Planning Efforts Research Articles

Decomposing Future Exposure from Increasing Flood Risk and Forecast Population Changes Across Shared Socioeconomic Pathways (SSPs) in the United States

Extreme weather events, like flooding, are expected to become more severe due to climate change and increasingly impact populations across the US. Adding to this challenge, populations have concurrently settled in risky areas that were previously thought to have low, or no, exposure. Objective: This research seeks to understand the unique contribution of population growth and climate change as independent components of future risk levels in the US. To do so, future population level forecasts are coupled with future flood projections along all five Shared Socioeconomic Pathways (SSPs) at the block group level across the US. The results indicate that, across the five SSPs, the most increase in exposure will occur in SSP5 (+470,719), and the least will occur in SSP 3 (+57,189). By decomposing the contributions from flood and population growth, we find that the population growth-induced effect contributed to an increase in the population exposure for all of the SSPs except for SSP3. This research, and these results, provide a foundation for understanding future risks of flood exposure in an isolated framework and lay the groundwork for the development and integration of planning, adaptation, and mitigation efforts that may be used to address the growing risk of flooding in the context of the population forecasts provided here.

Rethinking Tourism Post-COVID: A Public Health Perspective

This paper examines the evolving relationship between tourism and public health in the context of the COVID-19 pandemic. It explores how tourism contributed to the spread of the virus and the subsequent impact on public health systems. The pandemic has reshaped the tourism industry, emphasizing the need for public health measures to be integrated into tourism planning and recovery efforts. This study highlights the economic implications of COVID-19 on tourism, public health adaptations, and the future of sustainable and resilient tourism practices. By rethinking tourism from a public health perspective, the paper provides insights into creating a more resilient industry post-pandemic.

An Improved Machine Learning Framework Considering Spatiotemporal Heterogeneity for Analyzing the Relationship Between Subway Station-Level Passenger Flow Resilience and Land Use-Related Built Environment

The COVID-19 pandemic and similar public health emergencies have significantly impacted global travel patterns. Analyzing the recovery characteristics of subway station-level passenger flow during the pandemic recovery phase can offer unique insights into public transportation operations and guide practical planning efforts. This pioneering study constructs a station-level passenger flow recovery resilience (PFRR) index during the rapid recovery phase using subway AFC system swipe data. Additionally, it develops an analytical framework based on a multiscale geographically weighted regression (MGWR) model, the improved gray wolf optimization with Levy flight (LGWO), and light gradient boosting machine (LightGBM) regression to analyze passenger flow resilience on weekdays and weekends in relation to land use-related built environment types. Finally, SHAP attribution analysis is used to study the nonlinear relationships between built environment variables and PFRR index. The results show significant spatial heterogeneity in the impact of commercial, recreational, and residential land, as well as POI (points of interest) of leisure and shopping on PFRR. On weekdays, the most relevant built environment variables for PFRR are POI of enterprises and shopping numbers. In contrast, the contribution of built environment variables affecting PFRR of weekend is more balanced, reflecting the recovery of non-essential travel on weekends. Most land use-related built environment variables exhibit nonlinear associations with PFRR values. The proposed analytical framework shows significant performance advantages over other baseline models. This study provides unique insights into subway passenger flow characteristics and surrounding land use-related development layouts under the impact of public health emergencies.

A Study on the Water Management Knowledge of Traditional Villages from the Perspective of Stormwater Resilience—A Case Study of Changqi Ancient Village in Guangdong, China

With the advancement of resilience concepts, enhancing resilience capacity has become an effective approach to addressing rainwater and flooding issues. Most rural planning and construction efforts adopt urban planning models from economically developed regions, often leading to surface hardening, which subsequently causes drainage difficulties and severe surface water accumulation during the rainy season. In contrast, traditional Lingnan villages, exemplified by Guangdong’s Changqi Ancient Village, continue to function normally in flood-prone areas, suggesting that their water management knowledge merits investigation. Previous research on rainwater management in traditional Chinese villages has predominantly been qualitative, lacking scientific data support. This study employs an eco-social resilience perspective, combining field surveys and interviews with villagers, and utilizes the SWMM (Storm Water Management Model) software to conduct both qualitative and quantitative analyses of Changqi Ancient Village. The findings reveal the following: (1) The SWMM effectively quantifies rainwater and flood management in traditional villages. (2) From an ecological resilience perspective, the village’s geographical location is crucial. The topography, along with a rainwater regulation system comprising rivers, ponds, ditches, and permeable pavements, significantly influences the village’s drainage performance. (3) From a social resilience perspective, community participation is vital to the long-term stable development of traditional villages. This includes post-disaster collective fundraising by villagers for the restoration of rainwater and flood management facilities, the formulation of village regulations, and the construction and restoration of spiritual sites. (4) From an eco-social resilience perspective, the eco-social resilience system exhibits adaptive cyclical characteristics, where the geographical environment and the local economy significantly shape the ecological spatial patterns of Changqi, while positive interaction between nature and human society ensures the system’s dynamic equilibrium.

One Year of Wastewater Surveillance in South Africa Supporting COVID-19 Clinical Findings Across Two Waves of Infection

Wastewater-based epidemiology (WBE) has been an important tool for the detection of COVID-19 outbreaks. The retrospective analysis of COVID-19 data is vital to understand the spread and impact of the virus as well as to inform future planning and response efforts. In this study, we evaluated the SARS-CoV-2 RNA levels in wastewater from 21 wastewater treatment plants (WWTPs) in the City of Cape Town (South Africa) over a period of 12 months and compared the (inactive) SARS-CoV-2 viral RNA in wastewater between wave 2 (November 2020 to January 2021) and wave 3 (June 2021 to September 2021). The SARS-CoV-2 RNA expression was quantified in wastewater using quantitative real-time PCR (qRT-PCR) by targeting the nucleocapsid (N) gene, and the resultant signal was normalized to the WWTP design capacity and catchment size. Our findings show that the maximum SARS-CoV-2 RNA signal was significantly higher in wave 3 than in wave 2 (p < 0.01). The duration of wave 3 (15 weeks) was longer than that of wave 2 (10 weeks), and the wastewater surveillance data supported the clinical findings, as evidenced by the two distinct waves. Furthermore, the data demonstrated the importance of long-term wastewater surveillance as a key indicator of changing trends.

Rehabilitation Teams Across the Disaster: A Field Report

Background and Objectives: The article highlights the crucial role of rehabilitation teams in managing disasters. While the importance of rehabilitation in the post-disaster phase is well-recognized, the article underscores the need for greater emphasis on pre-disaster planning and mitigation efforts. Case Presentation: A case study on the 2017 Kermanshah earthquake illustrates the challenges and successes of physiotherapy in disaster relief. The Iranian Physiotherapy Association (IPA) swiftly established a temporary clinic staffed by volunteers. Physiotherapy addressed a range of injuries, including soft tissue and neurological problems. Challenges in delivering physiotherapy services during emergencies include resource constraints, accessibility issues, and infrastructure damage. Conclusion: The article concludes that improvements in these areas can significantly enhance physiotherapy services during crises, leading to better recovery outcomes for survivors. Increased collaboration of rehabilitation teams and implementing research, may improve disaster preparedness and response.

Functional ecology of plant communities as a guide for vegetation management

Plant functional traits determine how individual plants cope with varying environmental conditions, and extensive literature supports their role in influencing ecosystem properties. The study of plant functional traits could help the prediction of species responses to disturbances and environmental change, thus providing invaluable knowledge to refine conservation strategies of species and vegetation. However, applications of functional ecology for vegetation management are still underrepresented.The articles in this Special Issue of FLORA offer cutting-edge insights on the variation of plant traits and ecological strategies in response to environmental drivers, such as anthropogenic disturbance, climate and land use change. The results demonstrate how trait-based approaches can be used for the prediction of climate and land use change impacts on vulnerable sets of species or on biogeochemical cycles, reinforcing the concept that functional plant ecology can help identify the most effective procedures for vegetation management, such as the choice of mowing intensity in grasslands or planning vegetation recovery after wildfires.Our knowledge of plant trait coordination at the community level is still undefined, especially concerning the integration of above- and belowground traits. This represents a missed opportunity for vegetation management, especially considering that a complete understanding of the dynamics of the entire ecosystem is crucial for complete understanding of ecosystem properties. Since plant functional traits can represent a straightforward tool for monitoring changes in ecosystem structure and functions, their use could support vegetation monitoring as required by different programs of nature conservation. It would be useful to embrace a perspective that integrates plant traits with systematic conservation planning, ensuring effective and sustainable conservation efforts.

Interactive Effects of Built Environment and Parking Policy on Car Use: Examining Differences Between Work and Non-Work Trips

Considerable interest has been shown in decreasing car use through planning and policy-making efforts. However, little is known about the interactive effects of built environment (BE) and parking policy on car use, and it is unclear whether and how these effects differ across trip purposes. We conducted a web-based survey in Beijing and collected data from 1036 respondents, including 517 male and 519 female respondents. This study estimates the interactive effects of BE and parking policy on car use for home-based work and non-work trips by employing multilevel logit models. The results show that BE variables at trip origins and destinations are important for shaping car use for both home-based work and non-work trips. Specifically, land use mixture (Coeff. = −0.121), bus stop density (Coeff. = −0.006), and population density (Coeff. = −0.009) at residential locations are negative factors affecting car use for work trips, whereas distance to local center (Coeff. = 0.012) and distance to the city center (Coeff. = 0.019) at residential locations are positive factors. Land use mixture (Coeff. = −0.323), bus stop density (Coeff. = −0.008), road density (Coeff. = −0.002), and population density (Coeff. = −0.007) at residential locations are negative factors of car use for non-work trips. Among BE factors at destinations, land use mixture (Coeff. = −0.319), bus stop density (Coeff. = −0.015), road density (Coeff. = −0.008), distance to the local center (Coeff. = −0.018), and population density (Coeff. = −0.012) are negative factors for car use for work trips, whereas the negative factors for non-work trips are land use mix (Coeff. = −0. 218), bus stop density (Coeff. = −0.038), road density (Coeff. = −0.003), distance to the city center (Coeff. = −0.121), and population density (Coeff. = −0.009). The effects of BE variables can be strengthened or weakened by free parking and parking convenience. Moreover, the results identify significant differences in the effects between work and non-work trips. These findings inform planners and policymakers of how to coordinate the BE and parking policies to decrease car dependence.

Evergreen Migration for North Carolina Community College Libraries

The migration of North Carolina Community College Libraries to the Evergreen platform is the culmination of planning, training, and implementation efforts of librarians throughout the state over the last four and a half years. This article provides a brief overview of the process and outlines benefits for the 50 participating institutions, before concluding with suggestions for other libraries that are considering a similar migration.

Urban Open Space Utilization for Subsistence Agriculture: A Study of Esikhaleni Township

This research investigates the motivations driving the utilization of urban open spaces for subsistence agriculture and assesses its impact on the livelihoods of residents in Esikhaleni Township. Employing a mixed-methods approach, the study conducts structured interviews with local farmers and in-depth interviews with municipal officials from the uMhlathuze Municipality. The findings highlight food insecurity, the necessity for accessible fresh produce, agricultural passion, and rising food costs as primary drivers compelling Esikhaleni residents towards open space farming. Moreover, the research underscores the significant contribution of open space agriculture to the livelihoods of Esikhaleni residents, including improved access to fresh food, reduced food expenditures, and supplementary income generation through produce sales. The study concludes by recommending the integration of urban agriculture into urban planning efforts to safeguard land for agricultural purposes, thereby enabling residents of Esikhaleni Township to engage in sustainable agricultural practices.

Stronger increase of methane emissions from coastal wetlands by non‐native Spartina alterniflora than non‐native Phragmites australis

Societal Impact StatementThe invasive species S. alterniflora and P. australis are fast growing coastal wetland plants sequestering large amounts of carbon in the soil and protect coastlines against erosion and storm surges. In this global analysis, we found that Spartina and Phragmites increase methane but not nitrous oxide emissions, with Phragmites having a lesser effect. The impact of the invasive species on emissions differed greatly among different types of native plant groups, providing valuable information to managers and policymakers during coastal wetland planning and restoration efforts. Further, our estimated net emissions per wetland plant group facilitate regional and national blue carbon estimates.Summary Globally, Spartina alterniflora and Phragmites australis are among the most pervasive invasive plants in coastal wetland ecosystems. Both species sequester large amounts of atmospheric carbon dioxide (CO2) and biogenic carbon in soils but also support production and emission of methane (CH4). In this study, we investigated the magnitude of their net greenhouse gas (GHG) release from invaded and non‐invaded habitats. We conducted a meta‐analysis of GHG fluxes associated with these two species and related soil carbon content and plant biomass in invaded coastal wetlands. Our results show that both invasive species increase CH4 fluxes compared to uninvaded coastal wetlands, but they do not significantly affect CO2 and N2O fluxes. The magnitude of emissions from Spartina and Phragmites differs among native habitats. GHG fluxes, soil carbon and plant biomass of Spartina‐invaded habitats were highest compared to uninvaded mudflats and succulent forb‐dominated wetlands, while being lower compared to uninvaded mangroves (except for CH4). This meta‐analysis highlights the important role of individual plant traits as drivers of change by invasive species on plant‐mediated carbon cycles.

Disaster vulnerability in road networks: a data-driven approach through analyzing network topology and movement activity

The rise in natural disasters and climate-induced events, such as wildfires, hurricanes, and flooding, has significantly affected urban life. These events can disrupt daily activity and flows of individuals and goods on road and transit networks. To enhance urban resilience against disasters, it’s crucial to study and understand road network vulnerability, utilizing data-driven insights to inform planning and preparedness efforts. The aim of this paper is to develop a data-driven exploratory approach to assess vulnerability in road networks in response to a disruption. To accomplish this, we compare the centrality of road segments before, during, and after disaster, considering the network topological structure and movement activity as it is observed through large tracking data of cellphone traces on the network. The novelty of our approach lies in inferring the impact from movement data, instead of manually removing links from the network. The results obtained from this study suggest that incorporating movement data into the assessment of network functionality provides a more realistic estimation of the road network vulnerability in response to a disruption, compared to solely using network topology.

Model sensitivity in predicting extreme precipitation events in urban areas: A case study over Beijing

Understanding and forecasting the spatial and temporal distributions of extreme precipitation over urban areas is crucial for effective planning and mitigation efforts. However, this task remains challenging as accurate forecasting depends on properly representing urban surfacees and their interactions with the planetary boundary layer (PBL). We examined the hindcast of an extreme precipitation event over Beijing on 21–22 July 2012. The primary focus was assessing its sensitivity to two widely used PBL parameterizations (MYJ and YSU), two urban parameterizations (SLUCM and BEP_BEM), and two different land-use and land-cover (LULC) datasets.Sensitivity experiments were initialized at different times to explore the model dependence on initial conditions. The analyses were conducted over three selected regions: the entire model domain covering the Beijing metropolitan area, an upwind region of Beijing, and the entire urban area of Beijing. The results show that the MYJ PBL scheme performs better than the YSU PBL scheme in capturing near-surface air temperature as well as the location and timing of the heaviest precipitation. The variability in simulated precipitation among the chosen PBL schemes is lower compared to that among different time of initializations. The LULC impacted the spatial distribution of precipitation but its effect on the amount of precipitation was minimal. Overall, using a combination of the MYJ PBL scheme, SLUCM urban parameterization, and locally-enhanced Beijing LULC, and initializing the model simulations at 0000 UTC July 20, 2012, demonstrated superior performance in capturing precipitation levels, despite some spatial discrepancies in the precipitation distribution. The performance of BEP_BEM urban parameterization is similar to SLUCM across various factors such as average rain rate, maximum rain rate, and rain volume. These findings offer valuable insights towards better simulations of extreme precipitation and flooding in rapidly urbanizing areas such as Beijing.

Association between postoperative complications and hospital length of stay: a large-scale observational study of 4,495,582 patients in the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) registry

BackgroundPrecise estimates of risk-adjusted increases in postoperative length of stay (LOS) associated with postoperative complications across a range of complications and operations are not available in the existing literature.MethodsAssociations between preoperative characteristics, postoperative complications and postoperative LOS were tested using medians, interquartile ranges, and nonparametric rank sum tests in a retrospective cohort study using the 2005–2018 American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) dataset. A negative binomial model was used with postoperative LOS as the dependent variable and preoperative characteristics and postoperative complications as independent variables. The model was applied to estimate each patient’s postoperative LOS with and without each postoperative complication to measure the association between each complication and risk-adjusted change in postoperative LOS.ResultsA total of 4,495,582 patients were included. After risk-adjustment, occurrence of each postoperative complication was associated with significantly increased postoperative LOS (between + 3.9 and + 20.1 days, p < 0.0001). The longest risk-adjusted postoperative LOS increases were associated with prolonged ventilator use (+ 20.1 days), wound disruption (+ 19.4 days), and acute renal failure (+ 17.1 days).ConclusionOccurrence of any postoperative complication was associated with increased risk-adjusted postoperative LOS. Degree of increase varied by complication. These data could be useful for patient counseling, allocation of resources, discharge planning, and quality improvement efforts.

An Overview of Transdisciplinary and Bottom-up Approach for Urban Resilience: The Case of Turkey

While top-down strategies have traditionally dominated urban planning in Turkey, recent shifts towards participatory practices and project-based policies have aimed to involve citizens in decision-making processes. Nevertheless, in the case of Turkey, these participatory models are inadequate for effectively addressing resilience. This article therefore discusses the role of participatory processes in creating resilient cities, as well as how to strengthen transdisciplinary (TR) and bottom-up approaches to urban participation in Turkish urban contexts. The article presents a theoretical framework that connects TR and bottom-up approaches based on existing literature, practices, and planning policy examples. It argues that TR approaches complement bottom-up approaches to urban governance by enhancing urban and social resilience, strengthening local communities, and reducing urban inequalities. Urban planning efforts that promote collaboration, incorporate multiple perspectives, and involve local communities in decision-making processes can address complex urban issues while also fostering long-term sustainability and resilience. This approach not only instills a sense of ownership and empowerment among urban residents but also leverages knowledge and skills to generate more effective and sustainable solutions. By creating a framework that promotes long-term education and citizenship awareness, urban governance can sustain urban resilience in a more viable manner over the long term in Turkey.

URBAN FLOOD RESILIENCE: A MULTI-CRITERIA EVALUATION USING AHP AND TOPSIS

Floods are increasingly recognized as one of the most destructive natural disasters, driven by urban expansion, climate change, and unregulated development. This is particularly true in developing countries, where rapid urbanization has increased impervious surfaces, amplifying flood risks in urban areas. This study focuses on Albania, evaluating urban resilience against floods through the lens of water-related disaster data. Using a multi-criteria decision analysis (MCDA) approach, specifically the Analytic Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), the research assesses flood vulnerability and resilience in rapidly urbanizing regions. Integrating AHP and TOPSIS with mixed methods introduces a novel approach, offering a comprehensive evaluation framework for flood risk management. The findings highlight critical vulnerabilities and suggest that targeted urban planning and disaster mitigation efforts can enhance resilience. Future research could incorporate climate projections and granular urban data, supporting a more adaptive flood management strategy.

Enhancing bird habitat networks in metropolitan areas: Resilience assessment and improvement strategies – A case study from Shanghai

Constructing bird habitat networks (BHNs) is crucial for maintaining the health and service equilibrium of urban ecosystems, especially in large metropolitan areas where the pressure of urbanization is intense. However, most existing BHNs fail to account for the dynamic changes and unique requirements of local species, leading to homogenized construction outcomes and ecological corridor objectives. This study employs a comprehensive approach to identify bird habitat patches using multiple high-quality sources, then utilize circuit theory and complex network theory to construct and assess the resilience of BHN. Our key findings showed: (1)93 bird habitat sources were identified, predominantly situated in the continuous green spaces of southern and southeastern Shanghai, whereas habitat sources in the city center and other densely built-up areas are more dispersed, highlighting them as prime targets for future ecological restoration efforts. (2) The distribution of bird habitat corridors exhibits significant spatial heterogeneity, with primary corridors predominantly spanning the southwestern and eastern parts of the study area, while secondary corridors are more abundant in the western and northern parts, forming a denser network, whereas the central area shows fewer and more isolated corridors. (3) The decline in structural and functional resilience was notably more rapid under targeted attacks than under random attacks, underscoring the need to prioritize crucial bird habitat sources on the city's periphery, especially near highly urbanized areas, in urban planning and biodiversity conservation efforts to sustain ecological balance and biodiversity. These insights provide a crucial scientific basis for urban planners, emphasizing the integration of biodiversity conservation into urban development strategies by optimizing ecological sources and corridors to balance development with ecological preservation.

Geomorphology and sediment mobility on sand banks: A study of Dogfish Bank, Hecate Strait, Northeast Pacific Ocean

AbstractMovement of sediment along shallow continental shelves is a natural process with wide‐ranging environmental and economic implications, making it of high importance to marine spatial planning efforts in the offshore. Development of marine renewable energy, for instance, requires detailed understanding of the morphodynamics of mobile bedforms to select foundation types and ensure safe installation of infrastructure in shallow shelf environments. This study evaluates geomorphology and sediment mobility of Dogfish Bank (&lt; 20 mbsl) in the Hecate Strait offshore British Columbia, Canada, using hydroacoustic and airborne bathymetric data combined with seismic profiles and grain‐size information. These data reveal current‐swept features ranging from sediment‐depleted lag to sediment‐abundant sand ridges and dunes, with sand ribbons and furrows in‐between. Seismic reflection data show up to 15 m of surficial sand concentrated beneath north‐aligned sand ridges that dominate the bathymetry of northwest Hecate Strait. Sand ribbons (typically understood sediment‐limited features in shallow marine environments) are notably maintained over seabed with comparable sand thickness to adjacent dunes (i.e. sediment‐abundant features), suggesting local spatial variability in hydrodynamics and sediment characteristics (principally grain size) influence expression of mobile bedforms. Repeat mapping between 2008 and 2019 shows dunes and ribbons both migrate northwards, with largest seafloor changes along northeast‐facing lee sides of dunes, matching closely with published models of sediment mobility which suggest northward bedform migration is largely driven by storms. Median total migration distance is 164 m (northward) for dunes (time‐averaged rate of 14.9 m/year). Sand ribbons show less migration (median northward distance of 73 m) and migrate in a depth‐dependent manner. Because sand ribbons are typically flow‐parallel features, their lateral migration likely results from varying current directions and flow acceleration over shallower seabed. Sand ribbon migration should therefore a consideration in studies examining seabed change, particularly when they are formed over unconsolidated sediment.

Enhancing Adaptive Capacity by Engaging and Empowering Frontline Workers: A Case Study From a Water Utility

AbstractWater utility crews, including those who perform system maintenance and operations at drinking water, wastewater, and stormwater utilities, are experiencing the impacts of changing rainfall characteristics first‐hand. These frontline crews have relevant, experiential knowledge about changing climate‐related risks and adaptation needs that, to date, are not included in utilities' strategic climate planning or implementation efforts, resulting in critical knowledge systems and action gaps. In this co‐production case study with Seattle Public Utilities (SPU), a municipal public water utility in Washington State, we use surveys and interviews to document barriers and opportunities for frontline crew engagement to enhance SPU's climate adaptation strategies to extreme rainfall. We find that 66% of crew workers perceive changes to rainfall intensity over the past decade and 59% report responding more to rainfall‐related issues. These frontline crews are coping with changes in extreme precipitation by increasing preventative maintenance, working overtime during major storm events, and doing more pre‐storm planning and preparation. Crews identified several aspects limiting their ability to respond to and prepare for extreme rainfall. To enhance their adaptive capacity, crews documented needs for infrastructure improvement, workforce facilities improvement, increased access to appropriate personal protective equipment, improved communication and coordination across the utility, and enhanced workforce capacity, including increased staff numbers. Findings suggest that for more effective, equitable, and responsive climate adaptation, water utilities should explicitly solicit and include crews' knowledge and lived experiences in adaptation planning while prioritizing strategies that enhance frontline crews' capacity and working conditions as a form of reciprocal action.

Non-linear relationship between built environment and active travel: A hybrid model considering spatial heterogeneity

Exploring the mechanisms between the built environment and active travel is crucial for promoting green transportation and fostering the sustainable development of cities. Existing literature focuses on the correlation between the built environment and active travel in urban centers, with limited studies on suburban environments, ignoring the implications of spatial heterogeneity. This paper conducts a comprehensive spatio-temporal analysis of suburban residents’ active travel behavior and explores the nonlinear relationship between suburban built environment and active travel. A novel hybrid modeling framework that combines eXtreme Gradient Boosting and Multi-scale Geographic Weighted Regression is introduced to forecast suburban active travel demand with the consideration of the nonlinearity and spatial heterogeneity in parameter estimates. Shapley additive explanation is used to elucidate the non-linear relationship between built environment variables and active travel. The results indicate that the proposed hybrid model performs the best with high predictive power and interpretability. The density of tourist attractions, transportation facilities, and household properties emerges as the three most influential factors affecting residents’ active travel behavior. Social-economic attributes contribute 15.70% to the prediction, while three categories of built environment variables (accessibility, transportation facilities, and land use) contribute 7.31%, 5.13%, and 71.87%, respectively. The hybrid model appears to be effective in identifying the nonlinear relationship and threshold effects between built environment variables and active travel. Besides, the model provides actionable insights into designing sustainable and efficient suburban environments, supporting targeted planning and policy-making efforts.