) are crucial considerations for solar energy supply efficiency. Although considerable research has been devoted to detecting the rooftops of buildings, less attention has been paid to creating and completing 3D models of urban buildings. Therefore, there is a need to increase our understanding of the solar energy potential of the surfaces of building envelopes so we can formulate future adaptive energy policies for improving the sustainability of cities. The goal of this thesis was to develop a new approach to automatically model existing buildings for the exploitation of solar energy potential within an urban environment. By investigating building footprints and heights based on shadow information derived from satellite images, 3D city models were generated. Footprints were detected using a two level segmentation process: (1) the iterative graph cuts approach for determining building regions and (2) the active contour method and the adjusted-geometry parameters method for modifying the edges and shapes of the extracted building footprints. Building heights were estimated based on the simulation of artificial shadow regions using identified building footprints and solar information in the image metadata at pre-defined height increments. The difference between the actual and simulated shadow regions at every height increment was computed using the Jaccard similarity coefficient. The 3D models at the first level of detail were then obtained by extruding the building footprints based on their heights by creating image voxels and using the marching cube approach. In conclusion, 3D models of buildings can be generated solely from 2D data of the buildings’attributes in any selected urban area. The approach outperforms the past attempts, and mean error is reduced by at least 21%. Qualitative evaluations of the study illustrate that it is possible to achieve 3D building models based on satellite images with a mean error of less than 5 m. This comprehensive study allows for 3D city models to be generated in the absence of elevation attributes and additional data. Experiments revealed that this novel, automated method can be useful in a number of spatial analyses and urban sustainability applications

Measurement of Radon Gas Concentration in Soil and Water Samples in Salahaddin Governorate-Iraq Using Nuclear Track Detector (CR-39)

In the present work, we have measured the Radon gas concentration in environmental samples (soil and water) of selected regions in Salahaddin governorates by using alpha-emitters registrations which are emitted form Radon gas in (CR-39) nuclear track detector. The first part is concerned with the determination of Radon gas concentration in soil samples, results of measurements indicate that the highest value of Radon concentration in soil samples was found in (Takreat) region which was (100.75±11.25 Bq/m3), while the lowest of Radon concentration was found in (Al-Faris) region which was (45.25±15.75 Bq/m3) with an average value of (77.07±12.6 Bq/m3), the present results show that the Radon gas concentrations in soil is below the allowed limit from (ICRP) agency which is (200 Bq/m3). The second part is concerned with the determination of Radon gas concentration in water samples which are from stream channel in this areas, the results of measurements indicate that the highest value of Radon concentration in water samples was found in (Takreat) region which was (0.46±0.11 Bq/L), while the lowest one was found in (Al-Alim) region which was (0.24±0.10 Bq/L), with an average value of (0.333±0.5 Bq/L), the present results show that the Radon gas concentrations in water is below the allowed limit from (ICRP) agency which is (0.5994 Bq/L). In addition to the Radon gas concentrations, we have calculated the Radon exhalation rate in soil samples and the annual effective dose in water samples. Keywords:  environment (soil and water), Radon gas, solid state nuclear track detectors (CR-39)

Automatic extraction of urban structures based on shadow information from satellite imagery

The geometric visualisation of the buildings as the 3D solid structures can provide a comprehensive vision in terms of the assessment and simulation of solar exposed surfaces, which includes rooftops and facades. However, the main issue in the simulation a genuine data source that presents the real characteristics of buildings. This research aims to extract the 3D model as the solid boxes of urban structures automatically from Quickbird satellite image with 0.6 m GSD for assessing the solar energy potential. The results illustrate that the 3D model of building presents spatial visualisation of solar radiation for the entire building surface in a different direction

Shadow detection from very high resoluton satellite image using grabcut segmentation and ratio-band algorithms

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-the-art 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

Determination uranium concentration of teeth in Al-Samawa city using the CR-39 nuclear track detector

In this research, The uranium concentration in teeth samples was measured using a CR-39 track detector and the fission tracks registration method., for 25 samples of teeth distributed across Samawa City, each weighing (0.7) grams and (2) mm in thickness. Exposed done after preparing the samples into small spherical pellets covered with a 1x1cm2 CR-39 detector. These samples with detectors together were irradiated using an (241Am-Be) source with a neutron flux (5x103 n.cm-2.s-1) for one week. These samples were compared with standard samples to find uranium concentration. The results show that the maximum value of uranium concentration was (2.273 ppm) and value of the minimum uranium concentration was (0.626 ppm) and the concentration of uranium in females was higher than in males, the concentration of uranium was affected by several factors: the region of study, gender and age of the human.

Bacterial Skin Abscess

Patients with skin and soft tissue infections may appear with the abscess. Erroneous diagnosis of these entities is common, and should carefully consider the possible alternative diagnoses. Risk for developing skin abscess factors includes disruption of the skin barrier, edema, venous insufficiency, and immune suppression. However, healthy individuals who have no risk factors may also develop these diseases. The most common microbiologic cause of abscess, a commonly group Streptococcus or Streptococcus pyogenes; Staphylococcus aureus (including methicillin-resistant strains) is a notable but less common cause. The most common microbiologic cause of skin abscess is S. aureus; a skin abscess can be caused by more than one pathogen. The diagnosis is based on skin abscess usually on the clinical manifestations. It must be subject to patients with disposable abscess incision and drainage, with a test of culture and susceptibility of materials wet. There is no justification for the blood of patients in the cultures of the abovementioned circumstances. It can be a useful radiographic examination to determine whether the skin abscess is present (via ultrasound) to distinguish cellulitis from osteomyelitis (via magnetic resonance imaging). There may be a justification for radiological assessment in patients with immune suppression, diabetes, venous insufficiency, or lymphedema in patients with persistent symptoms of systemic lymphatic obstruction