Perimeter-area Fractal Dimension Research Articles

How many parameters are needed to represent polar sea ice surface patterns and heterogeneity?

Abstract. Sea ice surface patterns encode more information than can be represented solely by the ice fraction. The aim of this paper is thus to establish the importance of using a broader set of surface characterization metrics and to identify a minimal set of such metrics that may be useful for representing sea ice in Earth system models. Large-eddy simulations of the atmospheric boundary layer over various idealized sea ice patterns, with equivalent ice fractions and average floe areas, demonstrate that the spatial organization of ice and water can play a crucial role in determining boundary layer structures. Thus, various methods used to quantify heterogeneity in categorical lattice-based spatial data, such as those used in landscape ecology and Geographic Information System (GIS) studies, are employed here on a set of recently declassified high-resolution sea ice surface images. It is found that, in conjunction with ice fraction, patch density (representing the fragmentation of the surface), the splitting index (representing variability in patch size), and the perimeter–area fractal dimension (representing the tortuosity of the interface) are all required to describe the two-dimensional pattern exhibited by a sea ice surface. For surfaces with anisotropic patterns, the orientation of the surface relative to the mean wind is also needed. Finally, scaling laws are derived for these relevant landscape metrics, allowing for their estimation using aggregated spatial sea ice surface data at any resolution. The methods used in and the results gained from this study represent a first step toward developing further methods for quantifying variability in polar sea ice surfaces and for parameterizing mixed ice–water surfaces in coarse geophysical models.

Fractal-Based Pattern Quantification of Mineral Grains: A Case Study of Yichun Rare-Metal Granite

The quantification of the irregular morphology and distribution pattern of mineral grains is an essential but challenging task in ore-related mineralogical research, allowing for tracing the footprints of pattern-forming geological processes that are crucial to understanding mineralization and/or diagenetic systems. In this study, a large model, namely, the Segmenting Anything Model (SAM), was employed to automatically segment and annotate quartz, lepidolite and albite grains derived from Yichun rare-metal granite (YCRMG), based on which a series of fractal and multifractal methods, including box-counting calculation, perimeter–area analysis and multifractal spectra, were implemented. The results indicate that the mineral grains from YCRMG show great scaling invariance within the range of 1.04~52,300 μm. The automatic annotation of mineral grains from photomicrographs yields accurate fractal dimensions with an error of only 0.6% and thus can be utilized for efficient fractal-based grain quantification. The resultant fractal dimensions display a distinct distribution pattern in the diagram of box-counting fractal dimension (Db) versus perimeter–area fractal dimension (DPA), in which lepidolites are sandwiched between greater-valued quartz and lower-valued albites. Snowball-textured albites, i.e., concentrically arranged albite laths in quartz and K-feldspar, exhibit characteristic Db values ranging from 1.6 to 1.7, which coincide with the fractal indices derived from the fractal growth model. The zonal albites exhibit a strictly increasing trend regarding the values of fractal and multifractal exponents from core to rim, forming a featured “fractal-index banding” in the radar diagram. This pattern suggests that the snowball texture gradually evolved from rim to core, thus leading to greater fractal indices of outer zones, which represent higher complexity and maturity of the evolving system, which supports a metasomatic origin of the snowball texture. Our study demonstrates that fractal analyses with the aid of a large model are effective and efficient in characterizing and understanding complex patterns of mineral grains.

Identifying the Relationships between Landscape Pattern and Ecosystem Service Value from a Spatiotemporal Variation Perspective in a Mountain–Hill–Plain Region

Identifying the changes in landscape pattern and ecosystem service value (ESV) and clarifying their relationship in temporal changes and spatial variations can provide insight into regional landscape features and scientific support for regional landscape planning. Leveraging land use data from the Yihe River Basin, we quantitatively assessed the landscape pattern and ESV shifts spanning from 2000 to 2018 using the landscape pattern indexes and the equivalence factor method. We employed Pearson correlation metrics and the geographically weighted regression model to explore the interrelation of their spatiotemporal variations. Our results show the following: (1) Forestland represents the most expansive land cover category. Apart from construction land, all other types experienced a decline in area. The most notable change occurred in the area of construction land. (2) The aggregation of the overall landscape shows a downward trend. The levels of fragmentation, landscape diversity, and richness increased. (3) Throughout the entire study period, the overall ESV gradually decreased, and the land cover type with the greatest contribution to the ESV was forestland. (4) In terms of temporal changes, the patch density and edge density of the overall area are significantly negatively correlated with total ESVs. The largest values for the patch index, perimeter–area fractal dimension (PAFRAC), and aggregation are significantly positively correlated with total ESVs. (5) In terms of spatial variation, the contagion index (CONTAG), PAFRAC, and the Shannon diversity index (SHDI) were noticeably correlated with ESVs. The CONTAG is positively correlated with ESVs upstream, but negatively midstream and downstream. The SHDI is negatively correlated with ESVs upstream, but positively midstream and downstream. The PAFRAC exhibits a positive correlation with ESVs for the most part. The association between the landscape pattern indexes and ESVs exhibits temporal and spatial inconsistencies in most instances, suggesting a spatiotemporal scale effect in their relationship. This study recommends that the local government devises a long-term strategy for urban development and exercises stringent control over the unregulated expansion of construction land. Through reasonable territorial spatial planning, government departments could enhance the connectivity of the overall landscape pattern of the Yihe River Basin to achieve the reasonable allocation and sustainable development of regional resources.

Impact of built environment on urban surface temperature based on multi-source data at the community level in Beilin District, Xi'an, China.

With the global warming and rapid urbanization in China, the urban built environment has undergone rapid changes, and the land surface temperatures (LSTs) of urban communities have obvious spatial heterogeneity. To explore the key driving factors of community LSTs, the multi-source data and spatial statistical methods being jointly used to analyze the spatial characteristics and main influencing factors of LST at the community level in the Beilin District of Xi'an City, China. The results are as follows: (1) Compared with communities dominated by construction land, communities with large area of green space and water bodies have lower LST. (2) According to the Akaike's information criterion (AICc) and maximum of adjusted R2, and other parameters, the No.1236 model was selected as the optimal model to analyze the influencing factors of community LST by exploratory data analysis, including building density (BD), building height standard deviation (BHS), percentage of public administration and public services land (PASL), percentage of green space and square land (PGSL), population density (POPD), normalized difference impervious surface index (NDISI), and perimeter-area fractal dimension (PAFRAC). (3) For each increase of one unit in NDISI and BHS when other factors remain unchanged, the LST will increase by 0.569°C and decrease by 0.478°C, respectively. (4) From the spatial stability and distribution of Local-R2, the warming factors of community LST are mainly NDISI, PAFRAC, BD, and PASL, while the cooling factors are BHS and PGSL. The spatial heterogeneity of community LST is not only related to the change of underlying surface properties but is also affected by intra-urban architectural morphology. Therefore, reasonable planning of urban built environment is of great significance for mitigating heat islands.

Regional proximity effects of landscape pattern evolution: Evidence from 325 county-level areas in the middle reaches of the Yangtze River, China

Unravelling the evolution of landscape patterns is essential to understand regional socio-ecological processes and to solve conflicts between environment protection and human development. However, the role of landscape transition in regional landscape pattern evolution remains unclear. Taking 325 county-level areas in the middle reaches of the Yangtze River (MRYR) as an example, this study explored the spatiotemporal associations between landscape quantity and pattern from the 1970s to 2020. Employing the methods of landscape metrics and trend and correlation analysis, associations between landscape transition and landscape pattern were found. The main results were as follows: (1) From the 1970s to 2020, urban land nearly doubled from 0.93 to 1.89 million km2. Arable land and forest showed the largest quantity reductions of 0.88 million km2 and 0.28 million km2, respectively. Other landscapes showed both decreasing and increasing trends with a spatial overlap among counties. (2) Transition in landscape quantity drives the change in landscape patches, thus affecting the landscape pattern in counties. The percentage of landscape area at the class level (CPLAND) showed relative changes in the quantities of landscape categories in each observation year, but their extreme outliers presented larger changes. (3) Diverse correlation coefficients in terms of magnitude and direction suggested that the transition from natural landscape to human-influenced landscape and the reverse processes occurred. Aggregation and diversity metrics showed spatial interaction with similar distances and the perimeter-area fractal dimension (PAFRAC) showed spatial autocorrelation at local scale. Optimal bandwidths among arable land, forest, and urban land (129.2 km) revealed direct spatial interactions and causal relationships, as did waters and unused land (66.7 km). The findings explained the evolution of landscape patterns and highlighted key areas where various landscape changes occurred, and can provide scientific support for policy-making in regional landscape transition governance.

Responses of the Siberian crane population to temporal and spatial hydrological variations in stopover sites in northeast China

The Siberian crane (Grus leucogeranus), a critically endangered species, is used as an indicator species for ecosystem stability because of its sensitivity to the environment. The distribution of Siberian cranes has shown dramatic fluctuations on an order of magnitude at the main stopover site (Jilin Momoge National Nature Reserve) since the present century, which poses a great challenge to the conservation of endangered species. Research on the threshold values of key factors of the Siberian crane in stopover habitats and the relationship between the Siberian crane and hydrological temporal and spatial fluctuations can promote endangered species conservation. The response of population changes and distribution patterns of Siberian cranes to hydrological temporal and spatial patterns of wetlands was analyzed from 1984 to 2020. The results showed that population changes and distribution patterns of Siberian cranes were highly correlated with hydrological temporal and spatial patterns in the study area, and their variation trend was the same. However, there were obvious stage migration changes in the core activity area of the Siberian crane (1984–2000, 2001–2010 and 2010–2020). The habitat characteristics of fragmentation, dispersion and complex shape of water bodies changed from steady to dramatic fluctuations and then leveled off in the core activity area of Siberian cranes during the 37 years of migration transit. This was closely related to the early agricultural reclamation and the later ecological water replenishment project in the study area. In addition, the trend of the water pattern index of the spatial distribution of Siberian crane active habitat was also closely related to their habitat selection preference. When the perimeter area fractal dimension of water (1.27–1.40), landscape division index (0.73–0.95) and aggregation index (80.97–91.36) are within a certain stable threshold, the stopover habitat of the Siberian crane is suitable. This study will provide scientific guidance for the conservation of the Siberian crane population and the development of wetland restoration projects.

Relationships between Landscape Patterns and Hydrological Processes in the Subtropical Monsoon Climate Zone of Southeastern China

With rapid economic development, extensive human activity has changed landscape patterns (LPs) dramatically, which has further influenced hydrological processes. However, the effects of LPs changes on hydrological processes, especially for the streamflow–sediment relationship in the subtropical monsoon climate zone, have not been reported. In our study, 10 watersheds with different sizes in the subtropical monsoon climate zone of southeastern China were chosen as the study area, and the effect of the 14 most commonly used landscape metrics (LMs) on 4 typical hydrological indices (water yields (WY), the runoff coefficient (RC), the soil erosion modulus (SEM), and the suspended sediment concentration (SSC)) were analyzed based on land use maps and hydrological data from 1990 to 2019. The results reveal that the LP characteristics within the study area have changed significantly. The number of patches and landscape shape indices were significantly positively correlated with watershed size (p < 0.01). For most watersheds, the largest patch index was negatively correlated with WY, RC, and SEM, and the perimeter area fractal dimension was positively correlated with WY, RC, SEM, and SSC. The effects of several LMs on the hydrological indices had scale effects. WY/RC and the interspersion and juxtaposition index were negatively correlated in most larger watersheds but were positively correlated in most smaller watersheds. Similar results were found for Shannon’s diversity/evenness index and SEM. In general, an increase in a small patch of landscape and in landscape diversity would increase WY, the fragmentation of LPs would result in more soil erosion, and LPs would affect the relationship between streamflow and sediment yield. As a result, a proper decrease in landscape fragmentation and physical connectivity in the subtropical monsoon climate zone of southeastern China would benefit soil erosion prevention. These results enhance the knowledge about the relationship between LPs and hydrological processes in the subtropical monsoon climate zone of southeastern China and benefit local water and soil conservation efforts.

Linkages between soil erosion and long-term changes of landscape pattern in a small watershed on the Chinese Loess Plateau

Understanding the response of soil erosion to the changes of land use and landscape pattern is valuable for the optimization of soil and water conservation measures in a watershed. This study selected a typical hilly-gully watershed of the Chinese Loess Plateau, the Zhifanggou watershed, to assess its long-term land use changes from 1938 to 2020 and their impacts on sediment yield by using the spatially distributed soil erosion model WaTEM/SEDEM with an average annual rainfall erosivity of 2000–2010. The results indicated that the main land use types in the Zhifanggou watershed were cropland, forest and grassland, and experienced two changing periods: rapid agricultural reclamation during 1938–1958 and vegetation restoration during 1958–2020. The average annual sediment yields varied consistently with land use changes, showing evident changes from 51.84 t ha−1 y−1 in 1938 to 254.1 t ha−1 y−1 in 1958 and then to 4.27 t ha−1 y−1 in 2020. Correlation analysis suggested that sediment yield was closely related to the landscape indices of interspersion and juxtaposition index and Perimeter-area fractal dimension. The results indicated that increased vegetation cover and high spatial heterogeneity of landscapes could alter sediment transport pathways, reduce sediment connectivity, and induce less sediment discharged into the river. Our findings could provide a good reference for optimizing soil and water conservation measures in the watershed.

Air Pollution and Human Health: Investigating the Moderating Effect of the Built Environment

Air pollution seriously threatens human health and even causes mortality. It is necessary to explore effective prevention methods to mitigate the adverse effect of air pollution. Shaping a reasonable built environment has the potential to benefit human health. In this context, this study quantified the built environment, air pollution, and mortality at 1 km × 1 km grid cells. The moderating effect model was used to explore how built environment factors affect the impact of air pollution on cause-specific mortality and the heterogeneity in different areas classified by building density and height. Consequently, we found that greenness played an important role in mitigating the effect of ozone (O3) and nitrogen dioxide (NO2) on mortality. Water area and diversity of land cover can reduce the effect of fine particulate matter (PM2.5) and NO2 on mortality. Additionally, gas stations, edge density (ED), perimeter-area fractal dimension (PAFRAC), and patch density (PD) can reduce the effect of NO2 on mortality. There is heterogeneity in the moderating effect of the built environment for different cause-specific mortality and areas classified by building density and height. This study can provide support for urban planners to mitigate the adverse effect of air pollution from the perspective of the built environment.

三峡库区低山丘陵区多尺度景观指数响应及适宜粒度

PDF HTML阅读 XML下载 导出引用 引用提醒 三峡库区低山丘陵区多尺度景观指数响应及适宜粒度 DOI: 10.5846/stxb202106081511 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 三峡库区农林复合小流域土壤氮磷流失与径流侵蚀耦合机制研究（32171877） Suitable granularity and response of multi-scale landscape in low mountain and hilly area of the Three Gorges Reservoir Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:景观格局具有典型的空间异质性和尺度依赖性。在对景观格局进行分析研究时需跨越多个尺度，空间粒度大小在尺度聚合分析中至关重要。三峡库区低山丘陵区斑块破碎、景观格复杂性显著、景观格局特征及尺度变异规律仍待明确，本文以三峡库区秭归县为研究区，设定1-400m内23个粒度梯度水平，定量评估县域、乡镇以及小流域不同幅度上的景观格局指数以及拟合函数，探讨多空间幅度景观格局指数随粒度大小的变化特征。基于景观指数的粒度效应特征和拟合函数的曲线特征（最大曲率点、极值点），明确适宜不同幅度的山地景观格局指数研究的粒度阈值，以揭示库区低山丘陵区景观结构的复杂性和变异性。结果表明：不同景观指数对空间粒度变化和空间幅度变化的响应存在差异，不同景观指数的空间粒度响应主要呈现增加、降低、波动和无明显规律变化的趋势，其中斑块密度、最大斑块面积等指数对斑块形状和大小的变化敏感，而多样性指数的粒度变化敏感度较低；部分指数如斑块密度、边缘密度、周长面积分维数等对空间幅度的变化并不敏感，而最大斑块面积、景观形状指数、散布与并列指数、分离度等指数对空间幅度的变化敏感，适合进行不同幅度适宜粒度阈值的推定；边缘密度、平均斑块大小、景观形状指数、蔓延度、相似邻接比例等多个景观指数可高度拟合曲线函数，通过拟合函数的曲线特征分析确定景观指数的变化转折点，降低人工判断的差异性；基于251个小流域、12个乡镇和秭归县的6072幅栅格数据的各景观指数变化趋势和变化转折点，综合各景观指数的转折变化点，得出小流域、乡镇、秭归县景观格局分析的第一尺度粒度阈值分别为3m、4m、7m，第二尺度粒度阈值分别为50m、100m、100m，空间幅度越小则景观格局分析所需要的适宜粒度越小。 Abstract:Landscape patterns have typically spatial heterogeneity and scale dependence; thus it needs to span multiple scales in landscape pattern analysis. Therefore, the spatial granularity is crucial in scale aggregation. In the hilly area of the Three Gorges Reservoir area, patches are fragmented, landscape complexity is significant, and landscape pattern characteristics and scale variation are still to be clarified. In this study, we focused on Zigui County in the Three Gorges Reservoir, set 23 grain size gradient levels within 1-400 m, quantitatively evaluated the landscape pattern index and fitting function of the county, towns, and small basins at different amplitudes to explore more margin space landscape pattern index characteristics associated with the change in particle size. Based on the grain size effect characteristics of the landscape index and the curve characteristics (maximum curvature point and extreme value point) of the fitting function, a suitable grain size threshold of the mountain landscape pattern index with different amplitudes was determined, so as to reveal the complexity and variability of mountain landscape structure in the hilly region of the Three Gorges Reservoir. The responses of different landscape indices to the changes in spatial granularity and spatial amplitude differed. The responses of different landscape indices to the changes in spatial granularity can be summarized as four trends:increase, decrease, fluctuation, and no obvious regular change. Patch Density and the Largest Shape Index are sensitive to changes in patch shape and size, whereas the sensitivity of Diversity Index to the change in grain size is inapparent. Patch Density, Edge Density, and Perimeter-Area Fractal Dimension are not sensitive to the change in spatial amplitude, whereas the Largest Patch Index, Landscape Shape Index, Interspersion and Juxtaposition Index, and Splitting Index are sensitive to the change in spatial amplitude and are suitable for prediction of the threshold of appropriate grain size for different amplitudes. Landscape indices such as Edge Density, Mean Patch Size, Landscape Shape Index, Contagion Index, and Percentage of Like Adjacency can be highly fitted to the curve function, and the curve characteristics of the fitting function can be used to identify the turning point of the change in the landscape index and reduce the difference in artificial judgment. Based on the changing trends and turning points of the landscape indices of 6072 raster data of 251 small basins, 12 townships, and Zigui County, the first-scale granularity threshold for landscape pattern analysis of small basins, towns, and Zigui County is 3 m, 4 m, and 7 m, while the second-scale particle size threshold is 50 m, 100 m, and 100 m, respectively, integrating the turning points of each landscape index. Thus, the smaller the spatial amplitude, the smaller the suitable grain size for landscape pattern analysis. 参考文献 相似文献 引证文献

Изменение формы лесов на Среднерусской возвышенности в субмеридиональном направлении (количественное описание на основе ландшафтных метрик)

The article is dedicated to a quantitative description of the geometric shape of forests in the territory of the Central Russian Upland. This is a new direction in the research of forest insularity in the forest-steppe zone. It complements the existing works in the field of landscape ecology, which are dedicated to the area, location and fragmentation of forests in the forest-steppe zone. This study was carried out at four key sites with a size of 30 by 30 km each. The sites are located along the north-south line, and each site is located in one of the natural subzones of the Central Russian Upland (subzones of the northern, typical, southern forest-steppe and the steppe zone). For each site, forests were mapped using images from the Sentinel-2 satellite in the ArcGIS 10.5 program. Then, in the “R” free software environment for statistical computing, landscape metrics were calculated that characterize the complexity of the shape of forest areas, using the additional landscapemetrics package. Six landscape metrics were used, namely: average related circumscribing circle (CIRCLE), average contiguity index (CONTIG), average fractal dimension index (FRAC), perimeter-area fractal dimension (PAFRAC), average perimeter-area ratio (PARA) and average shape index (SHAPE). A comparison of landscape metrics for different key sites showed that the complexity of the forest form increases in the direction from north to south. This is due to a change in the landscape localization of forests. From north to south, the proportion of forests growing on watersheds decreases, and the proportion of ravine forests increases. The maximum increase in the complexity of the form is observed during the transition from the forest-steppe zone to the steppe zone. Of all the landscape metrics used, the PAFRAC and SHAPE metrics showed the greatest sensitivity to changes in the shape of forest areas. These metrics are most useful when comparing the forests shapes in different areas.

Exploring common factors influencing PM2.5 and O3 concentrations in the Pearl River Delta: Tradeoffs and synergies

Particulate matter with an aerodynamic equivalent dimeter less than 2.5 μm (PM2.5) and ozone (O3) are major air pollutants, with coupled and complex relationships. The control of both PM2.5 and O3 pollution requires the identification of their common influencing factors, which has rarely been attempted. In this study, land use regression (LUR) models based on the least absolute shrinkage and selection operator were developed to estimate PM2.5 and O3 concentrations in China's Pearl River Delta region during 2019. The common factors in the tradeoffs between the two air pollutants and their synergistic effects were analyzed. The model inputs included spatial coordinates, remote sensing observations, meteorological conditions, population density, road density, land cover, and landscape metrics. The LUR models performed well, capturing 54–89% and 42–83% of the variations in annual and seasonal PM2.5 and O3 concentrations, respectively, as shown by the 10-fold cross validation. The overlap of variables between the PM2.5 and O3 models indicated that longitude, aerosol optical depth, O3 column number density, tropospheric NO2 column number density, relative humidity, sunshine duration, population density, the percentage cover of forest, grass, impervious surfaces, and bare land, and perimeter-area fractal dimension had opposing effects on PM2.5 and O3. The tropospheric formaldehyde column number density, wind speed, road density, and area-weighted mean fractal dimension index had complementary effects on PM2.5 and O3 concentrations. This study has improved our understanding of the tradeoff and synergistic factors involved in PM2.5 and O3 pollution, and the results can be used to develop joint control policies for both pollutants.

Characterizing changes in land cover and forest fragmentation from multitemporal Landsat observations (1993-2018) in the Dhorpatan Hunting Reserve, Nepal

Natural forces and anthropogenic activities greatly alter land cover, deteriorate or alleviate forest fragmentation and affect biodiversity. Thus land cover and forest fragmentation dynamics have become a focus of concern for natural resource management agencies and biodiversity conservation communities. However, there are few land cover datasets and forest fragmentation information available for the Dhorpatan Hunting Reserve (DHR) of Nepal to develop targeted biodiversity conservation plans. In this study, these gaps were filled by characterizing land cover and forest fragmentation trends in the DHR. Using five Landsat images between 1993 and 2018, a support vector machine algorithm was applied to classify six land cover classes: forest, grasslands, barren lands, agricultural and built-up areas, water bodies, and snow and glaciers. Subsequently, two landscape process models and four landscape metrics were used to depict the forest fragmentation situations. Results showed that forest cover increased from 39.4% in 1993 to 39.8% in 2018. Conversely, grasslands decreased from 38.2% in 1993 to 36.9% in 2018. The forest shrinkage was responsible for forest loss during the period, suggesting that the loss of forest cover reduced the connectivity between forest and non-forested areas. Expansion was the dominant component of the forest restoration process, implying that it avoided the occurrence of isolated forests. The maximum value of edge density and perimeter area fractal dimension metrics and the minimum value of aggregation index were observed in 2011, revealing that forests in this year were most fragmented. These specific observations from the current analysis can help local authorities and local communities, who are highly dependent on forest resources, to better develop local forest management and biodiversity conservation plans.

Location of greenspace matters: a new approach to investigating the effect of the greenspace spatial pattern on urban heat environment

Although many prior efforts have found that both spatial composition and configuration of greenspaces significantly affect the urban heat environment globally, the spatially heterogeneous effects of greenspace spatial patterns on the urban heat environment remain poorly understood for urban spaces. We proposed a spatially explicit approach to investigate the spatially heterogeneous cooling effects of greenspaces and map the relative contributions of the greenspace spatial patterns to the characterization of the urban heat environment. The proposed approach integrated the best subsets regression method, geographically weighted regression (GWR), and hierarchical partitioning analysis. Two cities in southeastern China were selected to test our model. Landsat 5 image obtained in the summer was used to estimate the land surface temperature (LST) and greenspace spatial patterns were extracted from 0.5-m aerial images. The results revealed that LST of Guangzhou can be well predicted by the percent cover (PER), the number of patches (NP), the area-weighted mean of the patch area (AREA_AM), and the area-weighted mean of the perimeter-area fractal dimension (FRAC_MN), while that of Shenzhen can be predicted by PER, NP, AREA_AM and the mean of the related circumscribing circle (CIRCLE_MN). The inclusion of additional landscape metrics did not yield significantly higher accuracies. The dominant landscape metrics of greenspace that determine the LST varied spatially across the two cities, with the PER accounting for the greatest variation. The results of our work demonstrate that the location of greenspace is a significant factor affecting the urban heat environment. The proposed approach provides a new understanding of the interaction between the greenspace spatial patterns and urban heat environments, providing useful information for tailoring greenspace planning policies for specific local sites.

Impacts of Neighboring Buildings on the Cold Island Effect of Central Parks: A Case Study of Beijing, China

Urban parks have been considered as an effective measure to mitigate the urban heat island (UHI) effects. Many studies have investigated the impacts of shape, size and interior components on the cold island effect (CIE) of parks, while little attention has been given to the impact of neighboring buildings. Thus, taking twenty-two parks in Beijing as samples, this study investigated the impacts of the neighboring building on the CIE of central parks. The results showed that the average land surface temperature (LST) of parks are 30.98 °C in summer and −1.10 °C in winter. Parks have a strong CIE in summer, and average cold island footprint (CIF) and LST difference are 0.15 km2 and 2.01 °C higher than that in winter. The components of the building in the CIF of parks are dominated by middle-rise building (MRB), followed by low-rise building (LRB), and high-rise building (HRB) is the least dominant. The percentage of landscape (PLAND) and landscape shape index (LSI) of MRB, and perimeter area fractal dimension (PAFRAC) of LRB are significantly related to CIF in summer and winter. This study could extend scientific understanding of the impacts of neighboring buildings on the CIE of central parks, and could guide urban planners in mitigating the UHI effects through the rational allocation of buildings.

Submerged aquatic vegetation cover and complexity drive crustacean zooplankton community structure in a large fluvial lake: An in situ approach

Submerged aquatic vegetation (SAV) is considered an important driver of the zooplankton community, owing to the refuge offered by its structural complexity. However, non-destructive in situ approaches to assess quantitatively the features of SAV beds and their effects on zooplankton community are still lacking. This study aims to: 1) estimate SAV cover and complexity using subaquatic upward photographs (SUP) and 2) analyse the relationship between SAV variables and crustacean zooplankton composition and functional diversity (FD). SAV biomass and zooplankton were sampled at 52 stations in a large fluvial lake. Two metrics based on SUP were used to quantify SAV cover and complexity: 1) the percentage of the underwater landscape occupied by SAV (PLAND: SAV cover), and 2) its perimeter-area fractal dimension (PAFRAC: SAV complexity). Zooplankton composition and functional diversity were estimated based on crustacean species assemblages and functional traits. We used linear models to describe the relationships between SAV indices, environmental variables and zooplankton abundance, biomass and FD. SUP was an effective method to estimate in situ SAV cover and complexity. PLAND and PAFRAC were positively related to SAV biomass and zooplankton abundance, yielding a non-destructive assessment of the SAV-zooplankton relationships. Our study partially supports the habitat complexity-ecological niche availability hypothesis, as SAV cover and complexity influenced zooplankton functional groups and diversity indices. However, water transparency and depth also had important effects in interaction with PLAND and PAFRAC, and it remains difficult to fully disentangle the effects of SAV complexity from SAV cover on crustacean zooplankton community structure.

The Extent of Infrastructure Causing Fragmentation in the Hydrocarbon Basin in the Arid and Semi-Arid Zones of Patagonia (Argentina)

Fragmentation is a disruption in the connectivity of landscapes. The aims of this paper are (i) to quantitatively assess the fragmentation rates in three landscape units located in a hydrocarbon basin, and (ii) to model their behavior between 2001 and 2013 using landscape metrics at different scales of resolution. The following metrics were selected using principal component analysis (PCA): The Clumpiness Index (CLUMPY), patch density (PD), perimeter-area fractal dimension (PAFRAC) and effective mesh size (MESH). Results from our investigations pointed out that hydrocarbon activity increased the fragmentation at the sites. In particular, the CLUMPY index increased in all three landscape units, the average of PD decreased from 60 to 14 patches per 100 hectares, whereas the mean of MESH was quite constant, however, due to oil production, it decreased mainly in the coastal valleys. Finally, the PAFRAC also decreased at sites with oil production, being more evident in the plateau and coastal canyons. As a whole, outputs from our analyses clearly pointed out that the monitoring of landscape fragmentation trends in arid and semi-arid zones can be successfully achieved using metrics derived from satellite spectral information.

Relación entre la erosión de los barrancos y el modelo de paisaje agrícola en la región de suelo negro típico del noreste de China

The black soil region of Northeast China is an important grain producing area that faces serious erosion problem. We used SPOT5 remote sensing imagery from 2008 to establish the gully distribution in a typical black soil region located in the Wuyuer and Nemoer River basin, and Landsat Thematic Mapper imagery to designate landscape patterns. Ninety-three sub-basins were determined based on digital elevation model data using a hydrological analysis module for which landscape pattern metrics and gully density were obtained using FRAGSTATS software and the Geographic Information System (GIS) spatial analysis function, respectively. The results show a gully density of 4,219.2 m2/km2 with 10,149.5 ha of eroded dry land and 25,261.2 ha of destroyed dry land. Correlation analysis between gully density and the landscape percentage of dry land and forest, perimeter-area fractal dimension, contagion index, and Shannon’s diversity index indicate that regulation of the proportion of forest, dry land, and grass, and reasonable optimization of landscape arrangement is very important for soil erosion management and control. Additionally, the findings indicate that landscape differences between each sub-basin are not the principal reason for differences in gully erosion. Further research on gully formation should integrate the effect of natural forces and human activities.

Relationships between Riparian Vegetation Pattern and the Hydraulic Characteristics of Upslope Runoff

Riparian vegetation plays a vital role in inhibiting soil and water loss, but few studies have quantified the relationships between vegetation spatial pattern and the hydraulic characteristics of upslope runoff. This study investigated how hydraulic characteristics (e.g., runoff coefficient, flow regime, flow resistance, and flow shear stress of overland flow) responded to differences in vegetation cover (15% and 30%), slope gradient (5°, 10°, 15°, and 20°), and vegetation pattern in the riparian zone along the lower Yellow River, China, based on landscape pattern analysis and a runoff scouring experiment with flow rates of 9 and 15 L/min and an experimental plot size of 1 m × 3 m. We found that runoff generation on shallow slopes was moderated by increasing vegetation cover, but that this moderating effect decreased on steeper slopes. The regime of overland flow switched from laminar and subcritical on the 5° slope (Fr = 0.56–0.87) to laminar and critical on the 10°, 15°, and 20° slopes (Fr = 1.02–2.18). Flow resistance increased with vegetation cover and flow rate and decreased with slope gradients, and it was larger on shallow slopes with high vegetation cover. Flow shear stress had a range of 1.42–3.55 N m−2, and it increased with increasing slope gradient, vegetation cover, and flow rate. The hydraulic characteristics of upslope runoff, especially flow resistance, were significantly related to vegetation pattern at both the landscape and class levels. Flow resistance was negatively related to patch density, and positively related to perimeter–area fractal dimension and connectance index. The influencing mechanism of landscape patterns on soil erosion processes is dependent on the landscape scale, since the relationships between flow resistance and some landscape pattern indices (aggregation index, effective mesh size, and splitting index) were opposite at the landscape level compared to the class level. We conclude that fragmented vegetation distributions reduce flow resistance, and that riparian vegetation could be managed to inhibit slope erosion by increasing flow resistance.

Wavelet-Based Correlation Identification of Scales and Locations between Landscape Patterns and Topography in Urban-Rural Profiles: Case of the Jilin City, China

Landscapes display overlapping sets of correlations in different regions at different spatial scales, and these correlations can be delineated by pattern analysis. This study identified the correlations between landscape pattern and topography at various scales and locations in urban-rural profiles from Jilin City, China, using Pearson correlation analysis and wavelet method. Two profiles, 30 km (A) and 35 km (B) in length with 0.1-km sampling intervals, were selected. The results indicated that profile A was more sensitive to the characterization of the land use pattern as influenced by topography due to its more varied terrain, and three scales (small, medium, and large) could be defined based on the variation in the standard deviation of the wavelet coherency in profile A. Correlations between landscape metrics and elevation were similar at large scales (over 8 km), while complex correlations were discovered at other scale intervals. The medium scale of cohesion and Shannon’s diversity index was 1–8 km, while those of perimeter-area fractal dimension and edge density index were 1.5–8 km and 2–8 km, respectively. At small scales, the correlations were weak as a whole and scattered due to the micro-topography and landform elements, such as valleys and hillsides. At medium scales, the correlations were most affected by local topography, and the land use pattern was significantly correlated with topography at several locations. At large spatial scales, significant correlation existed throughout the study area due to alternating mountains and plains. In general, the strength of correlation between landscape metrics and topography increased gradually with increasing spatial scale, although this tendency had some fluctuations in several locations. Despite a complex calculating process and ecological interpretation, the wavelet method is still an effective tool to identify multi-scale characteristics in landscape ecology.