Track 3.5: Smart Risk Management and Climate Innovations

Street View Images (SVIs) have emerged as an increasingly valuable resource for comprehensive urban research applications. In seismically active regions, effective territorial management is essential for identifying structural weaknesses and enhancing urban resilience against earthquake hazards. Conventional seismic hazard evaluation approaches typically demand extensive on-site investigations and specialized instruments, creating significant barriers to widespread urban safety assessment due to resource limitations and the complexities of the process. The research introduces a methodology utilizing readily accessible SVIs data to evaluate pedestrian safety zones within urban environments, directly supporting adaptation strategies for hazardous geological events. Through the utilization of the sequential and multi-perspective characteristics of SVIs, image sequences can be reconstructed despite considerably large image intervals, enabling three-dimensional analysis for identifying hazardous and secure street zones using solely available visual data. This framework supports disaster-resilient infrastructure development and incorporates sustainable building enhancement strategies. The technique allows for comprehensive emergency preparedness encompassing risk reduction, damage limitation and, crisis response, through accessible evaluation tools. By utilizing existing urban documentation of Street View Images, actions can be taken using the proposed approach to address present and anticipated seismic hazards while developing actionable strategies that correspond with community needs for sustainable metropolitan growth. Through identification of secure pedestrian areas, findings would enable analysis of the risk locations during and after earthquakes, establishing safety evaluation as a fundamental component of municipal planning methodology. The risk assessment capabilities allow planners to pinpoint vulnerable districts and establish priorities for infrastructure enhancement, facilitating data-driven choices for seismic occurrences. This approach converts disaster resilience goals into municipal implementation by equipping city officials with economical instruments for thorough hazard mapping utilizing accessible street photography resources. The methodology supports evacuation pathway development, emergency protocol formulation, and regulatory frameworks considering seismic debris distribution patterns. Stakeholders and planners can employ these forecasts to direct building standard implementation, identify priority locations for structural evaluation, and guide public area development that strengthens community robustness. The system encourages ecological solution integration by locating areas where environmental infrastructure could offer additional safeguarding while preserving urban operations. Additionally, this assessment framework enables the surveillance and revision of hazard maps as landscapes transformation data for consideration, ensuring planning choices remain relevant and adaptive to evolving circumstances. The availability of street imagery makes this approach especially beneficial for data-limited places seeking comprehensive disaster reduction implementation without extensive requirements, ultimately fostering more resilient and responsive urban ecosystems.

Increasingly, the complexities of a changing world necessitate the use of emerging technologies to support research and informed decision-making in urban planning and management. In many rapidly urbanizing and institutionally weak Global South cities, including Abuja, Nigeria, traditional planning practices have struggled to keep pace with the ever-changing trends of environmental consequences associated with unapproved spatial development. In this light, encroachment by unapproved development into green belts and marginal lands continues to alter and constrict natural drainage paths, leading to flash floods and loss of biodiversity. This evidence suggests that unapproved development on marginal lands and green belts creates communities vulnerable to climate change impacts, therefore, adaptive planning systems anchored on real-time monitoring and environmental intelligence have become essential in urban planning and city management practices. This study investigates the effectiveness of current spatial monitoring approaches used for city monitoring and management, by using the case study of Abuja as an illustrative case. It also examines instances where unapproved development by some residential estates within green belts and marginal lands have led to the constriction of stream courses, resulting in flash floods. The core objective is to explore the potential of integrating emerging technologies such as Geographic Information Systems (GIS) and Unmanned Aerial Vehicles (UAVs) into urban and regional planning practices to enhance resilience, reduce climate-related vulnerabilities, and support data-driven decision-making particularly in institutionally weak global south cities including Abuja, Nigeria. The study adopts a qualitative case study approach, and the primary data sources which include cadastral maps, satellite imagery, and photographs to identify the extent of encroachment into green belts. Interviews were also conducted with urban and regional planning practitioners to assess the current practices and institutional capacity, monitoring procedures, and technological gaps. The findings revealed that the current practice of spatial monitoring in Abuja, Nigeria, relies primarily on physical site visitation, and has been evaluated to be significantly inadequate for timely detection of unapproved developments within green belts and marginal lands. This practice has therefore allowed the extensive encroachment of unapproved developments into stream courses, therefore contributing to the constriction of natural drainage channels, and increasing the frequencies and severity of flash floods during heavy rainfall. The findings also demonstrate a direct correlation between weak institutional capacity for proactive monitoring and the environmental consequences observed. The findings further showed that though the institutions charged with spatial monitoring possess basic geo-spatial tools such as GIS, they are under-utilized or disconnected from spatial monitoring protocols. This study therefore contributes to both theory and practice by highlighting the critical need to transition from a reactive to a proactive spatial governance framework by embracing technology-based spatial monitoring. It argues further, that when these tools are effectively aligned with institutional reforms and climate resilience planning, this can provide robust support for institutionally weak global south cities like Abuja, Nigeria, in adapting to the increasing challenges associated with environmental and urbanization trends, thus offering a practical pathway to enhance urban resilience and reduce vulnerability in the face of climate change.

This research project investigates the strategic urban planning/design approach proposed for Napier, a city exposed to significant natural hazards, and its implications for disaster risk reduction and resilience building. Central to this study is a community-led relocation concept designed to mitigate risks by systematically relocating people, buildings, and infrastructure from hazard-prone areas. The case study demonstrates effective pre-planning for relocation, identifying potential risks and the requisite modifications to the district plan to facilitate redevelopment from a risk management perspective. As part of the Coastal Hazards Overlay research initiative, this project explores two hypothetical scenarios: medium-density redevelopment in high-risk areas to minimize displacement and high-density development in the city centre to reduce pressure on hazardous zones. Both scenarios prioritize proactive land use planning, optimized resource utilization, and efficient recovery processes. The findings highlight the critical need for comprehensive hazard avoidance strategies, proactive relocation plans, and strong community engagement to enhance resilience. Effective pre-event planning can optimize time and resources, ensuring smoother transitions and more efficient recovery processes. The study also underscores the complexities induced by the local tenure system, which can hinder policy implementation and necessitate compromises that may lead to greater long-term costs. Consequently, current policies often settle for less effective alternatives. In the event of a severe disaster, these compromises may result in more significant consequences and higher costs. Incorporating natural hazard overlays into land use planning is essential for minimizing future hazard mitigation efforts and promoting long-term resilience. Additionally, community-led relocation initiatives that align with local aspirations are crucial for ensuring that redevelopment meets local needs and maintains community cohesion. This research contributes to the broader understanding of leveraging urban planning for disaster risk reduction and resilience building. By focusing on the unique case study of Napier, it elucidates the potential of pre-planning relocation. Nonetheless, the study's reliance on hypothetical scenarios and a desktop exercise supplemented by field research indicates that effective implementation will require thorough stakeholder consultation and alignment with local, regional, and national policies.

With rapid urbanization and intensified global climate change, extreme heat events in cities are becoming increasingly frequent. Extreme high temperatures not only increase the health risks for urban residents, but also pose a serious threat to the socio-economic and sustainable development of cities. In recent years, resilience has gradually gained attention as an important theory for evaluating the ability of urban systems to resist external disturbances. Strengthening the resilience of cities to extreme heat through urban planning is crucial for adapting to global climate change and maintaining sustainable development. Although a large number of studies have explored the mechanisms by which urban built environment affects heat resilience and urban heat island effect, these studies often focus on the role of landscape structure or ecological patches and overlook the influence of urban form. Therefore, this study conducts empirical analysis on Nanjing city to explore the complex relationship between urban compactness, land use, street view characteristics, and heat resilience. To comprehensively analyze the nonlinear and spatial heterogeneity effects of each characteristic on heat resilience (HR), research models including RF, GBDT, LightGBM, and XGBoost were constructed based on an explainable machine learning framework. This study designated 80% of the samples as the training set and 20% as the testing set for model training, and compared the predictive performance of various machine learning models using three metrics: R ², MSE, and MAE. The XGBoost model has better fitting effect and accuracy on the test set than the RF, GBDT, and LightGBM models, thus better explaining the relationship between the building environment characteristics and heat resilience in Nanjing city. To explain the XGBoost model, the SHAP method is used to quantify the contribution of features and explain nonlinear relationships. The research results indicate that building density, street aspect ratio, normalized vegetation index (NDVI), and green visual acuity are the main determining factors of heat resilience. Specifically, NDVI has a positive effect on the extreme heat recovery of cities. The heat response capability is affected by the openness of the sky and building density. In addition, the study also discovered the threshold effect of explanatory variables on heat resilience and the interaction between features. For example, both excessive or insufficient street aspect ratio and building density can lead to a decrease in urban heat resilience. The findings provide important reference for urban planning and policy-making, helping policymakers better understand the complex relationship between urban environmental features and heat resilience. Based on feature importance and threshold effects, by implementing a series of measures such as improving urban design, increasing vegetation coverage, and optimizing building layouts, the resilience to extreme heat events can be more effectively enhanced from a practical standpoint.

Medical land use—marked by 24/7 operations, high imperviousness (84.3 ± 5.7%), and low green coverage (12.2 ± 3.8%)—is a distinct yet under-recognized driver of urban heat island (UHI) intensification. Using a multi-scale approach, we analyzed Landsat-8/9 data across 30 Chinese cities (2013–2023), finding a +0.33 ± 0.05°C UHI increase per 1% medical land coverage, linked to reduced albedo and high anthropogenic heat flux (92.4 ± 18.7 W/m²). Meso-scale monitoring in Changzhou revealed sustained nocturnal heat anomalies (+2.07 ± 0.41°C for 3.6 ± 0.7 hours), while micro-scale hospital measurements showed HVAC systems contribute 72.4 ± 3.2% of waste heat and raise CO₂ by 24.3 ± 5.1%. Additional factors include low evapotranspiration and heat retention in high-aspect-ratio canyons. Together, these findings identify medical zones as embedded thermal amplifiers, necessitating their inclusion in urban climate models and mitigation strategies.

Solar radiation is the foundation of the earth's environmental evolution, which has enormous potential for utilization. However, excessive accumulation of solar radiation in high-density urban areas may also increase heat risks, especially when extreme heat events have become increasingly frequent in recent years. As solar radiation has both positive and negative effects on cities, it is crucial to explore spatial planning strategies that balance solar radiation utilization and heat risk resistance. Solving this problem is important for improving urban energy sustainability and climate resilience under extreme weather conditions. This study focuses on the types of urban forms that can balance solar radiation and heat risk, thereby better adapting to extreme weather conditions, particularly heatwaves and long periods of high temperatures. A new parameter named “heat vulnerability” is proposed to measure a city’s ability to resist heat risks, according to its spatial characteristics. Based on this concept, a research framework that couples solar potential with heat risk resilience is developed. This process is achieved by the spatial mapping and overlaying of multi-source data based on GIS analysis. Remote sensing data is corrected and downscaled to form a high-resolution urban dataset for mapping the distribution of solar radiation and heat vulnerability in detail. Heat vulnerability is calculated by urban morphological parameters, considering solar radiation capture, heat dissipation, and amplification effects. The relationship of the parameters is explored using machine learning methods, providing quantitative evidence for the formulation of climate resilience-oriented strategies. The main contribution of this study is the development of a new framework for coupling solar radiation and heat vulnerability, which offers a solid foundation for climate-resilient planning and policy-making. By comparing the results of different parts of the city, key areas that need to focus on cooling or solar radiation use are identified. The high resolution and spatial positioning of the research method enable it to guide precise interventions of planning strategies, such as urban form adjustment, photovoltaic utilization, and green infrastructure development. Additionally, this framework also makes it possible for planners to predict the solar potential and thermal risk resilience of schemes during the preliminary design stage. By adjusting urban form parameters in the digital model, the simulation results can be quickly generated. This allows planners to apply approaches that are better suited to the specific scenarios, thereby assisting urban design guidelines, key area renovations, and other initiatives.

With the consistent increase in global energy demand, accelerating the energy transition and deploying clean energy technologies have become crucial in addressing the climate crisis and reducing greenhouse gas emissions. Installation of photovoltaic (PV) panels on buildings not only provides renewable energy but also reduces the energy consumption of buildings, thereby facilitating the sustainable transformation of the building industry. Different urban forms determine the amount of solar radiation received at the same location, which also affects the energy consumption of the city. The degree of matching between the two reflects the effect of a city's utilization of solar energy. This research aims to explore how to design the tilt and azimuth angles of PV panels to match the energy consumption of buildings and ultimately propose the most suitable angle schemes for buildings of different forms. Furthermore, this study attempts to quantify the impact of different urban forms on the self-consumption rate (SC) and self-sufficiency rate (SS) of photovoltaic panels, and explores which urban form can improve the utilization of solar energy to promote sustainable urban development. In this research, the models of solar radiation received by PV panels with different angles and the power generation were established. The accuracy of the models was verified through measured data from Jiangsu Province, China. The hourly energy consumption data of buildings were obtained through simulation using EnergyPlus. Subsequently, the genetic algorithm was employed to optimize SC and SS or power generation, and the results were compared. Taking Nanjing City, Jiangsu Province, China, as an example, simulations were conducted for different types (industrial buildings, residential buildings, etc.) and forms (single-story or multi-story, pitched roof or flat roof, etc.) of buildings. It was found that there are differences in angle selection between using maximum power generation and using maximum SC/SS as the optimization objectives. The latter tends to be more inclined to the east by approximately 30°, with the tilt angle varying by 5° to 10°. Due to the different volumes of buildings, energy consumption varies significantly. Generally, for smaller-sized buildings, the angles under the two optimization objectives differ markedly, while for high-energy-consuming buildings, the difference is relatively smaller. This study offers suggestions for the installation of PV panels from a new perspective that integrates comprehensive building energy consumption. Furthermore, by analyzing the impact of different urban forms on the utilization of solar energy, this research can provide a scientific basis for urban planners, helping them optimize the urban spatial layout in urban planning and construction and improve the overall utilization efficiency of solar energy in cities, promoting the sustainable development of cities.