Landscape Pattern Metrics Research Articles

Impacts of Transportation Networks on the Landscape Patterns—A Case Study of Shanghai

During 1995–2010, a comparison of the comprehensive effects of four different types of urban roads on landscape diversity in Shanghai was performed. Remote sensing images from 1995, 2000, 2005, and 2010 and the transfer matrix mathematical model were used to conduct the research, which focused on studying the rule of land use change in the study area over the past 15 years. Seven different landscape indices (SHDI, SHEI, ED, NP, TE, AWMSI, and MSI) were also selected to analyze the landscape pattern of Shanghai in three different periods and to explore the regularity of its dynamic changes and influential factors. Buffer analysis and statistical analyses were applied to represent the relationship between the distance from different roads quantitatively (e.g., railway, highway, national highway, and provincial highway) and a series of landscape pattern metrics (e.g., SHDI, PD, ED, and IJI) thus exploring the influence of transportation routes on the surrounding ecological environment. The results showed that (1) each type of landscape in the study area changed considerably during the research periods, a great amount of cultivated land was transformed into construction land, and the water area largely decreased. (2) The transportation routes exerted different impacts on the road landscape during different periods, and the effects were more obvious at the early stage of road construction. (3) The national way and the highway influenced the patch density (PD) index and edge density (ED) index more clearly, while the national way and the railway had greater effects on the landscape diversity indices. This study presents an approach that can be applied to quantitatively describe the impacts of transportation routes on landscape patterns and has the potential to facilitate route network planning.

Assessing spatial–temporal heterogeneity of China’s landscape fragmentation in 1980–2020

Exploring the spatial–temporal heterogeneity of landscape fragmentation contributes to realizing the dynamic evolution of the landscape pattern and understanding the impacts of physical-geographical environment and human activities on landscape systems. Differing from previous studies that focused on using single landscape pattern metrics to characterize the landscape fragmentation, this study proposed a Landscape Fragmentation Index (LFI) to assess and analyze the spatial–temporal heterogeneity of China’s landscape fragmentation in 1980–2020. The result showed that the landscape pattern metrics characterizing patch size, patch shape, patch density, patch type, patch cluster, and patch distance were equipped with obvious phased change characteristics, and all of them have successively undergone the stable phase, fluctuation phase, and adjustment phase. In 1980–2020, China’s LFI was gradually increased to 0.393 from 0.383, annually rising by 0.07 percent points on average. Also, the annual average growth of urbanization rate and GDP respectively reached 1 percent point and 9.26 percent points. Besides, regarding spatial pattern, the landscape fragmentation showed relatively obvious fluctuation features in Southwest-Northeast (Hu Line) and Northwest-Southeast (Bole-Taipei Line) directions and Hu Line was manifested as the dividing line of landscape fragmentation while Bole-Taipei Line was shown as the equilibrium line. Spatial-temporal heterogeneity of China’s landscape fragmentation indicated that the fragmented landscape pattern was the combined effect of the physical-geographical environment and human activity interference.

Non-linearity impacts of landscape pattern on ecosystem services and their trade-offs: A case study in the City Belt along the Yellow River in Ningxia, China

Exploring the impacts of landscape pattern on ecosystem services (ESs) and their trade-offs could provide a new way to improve ESs without largely altering land use types. Using the City Belt along the Yellow River in Ningixa (CBYN) as a case study, we quantified five critical ESs (one provision service of crop production, three regulating services of carbon sequestration, nutrient retention and sand fixation, and one cultural service of recreational opportunity) in 1989–2019 through CASA model, InVEST model and empirical equations. Then we calculated landscape pattern metrics at landscape and class level through Fragstats 4.3 across multiple scales and quantified their impacts on each ES and ES trade-offs through random forest analysis, self-organizing mapping analysis and multivariable regression tree. The results suggested that 3 km is more suitable for analyzing the impacts of landscape pattern on ESs in the CBYN. The nonlinear relations between landscape pattern metrics and each ES were fitted with adjusted R2 ranging from 0.26 to 0.51, indicating the significant but limited impacts of landscape pattern on ESs. Specially, landscape-level metrics of CONTAG, SHDI and FRACMN have higher impacts on ESs than class-level ones. Significant synergies existed among agricultural production, carbon sequestration and nutrient retention, except in mountain region with higher or lower fragmentation. Sand fixation has synergy relations with the former three ESs, which would be altered in situations with higher or lower diversity. Our results provide a new direction for land use management to achieve high-quality development without largely altering existing land use situation.

Distribution and functional traits of small mammals across the Mediterranean area: landscape composition and structure definitively matter

• Small mammals’ taxonomic and functional composition vary with landscape pattern. • Species assemblages tend to be simpler in anthropogenic landscapes. • Seminatural and anthropogenic landscapes influence functional composition. • Understanding community assembly could help prioritise conservation actions. Mediterranean landscapes constitute a biodiversity hotspot where species distribution and composition have been shaped by a long history of traditional land use. In this work, we investigated the effects of landscape patterns on community composition and the functional, morphological, and ecological traits of 21 small mammal species in the Mediterranean region. We extracted species abundance and trait data from 86 georeferenced Common Barn-owl pellet sites collected in Central Italy, covering 33,000 km 2 , and stored in the OpenMICE database. Additionally, we measured 12 landscape metrics on land cover maps produced at intervals coeval with pellet collection dates. We explored the variation in species composition against landscape pattern metrics using canonical correspondence analysis (CCA). Moreover, we analysed the relationships among small mammals’ occurrence, their life history traits, and landscape pattern metrics using the fourth-corner model approach. Our results highlighted the key role of landscape composition and configuration in shaping small mammal species composition and their functional traits. Species and trait composition varied along two main landscape gradients, with a simplification of species assemblage towards increasing human pressure (i.e., artificial surfaces and agricultural areas) and decreasing cover of seminatural areas. The observed variability of species assemblages and functional traits across Mediterranean landscape gradients highlights the need to preserve diverse ecosystems and land cover types to maintain small mammal biodiversity and related ecosystem functioning.

Characterization of the spatial distribution of plateau pika burrows along an alpine grassland degradation gradient on the Qinghai-Tibet Plateau.

Plateau pika burrows are common feature of degraded grassland in the Qinghai–Tibet Plateau (QTP) and serve as an important indicator of pika activity and grassland degradation. However, the current understanding of the spatial pattern changes of pika burrows and their critical thresholds across a degradation gradient in alpine grassland is deficient. In this study, we investigated and quantified changes in the spatial pattern of plateau pika burrows under typical degraded alpine shrub meadows in the northeastern QTP using an unmanned aerial vehicle and landscape pattern metrics. The degradation of the alpine shrub meadow leads to a change in landscape pattern from a two‐layered structure of alpine shrub and alpine meadow to a mosaic of alpine meadow and bare soil, with plateau pika burrows scattered throughout. Moderate degradation is the tipping point for changes in surface landscape patterns, followed by the disappearance of alpine shrub, the retreat of alpine meadows and the encroachment of bare soil, and the increasing density and size of pika burrows. The area characteristics of alpine meadows have influenced changes in the spatial pattern of pika burrow, and maintaining its proportional area is a vital measure to control the threat of pika burrows to pastures. The results of this paper provide a methodological reference and guidance for the sustainable utilization of grassland on the QTP.

Effects of Urbanization on Landscape Patterns in the Middle Reaches of the Yangtze River Region

The middle reaches of the Yangtze River region (MRYRR) are China’s first trans-regional urban agglomeration, located in the center of the Yangtze River Economic Belt. The MRYRR is an important ecological reserve, and its land cover changes are affected by both socio-economic development and geographical environment. In this paper, Landsat ETM/TM/OLI remote sensing images were used to monitor land use and landscape patterns from 1990 to 2015. Through supervised classification, land use transfer matrix, landscape pattern metrics and correlation analysis, the spatial-temporal patterns of land use change and its relationship with socio-economic in the study area were revealed. The results showed that: (1) the main land use types in the study area were cropland (CL) and forestland (FL), accounting for more than three-quarters of the study area. During the study period, built-up land (BL) increased, CL decreased, FL increased first and then decreased; (2) the BL expanded mainly by occupying CL and FL, and regional landscape pattern was gradually fragmented, with complex patch shape and increasing diversity and heterogeneity. Among them, the BL is gradually gathered, and the FL and CL are gradually fragmented; (3) in the past 25 years, the urbanization process in this region has been obvious, and the Gross Domestic Product (GDP) has increased by 36 times. The socioeconomic variables were positively correlated with BL, orchard (OL) and Shannon diversity index (SHID), and negatively correlated with CL, Wasteland (WL), mean patch size (MPS) and contagion size (CONTAG). The results showed that the urbanization development has a great impact on the region, and the ecological protection task is still challenging. It is necessary to protect high-quality cropland and draw a red line for ecological protection. We should strengthen the construction of ecological corridors and ecological nodes to adapt to regional sustainable development.

Interaction between the characteristics of urban three-dimensional landscape pattern and social-environmental factors based on boosted regression tree

Vertical expansion makes the structure and pattern of the city more complicated. Traditional two-dimensional landscape pattern cannot completely reflect the ecological structure and functional characteristics of urban landscape. In this study, we used the three-dimensional landscape pattern metrics to quantify the regional three-dimensional landscape pattern, and used boosted regression tree (BRT) machine learning algorithms to comprehensively analyze the interaction between social-environmental factors and urban landscape patterns in the central part of Shanghai. Results showed that high building ratio, mean architecture height, and architecture height standard deviation had higher values in the surrounding area of the inner ring. The number of buildings and landscape shape index were higher in the outer ring than those in other area. Building coverage ratio, floor area ratio and Shannon's diversity index had higher values in the central part, with the metrics of Puxi being generally higher than those of Pudong. Population density and normalized vegetation index (NDVI) interacted most significantly with the three-dimensional landscape pattern, with GDP as the least influential factor. Within a certain range, the three-dimensional landscape pattern metrics increased with larger population density in the social factors, and decreased with lower rate of NDVI and water surface ratio in the environmental factors. Our results demonstrated that the BRT method was effective in quantifying the interaction between landscape pattern and social-environmental factors. Our results help improve the understanding of the relationship between ecological environment and human well-being in the central part of Shanghai and provide a scientific basis for the urban three-dimensional expansion planning.

Characterizing historical transformation trajectories of the forest landscape in Rome's metropolitan area (Italy) for effective planning of sustainability goals

AbstractWith the aim at developing a landscape dynamics framework for environmental planning and management and testing the effectiveness of protected areas in achieving the 2030 Agenda of the United Nations sustainability goals, we characterized the historical transformation trajectories of forest area changes from 1936 to 2010 in the Metropolitan City of Rome Capital (Italy). Remote sensing‐based products coupled with landscape pattern metrics and fragmentation analysis have been implemented, comparing different historical forest maps. The results show a remarkable forest area gain – from 17.6% to 25.5% – thanks to 68,299 ha of recently established forest. Statistical descriptors showed that the highest relative gain occurred in mountain zones, confirming a wide European forest recovery pattern in marginal areas from past deforestation and overexploitation. Deforestation mainly occurred in the flat and hilly areas where almost 26,000 ha of forests were lost since 1936. In summary, two main forest landscape dynamics were reconstructed: (I) the increase of forest cover fragmentation in the lowland areas; and (II) the rise in the forest area in the interior sectors of the mountain landscape, mainly within protected areas. Restoring the forest ecosystem's bioecological integrity has been highlighted as an urgent action for biodiversity conservation and carbon mitigation. In lowland areas, the study revealed the urgent need to establish new protected areas and rewilding spaces as landscape metrics are relatively below the sustainability targets for healthy forest ecosystems. The proposed framework can be used for testing the effectiveness of environmental planning and management in other forest landscapes to achieve the Agenda 2030 goals.

Using landscape metrics to characterize towns along an urban-rural gradient

ContextUrban-rural gradients are useful tools when examining the influence of human disturbances on ecological, social and coupled systems, yet the most commonly used gradient definitions are based on single broad measures such as housing density or percent forest cover that fail to capture landscape patterns important for conservation.ObjectivesWe present an approach to defining urban–rural gradients that integrates multiple landscape pattern metrics related to ecosystem processes important for natural resources and wildlife sustainability.MethodsWe develop a set of land cover composition and configuration metrics and then use them as inputs to a cluster analysis process that, in addition to grouping towns with similar attributes, identifies exemplar towns for each group. We compare the outcome of the cluster-based urban-rural gradient typology to outcomes for four commonly-used rule-based typologies and discuss implications for resource management and conservation.ResultsThe resulting cluster-based typology defines five town types (urban, suburban, exurban, rural, and agricultural) and notably identifies a bifurcation along the gradient distinguishing among rural forested and agricultural towns. Landscape patterns (e.g., core and islet forests) influence where individual towns fall along the gradient. Designations of town type differ substantially among the five different typologies, particularly along the middle of the gradient.ConclusionsUnderstanding where a town occurs along the urban-rural gradient could aid local decision-makers in prioritizing and balancing between development and conservation scenarios. Variations in outcomes among the different urban-rural gradient typologies raise concerns that broad-measure classifications do not adequately account for important landscape patterns. We suggest future urban-rural gradient studies utilize more robust classification approaches.

Spatial-temporal variations of landscape pattern and hot spot analysis in the Lixiahe Plain of Jiangsu Province from 1980 to 2018

Objective With an exploration of the temporal and spatial changes of landscape pattern as well as an investigation of its cold and hot spots, this paper is aimed to provide a scientific basis for regional ecological security and high-quality development. Method With landscape type data collected of the Lixiahe Plain, Jiangsu Province over the five periods of 1980, 1990, 2000, 2010 and 2018, an analysis was made of the characteristics of temporal and spatial changes of its landscape pattern in the past 40 years using landscape pattern metrics, transfer matrix and comprehensive dynamic index. Then, an investigation was conducted of the cold and hot spot regions of landscape changes on the basis of hot spot analysis. Result Cultivated land, lake wetland and construction land were the dominant landscape types in the study area with the coverage of cultivated land accounting for the largest proportion, but having decreased by 1 000.67 km2 in the past 40 years whereas the areas of lake wetland and construction land increasingly expanded, with the area of construction land increasing by 679.83 km2 and the area of grassland and unused land showed a slightly decreasing trend, while that of forest increased slightly. The landscape types had undergone complex mutual transformations in the past 40 years with those of cultivated land, lake wetland and construction land being the most remarkable with the comprehensive dynamic index of the grid landscape varying between 0 and 5.43% over the study period. The landscape change of the Lixiahe Plain had obvious directionality and agglomeration: the center of change was tilted along the “southeast-northwest” direction, and the hot spots of landscape change were located at Xinghua City, Gaoyou City, Yandu District and Jiangdu District. Conclusion The landscape pattern of the Lixiahe Plain underwent significant changes due to the increase of landscape diversity and the intensification of fragmentation and the impact of human activities on the landscape pattern. The implementation of the natural wetland restoration policy had a positive impact on the landscape ecological security in the Lixiahe Plain. [Ch, 4 fig. 4 tab. 32 ref.]

Impacts of Landscape Patterns on Ecosystem Services Value: A Multiscale Buffer Gradient Analysis Approach

In recent decades, substantial changes have occurred in the spatial structure and form of landscapes in metropolises; these have greatly impacted ecosystem provision capacities. Clarifying the impact mechanism of landscape patterns on ecosystem services can provide insights into regional ecological conservation and sustainable development measures. Although previous studies have explored the impacts of landscape patterns on ecosystem services at multiple scales, few studies have been conducted using the buffer gradient analysis approach. Using land-use/cover change data, this study measured the evolution of spatiotemporal features of landscape patterns and ecosystem services value (ESV) with 1, 2, and 3 km buffer-zone scales in Wuhan, China. Econometric models were then used to analyze the impacts of landscape patterns on ecosystem services at different buffer-zone scales. The results demonstrated that rapid urbanization in Wuhan has led to significant changes in landscape patterns, and the landscape pattern metrics exhibited significant spatial heterogeneity. The ESV in Wuhan exhibited a steady decline during the study period. Hydrological regulations and waste treatment functions contributed to the largest proportion of ESV, and raw material production functions contributed to the lowest proportion. Landscape pattern metrics exerted a significant influence on ESV; however, this influence varied greatly. The results of this study provide a new understanding of the influence mechanism of landscape patterns on ecosystem services at 1, 2, and 3 km buffer-zone scales. These findings are critical for facilitating landscape planning and regional sustainable development.

Spatiotemporal Dynamics of Urban Green Space Influenced by Rapid Urbanization and Land Use Policies in Shanghai

Urbanization has led to the continuous expansion of built-up areas and the ever-growing urban population, threatening the quantity and quality of urban green space (UGS). Exploring the spatiotemporal variations of UGS is substantially conducive to the formulation of land-use policies to protect the ecosystems. As one of the largest megacities all around the world, Shanghai has experienced rapid urbanization in the past three decades. Insights into how UGS changes in response to urbanization and greening policies are essential for guiding sustainable urban development. This paper employed integrated approaches to characterize the changing patterns and intensities of green space in Shanghai, China from 1990 to 2015. The spatiotemporal dynamics of the UGS pattern were derived through four main methods: green space ratio, dynamic change degree (DCD), transition matrix and landscape metrics. The results showed that Shanghai’s green space decreased from 84.8% in 1990 to 61.9% in 2015 while the built-up areas increased from 15.0% to 36.5%. Among the green space sub-types, farmland was largely encroached and fragmented by urban sprawl, especially in the Outer Ring Expressway and Suburban Ring Expressway belts of the city. About 1522 km2 of the green space has transferred into built-up areas, followed by farmland, waterbody, forest, and grassland in descending order. The 2000–2010 period witnessed the strong urban expansion and dramatic changes in UGS, but then the change around 2015 turned down and stable. The landscape pattern metrics showed that the entire green space in Shanghai was growingly fragmented and isolated during the past 25 years. Combined with the green space-related planning and policies issued in 1990–2015, the results revealed that both rapid urbanization and greening policies accounted for the spatiotemporal dynamics of UGS. Based on the results, some implicants to new urban planning and policies of Shanghai were highlighted.

Detecting urban landscape factors controlling seasonal land surface temperature: from the perspective of urban function zones.

Understanding the impact on the thermal effect by urbanization is of great significance for urban thermal regulation and is essential for determining the relationship between the urban heat island (UHI) effect and the complexities of urban function and landscape structure. For this purpose, we conducted case research in the metropolitan region of Beijing, China, and nearly 5000 urban blocks assigned different urban function zones (UFZs) were identified as the basic spatial analysis units. The seasonal land surface temperature (LST) retrieved from remote sensing data was used to represent the UHI characteristics of the study area, and the surface biophysical parameters, building forms, and filtered landscape pattern metrics were selected as the urban landscape factors. Then, the effects of urban function and landscape structure on the UHI effect were examined based on the optimal results of the ordinary least squares and geographically weighted regression models. The results indicated that (1) Significant spatiotemporal heterogeneity of the LST was found in the study area, and there was an obvious temperature gradient with "working-living-resting" UFZs. (2) All types of urban landscape factors showed a significant contribution to the seasonal LST, in the order of surface biophysical factors > building forms > landscape factors; however, their contributions varied in different seasons. (3) The major contributing factors showed a certain difference due to the variation of urban function and landscape complexity. This study expands the understanding on the complex relationship among urban landscape, function, and thermal environment, which could benefit urban landscape planning for UHI alleviation.

Scale-dependent effects of urban greenspace on particulate matter air pollution

Atmospheric particulate matter (PM) pollution has become a major global public health concern, particularly in urbanizing and rapidly developing nations such as China. Health effects from PM pollution include increases in cardiovascular and respiratory illnesses and problems during pregnancy and child development. Developing methods to mitigate PM pollution is a major priority for urban planning. Urban forests and other greenspaces are known to have both direct and indirect effects on PM concentrations, but uncertainty remains about how best to design greenspaces to reduce PM loads. This is partly because of contrasting effects that have been observed at different spatial scales. We used high-resolution satellite imagery and two years of daily PM concentration data from nine national air pollution monitoring stations in Zhengzhou, China, to examine the relative importance of seasonal cycling and greenspace effects on PM concentrations. We described patterns of urban greenspace at multiple spatial scales (buffer radii of 0.5 km – 3 km) using 15 different landscape pattern metrics. Multivariate methods (cluster analysis, principal component analysis) were used to process these into a smaller number of uncorrelated descriptors that described major patterns of variation in greenspaces. Linear mixed models were used to model seasonal cycling and greenspace effects on PM10 and PM2.5 concentrations for each spatial scale. We found that: 1) monthly mean, maximum, and standard deviations of concentrations of both PM2.5 and PM10 showed stationarity across seasons and months, being greatest in winter and smallest in summer; 2) urban greenspace patterns did not significantly affect PM2.5 concentrations; 3) increasing the overall abundance of greenspace, and percentage of large greenspace patches, at almost all scales significantly reduced PM10 concentrations; and 4) at larger spatial scales, increasing the amount of contact between the edges of greenspace patches and the surrounding urban area could reduce PM10 concentrations. In the context of urban planning and renewal, it may be possible to reduce PM10 pollution by carefully planning the shape and layout of greenspace networks across scales.

Understanding the drivers of sustainable land expansion using a patch-generating land use simulation (PLUS) model: A case study in Wuhan, China

Cellular Automata (CA) are widely used to model the dynamics within complex land use and land cover (LULC) systems. Past CA model research has focused on improving the technical modeling procedures, and only a few studies have sought to improve our understanding of the nonlinear relationships that underlie LULC change. Many CA models lack the ability to simulate the detailed patch evolution of multiple land use types. This study introduces a patch-generating land use simulation (PLUS) model that integrates a land expansion analysis strategy and a CA model based on multi-type random patch seeds. These were used to understand the drivers of land expansion and to investigate the landscape dynamics in Wuhan, China. The proposed model achieved a higher simulation accuracy and more similar landscape pattern metrics to the true landscape than other CA models tested. The land expansion analysis strategy also uncovered some underlying transition rules, such as that grassland is most likely to be found where it is not strongly impacted by human activities, and that deciduous forest areas tend to grow adjacent to arterial roads. We also projected the structure of land use under different optimizing scenarios for 2035 by combining the proposed model with multi-objective programming. The results indicate that the proposed model can help policymakers to manage future land use dynamics and so to realize more sustainable land use patterns for future development. Software for PLUS has been made available at https://github.com/HPSCIL/Patch-generating_Land_Use_Simulation_Model

Quantifying effects of urban land-use patterns on flood regimes for a typical urbanized basin in eastern China

Abstract Artificial adjustment and urbanization are key factors of global change and have significant influences on hydrological processes. This study focuses on the effects of urban land-use patterns on flood regimes in a typical urbanized basin in eastern China. Comprehensive assessments of urban land-use patterns were implemented on three levels: total imperviousness area (TIA) magnitude, landscape configuration and relative location in the basin. Hydrologic Engineering Center's Modeling System (HEC-HMS) was calibrated and validated using four groups of parameters associated with land-use conditions. Fourteen flood events were simulated based on 10 land-use scenarios with different land-use patterns. The results indicate that floods are closely associated with three landscape pattern indicators. First, over the past 20 years, the impermeability rate has increased from 3.92 to 17.48%, with the landscape pattern converted from extension growth form to fill-up growth form after 2003. Second, the average flood peak discharge increased by 80% due to impermeable surfaces expansion, with minor floods more sensitive to the expansion than major floods. Third, the contribution of imperviousness expansion to peak discharge in the inner basin is more remarkable than downstream of the river basin, with the landscape pattern metrics of TIA, arable land and forest land displaying strong correlations with flood characteristics.

Effects of Green Space Patterns on Urban Thermal Environment at Multiple Spatial–Temporal Scales

Land use/land cover (LULC) pattern change due to human activity is one of the key components of regional and global climate change drivers. Urban green space plays a critical role in regulating urban thermal environment, and its cooling effect has received widespread attention in urban heat island (UHI) related studies. To fully understand the effects of the landscape pattern of an urban green space in regulating the urban thermal environment, it is necessary to further study the thermal effects of the landscape pattern of the urban green space and its characteristics under varied spatial–temporal scales. In this paper, we took the urban core area of Hangzhou City as the study area and analyzed the relationships between the landscape metrics of the urban green space and land surface temperature (LST) under varied spatial scales by using correlation analysis and redundancy analysis (RDA) methods. Multi-temporal Landsat 8 thermal infrared sensor data were used to retrieve the spatial and temporal dynamics of LSTs in four consecutive seasons, and the land use classification was interpreted using SPOT (Systeme Probatoire d’Observation de la Terre) satellite imagery. The results showed that landscape dominance metrics—e.g., percentage of landscape (PLAND) and largest patch index (LPI)—were the most influential factors on urban LST. The spatial configuration of urban landscape, as represented by the fragmentation and aggregation and connectedness, also showed significant effects on LST. Furthermore, landscape pattern metrics had varied spatial scale effects on LST. Specifically, the landscape dominance metrics of urban forest showed an increased influence on LST as the spatial scale increased, while for urban water, the trend was opposite. These findings might have some practical significance for urban planning about how to spatially arrange urban green space to alleviate UHI at local and regional scales.

Identifying the Impact of Landscape Pattern on Ecosystem Services in the Middle Reaches of the Yangtze River Urban Agglomerations, China.

Clarifying the impact mechanisms of landscape patterns on ecosystem services is highly important for effective ecosystem protection, policymaking, and landscape planning. However, previous literature lacks knowledge about the impact mechanisms of landscape patterns on ecosystem services from a spatial perspective. Thus, this study measured landscape patterns and the ecosystem services value (ESV) using a series of landscape pattern metrics and an improved benefit transfer method based on land-use data from 2015. It explores the impact mechanisms of the landscape pattern metrics on the ESV using the ordinary least-squares method and spatial regression models in the middle reaches of the Yangtze River Urban Agglomerations (MRYRUA), China. We found that forestland was the main landscape type in the MRYRUA, followed by cultivated land, and the fragmentation degree of cultivated land was significantly higher than that of forestland. The findings demonstrate that landscape pattern metrics had a significant impact on ecosystem services, but could vary greatly. Moreover, ecosystem services in the MRYRUA exhibited significant spatial spillover effects and cross-regional collaborative governance was an effective means of landscape planning. This paper acts as a scientific reference and effective guidance for landscape planning and regional ecosystem conservation in MRYRUA and other similarly fast-growing urban agglomerations.

Spatial scale effects of the variable relationships between landscape pattern and water quality: Example from an agricultural karst river basin, Southwestern China

Understanding the spatially varying relationships between landscape pattern and water quality in the agricultural karst river system is helpful for landscape planning and management to protect water quality. In this study, empirical models were established to examine the impact of landscape pattern on the seasonal water quality at multi-spatial scales in a typical karst river basin in Southwestern China. Water samples from the Chishui River basin were collected and analysed during both the wet and dry seasons. Kruskal–Wallis tests revealed significant seasonal variations in water physic-chemical parameter variables, the values of which were all generally higher in the wet period than those in the dry period except for pH and SO42−. Moreover, the nutrient indicators including NO3−-N, PO43−-P, DOC and DSi showed obvious spatial variations, some of which were related to the spatial distribution of cropland that reflected the agricultural activities of the basin. Redundancy analysis results indicated that the landscape pattern metrics can better explain the variation of water physic-chemical parameters in the dry period than in the wet period. The results revealed that the overall variations of water physic-chemical parameters were better explained by landscape pattern metrics at catchment scales. Further, the results of multiple linear regression model showed that the scale effects of the relationship between landscape pattern and water quality varied across different metrics and parameters. The geographical characteristics of catchment had significant relationships with some water physic-chemical parameters, suggesting that it may have impacts on water quality through combining with land use. This study highlights the importance of spatial scale in reflecting land-water interactions.

Mapping Suburbs Based on Spatial Interactions and Effect Analysis on Ecological Landscape Change: A Case Study of Jiangsu Province from 1998 to 2018, Eastern China

As the transitional area between urban and rural areas, land-use change in suburbs is drastic, which generates negative effects on the ecological environment. However, the identification of the suburbs remains controversial. Usually, the density of the population and residential land is referenced, and the close spatial interactions between urban areas and suburbs are generally neglected. To fill this research gap, this study adopts a case study method to map the suburbs of Jiangsu based on estimating the spatial interactions. First, a regression model is built to estimate the population distribution. Second, a radiation model is utilized to evaluate the spatial interaction at a grid level. After the main urban area is identified based on the high density of the population and construction land, the interaction strength between the main urban grid and other grid areas is calculated, and the grids that share high values of interaction strength with urban grids are identified as suburban areas. Finally, the suburbs of Jiangsu in 1998 and 2018 are mapped, and the ecological landscape pattern metrics are used to verify the effects of suburban expansion. As a result, the suburban expansion of Jiangsu over the 20 years was significant, and the effects of suburban expansion on ecological land fragmentation were evident. On the basis of the results, the enlightenment of mapping suburbs on ecological landscape planning is discussed.