Urban Vegetation Research Articles

A comprehensive review of urban vegetation as a Nature-based Solution for sustainable management of particulate matter in ambient air.

Air pollution is one of the most pressing environmental threats worldwide, resulting in several health issues such as cardiovascular and respiratory disorders, as well as premature mortality. The harmful effects of air pollution are particularly concerning in urban areas, where mismanaged anthropogenic activities, such as growth in the global population, increase in the number of vehicles, and industrial activities, have led to an increase in the concentration of pollutants in the ambient air. Among air pollutants, particulate matter is responsible for most adverse impacts. Several techniques have been implemented to reduce particulate matter concentrations in the ambient air. However, despite all the threats and awareness, efforts to improve air quality remain inadequate. In recent years, urban vegetation has emerged as an efficient Nature-based Solution for managing environmental air pollution due to its ability to filter air, thereby reducing the atmospheric concentrations of particulate matter. This review characterizes the various mitigation mechanisms for particulate matter by urban vegetation (deposition, dispersion, and modification) and identifies key areas for further improvements within each mechanism. Through a systematic assessment of existing literature, this review also highlights the existing gaps in the present literature that need to be addressed to maximize the utility of urban vegetation in reducing particulate matter levels. In conclusion, the review emphasizes the urgent need for proper air pollution management through urban vegetation by integrating different fields, multiple stakeholders, and policymakers to support better implementation.

Public attitudes to urban wild deer (Cervus nippon) and management policies: A case study of Kyoto City, Japan

The expansion of urban areas has resulted in the fragmentation and reduction of natural habitats. This leads to a fundamental reconfiguration of interactions between humans and wildlife, with profound ecological, social, and policy implications. However there is a research gap in understanding public perceptions of urban wildlife and their management. This study pursues three objectives: (1) to explore the primary types of conflicts between the public and urban wildlife, focusing on Sika deer (Cervus nippon) as an example; (2) to examine public attitudes towards urban deer; and (3) to investigate differences in public acceptance of hunting and fencing management policies. A questionnaire survey was conducted in the urban area of Kyoto City, Japan in September 2022 (n = 759). The survey addressed issues related to deer behavior in the city, public perceptions of urban deer, and feedback on management policies We employed statistical descriptive analysis to study the main ways in which people interact with urban deer. Subsequently, we examined the urban deer image from the public perspective and public perceptions of urban deer. Additionally, mining analysis was conducted on open-ended responses, and public demands were explored in conjunction with feedback on current management schemes in Kyoto City The results indicate that the main type of human-urban deer conflict has an impact on damaging urban vegetation. Public attitudes towards urban deer and other wildlife (besides deer) show significant differences but tend towards negative attitudes. We found a positive inclination towards the efficacy of fencing as a viable solution concurrently revealing a low-approving sentiment regarding hunting policies. These findings bear implications for the development and enhancement of sustainable management strategies aimed at mitigating the complex challenges posed by the swift urbanisation and evolution of urban ecosystems.

Urban Above-Ground Biomass Estimation Using GEDI Laser Data and Optical Remote Sensing Images

Accurate estimating of above-ground biomass (AGB) of vegetation in urbanized areas is essential for urban ecosystem services. NASA’s Global Ecosystem Dynamics Investigation (GEDI) mission can obtain precise terrestrial vegetation structure, which is very useful for AGB estimation in large forested areas. However, the spatial heterogeneity and sparse distribution of vegetation in urban areas lead to great uncertainty in AGB estimation. This study proposes a method for estimating vegetation heights by fusing GEDI laser observations with features extracted from optical images. GEDI is utilized to extract the accurate vegetation canopy height, and the optical images are used to compensate for the spatial incoherence of GEDI. The correlation between the discrete vegetation heights of GEDI observations and image features is constructed using Random Forest (RF) to obtain the vegetation canopy heights in all vegetated areas, thus estimating the AGB. The results in Xuzhou of China using GEDI observations and image features from Sentinel-2 and Landsat-8 satellites indicate that: (1) The method of combining GEDI laser observation data with optical images is effective in estimating AGB, and its estimation accuracy (R2 = 0.58) is higher than that of using only optical images (R2 = 0.45). (2) The total AGB in the shorter vegetation region is higher than the other two in the broadleaf forest and the coniferous forest, but the AGB per unit area is the lowest in the shorter vegetation area at 33.60 Mg/ha, and it is the highest in the coniferous forest at 46.60 Mg/ha. And the highest average AGB occurs in October–December at 59.55 Mg/ha in Xuzhou. (3) The near-infrared band has a greater influence on inverted AGB, followed by textural features. Although more precise information about vegetation should be considered, this paper provides a new method for the AGB estimation and also a way for the evaluation and utilization of urban vegetation space.

Impact of Urban Forest and Park on Air Quality and the Microclimate in Jinan, Northern China

Though the impact of urban vegetation on air quality and the microclimate has attracted increasing attention, there have been few studies quantitatively assessing this impact in North China, where air pollution is severe. In this study, we investigated the impact of urban forests and urban parks on air quality and the microclimate in Jinan, northern China. Six sites were chosen to represent urban forest, urban park, and downtown areas, respectively. The results indicate that urban forest can effectively reduce PM2.5 and ozone (O3) concentrations in the warm season, when temperatures are higher and plants are lush. The PM2.5 and O3 concentrations in the urban forest areas were 6.3–6.5 μg m−3 and 21–23 μg m−3 lower than those in downtown areas during the period of 10:00–15:00. In contrast, urban park areas can reduce PM2.5 concentrations but have little impact on gaseous pollutants such as nitrogen dioxide and O3. Furthermore, both urban forest and urban park areas reduced temperatures, by approximately 4.1–6.8 °C and 1.36 °C, respectively, and increased relative humidity, by about 13.4–12.9% and 0.9%, promoting a more comfortable thermal environment for residents. Therefore, this study highlights the crucial role of urban vegetation in improving air quality and creating a comfortable environment for residents.

Thermal, water, and land cover factors led to contrasting urban and rural vegetation resilience to extreme hot months.

With continuing global warming and urbanization, it is increasingly important to understand the resilience of urban vegetation to extreme high temperatures, but few studies have examined urban vegetation at large scale or both concurrent and delayed responses. In this study, we performed an urban-rural comparison using the Enhanced Vegetation Index and months that exceed the historical 90th percentile in mean temperature (referred to as "hot months") across 85 major cities in the contiguous United States. We found that hot months initially enhanced vegetation greenness but could cause a decline afterwards, especially for persistent (≥4 months) and intense (≥+2 °C) episodes in summer. The urban responses were more positive than rural in the western United States or in winter, but more negative during spring-autumn in the eastern United States. The east-west difference can be attributed to the higher optimal growth temperatures and lower water stress levels of the western urban vegetation than the rural. The urban responses also had smaller magnitudes than the rural responses, especially in deciduous forest biomes, and least in evergreen forest biomes. Within each biome, analysis at 1 km pixel level showed that impervious fraction and vegetation cover, local urban heat island intensity, and water stress were the key drivers of urban-rural differences. These findings advance our understanding of how prolonged exposure to warm extremes, particularly within urban environments, affects vegetation greenness and vitality. Urban planners and ecosystem managers should prioritize the long and intense events and the key drivers in fostering urban vegetation resilience to heat waves.

Sentinel-2 Perspective: Land Use and Land Cover Dynamics in East and West Karbi Anglong

This study delves into the dynamics of land use and land cover (LULC) in East and West Karbi Anglong using Sentinel-2 satellite imagery. In response to escalating environmental changes, remote sensing technologies, particularly Sentinel-2, offer crucial insights for sustainable land management. Through an analysis of LULC patterns, the study aims to inform evidence-based decisions for environmental conservation and resource management in the region. The present study highlights the utility of remote sensing in LULC assessments and acknowledges the necessity for customized approaches in regions with distinctive features such as Karbi Anglong. Methodologically, temporally stratified Sentinel-2 datasets were utilized, with meticulous pre-processing and accuracy assessments ensuring reliability. Results indicate notable shifts in LULC classes, including urban expansion and vegetation decline. Despite limitations, such as potential inaccuracies in data processing, the study emphasizes the importance of monitoring environmental changes and advocating for sustainable land management strategies.

Microenvironment created by Plantago lagopus L. may affect cover and diversity of coexisting species in urban vegetation

Some plant species may exhibit new microenvironments which lead to significant changes in the cover and diversity of the coexisting species. In this investigation, we evaluated the effects of Plantago lagopus L. on the cover and diversity of the associated plant species in the urban vegetation. A total of 70 plots were conducted in sites with- and without this species in urban gardens. Cover of the associated species and different diversity indices including species richness, Shannon-Wiener, evenness, and Simpson indices were measured. The allelopathic potential of P. lagopus was verified using its rhizosphere and non-rhizosphere soils on two target species existing within the same environment. Some soil criteria and seed sizes of the associated species were also determined. Most of the coexisting weeds were reduced in terms of their cover in plots with Plantago. The reduction of plant diversity depended on its cover. Besides, the aboveground biomass was reduced in sites comprising Plantago. The degree of inhibition was not related to the seed size of the species found. This species reduced the incident solar radiation and the local temperature over the soil surface. The locations exhibiting such species contained lower contents of available potassium and zinc. Rhizosphere soil of P. lagopus substantially inhibited germination and growth of Amaranthus viridis, but it didn't do so for Medicago lupulina. Reduction in cover, diversity, and biomass of the urban weeds associated with P. lagopus may be related to the reduction of received solar radiation, soil temperature, and nutrient availability. The allelopathic potential of P. lagopus may have a partial role in this reduction. These results suggest that P. lagopus may create a microenvironment of new conditions not favorable for most of the coexisting species.

Spatiotemporal Variations of Urban Spatial Dispersion and Its Vegetation Degradation in Joglosemar’s Urban Growth Corridors, Indonesia

ABSTRACT Indonesia has several expanding metropolitan regions, such as the Joglosemar Urban Region. The Joglosemar Urban Region includes three major urban growth centres – the Semarang Metropolitan Region (SMR), the Surakarta Urban Region (SUR), and the Yogyakarta Urban Region (YUR) with three urban growth corridors connecting them. Urban growth corridors cover areas crossed by the main road network linking urban growth centres. Rapid and uncontrolled urban development can endanger environmental sustainability along the corridors. This study compares the three urban growth corridors within the Joglosemar Urban Region – the SMR-SUR, the SUR-YUR, and the SMR-YUR. It examines the spatiotemporal variations of urban compactness and urban vegetation degradation. This study uses Landsat Satellite Imagery from 2001, 2008, 2015, and 2022. The index-based calculation was employed to obtain the built-up area change, urban compactness, and vegetation degradation. The most dispersed urban areas observed had the greatest vegetation degradation. Among the three urban growth corridors, the SMR-SUR corridor recorded the highest vegetation degradation of −0.21, with an increase in compactness index of 0.02. Vegetation greenness is significantly reduced along urban expansion corridors with high spatial dispersion. Our assessment offers new insight to inform the government in enacting policy changes to control urban growth and its sustainability.

Multi-Sensor Classification Framework of Urban Vegetation for Improving Ecological Services Management

Recent climatic changes have profoundly impacted the urban microclimate, exposing city dwellers to harsh living conditions. One effective approach to mitigating these events involves incorporating more green infrastructure into the cityscape. The ecological services provided by urban vegetation play a crucial role in enhancing the sustainability and livability of cities. However, monitoring urban vegetation and accurately estimating its status pose challenges due to the heterogeneous nature of the urban environment. In response to this, the current study proposes utilizing a remote sensing-based classification framework to enhance data availability, thereby improving practices related to urban vegetation management. The aim of the current research is to explore the spatial pattern of vegetation and enhance the classification of tree species within diverse and complex urban environments. This study combines various remote sensing observations to enhance classification capabilities. High-resolution colored rectified aerial photographs, LiDAR-derived products, and hyperspectral data are merged and analyzed using advanced classifier methods, specifically partial least squares-discriminant analysis (PLS-DA) and object-based image analysis (OBIA). The OBIA method demonstrates an impressive overall accuracy of 95.30%, while the PLS-DA model excels with a remarkable overall accuracy of 100%. The findings validate the efficacy of incorporating OBIA, aerial photographs, LiDAR, and hyperspectral data in improving tree species classification and mapping within the context of PLS-DA. This classification framework holds significant potential for enhancing management practices and tools, thereby optimizing the ecological services provided by urban vegetation and fostering the development of sustainable cities.

Spatial patterns and driving forces of urban vegetation greenness in China: A case study comprising 289 cities

Urban vegetation in China has changed substantially in recent decades due to rapid urbanization and dramatic climate change. Nevertheless, the spatial differentiation of greenness among major cities of China and its evolution process and drivers are still poorly understood. This study examined the spatial patterns of vegetation greenness across 289 cities in China in 2000, 2005, 2010, 2015, and 2018 by using spatial autocorrelation analysis on the Normalized Difference Vegetation Index (NDVI); then, the influencing factors were analyzed by using the optimal parameters-based geographical detector (OPGD) model and 18 natural and anthropogenic indicators. The findings demonstrated a noticeable rise in the overall greenness of the selected cities during 2000–2018. The cities in northwest China and east China exhibited the rapidest and slowest greening, respectively, among the six sub-regions. A significant positive spatial correlation was detected between the greenness of the 289 cities in different periods, but the correlation strength weakened over time. The hot and very hot spots in southern and eastern China gradually shifted to the southwest. While the spatial pattern of urban greenness in China is primarily influenced by wind speed (WS) and precipitation (PRE), the interaction between PRE and gross domestic product (GDP) has the highest explanatory power. The explanatory power of most natural factors decreased and, conversely, the influence of anthropogenic factors generally increased. These findings emphasize the variations in the influence strength of multiple factors on urban greenness pattern, which should be taken into account to understand and adapt to the changing urban ecosystem.

Analysis of heavy metals and pathogen levels in vegetables cultivated using selected water bodies in urban areas of the Greater Accra Metropolis of Ghana

Open-surfaced water sources have been used to irrigate vegetable farms in cities. Open-surface water often contains unmonitored concentrations of health-threatening contaminants that pose health risks, especially when used to produce vegetables for human consumption. However, information on levels of heavy metals and faecal coliform bacteria in such vegetables in selected sites, especially in Greater Accra Metropolitan Area (GAMA) of Ghana is rare. This study examines the levels of heavy metals and faecal coliform in two vegetables-lettuce and bell pepper - that were cultivated using open-surface wastewater from drains and constructed reservoirs at different locations of the GAMA. Using concurrent mixed methods, questionnaires were administered to 67 vegetable farmers, followed by the collection of vegetable samples from three urban farm sites, Haatso and Dzorwulu and Weija irrigation scheme site (WISS) for laboratory analysis. The concentrations of Lead (Pb), Mercury (Hg) and Cadmium (Cd) were determined using atomic absorption spectroscopy after microwave digestion of the vegetables while total faecal coliform was quantified using MacConkey-Endo broth method. The results from all three sites showed that the concentrations of Cd (=0.001 μg/mg) and Pb (=0.005 μg/mg) in lettuce were within the World Health Organization's (WHO) permissible levels. However, the Hg (≥0.309 μg/mg) and faecal coliform (>5 count/100 ml) in the vegetables from all three sites exceeded the WHO permissible limits. Therefore, consumers of vegetables from such urban farms are exposed to health risks associated with Hg and faecal coliforms. There is the need to intensify education on the health risks of consuming vegetables produced from open-surface water sources from the observed sites. The enforcement of existing phytosanitary standards to enhance food safety and the quality of urban vegetables is also recommended.

Enhanced observations from an optimized soil-canopy-photosynthesis and energy flux model revealed evapotranspiration-shading cooling dynamics of urban vegetation during extreme heat

Previousstudies on the cooling of urban vegetation mainly focused on its transpiration or shading effect separately, neglecting to explore the combined evapotranspiration-shading cooling. Further, accurate quantification of evapotranspiration-shading cooling remains challenging due to heterogeneity of urban landscapes, which limits understanding of its high-resolution spatiotemporal patterns. Here, we integrate high-precision remote sensing data and the Soil-Canopy-Observations of Photosynthesis and Energy Fluxes (SCOPE) model to propose an optimized quantitative approach. The approach was used to investigate changes in evapotranspiration-shade cooling during extreme heat.Taking Shanghai metropolitan as case, the results show: (1) The cooling capacity of urban vegetation in nighttime (18:00–6:00) is enhanced during extreme heat, which is attributed to accumulated effect of shading and enhanced evapotranspiration due to elevated vapor-pressure deficit. (2) In densely built-up areas with limited vegetation, there is a significant lack of thermal regulation, especially in the early morning (7:00) and late evening (17:00), thus exacerbating thermal stress. (3) At midday (11:00–13:00) there was a slight decrease in evaporative cooling, probably caused by the behaviour of the stomatal closure at high temperatures. Concurrently, high radiation causes the shading effect of vegetation to become more prominent, amplifying the cooling contrast between areas with dense and sparse vegetation cover. Moreover, the study also highlights that grassland with >50% cover can provide cooling effects similar to that of forest land. Overall, our study not only enhances the understanding of urban vegetation's cooling effects but also underscores the importance of strategic urban vegetation planning in mitigating urban heat, particularly under the escalating frequency and intensity of heat waves.

Правовой режим городской растительности в России и зарубежных странах

The article notes that the legal regime of urban vegetation has been and remains the subject of debate for many years by both legal scholars and practitioners. The need to establish uniform rules for the legal protection of green spaces on the lands of populated areas at the federal level periodically leads to the emergence of new draft federal laws. However, despite all the efforts made, such rules have not yet been established. The authors of the article set the task of analyzing the existing legislation of Russia and the constituent entities of the Russian Federation, as well as the legislation of a number of foreign countries in the field of protection of urban vegetation in order to determine approaches to establishing a unified regime for such plantings.

Enhancing Urban Above-Ground Vegetation Carbon Density Mapping: An Integrated Approach Incorporating De-Shadowing, Spectral Unmixing, and Machine Learning

Accurately mapping urban above-ground vegetation carbon density presents challenges due to fragmented landscapes, mixed pixels, and shadows induced by buildings and mountains. To address these issues, a novel methodological framework is introduced, utilizing a linear spectral unmixing analysis (LSUA) for shadow removal and vegetation information extraction from mixed pixels. Parametric and nonparametric models, incorporating LSUA-derived vegetation fraction, are compared, including linear stepwise regression, logistic model-based stepwise regression, k-Nearest Neighbors, Decision Trees, and Random Forests. Applied in Shenzhen, China, the framework integrates Landsat 8, Pleiades 1A & 1B, DEM, and field measurements. Among the key findings, the shadow removal algorithm is effective in mountainous areas, while LSUA-enhanced models improve urban vegetation carbon density mapping, albeit with marginal gains. Integrating kNN and RF with LSUA reduces errors, and Decision Trees, especially when integrated with LSUA, outperform other models. This study underscores the potential of the proposed framework, particularly the integration of Decision Trees with LSUA, for advancing the accuracy of urban vegetation carbon density mapping.

Urbanization reduces Orthoptera diversity and changes community structure towards mobile species

Abstract Urban land use is regarded as one major driver for insect declines worldwide. We investigated how Orthoptera diversity and traits respond to the urban matrix and local vegetation parameters. Orthoptera were collected using a combined method of box‐quadrat sampling and pitfall trapping. We sampled 42 dry grasslands in Berlin, Germany, along gradients of urbanization (measured as proportion of sealed surface in the surrounding of the sites) and connectivity. We further included patch size and local vegetation parameters (plant richness, total vegetation cover, herb cover, neophyte cover) in our models. Urbanization was the main driver explaining Orthoptera species richness, Simpson diversity and functional diversity (functional dispersion), which all decreased with increasing proportion of sealed surface in the surrounding. Urbanization also influenced the Orthoptera species composition. Thereby, functional trait analyses revealed that the urban matrix acted as a habitat filter sorting towards mobile species. However, responses of the most common species showed that the effects of the urban matrix and vegetation parameters were species specific. Our results demonstrate predominantly negative effects of urbanization on Orthoptera diversity. Nevertheless, urban environments can provide important habitats, in particular for mobile species. Even small and isolated patches of dry grasslands can contribute to Orthoptera conservation in cities.

Vegetation structure and relative humidity drive the diurnal foraging activity of Malaysian giant ant workers in urban fragmented forests

Abstract The impacts of urban forest fragmentation on tropical ant foraging activity are poorly understood. The Malaysian giant ant (Dinomyrmex gigas) is among the largest ant species worldwide. Colonies of this species contribute to important ecosystem processes such as predation and nutrient cycling in the tropical forests of Southeast Asia. Here, we compared the diurnal foraging activity of D. gigas workers in urban‐fragmented and contiguous forests, and investigated how this was shaped by key environmental factors such as vegetation structure and microclimate. Specifically, we sampled ground‐foraging D. gigas workers in four urban/semi‐urban forest patches and two contiguous forests in Peninsular Malaysia across the wet and dry seasons. Surprisingly, we found that some urban forest patches, irrespective of area, supported greater foraging activity of D. gigas workers than contiguous forests. These differences in foraging activity were explained by differences in multiple stand‐level variables between urban forests patches and contiguous forests. Specifically, the abundance of foraging D. gigas workers increased with number of trees with Diamater at breast height (DBH) 5–30 cm, but it decreased with relative humidity, canopy cover, number of palms, number of shrubs and trees with DBH <5 cm. Our study highlights the importance of urban forest patches, microclimate and vegetation structure for driving the diurnal foraging activity of Malaysian giant ant. Small and relatively large forest patches were of comparable importance for the maintenance of biodiversity in urban landscapes. In the absence of landscape connectivity, reforestation is the most feasible option to restore the natural habitat of D. gigas in urban forest patches and mitigate microclimatic edge effects.

Urban Ecohydrology: Accounting for Sub‐Grid Lateral Water and Energy Transfers in a Land Surface Model

AbstractAlthough urbanization fundamentally alters water and energy cycles, contemporary land surface models (LSMs) often do not include key urban vegetation processes that serve to transfer water and energy laterally across heterogeneous urban land types. Urban water/energy transfers occur when rainfall landing on rooftops, sidewalks, and driveways is redirected to lawns or pervious pavement and when transpiration occurs from branches overhanging impervious surfaces with the corresponding root water uptake takes place in nearby portions of yards. We introduce Noah‐MP for Heterogenous Urban Environments (Noah‐MP HUE), which adds sub‐grid water transfers to the widely used Noah‐MP LSM. We examine how sub‐grid water transfers change surface water and energy balances by systematically increasing the amount of simulated water transfer for four scenarios: tree canopy expanding over pavement (Urban Tree Expansion), tree canopy shifting over pavement (Urban Tree Shift), and directing impermeable runoff onto surrounding vegetation (Downspout Disconnection) or into an engineered pavement (Permeable Pavement). Even small percentages of sub‐grid water transfer can reduce runoff and enhance evapotranspiration and deep drainage. Event‐scale runoff reduction depends on storm depth, rainfall intensity, and antecedent soil moisture. Sub‐grid water transfers also tend to enhance (reduce) latent (sensible) heat. Results highlight the importance not only of fine‐scale heterogeneity on larger scale surface processes, but also the importance of urban management practices that enhance lateral water transfers and water storage–so‐called green infrastructure–as they change land surface fluxes and, potentially, atmospheric processes. This work opens a pathway to directly integrate those practices in regional climate simulations.

Urban lawn vegetation structure impact arthropod abundance and cattle egret foraging success

The vegetation in urban green spaces is often managed by means of machines and/or pesticides including herbicides for aesthetics without regard to the potential consequences on arthropods, particularly insect abundance, and the animals, especially birds, that feed on insects and other arthropods. Using the green spaces on the University of Cape Coast campus and cattle egrets (Bubulcus ibis) that feed there as a test case, we investigated the influence of arthropod abundance and vegetation structure on the foraging success of cattle egrets. To achieve this, we measured the foraging efficiency (FE) and capture rate (CR) of cattle egrets, and their correlations with arthropod abundance, vegetation height, vegetation cover, and mode of vegetation clearing during the wet and dry seasons. Foraging cattle egrets were surveyed along seven permanent transects three times for each season. Using sweep nets and pitfall traps, arthropods were sampled at six randomly selected locations within each transect where cattle egrets were recorded. General linear models showed that arthropod abundance did not differ between seasons and was positively correlated with FE but not with CR. Moreover, arthropod abundance was positively related to the number of days since vegetation clearing but not to vegetation height, vegetation cover, or vegetation clearing method. Vegetation height and vegetation cover were negatively correlated with CR but not with FE. Also, CR was significantly higher in machine-cleared areas than in cutlass-cleared areas. Collectively, these findings highlight the influence of vegetation management practices, particularly machine-clearing, on arthropod abundance and its implications for avian foraging success in urban green spaces. The relationship between arthropod abundance and foraging efficiency emphasizes the importance of sustainable vegetation management strategies to support bird populations in urban environments.

Effects of different land-use planning instruments on urban shrub and tree canopy cover in Zurich, Switzerland

Sustainable urban development requires not only dense and land-saving construction, but also a large share of urban vegetation. A planned unit development (PUD) is a land-use planning instrument that is often used to improve urban quality in urban renewal and densification worldwide. In this study, we analyse the influence of PUDs on urban vegetation in the Canton of Zurich, Switzerland, by contrasting them with conventional zoning. We modelled the share of shrub and tree canopy cover per neighbourhood block using generalized linear mixed effect models (GLMM), with the type of planning instrument as the focal predictor amongst other control variables known from the literature to be influential on urban vegetation. Results show that PUDs are associated with significantly less urban vegetation cover than conventional zoning. This is unexpected and raises concerns. Given how important PUDs are as levers for improving urban quality, their observed inability to promote valuable shrub and tree structures leads us to recommend that good landscape planning and long-term management of (existing and new) urban vegetation be included as an additional standard criterion of high priority in the assessment of future PUDs.

High-resolution multi-scaling of outdoor human thermal comfort and its intra-urban variability based on machine learning

Abstract. As the frequency and intensity of heatwaves will continue to increase in the future, accurate and high-resolution mapping and forecasting of human outdoor thermal comfort in urban environments are of great importance. This study presents a machine-learning-based outdoor thermal comfort model with a good trade-off between computational cost, complexity, and accuracy compared to common numerical urban climate models. The machine learning approach is basically an emulation of different numerical urban climate models. The final model consists of four submodels that predict air temperature, relative humidity, wind speed, and mean radiant temperature based on meteorological forcing and geospatial data on building forms, land cover, and vegetation. These variables are then combined into a thermal index (universal thermal climate index – UTCI). All four submodel predictions and the final model output are evaluated using street-level measurements from a dense urban sensor network in Freiburg, Germany. The final model has a mean absolute error of 2.3 K. Based on a city-wide simulation for Freiburg, we demonstrate that the model is fast and versatile enough to simulate multiple years at hourly time steps to predict street-level UTCI at 1 m spatial resolution for an entire city. Simulations indicate that neighbourhood-averaged thermal comfort conditions vary widely between neighbourhoods, even if they are attributed to the same local climate zones, for example, due to differences in age and degree of urban vegetation. Simulations also show contrasting differences in the location of hotspots during the day and at night.