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Situated within the Ring of Fire and characterized by a tropical climate and high seismic activity, Indonesia is uniquely vulnerable to natural disasters such as floods and landslides. These events pose significant threats to both the population and infrastructure. This study predicts areas exposed to flood and landslide risk by considering various environmental factors related to climate, topography, and land use. The predictive performance of three machine learning models-naïve Bayes, k-nearest neighbors, and random forest (RF)-was evaluated by comparing the AUC, RMSE, and R 2 values of each model. Ultimately, the RF model, which demonstrated the highest accuracy, was used to prioritize disaster impact factors and generate hazard maps. The results identified the interaction of rainfall, land use, and slope aspect as the most critical determinants of hazard occurrence. The predicted hazard maps revealed that approximately 26.7 % of the study area was vulnerable to either floods or landslides, with 16.8 % of the area experiencing both. The new capital of Nusantara showed a relatively higher multi-hazard risk than did the overall study area and protected zones, with 22.1 % of the hazard area vulnerable to both flooding and landslides. In single hazard zones, areas classified as at risk for floods had a higher mean probability of experiencing both hazards (43 %), as compared to areas classified as at risk for landslides (22 %). As a result, urban planners and relevant stakeholders can now utilize the hazard maps developed in this study to prioritize infrastructure reinforcement and disaster risk areas, integrating land use planning with risk assessment to mitigate the impact of disasters. By employing these strategies, Indonesia and other countries facing similar challenges can now enhance their disaster preparedness and response capabilities in new capital regions and other areas, ultimately planning for more sustainable urban development., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors. Published by Elsevier Ltd.)

Numerous studies have investigated the relationship between the neighborhood environments and residents' health. However, other important settings, such as university campuses, have received little attention. This paper conducted a systematic review and synthesized existing empirical works examining the association between the university/college campuses built and natural environments and students' health. Following the PRISMA guidelines, we searched nine databases using keywords related to higher-education campuses and health-related outcomes. A total of 19 articles were identified, including fifteen cross-sectional studies, three experimental studies, and one longitudinal study. The majority of the studies were conducted in Asian countries and published in the past five years. The findings indicate that active transportation infrastructure, such as increased road intersections and better walkability, were found to be positively associated with students' physical activity. The natural environments, including perceived naturalness, blue space, and greenness was shown to support student's mental health and quality of life. Specifically, blue space was found to be the most preferred place for mental restoration, and scattered trees demonstrated a supportive effect in reducing depression symptoms. Even just viewing virtual trees had a restorative effect and feel less anxiety. Additionally, during the summer, tree shadows were identified as the most important factors for enhancing thermal comfort. This review emphasizes the crucial role of campus environments in promoting college students' health. Future longitudinal studies and investigations using multiple campuses would provide a more comprehensive understanding of this relationship. Such endeavors can contribute to the development of evidence-based strategies for designing and planning healthy campus environments that optimize students' well-being., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

The COVID-19 pandemic has disrupted people's daily routines, including travel behaviors, social interactions, and work-related activities. However, the potential impacts of COVID-19 on the use of campus locations in higher education such as libraries, food courts, sports facilities, and other destinations are still unknown. Focusing on three largest universities in Texas (Texas A&M university, the University of Texas at Austin, and Texas Tech University), this study compares changes in campus destination visitations between pre and post COVID-19 outbreak (2019 Fall and 2021 Fall semesters, respectively) using the mobility data from SafeGraph. It also examines the potential moderation effects of walkable distance (i.e. 1 km) and greenery (i.e. NDVI value). The results presented the significant effects of COVID-19 on decreasing visitations to various campus places. The visitation decreased more significantly for people living within 1 km (defined as a walkable distance) of campus and for the food, eating, and drinking places and the sports, recreation, and sightseeing places. This finding suggests that those living near campus (mostly students) decreased their reliance on campus destinations, especially for eating/drinking and recreation purposes. The level of greeneries at/around campus destinations did not moderate campus visitations after COVID-19. Policy implications on campus health and urban planning were discussed., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Compound hazards are derived from independent disasters that occur simultaneously. Since the outbreak of COVID-19, the coupling of low-probability high-impact climate events has introduced a novel form of conflicting stressors that inhibits the operation of traditional logistics developed for single-hazard emergencies. The competing goals of hindering virus contagion and expediting massive evacuation have posed unique challenges for community safety. Yet, how a community perceives associated risks has been debated. This research utilized a web-based survey to explore the relationship between residents' perceptions of conflicting risks and emergency choices made during a historic compound event, the flooding in 2020 in Michigan, US that coincided with the pandemic. After the event, postal mail was randomly sent to 5,000 households living in the flooded area, collecting 556 responses. We developed two choice models for predicting survivors' evacuation options and sheltering length. The impact of sociodemographic factors on perceptions of COVID-19 risks was also examined. The results revealed greater levels of concern among females, democrats, and the economically inactive population. The relationship between evacuation choice and concern about virus exposure was dependent upon the number of seniors in the household. Concern about a lack of mask enforcement particularly discouraged evacuees from extended sheltering., Competing Interests: None., (© 2023 Elsevier Ltd. All rights reserved.)

Climate change is contributing to an increasing frequency and intensity of floods in Korea. This study predicts areas with a high probability of flooding in coastal areas of South Korea owing to future climate change, which is likely to cause extreme rainfall and sea-level rise, using a spatiotemporal downscaled future climate change scenario with random forest, artificial neural network, and k-nearest neighbor techniques. In addition, the change in coastal flooding risk probability according to the application of different adaptation strategies (green spaces and seawalls) was identified. The results showed a clear difference in the risk probability distribution in the absence and presence of either adaptation strategy. Their effectiveness in moderating future flooding risks is subject to change owing to strategy type, geographic region, and urbanization intensity and the results show that green spaces are slightly more effective than seawalls when forecasting for 2050. This demonstrates the importance of a nature-based strategy. Moreover, this study highlights the need to prepare adaptation measures according to regional characteristics to mitigate the impact of climate change. Korea is surrounded by seas on three sides that have independent geophysical and climate characteristics. The south coast has a higher risk of coastal flooding than the east and west coasts. In addition, a higher urbanization rate is associated with a higher risk probability. This implies that climate change response strategies for coastal cities are necessary as the population and socioeconomic activities of coastal urban areas are likely to increase in the future., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Ltd.)

The importance of implementing green infrastructure (GI) for flood protection is supported by multiple substantial cross-sectional analyses. Yet, limited longitudinal research has been conducted which addresses how to maintain and improve the configuration of GI in order to minimize the cost of losses resulting from flooding. Structural damage from devastating storm events has repeatedly imposed substantial financial burdens on local governments in coastal regions. This study longitudinally examines the impacts of changes in GI patterns on flood damage cost in coastal Texas areas. Major flood events in the 36 Texan coastal watershed counties along the Gulf of Mexico were monitored from 2000 to 2017. Along with non-spatially weighted panel data models, we developed an advanced statistical model controlling for spatially correlated errors in flood loss and predicting flood loss with a set of time-series socioeconomic and environmental control variables. The results of the spatial panel data model reveal that long-term maintenance of larger, more irregular, more dispersed, less fragmented, and less connected patterns of GI will help to reduce county-level flood damage costs per capita over time. Most importantly, protecting larger patches within a closer proximity was found to be of the utmost importance for retaining the flood regulation services provided by GI. These findings suggest that planners and natural resource managers should enhance supportive land use policies to preserve existing GI and strategically locate new implementations in order to achieve long-term flood protection., Competing Interests: Declaration of interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Low impact development (LID) has been increasingly practiced since its emergence in the 1990s. Although the hydrological benefits of LIDs have been extensively documented, the climate impact on LID performance remains unclear with increasing variations in spatial and temporal climate patterns. This systematic review contributes to providing a structured summary of research on how LID systems are sensitive to climate variability by empirical and hypothetical research approaches. The selected 46 peer-reviewed journal articles published between 2003 and 2017 were analyzed by key variables, including climatic factors, LID types, and hydrologic measures used to quantify LID performance. A conceptual framework formulated in this study synthesizes the relationship between climate and LID effectiveness. The results of weighted meta-analysis reveal a greater sensitivity of runoff volume to changing storm frequency than peak discharge rates, while the capacity of LID systems to reduce both volume and peak discharge rates diminishes with increasing storm intensity. Future explorations of the sensitivity of LIDs to climate fluctuations will help strategize LID installation for targeted storm patterns and flood mitigation goals. To enhance existing methods and make a balance between empirical and hypothetical knowledge, this study suggests future directions of research and encourages development of effective stormwater management policy., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Rapid urbanization has accelerated land use and land cover changes, and generated the urban heat island effect (UHI). Previous studies have reported positive effects of neighborhood landscapes on mitigating urban surface temperatures. However, the influence of neighborhood landscape spatial patterns on enhancing cooling effects has not yet been fully investigated. The main objective of this study was to assess the relationships between neighborhood landscape spatial patterns and land surface temperatures (LST) by using multi-regression models considering spatial autocorrelation issues. To measure the influence of neighborhood landscape spatial patterns on LST, this study analyzed neighborhood environments of 15,862 single-family houses in Austin, Texas, USA. Using aerial photos, geographic information systems (GIS), and remote sensing, FRAGSTATS was employed to calculate values of several landscape indices used to measure neighborhood landscape spatial patterns. After controlling for the spatial autocorrelation effect, results showed that larger and better-connected landscape spatial patterns were positively correlated with lower LST values in neighborhoods, while more fragmented and isolated neighborhood landscape patterns were negatively related to the reduction of LST., Competing Interests: The authors declare no conflict of interest.

Although a substantial body of literature has provided evidence supporting the positive effects of natural environments on well-being, little has been known about the specific spatial patterns of urban nature in promoting health-related quality of life (HRQOL) among children. This study assessed the association that the urban natural environment measured by landscape spatial patterns may have with obesity and HRQOL among Hispanic children. Ninety-two 4th and 5th grade students were recruited from Houston, Texas, and the Pediatric Quality of Life Inventory (PedsQL) was used to capture the children's HRQOL. The quality of urban natural environments was assessed by quantifying the landscape spatial patterns, using landscape indices generated by Geographic Information Systems and remote sensing. From the bivariate analyses, children's body mass index showed a significantly negative association with their HRQOL. After controlling for socio-demographic factors, the results revealed that larger and more tree areas were positively correlated with children's HRQOL. In addition, those children living in areas with tree patches further apart from each other showed higher HRQOL. This research adds to the current multi-disciplinary area of research on environment-health relationships by investigating the roles of urban greeneries and linking their spatial structures with children's HRQOL.