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

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

Flood hazard assessment for extreme flood events

Climate change is expected to result in an increase in the frequency and intensity of extreme weather events. In turn, this will result in more frequent occurrences of extreme flood events, such as flash flooding and large-scale river flooding. This being the case, there is a need for more accurate flood risk assessment schemes, particularly in areas prone to extreme flooding. This study investigates what type of flood hazard assessment methods should be used for assessing the flood hazard to people caused by extreme flooding. Two flood hazard assessment criteria were tested, namely: a widely used, empirically derived method, and recently introduced, physically based and experimentally calibrated method. The two selected flood hazard assessment methods were: (1) validated against experimental data, and (2) used to assess flood hazard indices for two different extreme flood events, namely: the 2010 Kostanjevica na Krki extreme river flood and the 2007 Železniki flash flood. The results obtained in this study suggest that in the areas prone to extreme flooding, the flood hazard indices should be based on using the formulae derived for a mechanics-based analysis, as these formulations consider all of the physical forces acting on a human body in floodwaters, take into account the rapid changes in the flow regime, which often occur for extreme flood events, and enable a rapid assessment of the degree of flood hazard risk in a short time period, a feature particularly important when assessing flood hazard indices for high Froude numbers flows

Exploration of optimal time steps for daily precipitation bias correction:a case study using a single grid of RCM on the River Exe in southwest England

Bias correction is a necessary post-processing procedure in order to use Regional Climate Model (RCM) simulated local climate variables as the input data for hydrological models due to systematic errors of RCMs. Most of present bias correction methods adjust statistical properties between observed and simulated data based on a predefined duration (e.g., a month or a season). However, there is a lack of analysis about the optimal period for bias correction. This study has attempted to address the question whether there is an optimal number for bias correction groups (i.e., optimal bias correction period). To explore this optimal number we used a catchment in southwest England with the regional climate model HadRM3 precipitation data. The proposed methodology uses only one grid of RCM in the Exe catchment, one emission scenario (A1B) and one-member (Q0) among 11-members of HadRM3. We tried 13 different bias correction periods from 3-day to 360-day (i.e., the whole one year) correction using the quantile mapping method. After the bias correction a low pass filter is used to remove the high frequencies (i.e., noise) followed by estimating Akaike’s information criterion. For the case study catchment with the regional climate model HadRM3 precipitation, the results showed that about 8-day bias correction period is the best. We hope this preliminary study about the optimum number of bias correction period for daily RCM precipitation will stimulate more research activities to improve the methodology with different climatic conditions so that more experience and knowledge could be obtained. Future efforts on several unsolved problems have been suggested such as how strong the filter should be and the impact of the number of bias correction groups on river flow simulations

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

Appropriate model use for predicting elevations and inundation extent for extreme flood events

Flood risk assessment is generally studied using flood simulation models; however, flood risk managers often simplify the computational process; this is called a “simplification strategy”. This study investigates the appropriateness of the “simplification strategy” when used as a flood risk assessment tool for areas prone to flash flooding. The 2004 Boscastle, UK, flash flood was selected as a case study. Three different model structures were considered in this study, including: (1) a shock-capturing model, (2) a regular ADI-type flood model and (3) a diffusion wave model, i.e. a zero-inertia approach. The key findings from this paper strongly suggest that applying the “simplification strategy” is only appropriate for flood simulations with a mild slope and over relatively smooth terrains, whereas in areas susceptible to flash flooding (i.e. steep catchments), following this strategy can lead to significantly erroneous predictions of the main parameters—particularly the peak water levels and the inundation extent. For flood risk assessment of urban areas, where the emergence of flash flooding is possible, it is shown to be necessary to incorporate shock-capturing algorithms in the solution procedure, since these algorithms prevent the formation of spurious oscillations and provide a more realistic simulation of the flood levels

The well-being and work-related stress of senior school leaders in Wales and Northern Ireland during COVID-19 “educational leadership crisis”: A cross-sectional descriptive study

The COVID-19 pandemic caused far-reaching societal changes, including significant educational impacts affecting over 1.6 billion pupils and 100 million education practitioners globally. Senior school leaders were at the forefront and were exposed to particularly high demands during a period of “crisis leadership”. This occupation were already reporting high work-related stress and large numbers leaving the profession preceding COVID-19. This cross-sectional descriptive study through the international COVID-Health Literacy network aimed to examine the well-being and work-related stress of senior school leaders (n = 323)in Wales (n = 172) and Northern Ireland (n = 151) during COVID-19 (2021–2022). Findings suggest that senior school leaders reported high workloads (54.22±11.30 hours/week), low well-being (65.2% n = 202, mean WHO-5 40.85±21.57), depressive symptoms (WHO-5 34.8% n = 108) and high work-related stress (PSS-10: 29.91±4.92). High exhaustion (BAT:high/very high 89.0% n = 285) and specific psychosomatic complaints (experiencing muscle pain 48.2% n = 151) were also reported, and females had statistically higher outcomes in these areas. School leaders were engaging in self-endangering working behaviours; 74.7% (n = 239) gave up leisure activities in favour of work and 63.4% (n = 202) sacrificed sufficient sleep, which was statistically higher for females. These findings are concerning given that the UK is currently experiencing a “crisis” in educational leadership against a backdrop of pandemic-related pressures. Senior leaders’ high attrition rates further exacerbate this, proving costly to educational systems and placing additional financial and other pressures on educational settings and policy response. This has implications for senior leaders and pupil-level outcomes including health, well-being and educational attainment, requiring urgent tailored and targeted support from the education and health sectors. This is particularly pertinent for Wales and Northern Ireland as devolved nations in the UK, who are both implementing or contemplating major education system level reforms, including new statutory national curricula, requiring significant leadership, engagement and ownership from the education profession.<br/

Evaluating the Atibaia river hydrology using JULES6.1

Land surface models such as the Joint UK Land Environment Simulator (JULES) are increasingly used for hydrological assessments because of their state-of-the-art representation of physical processes and versatility. Unlike statistical models and AI models, the JULES model simulates the physical water flux under given meteorological conditions, allowing us to understand and investigate the cause and effect of environmental changes. Here we explore the possibility of this approach using a case study in the Atibaia River basin, which serves as a major water supply for metropolitan regions of Campinas and São Paulo, Brazil. The watershed is suffering increasing hydrological risks, which could be attributed to environmental changes, such as urbanization and agricultural activity. The increasing risks highlight the importance of evaluating the land surface processes of the watershed systematically. We explore the use of local precipitation collection in conjunction with data from a global meteorological reanalysis to simulate the basin hydrology. Our results show that key hydrological fluxes in the basin can be represented by the JULES model simulations