Landscape and Urban Planning最新文献

As human populations grow and anthropogenic change increases, costly wildland fires increasingly affect rural, public–private interface landscapes. Climate change, a history of fire suppression, and biological invasions are increasing fire risk in systems worldwide. Fires that ignite in one jurisdiction can spread across ownership boundaries, with the result that landscape-scale fire management and planning requires understanding differential fire response and management across jurisdictions. To illuminate relationships between landowner attitudes and fire management and their experience with past wildfires, we combined geospatial wildfire data from the Monitoring Trends in Burn Severity (MTBS) database and survey response data from 586 private landowners across three national park-centered ecosystems in the American West. We aimed to examine whether landowners’ attitudes toward their land, neighbors, public agencies, and fire itself were related to (a) whether they had experienced fire on their parcels, and (b) the extent and severity of the most recent fire event and the time elapsed since that fire. We found that the degree to which respondents reported that they manage for fire is related to whether a fire had burned on their parcels during their land tenure or, if prior to their tenure, within two years of their acquisition of the land. For those respondents that had thus experienced fire, their level of concern about wildfire, interactions with neighbors and public agencies, and perception that their land contributed to a broader economic or natural system were all related to the time that had elapsed since the fire. Furthermore, total burned area and the percent of the burn that was high severity interacted with time since fire to predict respondents’ attitudes and perceptions. Our findings illustrate the importance of personal past experiences in shaping private land managers’ relationships and viewpoints, as well as the likelihood that they invest in current fire management.

Developing a model to evaluate urban streetscapes based on subjective perceptions is important for quantitative understanding. However, previous studies have only considered limited types of subjective perceptions, neglecting the relationships between them. Further, accurately measuring subjective perception with low computational costs for large-scale urban regions at high spatial resolutions has been difficult. We present a deep-learning-based multilabel classification model that can measure 22 subjective perceptions scores from street-view images. This model uses the results of a web questionnaire survey encompassing 22 subjective perceptions, with 8.8 million responses. Our model demonstrates high accuracy (0.80–0.91) in measuring subjective perception scores from street-view images and achieves low computational cost by training on 22 subjective perception relationships. The 22 subjective perceptions were analyzed using PCA and k-means analysis. By categorizing the 22 subjective perceptions into a two-dimensional space visualized and grouped into distinct groups—positive, negative, calm, and lively—we unearthed vital insights into the intricate nuances of human perception. In addition, the study used semantic segmentation to extract landscape elements from street-view images and applied ℓ1-regularized sparse modeling to identify the landscape elements structurally correlating with each subjective perception class. The analysis revealed that only seven out of nineteen landscape elements significantly correlated with subjective impressions, and these effects varied by class. Notably, sky coverage positively influences positive subjective perceptions, such as attractiveness and calmness, but negatively affects lively impressions. The proposed model can be used to map the overall image of a city and identify landscape design issues in community development design.

Spatial equity in urban park recreational services can significantly contribute to sustainable urban planning. However, there are shortcomings in research comparing the spatial equity of different categories of parks and urban parks overall from the perspective of recreational opportunities and recreational environment quality available to residents across various neighborhoods. In this paper, emphasizing park access within a 10-minute walk, we proposed an evaluation system at the neighborhood level for regional parks, community parks, and urban parks overall (regional and community parks combined) from this under-researched perspective. Taking Singapore as a case study, the feasibility of this evaluation system has been verified. We applied Lorenz curve, Gini coefficient, locational entropy, and spatial autocorrelation analysis to compare the differences of horizontal spatial equity and spatial distribution patterns of different categories of parks and urban parks overall from the perspective of recreational opportunities and recreational environment quality. Results showed that the horizontal spatial inequity of recreational opportunities is higher than that of recreational environment quality with respect to regional parks, community parks, and urban parks overall. Compared with regional parks, community parks have a greater effect on improving the horizontal spatial equity of recreational opportunities and recreational environment quality of urban parks overall. Park recreational opportunities and recreational environment quality available to residents in each neighborhood have significant spatial accumulation patterns. The evaluation system and its application enable a more comprehensive assessment of the spatial distribution of neighborhood-level park recreational opportunities and recreational environment quality.

Cities are shown to provide favourable conditions for western honeybees (Apis mellifera) by protecting them from agricultural pesticides and offering a greater diversity of flora. Nevertheless, while current research primarily focuses on the causes of pollinator – and particularly honeybee – decline, including pesticide exposure, climate change, and habitat fragmentation, little attention is dedicated to urban apiculture and factors associated with the survival of honeybees within cities. Here, we analyse data from 3,697 honeybee hives in Montreal and Toronto to assess the effect of urban and environmental factors on hive survival. We find ground-level ozone concentrations, the height at which hives are located, and the number of surrounding hives to be negatively associated with hive survival, which may point towards an issue of hive saturation. Conversely, vegetation density and the COVID-19 pandemic are positively associated with the likelihood of hive survival, emphasizing the effect of urban air pollution. These findings highlight the need for urban planners to consider neighborhood-scale environmental factors to identify potential venues for enhancing honeybee survival within cities beyond existing urban beekeeping initiatives.

Visibility analyses are one of the fundamental geospatial processing tasks applied in various fields. Recent technological advancements have accelerated viewshed calculations and improved their accuracy thanks to the growing availability of high-resolution spatial data. However, limitations of standard GIS tools, primarily related to the inability to perform analyses in a fully three-dimensional environment and the restriction to only point-based object analyses, have hindered the development of visibility analyses methods that accurately replicate human perspectives. This article presents a novel approach that combines GIS with 3D graphic software and uses high resolution LIDAR data. The presented method not only addresses the limitations of traditional GIS methods but also opens up new possibilities for comprehensive 3D visibility analyses that can better represent real-world scenarios. The proposed methodology, which ensures compatibility of the results with GIS for further spatial analysis, has the potential to enhance decision-making processes in fields such as urban planning, landscape management and protection, environmental impact assessment, infrastructure planning and development. By presenting a case study involving a photovoltaic farm, this article demonstrates the practical applicability and benefits of the proposed method in real-world scenarios.

Participatory modeling is a collaborative approach to formalize shared representations of a problem and, through the joint modeling process, design, and test solutions. This approach is particularly well-suited to address complex socio-environmental problems like climate change and its implications on equitable and sustainable resource management and landscape planning. Despite its potential to inform landscape and environmental planning and policy, participatory modeling has yet to become a mainstream practice in our field. The reasons are several. First, it is hard to standardize the approach, as it must be heavily tailored to the characteristics and context of each planning problem, including the stakeholders engaged in the process. It is also onerous, requiring long-term commitment and a broad range of skills that can only be attained through extensive training and collaboration. These and other barriers are currently being addressed with a resurgence of knowledge co-production and ethical participation in scholarship, in practice, and in funding agendas. While most of the participatory modeling scholarship has focused on modeling tools and engagement techniques, multiple other dimensions must be recognized and articulated for impactful planning support. Grounding this perspective on a more fully integrated picture of participatory modeling, I identify some of these gaps and suggest an interdisciplinary research agenda to further evolve and scale up this practice for landscape and environmental planning and policy. The agenda highlights aspects of interface design and model biases, value elicitation and inclusion, management of diversity and innovation through facilitation, and the potential of novel computer-assisted assessment methodologies.

As the number of highly destructive wildfires grows, it is increasingly important to understand the long-term changes that occur to fire-affected places. Integrating approaches from social and biophysical science, we document two forms of neighborhood change following the 2018 Camp Fire in the United States, examining the more than 17,000 residential structures within the burn footprint. We found that mobile or motor homes, lower-value residences, and absentee owner residences had a significantly higher probability of being destroyed, providing evidence that housing stock filtering facilitated socially stratified patterns of physical damage. While the relationship between building value and destruction probability could be explained by measures of building density and distance to nearby roads, building type remained an independent predictor of structure loss that we could not fully explain by adding environmental covariates to our models. Using a geospatial machine learning technique, we then identified buildings that had been reconstructed within the burn footprint 20 months after the fire. We found that reconstructed buildings were more likely to have been owner-occupied prior to the fire and had higher average pre-fire property value, suggesting an emerging pattern of cost-burden gentrification. Our findings illustrate the importance of examining the built environment as a driver of socially uneven disaster impacts. Wildfire mitigation strategies are needed for mobile and motor home residents, renters, low-income residents, and dense neighborhoods.

Green space may be an important physical activity facilitator for children and adolescents. However, to date, most studies focused on urban green space, and few studies investigated associations between green space and physical activity across urban and rural areas, which was the goal of this study. Data were obtained from a German cohort study, including 1,211 youth aged 6–17 years. Residential green space was assessed within a 1000 m street-network buffer using land cover and land use data and divided into quartiles, urbanicity using the European Urbanization Degree, and moderate-to-vigorous physical activity (MVPA) using accelerometers. Associations were investigated via linear regression analysis stratified by urbanicity degree, controlling for relevant confounders. We found that in rural areas, compared to youth in the bottom green quartile, those within the middle (2nd) and upper (3rd) green quartiles engaged in less MVPA. This relationship was not observed for youth in towns and cities. Interactions occurred between green space and socio-demographic characteristics for children and adolescents in cities: Compared to the bottom green quartile, boys or younger children within the middle green quartile engaged in more MVPA. However, socially disadvantaged children and adolescents in cities engaged in less MVPA in the upper compared to the bottom green quartile. Our results show that associations between green space and MVPA do not only differ between urban and rural areas but also among youth sub-populations. These findings are important to consider for planning policies to create inclusive active living environments across urban and rural areas.

The role of nature in enhancing urban well-being is well-established, but perceived naturalness may not always align with scientific definitions. Our study aimed to investigate whether areas selected for nature-related activities demonstrate increased biodiversity, offer diverse experiences, and integrate both social and ecological perspectives. We aimed to bridge the gap between perceived naturalness and objective ecological richness. Integrating social and environmental parameters, we considered both objective indicators, such as the presence of rare species, and subjective perspectives. Extensive geotagged surveys among 401 working-age Warsaw residents, coupled with field analyses, and biodiversity data collected for the scale of the whole city, allowed to juxtapose human perception with tangible ecological indicators. Our results revealed that only 14% of the locations identified by respondents as natural were associated with high biological diversity. In contrast, over 30% were in areas with low biological diversity, lacking rare species. Factors like presence of natural and semi-natural vegetation types, distance from buildings, population density, presence of water, noise, and extreme temperatures were found to be significant. We distinguished four types of natural areas: close to home, open grassland, high naturalness, and forested, reflecting different preferences and alternative choices when high-quality natural areas are not nearby. Most notably, urban parks emerged as key locations for nature contact, even though objective measures of biodiversity were often low. This underscores the need for a comprehensive understanding of how urban residents interact with and value natural spaces, bridging the gap between subjective experiences and objective ecological richness within the city's green areas. Our study highlights the complex interplay between the physical properties of urban green spaces, individual perceptions, and the ecological aesthetics influencing these interactions. In particular, the concept of perceived naturalness emerges as a critical factor, often contrasting with objective, quantifiable naturalness, and necessitating a nuanced approach in urban planning and public health contexts to cater to diverse needs and preferences of city dwellers.

This study uses a quasi-experimental design to evaluate the impacts of the major wildfires in California from 2016 to 2021 on property value at the neighborhood level, as defined by Census tracts. I construct a 12-year (2010–2021) panel data set and run spatial panel models with random effects to compare changes in home values between neighborhoods affected by wildfires and control neighborhoods identified through propensity score matching. The analysis shows that the overall impact of wildfires on home values in fire-touched neighborhoods is not statistically significant. When considering the proportion of land burned by wildfires in a neighborhood, a statistically significant impact emerges, with home values declining by 0.014 % for every 10-percentage point increase in the proportion of land burned. Nonetheless, the impact of wildfires on home values in nearby neighborhoods within five miles of wildfire perimeters is statistically significant. On average, major wildfires cause a 2.2 % price drop in nearby neighborhoods. The price drop in nearby neighborhoods is positively associated with proximity to wildfires, fire frequency, and fire scale. With the relatively modest impact of wildfires on property values, relying on market-based approaches may not be effective in curbing the future growth in fire-prone and amenity-rich communities.