基于三维绿量的太原市绿地热环境效应研究

城市化进程导致热岛效应加剧,三维绿量对城市绿地的热环境效应有显著影响。利用2020年9月太原市Landsat 8遥感影像,结合样地三维绿量实测数据,借助遥感及GIS技术,建立太原市三维绿量反演模型,测算太原市城区三维绿量,分析其绿量分布格局;同时利用针对Landsat 8 TIRS第10波段的单窗算法(TIRS10＿SC)反演太原市地表温度,探讨城市绿地三维绿量对热环境的影响作用。结果表明：(1)太原市北部、西南及东西两山植被覆盖较好,三维绿量高,城市中部硬质半硬质区域三维绿量低,城市公园作为高绿量节点镶嵌于城市中部;在绿地空间结构上,乔木层平均树高对三维绿量的影响较大,二者的关系模型为Y=469.912x+936.466。(2)三维绿量与地表温度呈显著负相关,二者的关系模型为Y=5.828x^-0.029,三维绿量较小时,降温趋势显著,随着三维绿量不断增大,降温趋势渐缓;绿量密度在5～18 m³/m²之间的乔灌草或乔草复层配置能较好地发挥降温效果。(3)三维绿量的空间分布对地表温度有一定影响,绿量密度高、连通性高,具有稳定大面积斑块的区域,其地表温度低,降温效果好;相反,绿量密度低、破碎度高的区域,其地表温度高,降温效果差。     

Impact of urban park’s tree,grass and waterbody on microclimate in hot summer days: A case study of Olympic Park in Beijing,China

Urban heat island (UHI) often cause negative impact and has been linked to heart stroke rate, morality, human comfort, energy consumption and air pollution. Fortunately, urban green spaces have been considered as an effective element to mitigate UHI through their cooling effect. However, further empirical research is necessary in order to efficiently guide the design and planning of urban green space. We observed the impacts of urban park's tree, grass and waterbody on microclimate inside the Olympic park of Beijing during summer days. The results indicated that, on average, the park was 0.48–1.12 °C cooler during the day, as well as increased air humidity 2.39–3.74% and reduced human comfort index 1.02–2.43 to generate more comfortable thermal environment. Urban park's cluster trees with short ground vegetation generated higher cooling effect than single trees, grass and waterbodies; proper irrigation regime enhanced the cooling effect of grasses, even the irrigated grass have similar cooling effect with small waterbody on sunny, windless summer days. Therefore, we advise to increase undergrowth coverage and grass irrigation management in order to take advantage of cooling effect of urban parks.     

Using green infrastructure for urban climate-proofing: An evaluation of heat mitigation measures at the micro-scale

Urban green infrastructure (UGI) has been increasingly promoted as a key measure to mitigate heat stress in cities caused by the urban heat island effect and climate change impacts, including climate variability and extremes. However, comparable information concerning the performance of different UGI types to moderate such impacts is mostly lacking. This creates serious challenges for urban planners who need to decide on the most effective measures while considering spatial and administrative constraints. This study investigates how different types and quantities of UGI, i.e. trees, green roofs, and green facades, affect pedestrian thermal comfort. The study was applied to high-density residential areas under current and future climatic conditions. Climate change will on average increase afternoon Physiological Equivalent Temperature (PET) values by 2.4 K; however, this could be vastly reduced by different UGI scenarios. Planting trees had the strongest impact with an average PET reduction of 13% compared with existing vegetation. Trees shade open spaces and provide evapotranspirative cooling. Another valuable adaptation option is green facades, which have mitigating effects of 5%–10%. In contrast, the effects of green roofs were negligible. Our results indicate that increasing the share of green cover did not directly correspond to the magnitude of the PET reduction. Placing vegetation strategically in heat-exposed areas is more effective than just aiming at a high percentage of green cover. We conclude that our extensive comparative analysis provides empirical evidence to support UGI on the micro-scale and assists planners and decision-makers to effectively select and prioritise concrete measures to adapt to climate change.     

Effects of vegetation,urban density,building height,and atmospheric conditions on local temperatures and thermal comfort

This paper shows the effects of several variables, which co-cause the Urban Heat Island effect on temperature distribution and outdoor thermal comfort (by using the Predicted Mean Vote, PMV) on dense urban environments. The study was conducted by means of a three-dimensional microclimate model, ENVI-met 3.1, which forecasts the microclimatic changes within urban environments. The effects of building density (% of built area) and canyon effect (building height) on potential temperature, mean radiant temperature, and Predicted Mean Vote distribution are quantified. The influence of several types of green areas (vegetation on the ground and on roofs) on temperature mitigation and on comfort improvements is investigated for different atmospheric conditions and latitudes in a Mediterranean climate. The research quantifies the effects of the variables investigated on temperature distributions and in determining outdoor comfort conditions. Vegetation on the ground and on roofs mitigates summer temperatures, decreases the indoor cooling load demand, and improves outdoor comfort. The results of the study demonstrate that density and height of buildings in a city area influence potential temperature, mean radiant temperature, and Predicted Mean Vote distribution; for most of the cases examined higher density causes higher temperatures and with taller buildings vegetation has higher cooling effects. Considering the cooling effect of vegetation, a difference can be noticed depending on the amount of green areas and vegetation type. The results of this study show also that vegetation is more effective with higher temperatures and lower relative humidity values in mitigating potential temperatures, mean radiant temperatures, and PMV and in decreasing the cooling load demand.     

Numerical characteristics and spatial distribution of panoramic Street Green View index based on SegNet semantic segmentation in Savannah

Panoramic green view index (PGVI) is an emerging index of urban greenery, which attracts researchers’ attention in recent years. It provides a quantitive method for reflecting real-life feelings about green space in urban areas. The PGVI needs to be calculated from massive datasets, which can be realized by artificial intelligence (AI) techniques. In this work, we used SegNet, an AI semantic segmentation tool, to distinguish urban elements, such as buildings, sky, and people. In total, 6874 panoramic street pictures with an interval of 10 m in the Savannah Historic District were used for the analysis of PGVI and its distribution. Results show that both the PGVI value and its distribution types can reflect the characteristics of regional green space. Good urban greenery can be distributed normally, which also provides a method for greenery classification. The crucial factors influencing PGVI are the trees. Dense low trees with big canopies have a very positive influence. In addition, the grade and width of the road, the parks, and squares along the street also have an impact on PGVI. In Savanah Historic District, the road width of nearly 10 m, and the location near parks and squares, can significantly increase the PGVI of streets.     

Does green space influence assaults? Evidence from Toronto,Canada

Criminal behavior has been traditionally linked to green space. However, studies on the relationship between green space and crime vary in their conclusions and even contradict each other. This variability is primarily attributed to the mixing-up of specific crimes and the less-explored influencing mechanisms. This study considers Toronto and focuses on a specific kind of crime, assault, for exploring whether green space influences the neighborhood assault rate. If so, then how does it affect the assault rate? By considering the neighborhood as the spatial analysis unit, the indicators of green space and its component structure (namely the composition of trees, shrubs, and grass) are included in the regression analysis model used in this study. The dual effect (both positive and negative) of walkability on crime is treated as the moderator in the regression model. Our analysis revealed that high percentages of green space, tree area, and grass area potentially inhibit assault occurrence, while the shrub area percentage has no statistically significant association with the assault rate. When walkability reaches a certain degree (84th or/and 50th percentiles in this study), it can enhance the inhibitory impact of the green space and its component structure (including trees, shrubs, and grass) on the assault rate. Comparatively, this reduction effect is more significant for green space composed of grass. Therefore, we can infer that increasing the percentage of trees and grass, while simultaneously improving walkability, can reduce residents’ risk of being assaulted at the neighborhood level.     

Green infrastructure practices for improvement of urban air quality

Green Infrastructure (GI) practices have shown to be promising in mitigating the air pollution in urban areas of several cities across the world. GI practices such as trees, green roofs and green walls are widely used in United States and Europe to mitigate the air pollution. However, there is yet limited knowledge available in identifying the most suitable GI strategy for an urban area in improving the air quality. Furthermore, it is evident that Australia is still lagging behind in adapting GI to mitigate air pollution, compared with US and Europe. Therefore, this study analyzed the air quality improvement through several GI scenarios consisting of trees, green roofs and green walls considering a case study area in Melbourne, Australia by using the i-Tree Eco software. The results were compared with case studies in different cities across the world. The results showed that the i-Tree Eco software can be successfully applied to an Australian case study area to quantify the air quality improvement benefits of GI. The results were further assessed with several environmental, economic and social indicators to identify the most suitable GI scenarios for the study area. These indicators were quantified using different methods, to assess the effectiveness of different GI scenarios. The results showed that, trees provided the highest air pollution removal capability among the different GI considered for the study area. Combination of different GI such as green roofs and green walls with trees did not provide a significant increment of air quality improvement however, has provided more local benefits such as building energy savings. The results obtained from this study were also beneficial in developing policies related to future GI applications in major cities of Australia for the air quality improvement.     

Impacts of land use and topography on the cooling effect of green areas on surrounding urban areas

Few studies have examined the influence of land use and terrain on the cooling effect of green areas on surrounding urban areas. We investigated the spatial distribution of the cooling effect of green areas on surrounding urban areas in Heiwa Park, Nagoya, central Japan, by applying surface temperature (T_s) information obtained from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) image data. The cooling effect was found to extend in many directions into the urban areas. The spatial distribution of T_s showed that commercial areas interrupted the flow of park cooling, whereas other types of urban areas expanded park cooling more effectively. We hypothesise that this was the result of differences in geometric and thermal properties and anthropogenic heat release between commercial and other areas. The spatial distribution of T_s also reflected the effects of topography on park cooling. The green area at our study site was located on a hill, and the downward slope and valley terrain inside the park increased the cooling effect towards the surrounding urban areas. To improve the thermal environment of urban areas and the comfort levels of residents, effective utilisation of the cooling effect of green areas should be incorporated into urban designs that consider the effects of land use and topography.     

The role of green roofs in mitigating Urban Heat Island effects in the metropolitan area of Adelaide,South Australia

Changing an urban environment and replacing vegetated surfaces with low albedo materials is one of the reasons for increasing temperatures in an urban environment and consequently also one of the key causes of urban heat island effects. In this study, an experimental investigation at the micro-scale and also a numerical simulation at the macro-scale of a typical urban environment in Adelaide were conducted to estimate the potential for mitigating the UHI effect. The results showed that existing low albedo materials such as asphalt, metal roofs and brick pavements contribute to the heat island potential. Also, urban development and a lack of natural vegetation contribute to increased temperatures in cities. The ability of two types of extensive and intensive green roofs to reduce the surrounding micro-climate temperature were monitored. The results showed that they have significant cooling effects in summer time and could behave as an insulation layer to keep buildings warmer in the winter. Furthermore, different scenarios of adding green roofs to the Adelaide urban environment were investigated using the Envi–MET model. The scenario modelling of adding green roofs in a typical urban area in Adelaide, Australia, supported the hypothesis that this can lead to reductions in energy consumption in the Adelaide urban environment. Also an increased use of other water sensitive urban design technologies such as green walls and street trees together with the adoption of high albedo materials is recommended for achieving the optimum efficiency in terms of reducing urban temperatures and mitigating urban heat island effects.     

Wind tunnel study on aerodynamic characteristics of shrubby specimens of three tree species

With the popularization of green roofing systems, their wind resistant performance is becoming more and more important especially in typhoon areas. A prerequisite study was carried out to determine the aerodynamic characteristics of suitable trees to provide basic scientific data. Shrubby specimens of three tree species appropriate for intensive green roofs with different aerodynamic forms were tested through a boundary layer wind tunnel experiment, including one deciduous tree, one coniferous tree and one broadleaf evergreen tree. Drags and overturning moments under different wind speeds were measured; wind-speed-specific frontal areas and tip displacements were recorded. After initial tests, trees were pruned to investigate the effect of crown porosity, and the effects of view angle and turbulence intensity were also considered. The results showed that even considering frontal area reduction due to increasing wind speeds, drag coefficients decreased with increase in wind speed for deciduous and coniferous trees. Drag coefficient characteristics for different trees agreed well with those obtained from previous researches. The effect of crown porosity varied among tree species, but view angle and turbulence intensity did not significantly affect it.     

Evaluating the potential for urban heat-island mitigation by greening parking lots

Artificial urban land uses such as commercial and residential buildings, roads, and parking lots covered by impervious surfaces can contribute to the formation of urban heat islands (UHIs), whereas vegetation such as trees, grass, and shrubs can mitigate UHIs. Considering the increasing area of parking lots with little vegetation cover in Nagoya, Japan, this study evaluated the potential for UHI mitigation of greening parking lots in Nagoya. The relationships between land surface temperature (LST) and land use/land cover (LULC) in different seasons were analyzed using multivariate linear regression models. Potential UHI mitigation was then simulated for two scenarios: (1) grass is planted on the surface of each parking lot with coverage from 10 to 100% at an interval of 10% and (2) parking lots are covered by 30% trees and 70% grass. The results show that different LULC types play different roles in different seasons and times. On average, both scenarios slightly reduced the LST for the whole study area in spring or summer. However, for an individual parking lot, the maximum LST decrease was 7.26 °C in summer. This research can help us understand the roles of vegetation cover and provide practical guidelines for planning parking lots to mitigate UHIs.     

城镇密集区生态绿地中近自然植物群落的应用

以生态学的自然植被和群落演替的基本理论为依据的城市"近自然"植物群落理论在城镇密集区的绿地建设中越来越重要。在成都市植物多样性调查和"近自然植物群落"理论为基础的前提下,以青龙场片区为例,提出适合成都市城镇密集区的近自然植物群落的营建模式,对城市生态绿地系统结构的优化和组合有一定的理论和实际意义。     

Assessing the impacts of urbanization-associated green space on urban land surface temperature: A case study of Dalian,China

Taking Dalian City as the study area, the spatial distribution of urban green space and land surface temperature (LST), as well as their evolution in 1999, 2007 and 2013, were obtained through remote sensing (RS) interpretation and inversion. Landsat ETM and SPOT data were used for this purpose. By combining the temperature and vegetation index models (TVX), the effects of urban green space reduction on the thermal environment during city development were evaluated. The results show the following. (1) During 1999–2013, 88.1 km² of urban green space was converted to other land uses, accounting for a 29.4% reduction in urban green space in the study area. (2) During the study period, the LST in this area increased by +8.455 K. The evolution of the regional thermal landscape can be characterized by increases in the LST, greater complexity of the thermal landscape structure, increase and aggregation of high-temperature areas, and reduction and fragmentation of low-temperature areas. (3) During the process of urbanization, urban green space with low land-surface temperature was converted to other land use types with high land-surface temperature. When development occurred at the price of urban green space, negative effects on the regional thermal environment were observed.     

Visual structure of landscapes seen from built environment

Vegetation in cities keeps climate warming down and improves the health of people and ecosystems while making for a pleasant urban setting. Contemporary urban planning promotes sustainable green cities. Green and blue infrastructures, which help maintain an eco-friendly environment, are the primary instruments of this movement. This paper attempts to show the relative weight of plant life (trees, grass, orchards, etc.) seen from buildings in different urban settings (local urban patterns of high or low density of buildings). Landscapes open to view are identified by combining a digital elevation model and an 11-class land-use layer (including buildings, facilities, grey infrastructures, green and blue surfaces) in a computational tool that calculates viewsheds. The results show that vegetation is very much present in urban landscapes. In high-density built areas of city centres, the landscape is varied although not open and is dominated by trees, low-rise residential buildings and grass. Grey infrastructures and bushes are also very common. In low-density built areas the rank order of objects in view is similar but the landscape is more panoramic.     

GeoAI to implement an individual tree inventory: Framework and application of heat mitigation

Individual Tree Inventory (ITI) is critical for urban planning, including urban heat mitigation. However, an ITI is usually incomplete and costly due to data collection challenges in the dynamic urban landscape. This research developed a methodical GeoAI framework to build a comprehensive ITI and quantify tree species cooling on rising urban heat.The object detection Faster R-CNN model with Inception ResNet V2 was implemented to detect individual trees canopy and seven tree species (Callery pear, Chinese elm, English elm, Mugga ironbark, Plane tree, Spotted gum and White cedar). The land surface temperature (LST) was derived from Landsat 8 surface reflectance imagery. Two models for ITI were further developed for spatial and statistical analysis. Firstly, an ‘Individual tree-based model’ stores the attributes of tree species and its vertical configuration obtained from LiDAR, along with its tree canopy area and surface temperature. Secondly, the ‘LST zone-based model’ stores tree canopy cover and building areas in each zone unit. Pearson correlation, global linear regression, and geographically weighted regression (GWR) were applied to establish the relationship between tree attributes, building areas (explanatory variables) with local temperature (dependent variable). Results showed that English elm has the highest cooling and least by Mugga ironbark in the study area. GWR results demonstrate that 94% of the LST was explained by tree height and tree canopy area. The LST zone-based model showed that 85% of the LST was explained by the percentage of tree species and buildings. Maps of the local R² and coefficients of the independent variables provide spatially explicit information on the cooling of different tree species compared to building areas. The implemented GeoAI approach provides important insights to urban planners and government to monitor urban trees with the enhanced Individual Tree Inventory and strategies mitigation plan to reduce the impact of climate change and global warming.     

Seasonal variations in the cooling effect of urban green areas on surrounding urban areas

We measured air temperature in an urban green area that includes forest and grassland and in the surrounding urban area for a full year in Nagoya, central Japan, to elucidate seasonal variations of the difference in air temperature between urban and green areas. We determined the range of the “cool-island” effect as well as the relationship between vegetation cover and air temperature throughout the year. The temperature difference between urban and green areas was large in summer and small in winter. The maximum air temperature difference was 1.9 °C in July 2007, and the minimum was ?0.3 °C in March 2004. The difference was larger during the day than during the night in summer, whereas in winter the opposite relationship was true. However, winter diurnal variation was not particularly noticeable, a behaviour thought to be related to reduced shading by deciduous trees in the green area. During the night, the cooling effect of the green area reached 200–300  m into the urban area. During the day, the cooling effect between August and October 2006 exceeded 300 m and varied widely, although there was no correlation beyond 500 m. The correlation between air temperature and forest-cover ratio within a radius of 200 m from each measurement site was significant from 16:00 to 19:00. There was also a correlation during the night; this correlation was weakest in the early morning. The effect of the forest-cover ratio on air temperature was most pronounced in August 2006 and June 2007.     

Simulated productivity of heterogeneous patches in Southern African savanna landscapes using a canopy productivity model

A daily model of terrestrial productivity is used to simulate the annual productivity of heterogeneous vegetation structure at three savanna/woodland sites along a large moisture gradient in southern Africa. The horizontal distributions of vegetation structural parameters are derived from the three-dimensional canopy structure generated from detailed field observations of the vegetation at each site. Rainfall and daily climatic data are used to drive the model, resulting in a spatially explicit estimate of vegetation productivity in 100 m² patches over an area 810,000 m² (8,100 patches per site). Production is resolved into tree and grass components for each subplot. The model simulates the relative contribution of trees and grasses to net primary productivity (NPP) along the rainfall gradient. These simulated production estimates agree with previously published estimates of productivity in southern African savannas. Water-use efficiency of each site is directly related to the structural composition of the site and the differing water-use efficiencies for tree and grass functional types. To assess the role of spatial scale in governing estimates of vegetation productivity in heterogeneous landscapes, spatial aggregation is performed on the canopy mosaic at the northern-most (wettest) site for 625 m², 2500 m² and 5625 m² resolutions. These simulations result in similar overall patterns of average NPP for both trees and grasses, but drastically reduced distributions of productivity due to reduced structural heterogeneity. In particular, the aggregation of the detailed spatial mosaic to coarser resolutions is seen to eliminate information regarding demographic processes such as regeneration and mortality, and the dependence of grass productivity on over-story density. These results indicate that models of system productivity in savanna/woodland ecosystems must retain high spatial resolution to adequately characterize multi-year structural responses and to accurately represent the contribution of grass biomass to overall ecosystem production.This revised version was published online in May 2005 with corrections to the Cover Date.     

Green Veining: Landscape Determinants of Biodiversity in European Agricultural Landscapes

Many semi-natural landscape elements, the so-called green veining, are disappearing from the intensively used agricultural landscapes of Europe. In order to develop or restore biodiversity in these networks, it is necessary to quantify the relation between biodiversity and amount, spatial arrangement and management intensity of green veining elements. In this review, we investigate whether biodiversity increases with the amount of green veining in an agricultural landscape following the species–area relationship, and whether a certain level of biodiversity can be reached at lower densities of green veining if green veining elements are better connected (higher spatial connectivity) or if they are managed less intensively (lower management intensity). We reviewed studies on aboveground biodiversity in green veining structures in 39 scientific papers on field and experimental studies within Europe. More of these studies focussed on management intensity than on amount or spatial configuration of green veining. Also more studies focussed on the spatial scale of individual landscape elements than on the farm or landscape scale, which may be caused by the large number of studies focussing on plant or invertebrate species. Species living at larger spatial scales, e.g. mammals and birds were not often studied at the level of green veining elements as they also use agricultural fields as part of their habitat. We could not verify the species–area relation for green veining, nor the effect of amount, spatial configuration or management intensity on this relation, because only few studies quantified the found effects and no studies were found on the effect of management intensity or spatial configuration on the species–area curve in green veining. We addressed the most important challenges for future field and model research in order to fill the identified gaps in knowledge.     

Efficient cooling of cities at global scale using urban green space to mitigate urban heat island effects in different climatic regions

In the context of rapid urbanization and global warming, how to use urban green space (UGS) with high-efficiency to mitigate the urban heat islands (UHIs) effect in different climate zones has become an urgent issue. However, few studies have provided specific guidance for urban vegetation planning adapting to different climate zones on a global scale. In this study, a cooling effect framework was employed to analyze the influence of UGS patch characteristics, natural and anthropogenic factors on its cooling effect across different climatic zones. We found that the urban cooling islands (UCI) intensity, extent, and gradient of UGS increased with latitude, with lower cooling effect concentrated in arid zones around 30 °N, while the largest (0.38 ha) and smallest (0.24 ha) threshold value of efficiency (TVoE) were found in the temperate and arid climate zones. The larger the UGS area, the better the cooling effect in all climate zones. Moreover, complex shapes have a greater UCI intensity in tropical and temperate zones than other regions, while the normalized difference vegetation index (NDVI) has a stronger effect in arid zones. In the continental zone, patch characteristics had little effect. The overall explanation rate of natural and anthropogenic factors on the cooling effect of UGS was 53.5 %, among which natural factors were approximately twice that of anthropogenic factors. Notably, natural factors dominated in the tropical and arid zones affecting UCI, and anthropogenic factors dominated in the temperate and continental zones. The findings of this study expand our understanding of the cooling effect of UGS in different climatic zones around the world and provide insights for urban sustainable development.     

A general grass growth model for urban green spaces management in tropical regions: A case study with bahiagrass in southeastern Brazil

Urban green spaces (UGS) positively impact the population, providing essential ecosystem services and improving public health. Urban vegetation management needs to optimize mowing process costs and reducing impacts on the natural ecosystem. Thus, we implemented a general grass growth model suitable for UGS management in tropical areas, focused on lawns, public parks and squares, roadsides, and around waterways. The model incorporates local edaphoclimatic conditions to simulates the daily dynamics of leaf area index (LAI), biomass, evapotranspiration, and soil water content, going under mowing processes or not, with spatialization capability which might be integrated within geographic information system (GIS) environments. A case study assessing bahiagrass (Paspalum notatum Flüggé) vegetation species in São Carlos, southeastern Brazil, is presented, considering two scenarios to demonstrate the spatial capabilities of the model: (i) UGS as a single area, and (ii) several areas independently. For model validation, vegetation indices calculated based on data from an unmanned aerial vehicle (UAV) and CubeSat imagery (PlanetScope) were used to retrieve LAI time series, calibrated with spectral signatures from leaf ground sampling. For performance analysis, LAI time series from the model and LAI retrieved from both sensors were compared via determination coefficient (R²⁾ and root mean square error (RMSE). Our findings suggest that the proposed model is accurate, and due to its spatialization capability and integration with a GIS, its application may help government administrations to optimize UGS mowing processes.