Climate vulnerability is higher in coastal regions. Communities can largely reduce their hazard vulnerabilities and increase their social resilience through design and planning, which could put cities on a trajectory for long-term stability. However, the silos within the design and planning communities and the gap between research and practice have made it difficult to achieve the goal for a flood resilient environment. Therefore, this paper suggests an AI (Artificial Intelligence)-driven platform to facilitate the flood resilience design and planning. This platform, with the active engagement of local residents, experts, policy makers, and practitioners, will break the aforementioned silos and close the knowledge gaps, which ultimately increases public awareness, improves collaboration effectiveness, and achieves the best design and planning outcomes. We suggest a holistic and integrated approach, bringing multiple disciplines (architectural design, landscape architecture, urban planning, geography, and computer science), and examining the pressing resilient issues at the macro, meso, and micro scales.

Identification of traffic crash hot spots is of great importance for improving roadway safety and maintaining the transportation system’s sustainability. Traditionally, police crash reports (PCR) have been used as the primary source of crash data in safety studies. However, using PCR as the sole source of information has several drawbacks. For example, some crashes, which do not cause extensive property damage, are mostly underreported. Underreporting of crashes can significantly influence the effectiveness of data-driven safety analysis and prevent safety analysts from reaching statistically meaningful results. Crowdsourced traffic incident data such as Waze have great potential to complement traditional safety analysis by providing user-captured crash and traffic incident data. However, using these data sources also has some challenges. One of the major problems is data redundancy because many people may report the same event. In this paper, the authors explore the potential of using crowdsourced Waze incident reports (WIRs) to identify high-risk road segments. The researchers first propose a new methodology to eliminate redundant WIRs. Then, the researchers use WIRs and PCRs from an I-35 corridor in North Texas to conduct the safety analysis. Results demonstrated that WIRs and PCRs are spatially correlated; however, their temporal distributions are significantly different. WIRs have broader coverage, with 60.24 percent of road segments in the study site receiving more WIRs than PCRs. Moreover, by combining WIRs with PCRs, more high-risk road segments can be identified (14 miles) than the results generated from PCRs (8 miles).

There is a growing and critical need to develop solutions for communities that are at particular risk of the impacts of the nexus of hazardous substances and natural disasters. In urban areas at high risk for flooding and lacking proper land-use controls, communities are vulnerable to environmental contamination from industrial land uses during flood events. This research uniquely applied a series of landscape pzerformance models to evaluate such associations including (1) the Green Values National Stormwater Calculator, (2) the Value of Green Infrastructure Tool, and (3) the Long-Term Hydrologic Impact Assessment Model. This paper presents a framework for combining landscape performance models, which are often only individually applied, to evaluate green infrastructure impacts on flood mitigation and pollutant transfer during flooding events using the Sunnyside neighborhood in Houston, Texas, USA, as a case site. The results showed that the plan reduced the risk of flooding, decreased stormwater runoff contaminants, and provided a possible direction to protect vulnerable communities.

Integration of natural and cultural resource management is urgently needed to combat the effects of climate change. Scientists must contend with how human-induced climate change and rapid population expansion are fundamentally reworking densely inhabited coastal zones. We propose that a merger of archaeology, environmental science, and land management policy—different yet intertwined domains—is needed to address dramatic losses to biocultural resources that comprise coupled cultural-natural systems. We demonstrate the urgency of such approaches through analyses of coastal archaeological regions within the U.S. Atlantic and Gulf coasts where sea level rise is a primary threat, and we extend our findings globally through an assessment of primary risk factors and forecasts for archaeological sites in the Netherlands, Peru, and Oceania. Results show that across the U.S. Gulf Coast and in Oceania, where little hard infrastructure is in place to protect archaeological sites, hundreds of low-lying coastal sites will be lost under future climate scenarios. In other coasts, like that of the Rhine-Meuse Delta (the Netherlands), risks range from erosion caused by periods of flooding to the degradation of wetland sites caused by extreme droughts. In coastal Peru, population pressures pose the primary risk to archaeological sites through rapid agro-industrial growth, urban expansion, and El Niño climate variability. Across all risks, we propose that management strategies to mitigate losses to biocultural resources must be approached as a restoration process of linked sociocultural and physical environmental systems.

Climate change issues are gradually gaining attention in the planning field, especially in urban regions due to high vulnerability caused by their dense population and complex networks. Communities depend on local policy tools to identify threats, determine goals, and implement strategies. Consequently, many cities around the world have developed climate adaptation plans to reduce climate impacts in the past decades. This study applied a plan evaluation framework to analyze and compare the plan quality of the latest climate adaptation plan in Taipei and Boston. The study examines key elements of adaptation plans to reveal strengths and weaknesses, and to compare and learn between adaptation plans internationally. Findings suggest that the framework provides comparable measures and analysis across international settings. We find that Taipei has a weak fact base and fails to address uncertainty, which importance in adaptation plans has been acknowledged only recently. We also identified shortfalls in public participation and implementation items in both cities. The study concludes by discussing results and giving recommendations to inform more effective approaches as practitioners develop or reevaluate climate adaptation plans.