Landscape and Urban Planning最新文献

Strategic planning approaches are essential for addressing the complex and multi-dimensional challenges in selecting blue-green infrastructure (BGI) location. The development of planning support systems (PSS) for BGI siting often lacks a value-based approach with early stakeholder engagement. In this study, we used value-focused thinking (VFT) to adapt and develop a BGI planning support framework to the Canadian urban context, moving towards an objective-driven framework. We provide a hierarchical objectives framework for BGI planning in urban areas, aligned with stakeholder values, with three-level information: higher-level objectives, lower-level objectives and measurable spatial attributes. To assess site performance across these attributes, value scales elicitation was conducted with 17 experts. The engagement of 37 stakeholders in co-creating and validating our objectives set helped identify common concerns and refine our framework, focusing on the most relevant objectives for stakeholders. The VFT approach and the resulting framework can be easily transferred to other cities in Quebec (Canada), but also to other urban contexts looking to optimize BGI site selection to maximize benefits across the multiple functions of BGI and opportunities arising from the urban context.

Effective climate change adaptation planning requires evaluating the interplay of physical landscape characteristics and community perceptions of places. Geographic information system (GIS)-based approaches to measuring environmental values can identify locations for planning prioritization. But they seldom are used to consider spatial differences in socio-ecological worldview. This study aims to identify how place-based risk perceptions and landscape values can inform climate change adaptation using a Q+PPGIS method. We integrated mapped landscape values and climate risks (from 39 PPGIS participants) with elicited discourses (for 28 Q-method participants) to develop a novel land classification approach (reflexive Q+PPGIS). The results demonstrate significant differences between wilderness as a discourse and perceived, and the physical features associated with mapped wild areas. Similar differences in discourse and spatial patterns are observed for climate risks. For example, participants’ mapped areas of bushfire risk do not align with agencies identified risk areas, their jurisdictions, and capacities to take action. This disconnect presents a challenge to adaptation. Local governments can use this new method to show constituents multiple and often competing community demands for action, enabling honest conversations about feasible actions, responsibilities, and resource allocation.

After the Great East Japan Earthquake in 2011, the Japanese government reconstructed coastal protection facilities to mitigate extreme disasters and coastal erosion. However, the substantial compression of coastal zones poses a challenge in coping with sea level rise, while maintaining a sustainable coastal ecosystem. To clarify the impact of environmental factors and sea level rise on coastal ecosystems in highly developed regions, this study integrated field surveys, geo-detector analysis, and coastal inundation models into the research framework. It explored the relationship between environmental factors and vegetation patterns and predicted the inundation areas and vegetation survivorship of 12 transects in the study area from 2030 to 2150. The results indicated that the distance from the tide embankment (DTE) and elevation (DEM) were the main driving factors, and the combination of the potential of hydrogen (pH) and DTE had a major impact on vegetation coverage. Notably, the distribution of vegetation was positively correlated with the width of the coastal zone, and when the width was less than 60 m, vegetation could not survive. With sea level rise, almost no vegetation will survive until 2150. Appropriate coastal width and height are conducive to maintaining the sustainability of coastal ecosystems.

Location-based games provide an opportunity to collect crowdsourced, spatially explicit data that can be used in decision-making processes in forest planning. While these games have been more widely used in collecting mapping and modelling data, there is limited research on their suitability for collecting location-based data on human preferences, opinions, and emotions in these contexts. Collecting human-centred data can be resource-intensive and costly, hence exploring the potential of location-based games is important. This study investigates the use of geocaching in gathering meaningful data in urban and rural settings. A methodology was developed wherein surveys were embedded in geocaches on trails located in urban and rural forests in Finland. These surveys collected quantitative, qualitative, and photographic data relating to human-forest relationships and landscape preferences. The findings indicate that trails closer to urban areas with higher population density showed increased cache log volume and survey response rates. Moreover, trails tended to collect most information in the first summer after establishment. It is recommended that future studies employing this methodology create shorter, easily accessible, circular trails and that survey questions should be clear and incorporate a method to verify that submitted responses reflect experiences at the chosen location. Furthermore, forest planning professionals and researchers seeking to utilise location-based games in data collection are advised to engage with the communities active in playing them to ensure success..

European cities consistently seek to improve urban environments for their residents, yet often struggle to find solutions to address urban issues while engaging citizens. The European Union funds research and innovation projects proposing nature-based solutions to address climate change, biodiversity, human health and wellbeing in cities under the Horizon 2020 and Horizon Europe programs. The presented research from the project UPSURGE is based on a survey of 5,990 urban residents in 6 European countries. The study focuses on the planning phase of nature-based solutions in cities, in which trade-offs have to be made between different options, such as the design, effectiveness, financial contributions from residents or participatory options. Based on an innovative survey including a choice experiment, the aim is to assist public participation processes in various countries, help planning teams define priorities and design governance measures which ensure long-term dedication to development plans. The results reflect respective exposure to climate change across the continent; such as Greek respondents being more affected by high temperatures compared to those from the United Kingdom. However, the study also revealed different preferences in regard to a participatory planning process, willingness to pay and importance of biodiversity.

Urban natural spaces with high wildness degrees could harbor greater biodiversity and provide more experiences of nature for urbanites than green–blue spaces that are perfectly manicured and regularly maintained. Existing empirical studies have suggested that people tend to prefer moderately wild landscapes. However, urbanites’ preferences for varying wildness degrees of urban landscapes have rarely been studied in developing countries with fast-growing cities. Using a photograph-based survey, this study compared citizens’ preferences for an urban wildness gradient of urban lakeshores between developed (Tours, France) and developing (Wuhan, China) contexts. In Tours and Wuhan, respectively, 120 and 295 questionnaires were collected, focusing on lakeshore visitors only. Bootstrapping and thematic analysis of the survey responses affirmed that urban lakeshores with medium-degree wildness are consistently preferred across developed and developing contexts, a result that can be attributed to the perceived balance between landscape coherence/legibility and complexity/mystery. Moreover, some respondents (25.8 % from Tours and 32.6 % from Wuhan) showed a strong preference for complex and unstructured lakeshore landscapes with high wildness for different reasons. In Tours, respondents’ preference for high wildness degree was associated with more frequent visits to lakeshore areas. In Wuhan, a similar preference was associated with increasing age. While increasing the wildness of urban lakeshores from low to medium could adequately meet public preferences, attracting more frequent visits and helping younger residents to appreciate urban wildness should be considered for successfully restoring/enriching biodiversity and mobilizing public support for wild urban landscapes.

Exposure to greenspaces has well-established benefits for the health and well-being of urban dwellers. Among these greenspaces, peri-urban parks (PUPs), which are human-modified, large-scale, and public-accessible greenspaces located on the urban fringe, have received increasing attention from policymakers and researchers in recent years, as the limited provision of greenspaces in urban areas barely meet the residents’ needs for nature engagement. However, the associations between PUPs and life expectancy and their potential socioeconomic inequalities remain unclear. In this study, we employed a longitudinal, territory-wide death-registration dataset to address such research gaps. The results showed that both the area and greenery of PUP significantly decreased life expectancy loss with standardized coefficients of −0.156 (p = 0.001) and −0.173 (p < 0.001), respectively. The life-expectancy benefits of PUP greenery remain significant throughout 200–8000 m buffer radii. Nevertheless, socioeconomic inequalities were found between PUPs and life expectancy associations. We found that people with higher socioeconomic status (SES) received higher PUP exposure. In addition, contrary to the hypothesis of equigenesis theory, higher-SES populations received greater benefits in life expectancy than lower-SES populations, even after controlling for inequalities in PUP exposure. Our findings uncover a complex relationship between PUPs, life expectancy, and SES, highlighting the need for targeted interventions for people with different SES to ensure equitable health benefits for all.

Green infrastructure (GI) has developed as a sustainable approach to the mitigation of urban floods. While machine learning (ML) models have exhibited advantages in urban flood simulation, their direct application to support the quantitative planning of GI at the city scale remains a challenge. To address this, an interpretable ML model based on support vector machine (SVM) and the Shapley additive explanations (SHAP) approach is integrated with the non-dominated sorting genetic algorithm-II (NSGA-II) in this study. The model is applied to the case of central Beijing, China, and demonstrates a robust performance with a high area under curve (AUC) value of 0.94. The results of the urban flood susceptibility assessment identify the urban-rural transition zone in the study area as being under a greater flood threat. Via model interpretation with SHAP, the dominant roles of GI and grey infrastructure (GrI) in preventing flood are revealed and the non-linear complementarity between the two is demonstrated to be more significant in study units with a GI proportion of less than 0.45. Supported by the NSGA-II-based optimization framework, optimal GI plans under different total implementations of GI are achieved, among which a solution with a 3.21% increase in the total GI area is selected as that with the best investment efficiency. The pattern of GI implementation is suggested to be dispersed and small-scale by model. This study provides a tool with broad application prospects, effectively integrating GI implementation with urban planning. The findings of this study not only provide important references for the determination of the priority areas of new ecological space in Beijing, but also provide areas that share similar characteristics with new insight into GI planning and the management of urban floods.

Childhood nature experiences have been identified as critical factors of Nature Relatedness (NR) at the individual level. This exploratory study delved into the distinct contribution of different forms of childhood experiences to NR in early adulthood, focusing on the living environment and actual contact with nature, along with nature education and the influence of people around. NR scores and self-reported experiences of Chinese college students (n = 431) were collected using a questionnaire survey. Objective environmental indicators (normalized difference vegetation index, land cover, and nighttime light) in 13 buffers of different sizes were adopted to precisely depict their historical living environments. Based on the results of bivariate correlations and hierarchical linear regressions, the quantity of natural components in the childhood living environment did not predict long-term NR. Nighttime light and impervious surface at large geographic scales had significant but weak negative correlations with NR. Experiences of actual contact with nature, especially the experiences of interactive behaviors rather than merely visiting natural spaces, are better predictors than the objective environment. The interactive behaviors of observing natural processes and cultivating plants had significantly independent contributions to NR, even when other factors were included in the regression models. Nature education could not replace the role of actual contact with nature. This study implies that an urbanized living environment will not necessarily reduce the level of NR of future generations. Rather than simply increasing the quantity of natural components in urban areas, it is more important to support children’s interactive behaviors with nature.