Effect of urban green patterns on surface urban cool islands and its seasonal variations

Urban green spaces often form urban cool islands (UCIs), which are important for human health and urban sustainability. Previous studies have emphasized the cooling effects of urban green spaces on their surrounding areas at landscape level. Less attention, however, has been directed to effects of urban green space patterns on their own UCIs at patch level. In this study, we focused on the effects of spatial patterns of urban green patches on their own surface UCIs. The urban green spaces of Beijing, China, were extracted from one QuickBird image and were classified as Trees, Shrubs, Grass, Crops, River and Lake. Land surface temperatures (LSTs) were derived from four Landsat images, each in one season. The UCI was represented by the minimum LST of each urban green patch. Results showed spatial patterns of urban green patches had significant effects on their UCIs in four seasons. In detail, the size, edge and connectivity of urban green spaces all affected the UCIs negatively, and the influence was stronger in warm seasons. Shape of urban green space also had effects on UCIs, but the effects were stronger in cool seasons. Great differences were found between predictive values of metrics for different green types. Shape metrics were more important for indicating UCIs of River, Trees and Crops than were patch size and connectivity. However, patch size and connectivity metrics were more effective in determining UCIs of Shrubs, Grass and Lake than were shape metrics. Further, among shape metrics, only shape index was a good indicator of UCIs. The results of this study suggest that a combination of specific urban green types and pattern metrics are a prerequisite for analyzing the influence of urban green patterns on UCIs and for urban green design.     

Forest fragmentation in Loudoun County,Virginia, USA evaluated with multitemporal Landsat imagery

In order to study forest fragmentation in the Virginia, USA Piedmont, a series of Landsat images from 1973, 1987, and 1999 covering a rapidly developing area (Loudoun County) was used to classify forest from non-forest. The classified images were analyzed using a geographic information system (GIS) to determine the spatial and temporal patterns of fragmentation, and to relate these patterns to infrared radiance provided by Landsat Enhanced Thematic Mapper Plus (ETM+) band 6. The analysis was concentrated on eleven major watersheds of Loudoun County. The relationship between urbanized area per watershed and mean fragment size showed a strong negative decay form (r ²=0.757, p<0.0001). Analysis of four landscape metrics showed increasing fragmentation of forest cover, particularly from 1987 to 1999, as well as an increase in forest edge and shape complexity. Of the landscape metrics used, the perimeter-to-area (P/A) ratio showed the strongest relationship with mean radiance of forest patches. In addition, there was a negative, linear relationship between distance from major roads and band 6 radiance of forested pixels. Overall, the study shows that landscape metrics can convey meaningful information on biophysical changes associated with forest fragmentation at broad scales. These changes suggest that ambient temperature increases associated with urban sprawl may have important, long-term implications for ecophysiological processes.     

Zoning,land use,and urban tree canopy cover: The importance of scale

Declining urban tree canopy cover in the United States underscores the importance of elucidating factors that influence the distribution of urban trees. This is particularly relevant as most urban trees are located on private property while their canopies maintain ecosystem services that constitute public goods. Thus, municipalities establish institutions in the form of canopy cover goals and various policies to incentivize private actions to meet those goals. However, urban land use, as governed by municipal zoning policies, plays a role in the abundance, distribution, and potential future location of urban trees independent of policies meant specifically to manage canopy. For instance, previous research finds that lands zoned for residential and park development have the highest canopy cover relative to other land uses. Yet, little research has explored whether this conclusion holds across scales of analysis and how it might influence our understanding of potential canopy cover and relative canopy cover. Thus, we ask, does the nature of the relationship between zoning and canopy cover change between aggregated and disaggregated zoning scales and how might this knowledge improve the sustainability of urban forest management? To answer this question, we classified high resolution National Agriculture Imagery Program (NAIP) images of Bloomington, Indiana land cover and compared existing, potential and relative canopy cover across aggregated and disaggregated zones. Results demonstrate an important exception to the oft-cited theory that residential lands have higher canopy cover, a conclusion that our data supports only at the scale of an aggregated interpretation of zoning. At a disaggregated scale, residential high density zones are significantly different than all other residential zones and more akin to commercial zones in terms of all canopy metrics. For urban forest managers and urban planners, this suggests the relevance of fine-scale variation in land-use policies and related canopy cover policies.     

Global analysis and simulation of land-use change associated with urbanization

A combination of rapid population growth and an accelerating demographic shift from rural to urbanized habitats has resulted in urbanization becoming an increasingly global phenomenon. Two alternate hypotheses describing urban landscape trajectories suggest urbanization is either leading to more homogeneous global patterns or urbanization has dichotomous trajectories of increasing dispersal or coalescence. To better understand the global variation in urban land-cover patterns and trajectories we described the variation in urban landscape structure for 120 cities distributed throughout the world assessed at circa 1990 and 2000. We coupled these data to a low-dimensional neighborhood based model of urban growth using a data-model fusion approach. Trajectories of urban growth were assessed using both the original data and model projections to 2030. The patterns of landscape change were related to both the rate of growth and income. The historical patterns of change showed a trend of increasing landscape complexity and this trend was projected to continue. Urban rate of growth was closely related to the change in several landscape metrics. Income was associated with landscape dynamics and this effect interacted with city size. Large cities were less sensitive to the income effect than small cities. Along with changes to the magnitude of each metric, the overall variation in metrics between years generally exhibited a decrease in variability and this variability was projected to continue decreasing. These findings supported the hypothesis that urban landscapes are becoming more homogeneous and that the dispersal-coalescing dichotomy represent endpoints rather than alternate states of urban growth.     

The influence of patch-delineation mismatches on multi-temporal landscape pattern analysis

Investigations of land-cover change often employ metrics designed to quantify changes in landscape structure through time, using analyses of land cover maps derived from the classification of remote sensing images from two or more time periods. Unfortunately, the validity of these landscape pattern analyses (LPA) can be compromised by the presence of spurious change, i.e., differences between map products caused by classification error rather than real changes on the ground. To reduce this problem, multi-temporal time series of land-cover maps can be constructed by updating (projecting forward in time) and backdating (projecting backward in time) an existing reference map, wherein regions of change are delineated through bi-temporal change analysis and overlaid onto the reference map. However, this procedure itself creates challenges, because sliver patches can occur in cases where the boundaries of the change regions do not exactly match the land-cover patches in the reference map. In this paper, we describe how sliver patches can inadvertently be created through the backdating and updating of land-cover maps, and document their impact on the magnitude and trajectory of four popular landscape metrics: number of patches (NP), edge density (ED), mean patch size (MPS), and mean shape index (MSI). In our findings, sliver patches led to significant distortions in both the value and temporal behaviour of metrics. In backdated maps, these distortions caused metric trajectories to appear more conservative, suggesting lower rates of change for ED and inverse trajectories for NP, MPS and MSI. In updated maps, slivers caused metric trajectories to appear more extreme and exaggerated, suggesting higher rates of change for all four metrics. Our research underscores the need to eliminate sliver patches from any study dealing with multi-temporal LPA.     

Improved methods for quantifying potential nutrient interception by riparian buffers

Efforts to quantify the effects of riparian buffers on watershed nutrient discharges have been confounded by a commonly used analysis, which estimates buffer potential as the percentage of forest or wetland within a fixed distance of streams. Effective landscape metrics must instead be developed based on a clear conceptual model and quantified at the appropriate spatial scale. We develop new metrics for riparian buffers in two stages of increasing functional specificity to ask: (1) Which riparian metrics are more distinct from measures of whole watershed land cover? (2) Do functional riparian metrics provide different information than fixed-distance metrics? (3) How do these patterns vary within and among different physiographic settings? Using publicly available geographic data, we studied 503 watersheds in four different physiographic provinces of the Chesapeake Bay Drainage. In addition to traditional fixed-distance measures, we calculated mean buffer width, gap frequency, and measures of variation in buffer width using both “unconstrained” metrics and “flow-path” metrics constrained by surface topography. There were distinct patterns of relationship between watershed and near-stream land cover in each physiographic province and strong correlations with watershed land cover confounded fixed-distance metrics. Flow-path metrics were more independent of watershed land cover than either fixed-distance or unconstrained measures, but both functional metrics provided greater detail, interpretability, and flexibility than the fixed-distance approach. Potential applications of the new metrics include exploring the potential for land cover patterns to influence water quality, accounting for buffers in statistical nutrient models, quantifying spatial patterns for process-based modeling, and targeting management actions such as buffer restoration.     

Analysis and simulation of land-use change in the central Arizona – Phoenix region,USA

To understand how urbanization has transformed the desert landscape in the central Arizona – Phoenix region of the United States, we conducted a series of spatial analyses of the land-use pattern from 1912–1995. The results of the spatial analysis show that the extent of urban area has increased exponentially for the past 83 years, and this urban expansion is correlated with the increase in population size for the same period of time. The accelerating urbanization process has increased the degree of fragmentation and structural complexity of the desert landscape. To simulate land-use change we developed a Markov-cellular automata model. Model parameters and neighborhood rules were obtained both empirically and with a modified genetic algorithm. Land-use maps for 1975 and 1995 were used to implement the model at two distinct spatial scales with a time step of one year. Model performance was evaluated using Monte-Carlo confidence interval estimation for selected landscape pattern indices. The coarse-scale model simulated the statistical patterns of the landscape at a higher accuracy than the fine-scale model. The empirically derived parameter set poorly simulated land-use change as compared to the optimized parameter set. In summary, our results showed that landscape pattern metrics (patch density, edge density, fractal dimension, contagion) together were able to effectively capture the trend in land-use associated with urbanization for this region. The Markov-cellular automata parameterized by a modified genetic algorithm reasonably replicated the change in land-use pattern.     

Impact of data integration technique on historical land-use/land-cover change: Comparing historical maps with remote sensing data in the Belgian Ardennes

Historical reconstructions of land-use/cover change often require comparing maps derived from different sources. The objective of this study was to measure land-use/cover changes over the last 225 years at the scale of a Belgian landscape, Lierneux in Ardennes, on the basis of a heterogeneous time series of land cover data. The comparability between the land-cover maps was increased following a method of data integration by map generalisation. Two types of time series were built by integrating the maps either by reference to the initial map of the time series or by pair of successive maps. Land-cover change detection was performed on the initial time series without data integration and on the two types of integrated time series. Results reveal that land cover and landscape structure have been subject to profound changes in Lierneux since 1775, with an annual rate of change at the landscape level of up to 1.40%. The major land-cover change processes observed are expansion of grasslands-croplands and reforestation with coniferous species, leading to amore fragmented landscape structure. The annual rates of land-cover change estimated from integrated data are significantly different from the annual rates of change estimated without a prior integration of the data. There is a trade-off between going as far back in time as possibleversus performing change detection as accurately as possible. This revised version was published online in July 2006 with corrections to the Cover Date.     

Surface metrics: an alternative to patch metrics for the quantification of landscape structure

Modern landscape ecology is based on the patch mosaic paradigm, in which landscapes are conceptualized and analyzed as mosaics of discrete patches. While this model has been widely successful, there are many situations where it is more meaningful to model landscape structure based on continuous rather than discrete spatial heterogeneity. The growing field of surface metrology offers a variety of surface metrics for quantifying landscape gradients, yet these metrics are largely unknown and/or unused by landscape ecologists. In this paper, we describe a suite of surface metrics with potential for landscape ecological application. We assessed the redundancy among metrics and sought to find groups of similarly behaved metrics by examining metric performance across 264 sample landscapes in western Turkey. For comparative purposes and to evaluate the robustness of the observed patterns, we examined 16 different patch mosaic models and 18 different landscape gradient models of landscape structure. Surface metrics were highly redundant, but less so than patch metrics, and consistently aggregated into four cohesive clusters of similarly behaved metrics representing surface roughness, shape of the surface height distribution, and angular and radial surface texture. While the surface roughness metrics have strong analogs among the patch metrics, the other surface components are largely unique to landscape gradients. We contend that the surface properties we identified are nearly universal and have potential to offer new insights into landscape pattern–process relationships. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Spatiotemporal pattern of urbanization in Shanghai, China between 1989 and 2005

Quantifying the spatiotemporal pattern of urbanization is necessary to understand urban morphology and its impacts on biodiversity and ecological processes, and thus can provide essential information for improving landscape and urban planning. Recent studies have suggested that, as cities evolve, certain general patterns emerge along the urban–rural gradient although individual cities always differ in details. To help better understand these generalities and idiosyncrasies in urbanization patterns, we analyzed the spatiotemporal dynamics of the Shanghai metropolitan area from 1989 to 2005, based on landscape metrics and remote sensing data. Specifically, the main objectives of our study were to quantitatively characterize the spatiotemporal patterns of urbanization in Shanghai in recent decades, identify possible spatial signatures of different land use types, and test the diffusion coalescence hypotheses of urban growth. We found that, similar to numerous cities around the world reported in previous studies, urbanization increased the diversity, fragmentation, and configurational complexity of the urban landscape of Shanghai. In the same time, however, the urban–rural patterns of several land use types in Shanghai seem unique—quite different from previously reported patterns. For most land use types, each showed a distinctive spatial pattern along a rural–urban transect, as indicated by landscape metrics. Furthermore, the urban expansion of Shanghai exhibited an outward wave-like pattern. Our results suggest that the urbanization of Shanghai followed a complex diffusion–coalescence pattern along the rural–urban transect and in time.     

A method for the use of landscape metrics in freshwater research and management

Freshwater research and management efforts could be greatly enhanced by a better understanding of the relationship between landscape-scale factors and water quality indicators. This is particularly true in urban areas, where land transformation impacts stream systems at a variety of scales. Despite advances in landscape quantification methods, several studies attempting to elucidate the relationship between land use/land cover (LULC) and water quality have resulted in mixed conclusions. However, these studies have largely relied on compositional landscape metrics. For urban and urbanizing watersheds in particular, the use of metrics that capture spatial pattern may further aid in distinguishing the effects of various urban growth patterns, as well as exploring the interplay between environmental and socioeconomic variables. However, to be truly useful for freshwater applications, pattern metrics must be optimized based on characteristic watershed properties and common water quality point sampling methods. Using a freely available LULC data set for the Santa Clara Basin, California, USA, we quantified landscape composition and configuration for subwatershed areas upstream of individual sampling sites, reducing the number of metrics based on: (1) sensitivity to changes in extent and (2) redundancy, as determined by a multivariate factor analysis. The first two factors, interpreted as (1) patch density and distribution and (2) patch shape and landscape subdivision, explained approximately 85% of the variation in the data set, and are highly reflective of the heterogeneous urban development pattern found in the study area. Although offering slightly less explanatory power, compositional metrics can provide important contextual information.     

Temporal variation of characteristic scales in urban landscapes: an insight into the evolving internal structures of China’s two largest cities

Urbanization has induced profound landscape changes. While the spatiotemporal patterns of urban landscapes have been extensively studied, the manner by which the internal structures of already urbanized areas change remains little understood. Characteristic scales are an important measure of landscape structure, and they represent the typical spatial extents of landscape elements in hierarchies. In this study, we quantified temporal variations of the characteristic scales in the central urban landscapes of Beijing and Shanghai over an 18?year period. Using transect data from Landsat images, characteristic scales were identified through wavelet analysis and then classified into several discrete domains using the k-means clustering method. These characteristic scale domains appeared to correspond with the typical extents of the blocks and block clusters in the study areas. Results showed that the number of the characteristic scale domains changed within a small range of 3?C5 while the mean values of the characteristic scales within the domains showed substantial temporal variation. Larger characteristic scales were more variable than smaller ones in both cities. Distinguishing relative change rates of building forms, land use and street layout of urban landscapes allowed us to interpret these differences. The street layout of urban landscapes usually reacts slowly to the force of change, acting as the skeleton of the urban landscape. As a result, block sizes can remain relatively stable and corresponding characteristic scales present inheritance features. Land use and building forms are more susceptible to changes. Block clusters with flexible extents could result in significant variation of characteristic scales.     

Soil occupation efficiency and landscape conservation in four Mediterranean urban regions

This study investigates the relationship between soil sealing and landscape conservation in four Mediterranean regions (Athens, Barcelona, Lisbon, Rome) characterized by different patterns of urban expansion. Per-capita sealed land, a landscape conservation index and selected territorial variables were considered into a multivariate exploratory framework aimed at assessing the correlation between land-use efficiency (based on the degree of soil sealing per-capita) and the quality of suburban landscape. A population density gradient with intensity of sealed land decreasing with the distance from the central city was observed in compact urban regions such as Athens and Barcelona. A mixed urban gradient was observed in Rome and Lisbon. In all the considered cities the spatial distribution of per-capita sealed land was not correlated with the urban gradient indicating that land consumption follows place-specific patterns irrespective of landscape quality. These findings suggest that urban containment and landscape conservation are policy targets requiring environmental measures irrespective of the prevailing morphology of the urban region (compact vs dispersed). In this context, green infrastructure planning is a promising tool for landscape conservation and the containment of soil sealing within fragile and dynamic contexts such as the wildland-urban interface.     

Green and calm: Modeling the relationships between noise pollution propagation and spatial patterns of urban structures and green covers

The mechanism of noise pollution propagation is considerably affected by 1) the type and configuration of its receiving environment and 2) the distance that sound waves pass to reach that environment. This study adopts a spatio-statistical approach to quantify and model associations between noise pollution levels and landscape metrics of land categories (built-up structures and urban green covers). Accordingly, noise levels were measured employing a sound pressure meter to quantify equivalent levels (Leq in dB A), in addition to their corresponding percentiles (L₁₀ and L₉₀). A collection of 30 sampling points were selected to measure noise data within the fall season and between 4 p.m. and 8 p.m. hours of the day. A hierarchical distance-sampling framework based on buffer areas with different radius (300 m, 600 m and 1 km) around each sampling point was compiled to measure composition and configuration metrics of land categories within each buffer area. The results derived from Pearson correlation analysis and multiple-linear regression models indicated that there is a distance-dependent relationship between the metrics of green areas and noise levels. We didn’t find remarkable distance-dependency between built-up structures and noise levels. Based on our new spatio-statistical approach, we conclude that more connected and compacted pattern of green areas closer to pollution centers can significantly alleviate the effects of noise propagation mechanism and appropriate pattern of built-up areas follows a low density distribution with coming green areas in between. Findings of this study highlight the potential of landscape ecology approach as an effective planning paradigm for designing greener and calmer cities.     

Impacts of road corridors on urban landscape pattern: a gradient analysis with changing grain size in Shanghai, China

Urbanization is one of the most important driving forces for land use and land cover change. Quantifying urban landscape pattern and its change is fundamental for monitoring and assessing ecological and socioeconomic consequences of urbanization. As the largest city in the country, Shanghai is now the fastest growing city in China. Using land use data set of 2002 and combining gradient analysis with landscape metrics, we analyzed landscape pattern of Shanghai with increasing grain size to study the impacts of road corridors on urban landscape pattern. Landscape metrics were computed along a 51×9 km² transect cutting across Shanghai with a moving window. The results showed that the urban landscape pattern of Shanghai was greatly changed when road corridors were merged with urban patches and the variation of patch density would alter when grain size changed. As a linear land use type, road corridors exhibited a different spatial signature comparing with other land use types and distinctive behavior with increasing grain size. Merging road and urban patches resulted in a sharp reduction in patch density, mainly caused by segmentation of roads corridors. The results suggested that grain size around 7.5 m might be optimal for urban landscape analysis. Landscape patch density is significantly correlated with road percent coverage and the most important effect of road corridors in urban landscape is increased habitat fragmentation.     

Challenges in marine,soft-sediment benthoscape ecology

The thematic resolution of mapped data determines the amount of detail of geospatial information, and influences various aspects of landscape classification and the relevance of derived pattern attributes to particular ecological questions. Here we show that changing thematic resolution may significantly affect landscape metrics and in turn their ability to detect landscape changes. The effects of thematic resolution on many landscape metrics tend to show consistent general patterns, but the details of these patterns are likely to be dependent on specific landscape patterns and classification criteria. Thus, the effects of thematic resolution, like those with regard to grain and extent, must be considered in landscape pattern analysis.     

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.     

The utility of ancient forest indicator species in urban environments: A case study from Poznań, Poland

We aimed to assess the impact of land-use structure on AFIS occurrence and evaluation of these bioindicators in urban conditions. We compiled data about forest continuity based on archival maps and forest management plans; floristic records of 79 AFIS occurrences were collected within a 1 × 1 km grid and land-use form structure in Poznań (W Poland). We tested fidelity of AFIS using χ² tests and effects of land-use structure using random forest models. We also checked spatial autocorrelation and its impact on AFIS distribution patterns within old and recent forests, using spatially explicit generalized linear models. We found a strong relationship between AFIS number per grid square and fraction of forests and waters in land-use structure. Relationships between AFIS distribution and land-use shows that AFIS are a good proxy describing human impact or an urbanity gradient. AFIS number per grid square shows small, but significant positive spatial autocorrelation, which suggests possibilities of migration into new forests. AFIS, treated as a bioindicative group of species, may be a useful indicator of landscape and land-use structure transformation in urban environments. Occurrence of many AFIS that are endangered at the city scale indicates the need for conservation of old forests in urban areas, to preserve biodiversity in urban environments. Thus, AFIS may act as indicators of old forests with high conservation value in cities, which need special protection.     

Impact of error on landscape pattern analyses performed on land-cover change maps

Researchers have emphasized the value of linking observed patterns of land-cover change to the processes driving changes in land-use to explain the dynamics of a land change system. The association of pattern and process requires an accurate quantification of the spatial characteristics of land-cover change. The objective of this research is to assess the impact of error on the accuracy of landscape pattern analyses performed on maps of change. Simulation was used to develop of a series of error-free and error-perturbed change maps, which varied with respect to the pattern of change occurring between the time-1 and time-2 land-cover maps and the patterns of error associated with the time-1 and time-2 land-cover maps. A variety of change and error patterns were examined. The error-free and error-perturbed change maps were compared by calculating landscape pattern metrics, which revealed the degree to which error altered the pattern of change. The introduction of error notably changed the structure of the persistent and transitioning classes, with metrics indicating a more fragmented and variable landscape under error. Agreement between the error-free and error-perturbed maps improved when a greater amount of change occurred within the time-series, change was concentrated at the boundaries of land-cover classes and when time-2 errors were increasingly correlated to their time-1 counterparts. These results have several implications for change pattern analyses given the fundamental nature of land-cover change.