Spatial and temporal variability of air temperature across urban neighborhoods with varying amounts of tree canopy

Recent studies have emphasized the presence of microclimates in urban settings, but most do not have the high resolution observations necessary to understand the interactions taking place at a neighborhood scale. This study used a network of 10 identical weather stations and high resolution land cover data in Knoxville, Tennessee, to analyze the microclimates of a medium-sized city with a temperate climate. Two stations were installed in each of four urban neighborhoods in locations with varying localized tree cover, and two additional stations were installed in the center of downtown and in a nearby urban nature center. The intra-neighborhood results suggested that there is significant temperature variability within a single neighborhood based on the tree canopy density immediately surrounding a given weather station. However, the inter-neighborhood variability (differences between neighborhoods) was similar in magnitude, which suggests that the overall differences in neighborhood characteristics also have an effect on climate. Land cover at the neighborhood scale (in particular tree canopy percentages at the 500-m radii) had the highest correlation with the minimum daily temperature (Tmin) during the summer season. Maximum daily temperature (Tmax) relied most on the distance of each station from Downtown and the amount of impervious area in the 50 m surrounding each station. Tmax was also most influenced by surrounding land cover during dry conditions (a Dry Moderate air mass). Overall, highly localized impervious land cover percentages and larger-scale forested canopy were important in explaining temperature fluctuation, pointing to the importance of scale in microclimate assessments. Dry air masses enhanced the relationship between land cover and temperature during the day, while moist air masses did the same overnight. These data can be used to better inform planning strategies to build resiliency to extreme heat into urban environments by considering the influence of tree canopy.     

Elephants,termites and mound thermoregulation in a progressively warmer world

Context

With global change, microclimates become important refuges for temperature-sensitive, range-restricted organisms. In African savannas, woody vegetation on Macrotermes mounds create widely-dispersed microclimates significantly cooler than the surrounding matrix, which buffer against elevated temperatures at the finer scale of mounds, allowing species to persist at the landscape scale. Termite colonies cultivate symbiotic fungi to digest lignin, but the fungi require temperatures between 29 and 32 °C, which termites strive to maintain. Mound-associated vegetation is a hot-spot for elephant herbivory, so removal of woody species cover by elephants could influence mound-associated microclimates, impacting temperature regulation by termites.

Objectives

We explored the interaction between two prominent ecosystem engineers (termites and elephants) to ascertain whether elephant removal of mound woody cover affects (1) external mound-associated microclimate and (2) internal mound temperature.

Methods

We surveyed 44 mounds from three sites in Kruger National Park, South Africa, during an El Niño/Southern Oscillation-induced drought and heatwave, recording whether sub-canopy, external, mound-surface and internal mound temperatures varied with vegetation removal by elephant.

Results

Elephant damage to mound-associated vegetation reduces the fine-scale microclimate effect provided by vegetation on Macrotermes mounds. Despite this, termites were able to regulate internal mound temperatures, whereas internal temperatures of abandoned mounds increased with elevated surface temperatures.

Conclusions

Termites can persist despite loss of mound-associated microclimates, but the loss likely increases energetic costs of mound thermoregulation. Since mound vegetation buffers against drought, loss of widely-dispersed, fine-scale microclimates could increase as megaherbivores remain constrained to protected areas, impacting climate-sensitive organisms and ecosystem function at a range of scales.

     

Patch-level based vegetation change and environmental drivers in Tarim River drainage area of West China

Information on vegetation-related land cover change and the principle drivers is critical for environmental management and assessment of desertification processes in arid environments. In this study, we investigated patch-level based changes in vegetation and other major land cover types in lower Tarim River drainage area in Xinjiang, West China, and examined the impacts of environmental factors on those changes. Patterns of land cover change were analyzed for the time sequence of 1987–1999–2004 based on satellite-derived land classification maps, and their relationships with environmental factors were determined using Redundancy Analysis (RDA). Environmental variables used in the analysis included altitude, slope, aspect, patch shape index (fractal dimension), patch area, distance to water body, distance to settlements, and distance to main roads. We found that during the study period, 26% of the land experienced cover changes, much of which were the types from the natural riparian and upland vegetation to other land covers. The natural riparian and upland vegetation patches were transformed mostly to desert and some to farmlands, indicating expanding desertification processes of the region. A significant fraction of the natural riparian and upland vegetation experienced a phase of alkalinity before becoming desert, suggesting that drought is not the exclusive environmental driver of desertification in the study area. Overall, only a small proportion of the variance in vegetation-related land cover change is explainable by environmental variables included in this study, especially during 1987–1999, indicating that patch-level based vegetation change in this region is partly attributable to environmental perturbations. The apparent transformation from the natural riparian and upland vegetation to desert indicates an on-going process of desertification in the region.     

Gradual or abrupt? An algorithm to monitor urban vegetation dynamics in support of greening policies

While greening becomes a more and more popular strategy to address multiple urban challenges and to enhance wellbeing and human-nature connectedness, there is an increasing need for usable methods and indicators to monitor its implementation. Earth observations produce a wealth of data on vegetation dynamics, but their use for monitoring urban greening policies is still limited. In this article, we develop and test an algorithm for the analysis of urban vegetation dynamics based on NDVI time series. Specifically, we focus on yearly greenest pixel composites that illustrate the maximum value of NDVI during the year (“greenness”): a key structural attribute to monitor urban ecosystems in the European Union. The algorithm is inspired by earlier examples of segmentation algorithms but fits the specific requirements of the targeted use in urban areas. It takes the series of NDVI values associated to each pixel, detects existing (multiple) break points, and quantifies related abrupt changes, as well as significant gradual changes that occurred during a selected period. We tested the algorithm on a 30-year Landsat series in Berlin and partially validated the output through a comparison with infrared ortophotos. The results reveal a net increase in NDVI between 1988 and 2017 in 84% of the pixels, with an average change over the whole city of + 0.096. Around 20% of the pixels show at least one abrupt change. Most abrupt changes (71.5%) were positive, but the negative ones had on average a greater absolute value (−0.170 vs +0.085). However, considering the cumulative impacts during the whole period, 97% of the total change is attributable to gradual changes. The validation proves that abrupt changes successfully capture variations in the extent of vegetation due to land cover changes (e.g., vegetation removal or new greening interventions), while gradual changes can be associated to vegetation growth or decline. We discuss the strengths and limitations of the proposed algorithm, and how the spatially- and temporally-explicit results can be a step forward in the interpretation of urban vegetation dynamics towards an effective monitoring of the impacts of local greening policies.     

Micro-scale urban surface temperatures are related to land-cover features and residential heat related health impacts in Phoenix,AZ USA

Context

With rapidly expanding urban regions, the effects of land cover changes on urban surface temperatures and the consequences of these changes for human health are becoming progressively larger problems.

Objectives

We investigated residential parcel and neighborhood scale variations in urban land surface temperature, land cover, and residents’ perceptions of landscapes and heat illnesses in the subtropical desert city of Phoenix, AZ USA.

Methods

We conducted an airborne imaging campaign that acquired high resolution urban land surface temperature data (7 m/pixel) during the day and night. We performed a geographic overlay of these data with high resolution land cover maps, parcel boundaries, neighborhood boundaries, and a household survey.

Results

Land cover composition, including percentages of vegetated, building, and road areas, and values for NDVI, and albedo, was correlated with residential parcel surface temperatures and the effects differed between day and night. Vegetation was more effective at cooling hotter neighborhoods. We found consistencies between heat risk factors in neighborhood environments and residents’ perceptions of these factors. Symptoms of heat-related illness were correlated with parcel scale surface temperature patterns during the daytime but no corresponding relationship was observed with nighttime surface temperatures.

Conclusions

Residents’ experiences of heat vulnerability were related to the daytime land surface thermal environment, which is influenced by micro-scale variation in land cover composition. These results provide a first look at parcel-scale causes and consequences of urban surface temperature variation and provide a critically needed perspective on heat vulnerability assessment studies conducted at much coarser scales.

     

Street trees and Urban Heat Island in Glasgow: Mitigation through the ‘Avenues Programme’

Glasgow, Scotland, is embarking on an ambitious plan to convert all city centre thoroughfares into tree-lined streets (the ‘Avenues Programme’) to make the city centre more people-friendly, attractive, greener, sustainable and economically competitive. While it is well-known that urban green infrastructure (UGI) is a promising strategy to address overheating in urban areas, evidence for the surface temperature, air temperature and thermal comfort effects of street trees is contradictory. In the context of a city-centre-wide ‘Avenues Programme’ in Glasgow, we explore its co-benefits in terms of temperature and thermal comfort. We used a multi-method approach, combining GIS-based spatial analysis with fieldwork, microclimate modelling and statistical analysis to determine the scale of the overheating problem and the likely role of its mitigation based on the ‘Avenues Programme’ case study. We show that the Surface Urban Heat Island (SUHI) differences within the city are of the same magnitude as the urban-rural anomaly and “hot” spots are localized in the city centre area and are clustered in different patterns depending on the severity of background temperatures. Therefore, small, isolated patches of vegetation would not be effective for cooling the clusters of overheated areas. Air temperature showed non-linear relationship with tree canopy cover and the relationship is stronger at medium scale. The ‘Avenues Programme’ as a whole, could eliminate the UHI effect in the city centre, with some tree species completely eliminating the UHI in the city centre. Once complete, the ‘Avenues Programme’ could significantly improve thermal comfort during heatwaves from the current ‘hot’ category to ‘slightly warm’ across the city centre.     

Probabilistic models of fire occurrence across National Park Service units within the Mojave Desert Network,USA

The frequency and size of wildfires within the Mojave Desert are increasing, possibly due to climate and land cover changes and associated increases in non-native invasive plant biomass, as measured by normalized difference vegetation index (NDVI). These patterns are of particular concern to resource managers in regions where native plant communities are not well adapted to fire. We used an information-theoretic and mixed-model approach to quantify the importance of multiple environmental variables in predicting, separately, the probabilities of occurrence of all fires and the occurrence large (>20 ha) fires in five management units administered by the National Park Service in the Mojave Desert Network and based on fire ignition data obtained for the period 1992–2011. Fire occurrence was strongly associated with areas close to roads, high maximum NDVI values in the year preceding ignition, the desert montane ecological zone, and high topographic roughness. Large fire probability was strongly associated with lightning-caused ignition events, high maximum NDVI values in the spring preceding ignition, high topographic roughness, the middle-elevation shrubland ecological zone, and areas further from roads. Our probabilistic models and maps can be used to explore patterns of fire occurrence based upon variability in NDVI values and to assess the vulnerability of Mojave Desert protected areas to undesirable fire events.     

Effect of street trees on microclimate and air pollution in a tropical city

One of the fastest growing cities in India, Bangalore is facing challenges of urban microclimate change and increasing levels of air pollution. This paper assesses the impact of street trees in mitigating these issues. At twenty locations in the city, we compare segments of roads with and without trees, assessing the relationship of environmental differences with the presence or absence of street tree cover. Street segments with trees had on average lower temperature, humidity and pollution, with afternoon ambient air temperatures lower by as much as 5.6 °C, road surface temperatures lower by as much as 27.5 °C, and SO₂ levels reduced by as much as 65%. Suspended Particulate Matter (SPM) levels were very high on exposed roads, with 50% of the roads showing levels approaching twice the permissible limits, while 80% of the street segments with trees had SPM levels within prescribed limits. In an era of exacerbated urbanization and climate change, tropical cities such as Bangalore will have to face some of the worst impacts including air pollution and microclimatic alterations. The information generated in this study can help appropriately assess the environmental benefits provided by urban trees, providing useful inputs for urban planners.     

Urban forest structure and land cover composition effects on land surface temperature in a semi-arid suburban area

Using multispectral imagery and LiDAR data, we developed a high-resolution land cover dataset for a semi-arid, Colorado (USA) suburb. These data were used to evaluate patterns of land cover composition and vertical structure in relation to land use and age of development. Landsat 5 TM thermal band data for six separate dates were used to compare land surface temperature (LST) in urbanized and remnant shortgrass steppe reference areas. We used 2010 census blocks to extract LST and various explanatory variables for use in Random Forest models evaluating the relative importance of land cover composition, LiDAR-derived vertical structure variables, and the Normalized Difference Vegetation Index (NDVI) on LST patterns.We found that land cover, vertical structure, and LST varied between areas with different land use and neighborhood age. Older neighborhoods supported significantly higher tree cover and mean tree height, but differences in LST were inconsistent between Landsat image dates. NDVI had the highest variable importance in Random Forests models, followed by tree height and the mean height difference between trees and buildings. Models incorporating NDVI, vertical structure, and land cover had the highest predictive accuracy but did not perform significantly better than models using just vertical structure and NDVI. Developed areas were cooler on average than shortgrass steppe reference areas, likely due to the influence of supplemental irrigation in urbanized areas. Patterns of LST were spatially variable, highlighting the complex ways land cover composition and vertical structure can affect urban temperature.     

The impact of habitat characteristics on bird presence and the implications for wildlife management in the environs of Ottawa,Canada

Urban forestry is increasingly vital for both wildlife conservation and human use, despite frequent conflicts between these functions. A fundamental task in urban habitat and recreation forestry is the identification of those habitat characteristics important for animal species and the evaluation of these within the geographies of human presence, urban proximity and land cover variation and change. This paper examines the habitat characteristics for birds in urban built, green and greenbelt areas of Ottawa, Canada, and an area of continuous Ontario forest, to determine the effects of vegetation density and patch size, and human presence on bird presence. Bird presence was measured by point counts, and land cover was mapped using field observation and aerial photographs (1955 and 1999). At the species level, the pre-dominantly forest birds were affected by human presence and were primarily associated with tree stands in the greenbelt and continuous forest. In dense urban areas there were larger numbers of a few ‘generalist’ species. Both forested and urban (residential/commercial) environments increased in area between 1955 and 1999, creating the two types of land cover favouring the largest number of birds, while the less habituated grass/farmed areas declined in area. More informed bird conservation and recreation management will depend on paying greater attention to vegetation cover combinations with urban development.     

The effects of land tenure and land use on the urban forest structure and composition of Melbourne

The urban forest provides valuable ecosystem services for enhancing human well-being. Its structure and composition determine the quantity and quality of these services. There has been little research on the heterogeneity in structure and composition of urban forests in the Australasian region, especially in the centre of a highly dynamic and rapidly urbanizing city. This paper quantifies the structure and the composition of the urban forest of Melbourne, Australia's city centre. The effects of land tenure and land use on the heterogeneity of canopy cover, tree density and canopy size were explored. Species and family composition by land use, land ownership and street type were also analysed using the Shannon–Wiener and Jaccard similarity indices. Most of the canopy cover in the city centre is located on public land and is unevenly distributed across the municipality. The mean canopy cover (12.3%) is similar to that found for whole city studies around the world, which often include peri-urban forests. Similarly to other cities, structure varied across different land uses, and tree size, density and cover varied with land tenure and street type. The diversity index shows that the urban forest is rich in species (H′ = 2.9) and is dominated by native species. Improving the distribution, and increasing tree cover and variety of species will result in a more resilient urban centre, able to provide multiple ecosystem services to their residents and its large population of visitors and workers. The study of the urban centre provides further understanding of compact city morphologies, and allows inter-city comparison independent of the size.     

The impact of distinct anthropogenic and vegetation features on urban warming

We investigate the direct relationship between detailed urban land cover classes, derived from fine resolution QuickBird satellite data, and land surface temperatures (Celsius), generated from ASTER imagery, over Phoenix, Arizona. Using daytime and nighttime temperatures in both winter and summer and all observation points (n = 11,025), we develop linear, non-linear and multiple regression models to explore the relationship. Conventional wisdom suggests that all urban features result in increased temperatures. Rather, our results show that a mass of buildings is not necessarily or holistically responsible for extreme heat in desert cities. It is the construction of other impervious dark surfaces (i.e., asphalt roads) associated with buildings that result in extreme heat. Moreover, our results suggest that buildings, especially commercial buildings with high albedo roofs, actually reduce temperatures. The addition of trees and shrubs, as opposed to grass, around buildings can further mitigate extreme heat by providing more cooling during the summer and increasing nighttime temperatures in the winter. In conclusion, the compositional design of and avoidance of dark impervious materials in desert cities help mitigate extreme temperatures. It is important to note, however, that design choices that reduce extreme heat must be made within the broader context of tradeoffs and unintended consequences to ensure the sustainability of these cities.     

The value of vegetation cover for ecosystem services in the suburban context

Latin-American cities can be characterized by dynamic processes of urbanization that encroach upon the natural and semi-natural surrounding landscapes. Our study presents the effects of landscape development, transformed from semi-natural conditions into a mostly disperse suburban settlement. We explore the impact that this transformation has had on this context by three ecosystem services that regulate rainwater runoff, enhance microclimate conditions and help to improve air quality by monitoring vegetation cover. We have designed a spatio-temporal hierarchical analysis which employs remote sensing techniques to capture the structural changes of this landscape over long, medium and short term scales on two spatial levels. This methodological approach was tested in the Metropolitan Area of Santiago (MAS) as case study area. Despite of the increase in impervious surfaces due to urban processes, there has also been an increase in vegetation cover, which has led to an improvement in the provision of the above-mentioned ecosystem services. Hence, if diverse urbanization processes continue and they are coupled with an increase in vegetation cover, the provision of ecosystem services could also expand. This phenomenon can be observed in some areas, where public and private green spaces are created and maintained. Our data analyses give evidence that certain types of suburban areas which increase the share of vegetation cover can provide daily ecological benefits for urban neighborhoods, and beyond, for adjacent areas. Moreover, suburban development can successfully provide ecological benefits to citizens. Such processes can only be ecologically sustainable if the composition of vegetation is well-adapted to the regional climatic conditions.     

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.     

Spatial variations of plant species diversity in urban soil seed banks in Beijing,China: Implications for plant regeneration and succession

The near-to-nature urban forestry concept and practices are widely recognized for urban greening, urban ecosystem restoration, urban greenspace management for biodiversity conservation and ecosystem services provision. However, the regeneration and succession of urban vegetation are rarely studied due to the complex settings of the urban environment. To this end, we conducted a large-scale field investigation in the metropolitan area of Beijing, China to explore the spatial variations in plant species composition and diversity in soil seed banks, and their similarity to the aboveground vegetation to assess the potential of urban plant regeneration. Overall, 657 vegetation and soil sampling plots from 219 grids, measuring 2 km × 2 km each, were investigated within two perpendicular 10 km wide transects running across the urban center in north-south and east-west directions within the 6th Ring Road of the city. We recorded a total of 102 plant species in soil seed banks, including 13 tree species, 10 shrub species, and 79 herb species. We found that the soil seed bank species diversity and its similarity to that of the aboveground vegetation communities decreased significantly with the urbanization intensity. Higher urbanization intensity is typically associated with increased human management and a reduction in Greenspace Area (GSA). Soil seed bank species richness increased significantly when GSA exceeded 45 % and the similarity of species composition and diversity between soil seed banks and aboveground vegetation communities was the highest in forest parks. This suggests that habitats under forest park management are more conducive to plant regeneration. Soil seed bank species diversity first increased and then decreased significantly with increased distance to the city center, whereas the species similarity between the soil seed banks and the aboveground vegetation communities showed little change with the ring roads going out. The results of this study have important implications for further understanding the potential for urban vegetation regeneration and sustainability, which have significant implications for urban biodiversity conservation and restoration.     

A decision-making framework for promoting the optimum design and planning of Nature-based Solutions at local scale

Urbanization is a key driver of land use/land cover changes climate change. It produces a reduction in natural capital with alteration to the energy budget of land, air ventilation and land surface temperature. The urban morphology derived from the combination of natural capital and human-derived capital is important in urban ecosystem services (UESs) provisioning to mitigate the Urban Heat Island (UHI) effect. Here we report a decision-making framework starting from an applicative case study to assess UESs and promote the best design and planning of Nature-based Solutions (NbS) at local scale. The human thermal comfort has been chosen here as a surrogate to estimate climate regulation as a priority UES in mitigating UHI. The analysis of human thermal comfort in different urban neighbourhood planning scenarios of a city located in Southern Italy has been carried out using the microclimate model ENVI-met. The analysis has been developed to highlight the variation in human thermal comfort in terms of Physiological Equivalent Temperature index (PET) between past agricultural scenarios (no longer more present), current state and several proposed urban scenarios. Such new scenarios have been developed by considering different building arrangements according to municipal planning rules of the city and choosing different types of NbS composition and structure. The analysis has allowed to identify the best scenario characterized by the presence of a community garden with olive groves and estimate the capacity of NbS to reduce the human thermal comfort by about 3.5ºC and improve the PET in selected locations within the current state. In accordance with the aim and topics of the Special Issue, this study shows how such a framework can be useful to support decision-making processes in choosing the best strategy in terms of urban plans and thus making the urban transformation process more sustainable, contributing to assessing the global targets of the 2030 Agenda at local scale.     

Modelling tree canopy cover and evaluating the driving factors based on remotely sensed data and machine learning

Quantifying urban tree cover is important to ensure sustainable urban ecosystem. This study calculates urban percent tree cover (PTC) for Bursa city, Turkey from Sentinel-2 data and evaluates the driving factors of PTC using an Artificial Neural Network-Multi Layer Perception (ANN-MLP) approach. For the PTC calculation, a Regression Tree (RT) analysis was performed using several vegetation indices (NDVI, LAI, fCOVER, MSAVI2, and MCARI) to improve accuracy. Socio-economic, topographic, and biophysical variables were incorporated into the ANN-MLP approach to evaluate the factors that drive urban PTC. A PTC prediction map was generated with an accuracy of 0.95 and a coefficient of determination of 0.87. The ANN-MLP training process yielded a correlation coefficient value of 0.71 and an R-square of 0.82 was achieved between the predicted ANN-MLP and observed tree cover maps. A priority tree cover map was generated considering statistical relationships between the factors and the ANN-MLP prediction map in addition to visual interpretations at the urban scale. Results demonstrate that, unlike other urban forms, PTC has a statistically negative relationship with the gross dwelling density (R2 =0.31). Topographic variables including slope and DEM were positively correlated with PTC with the R2 value of 0.80 and 0.72 respectively. The integration of remote sensing data with vegetation indices and driving factors yielded accurate prediction for identifying and evaluating the variability in the urban PTC.     

Detection of unfavourable urban areas with higher temperatures and lack of green spaces using satellite imagery in sixteen Spanish cities

This paper seeks to identify the most unfavourable areas of a city in terms of high temperatures and the absence of green infrastructure. An automatic methodology based on remote sensing and data analysis has been developed and applied in sixteen Spanish cities with different characteristics. Landsat-8 satellite images were selected for each city from the July-August period of 2019 and 2020 to calculate the spatial variation of land surface temperature (LST). The Normalized Difference Vegetation Index (NDVI) was used to determine the abundance of vegetation across the city. Based on the NDVI and LST maps created, a k-means unsupervised classification clustering was performed to automatically identify the different clusters according to how favourable these areas were in terms of temperature and presence of vegetation. A Disadvantaged Area Index (DAI), combining both variables, was developed to produce a map showing the most unfavourable areas for each city. Overall, the percentage of the area susceptible to improvement with more vegetation in the cities studied ranged from 13 % in Huesca to 64–65 % in Bilbao and Valencia. The influence of several factors, such as the presence of water bodies or large buildings, is discussed. Detecting unfavourable areas is a very interesting tool for defining future planning strategy for green spaces.     

Drivers of diversity and tree cover in gardens,parks and streetscapes in an Australian city

While we know that urban vegetation is often distributed unequally, most studies have been undertaken in cities with relatively high levels of income inequality, using a single measure of distribution (usually tree cover) and in a single land use. This study explores predictors of both tree cover and species richness in gardens, streetscapes and parks in Ballarat, Australia. Spatial regression models found that education level was a more important predictor of tree cover than household income across all land uses in Ballarat which can be explained by some people with high incomes relative to education level choosing to live in new residential developments with disproportionately low levels of tree cover. Inequality in tree cover was greater in streetscapes than in residential gardens, suggesting that ‘top down’ political factors are more important than individual behaviours in determining tree cover in Ballarat. In contrast, physical rather than socioeconomic factors were better predictors of species richness across all land uses, highlighting that different measures of vegetation distribution are not necessarily correlated.     

The temporal trend of urban green coverage in major Chinese cities between 1990 and 2010

Information on changes in urban green spaces and the causes of these changes is important for urban planning. In this study the trends of urban green coverage (UGC) between 1990 and 2010 in 30 major Chinese cities were studied using classified Landsat satellite images. Associations between the trends and natural and socio-economic variables were analyzed using the maximum information-based nonparametric exploration method. The results showed that, overall, the studied cities have become greener over the past two decades. Greening in old city districts and expanded built-up areas (BUAs) led to the increase of urban green coverage at a mean annual rate of 1.51%. However rapid urbanization also caused a dramatic turn-over in vegetation covers. On a regional scale, around 46.89% of original vegetation cover was converted to other land cover types. The trends of UGC cannot be attributed to any one of natural or socio-economic variables alone. The combined influences of economic growth, climate change, and urban greening policies are the most likely causes behind the detected trend. One lesson from this study is that the preservation of existing vegetation cover must be a priority in urban greening programs.