Landscape Pattern Analysis Research Articles

Using pan-sharpened high resolution satellite data to improve impervious surfaces estimation

Impervious surface is an important environmental and socio-economic indicator for numerous urban studies. While a large number of researches have been conducted to estimate the area and distribution of impervious surface from satellite data, the accuracy for impervious surface estimation (ISE) is insufficient due to high diversity of urban land cover types. This study evaluated the use of panchromatic (PAN) data in very high resolution satellite image for improving the accuracy of ISE by various pan-sharpening approaches, with a further comprehensive analysis of its scale effects. Three benchmark pan-sharpening approaches, Gram-Schmidt (GS), PANSHARP and principal component analysis (PCA) were applied to WorldView-2 in three spots of Hong Kong. The on-screen digitization were carried out based on Google Map and the results were viewed as referenced impervious surfaces. The referenced impervious surfaces and the ISE results were then re-scaled to various spatial resolutions to obtain the percentage of impervious surfaces. The correlation coefficient (CC) and root mean square error (RMSE) were adopted as the quantitative indicator to assess the accuracy. The accuracy differences between three research areas were further illustrated by the average local variance (ALV) which was used for landscape pattern analysis. The experimental results suggested that 1) three research regions have various landscape patterns; 2) ISE accuracy extracted from pan-sharpened data was better than ISE from original multispectral (MS) data; and 3) this improvement has a noticeable scale effects with various resolutions. The improvement was reduced slightly as the resolution became coarser.

Landscape metrics application in ecological and visual landscape assessment

The development of landscape-ecological approach application in spatial planning provides exact theoretical and empirical evidence for monitoring ecological consequences of natural and/or anthropogenic factors, particularly changes in spatial structures caused by them. Landscape pattern which feature diverse landscape values is the holder of the unique landscape character at different spatial levels and represents a perceptual domain for its users. Using the landscape metrics, the parameters of landscape composition and configuration are mathematical algorithms that quantify the specific spatial characteristics used for interpretation of landscape features and processes (physical and ecological aspect), as well as forms (visual aspect) and the meaning (cognitive aspect) of the landscape. Landscape metrics has been applied mostly in the ecological and biodiversity assessments as well as in the determination of the level of structural change of landscape, but more and more applied in the assessment of the visual character of the landscape. Based on a review of relevant literature, the aim of this work is to show the main trends of landscape metrics within the aspect of ecological and visual assessments. The research methodology is based on the analysis, classification and systematization of the research studies published from 2000 to 2016, where the landscape metrics is applied: (1) the analysis of landscape pattern and its changes, (2) the analysis of biodiversity and habitat function and (3) a visual landscape assessment. By selecting representative metric parameters for the landscape composition and configuration, for each category is formed the basis for further landscape metrics research and application for the integrated ecological and visual assessment of the landscape values. Contemporary conceptualization of the landscape is seen holistically, and the future research should be directed towards the development of integrated landscape assessment as a guideline for spatial development planning.

Long-term remote sensing monitoring coal mining activity in resource-based cities: a case study of Qitaihe City, Northeastern China

Mining activity has strongly impacted the sustainable socioeconomic development of resource-based cities. The systematic monitoring of the change in mining activity can provide evidence for the transition and future development of resource-based cities. This paper chose Qitaihe, one of the four coal mining cities in northeastern China as the study area. Remote sensing and Geographical Information Systems (GIS) technique, as well as methods on landscape pattern analysis were used to study the evolution of mining activity from 4 different periods over 58 years’ time. Results showed that the area of land used in mining increased by about six times during the study period with cultivated land the main type that contributed to this increase. Mining activity showed an eastward trend, developing from one concentration circle to four circles, from a disordered system to a relatively integrated system. It was also suggested that differentiated policies should be adopted in different mining circles. This study also provides a framework for future city planning and sustainable development.

广西滨海区域景观格局分析及土地利用变化预测

广西滨海区域景观格局分析及土地利用变化预测

近40年艾比湖湿地自然保护区生态干扰度时空动态及景观格局变化

PDF HTML阅读 XML下载 导出引用 引用提醒 近40年艾比湖湿地自然保护区生态干扰度时空动态及景观格局变化 DOI: 10.5846/stxb201609081825 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 新疆维吾尔自治区自然科学基金项目（2016D01C029）；自治区青年科技创新人才培养工程项目（2013731002）；国家自然科学基金项目（41361045，41130531）；国家自然科学基金（新疆联合基金本地优秀青年人才培养专项）（U1503302） Analysis of the temporal and spatial dynamics of landscape patterns and hemeroby index of the Ebinur Lake Wetland Nature Reserve, Xinjiang, over the last 40 years 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:以新疆艾比湖湿地为研究区，利用1972、1998、2007年及2013年4个时期的 Landsat遥感影像作为数据源，并结合湿地的土地覆被状况，参考《全国土地利用分类》建立艾比湖湿地生态干扰类型分类系统。借助生态干扰度指数、景观格局指数以及GIS空间分析方法，探讨艾比湖湿地的生态干扰度的时空动态及景观响应机制。结果表明：（1）1972-2013年，研究区的生态干扰度总体呈现较为稳定的趋势，但其空间分布发生变化。生态干扰度类型之间的转化速率有加快的趋势。（2）1972-2013年，边缘密度指数（ED），平均形状指数（MSI），面积加权的平均斑块分形指数（AWMPFD）及景观分离度（DIVISION）4项景观格局指数大体呈上升的趋势，2013年区域的景观指数较为稳定。（3）景观格局指数与生态干扰程度有密切的一致性。生态干扰度与景观格局指数空间分布相关性大小依次为：边缘密度指数（ED） < 景观丰度密度（PRD） < 香农多样性指数（SHDI） < 平均形状指数（MSI） < 面积加权的平均斑块分形指数（AWMPFD） < 景观分离度（DIVISION）。客观系统的认识和评价艾比湖湿地的生态系统及环境，可为干旱区实现自然环境的保护，协调土地利用及环境保护之间的关系提供较为实用的参考。 Abstract:Wetlands are an important part of ecological systems. Wetlands not only provide the survival habitats and resources for plants, animals, and human but also are highly beneficial for the environment. In arid zones in particular, wetlands have received considerable scientific attention. The hemeroby index provides a measure of the magnitude to which the vegetation of an ecological environment deviates from the natural state as a consequence of human activities. It is beneficial to manage rationally for economic development in order to protect the ecological environment. The present study fills a gap in our understanding of the sustainable development of the wetland ecosystem in the Ebinur Lake Wetland Nature Reserve, Xinjiang Uyghur Autonomous Region, China. A hemeroby-type classification system for the Ebinur Lake Wetland Reserve was established based on multiple datasets, including Landsat MSS/TM/ETM+/OLI image data obtained in 1972, 1998, 2007, and 2013. The study explored the spatiotemporal dynamics of hemeroby and the landscape pattern response through hemeroby, landscape pattern, spatial patch, and GIS spatial analyses in the study area. The following results were obtained: (1) From 1972 to 2013, the ecological hemeroby degree for the Ebinur Lake wetland showed a relatively stable trend; however, there were marked changes in its spatial distribution. The distribution of the partially disturbed type of wetland has obviously changed. This indicates that the degree of naturalness of wetland vegetation is unstable and susceptible to human interference in this area. There was a high conversion rate of different hemeroby index (HI) types from 1972 to 2013. Dynamic changes in hemeroby degree are more likely to be attributed to natural, human, and policy-driven forces that result in a comprehensive effect. During the period 1972-2013, changes in natural factors (mean annual evaporation, temperature, and precipitation) and human factors (livestock, population, and GDP) led to change in the distribution of vegetation and Ebinur Lake area, which influenced the degree of naturalness of the ecological system. (2) During the period 1972-2013, there were significant increases in four landscape pattern indices, edge density (ED), mean shape index (MSI), area-weighted mean patch fractal dimension index (AWMPFD), and landscape division (DIVISION). However, in 2013, the regional landscape index was relatively stable. (3) High values of ED and AWMPFD were recorded for areas with a high HI. This shows that landscape patch fragmentation and complexity is higher in areas with a high HI, and that the degree of naturalness is unstable. Low values of patch fragmentation and complexity are mainly concentrated in areas with a low HI. This indicates that landscape pattern indices and the HI have good consistency and correlation with regard to spatial distribution. The HI was positively correlated with DIVISION, AWMPFD, MSI, Shannon's diversity index, patch richness density, and ED, in a decreasing order of influence. Evaluation of the ecological environment of the Ebinur Lake region provides a practical reference for the protection of the natural environment and resources, and will prove beneficial for the coordinated management of the environmental for sustainable development. 参考文献 相似文献 引证文献

内蒙古高格斯台罕乌拉自然保护区土地覆盖与景观格局变化分析

土地覆盖变化和景观格局变化是研究生态环境变化及野生动物生境格局变化的重要基础。本研究基于内蒙古高格斯台罕乌拉国家级自然保护区1995、2004和2014年7月份3期landsat TM系列数据，运用RS、GIS技术及景观生态学的方法，系统分析了该区1995~2014年土地覆盖与景观格局变化，定量分析了土地覆盖类型变化度、斑块面积指数、斑块形状指数、边缘密度指数以及多样性指数等指标。研究结果表明：土地覆盖类型主要为草地、林地和灌丛半灌丛，约占保护区总面积的80%~90%；其中1995~2014年草地面积减少245.74 km2，林地增加99.73 km2，灌丛半灌木丛减少4.38 km2；从景观格局来看，1995~2014年间，斑块数量、斑块密度、平均形状指数均有较大波动，均为先增加后减少；而聚集度先变小后又增大；Shannon’s多样性指数逐渐递增，最大斑块指数逐渐减小。说明1995~2004年，景观趋于丰富和复杂化，2004年以后，破碎化程度减小并趋于稳定。该研究结果表明随保护区级别晋升，管护力度加大，保护区环境得到改善，但仍然面临土地退化的严重挑战。 Land coverage and landscape pattern changes are the important basis of the study in the change of ecological environment and wildlife habitat pattern. In our study, we got the three phases dataset of lands at TM at summer in July 1995, 2004 and 2014 in Gaogesitai-Hanwula national nature reserve, Inner Mongolia, and used techniques of remote sensing (RS), geographic information systems (GIS) and landscape pattern analysis method to systematically analyze the land coverage and landscape pattern change from 1995 to 2014, and quantificationally analyze land cover types change degrees, patch area index, patch shape index, edge density index and diversity index. Our results showed the grassland, woodland, brush and half shrubs were the main land coverage type. They occupied 80% - 90% of the total area. From 1995 to 2014, grassland decreased by 245.74 km2, forest land increased by 99.73 km2 and brush and half shrubs decreased by 4.38 km2. From 1995 to 2014 by the landscape pattern, patch number, patch density and mean shape index showed great fluctuations (increased firstly and then decreased quickly); the degree of aggregation firstly decreased and then increased; Shannon’s diversity indices gradually increased; and the largest patch index gradually decreased. It showed the landscape tended to be more abundant and complex from 1995 to 2004, and the degree of fragmentation was decreasing and tending to be stable. Our results also showed as the promotion of the level and the improvement of protection for the nature reserve, the environment of nature reserve was improved. However, it still faced the enormous challenge due to the land degradation.

Spatial characteristics analysis of Huizhou-Styled Village based on ideal ecosystem model and 3D landscape indices: A case in Chengkan, China

Huizhou-Styled Village is a typical representative of the traditional Chinese ancient villages. It preserves plentiful information of the regional culture and ecological connotation. The Huizhou-Style is the apotheosis of harmony between the Chinese ancient people and nature. The research and protection of Huizhou-Styled Village plays a very important role in fields of ecology, geography, architecture and esthetics. This paper took Chengkan Village of Anhui Province as an exa-mple, and proposed a new model of ideal ecosystem oriented in theories of Feng-shui and psychological field. The new method of characterizing 3D landscape index was introduced to explore the spatial patterns of Huizhou-Styled Village and the functionality of the composited landscape components in a quantitative way. The results indicated that, Chengkan Village showed a spatially composited pattern of "mountain-forest-village-river-forest". It formed an ideal settlement ring structure with human architecture in the center and natural landscape around in the horizontal and vertical horizons. The traditional method based on the projection distance caused the deviation of the landscape index, such as underestimating the area and distance of landscape patch. The 3D landscape index of average patch area was 6.7% higher than the 2D landscape index. The increasing rate ofarea proportion in 3D index was 1.0% higher than that of 2D index in forest lands. Area proportion of the other landscapes decreased, especially the artificial landscapes like construction and cropland landscapes. The area and perimeter metric were underestimated, whereas the shape metric and the diversity metric were overestimated. This caused the underestimation of the dominance of natural patches was underestimated and the overestimation of the dominance of artificial patches during the analysis of landscape pattern. The 3D landscape index showed that the natural elements and their combination in Chengkan Village ecosystem reflected better ecological function, the key elements and the composited landscape ecosystem preserved higher stability, connectivity and aggregation. The quantitative confirmation showed that the Huizhou-Styled Village represented by Chengkan Village is an ideal ecosystem.

Land change and loss of landscape diversity at the Caatinga phytogeographical domain – Analysis of pattern-process relationships with MODIS land cover products (2001–2012)

Tropical dry forests are increasingly threatened by land degradation. For the Caatinga seasonally dry forests in Northeast Brazil, recent studies revealed both woody vegetation loss and (re-)gain. A conclusive analysis of land cover and landscape diversity changes is still lacking. To fill this gap, we surveyed pattern-process relationships for the Caatinga phytogeographical domain on different spatial levels for the years 2001–2012 from MODIS land cover data. By a landscape pattern analysis, a set of five landscape metrics was calculated using FRAGSTATS. The spatio-temporal results revealed a general decrease of fragmentation and diversity. The savanna class which comprises also Caatinga dry forests covered large parts of the landscape and gained considerably, whereas other vegetation classes decreased. The distribution of the low vegetated shrublands and grasslands implied degradation risks, in particular at the São Fransisco River valley. Large-scaled agriculture was found in the proximity to water reservoirs in the lowlands, which led to local increases of the landscape’s diversity. We quantified both gains and losses of woody vegetation with a notable net gain of 6.7% of the study area. Main changes may be attributed to socio-economic shifts from local to large-scaled agriculture and water infrastructural activities. Overall, our study shows that a multi-temporal, global dataset along with a landscape pattern analysis provides valuable contributions to landscape research and for detecting land cover and landscape diversity changes.

Analysis of sea use landscape pattern based on GIS: a case study in Huludao, China.

This study aims to analyse sea use landscape patterns on a regional scale based on methods of landscape ecology integrated with sea use spatial characteristics. Several landscape-level analysis indices, such as the dominance index, complex index, intensivity index, diversity index and sea congruency index, were established using Geographic Information System (GIS) and applied in Huludao, China. The results indicated that sea use landscape analysis indices, which were created based on the characteristics of sea use spatial patterns using GIS, are suitable to quantitatively describe the landscape patterns of sea use. They are operable tools for the landscape analysis of sea use. The sea use landscape in Huludao was dominated by fishing use with a landscape dominance index of 0.724. The sea use landscape is a complex mosaic with high diversity and plenty of fishing areas, as shown by the landscape complex index of 27.21 and the landscape diversity index of 1.25. Most sea use patches correspond to the marine functional zonation plan and the sea use congruency index is 0.89 in the fishing zone and 0.92 in the transportation zone.

Enhancing urban landscape configurations by integrating 3D landscape pattern analysis with people’s landscape preferences

Rapid urbanization in China has become an important social-economic issue. During the process of urbanization, a diversity of factors should be balancedly considered for the design of landscape configuration. Amongst these factors, people’s landscape preferences are given growing emphasis. Landscape preferences have been widely examined and some studies have been designed to link landscape preferences to landscape patterns. However, most studies have been conducted from a 2D perspective and therefore cannot simulate people’s actual perception of local landscape configurations. This paper proposes a framework, based on which 3D landscape pattern analysis and landscape preferences can be efficiently integrated for evaluating urban landscape configurations. Airborne light detection and ranging (Lidar) is an ideal tool for conducting 3D landscape pattern analysis. In accordance with 3D landscape pattern analysis, standardized and generally applicable surveys of landscape preferences can be designed and conducted in different areas. A case study was conducted in Cambridge and Canvey, UK to demonstrate how 3D urban landscape patterns can be analyzed. Furthermore, a case study was conducted in Cambridge, UK and Nanjing, China to explain how people’s landscape preferences can be acquired and compared. Landscape pattern analysis indicated that 3D landscape models effectively revealed comprehensive landscape patterns and simulated people’s perception of local landscape configurations. For instance, cross-culture surveys on general landscape preferences proved the existence of commonly shared landscape preferences, which may be used as evaluation criteria. This methodology provides reference for landscape planners and decision makers to enhance urban landscape configurations. The methodology is of potential contribution to China’s rapid urbanization by suggesting practical approaches to improve landscape patterns according to people’s preferences.

Novel shape indices for vector landscape pattern analysis

ABSTRACTThe formation of an anisotropic landscape is influenced by natural and/or human processes, which can then be inferred on the basis of geometric indices. In this study, two minimal bounding rectangles in consideration of the principles of mechanics (i.e. minimal width bounding (MWB) box and moment bounding (MB) box) were introduced. Based on these boxes, four novel shape indices, namely MBLW (the length-to-width ratio of MB box), PAMBA (area ratio between patch and MB box), PPMBP (perimeter ratio between patch and MB box) and ODI (orientation difference index between MB and MWB boxes), were introduced to capture multiple aspects of landscape features including patch elongation, patch compactness, patch roughness and patch symmetry. Landscape pattern was, thus, quantified by considering both patch directionality and patch shape simultaneously, which is especially suitable for anisotropic landscape analysis. The effectiveness of the new indices were tested with real landscape data consisting of three kinds of saline soil patches (i.e. the elongated shaped slightly saline soil class, the circular or half-moon shaped moderately saline soil, and the large and complex severely saline soil patches). The resulting classification was found to be more accurate and robust than that based on traditional shape complexity indices.

Application of Landscape Pattern Analysis to Quantitatively Evaluate the Spatial Structure Characteristics of PreferentialFlow Paths in Farmland

Abstract. The distribution of soil preferential paths is a natural process with highly spatiotemporal variability. However, an adequate analysis method to evaluate the spatial structures of soil preferential paths from the viewpoint of ecology has not yet been developed. Hence, the quantification of the complicated distribution patterns of soil preferential paths and their relation to biota activities from the ecological perspective remains elusive. This article presents a new method that combines the image processing technology of morphology and spatial pattern analysis (i.e., quantitative parameters W i , M i , U i , and g(r) function) of landscape ecology to quickly observe and quantify the spatial distribution characteristics of preferential flow paths. The study was conducted on soybean fields in the Three Gorges Reservoir Areas in China. Results demonstrated that the proposed method can describe the spatial connectivity, development degree, and rapid water conductivity of different preferential flow paths (paths of 2.5-5.0 mm were the highest, whereas paths of 1.0-2.5 mm were the lowest). All the preferential flow paths, except for the paths of 1.0-2.5 mm (random distribution pattern), mainly demonstrated a gradual tendency to follow a clumped distribution pattern and community structure relative to soil depth. In addition, all the paths showed low spatial complexity because of their uniform composition relative to soil depth. Soil intra-structure ( 5.0 mm) and plant roots effectively influenced the distribution patterns and formation of the preferential paths in the deep farmland soil. Plant roots, in particular, significantly influenced the formation and distribution of the preferential flow paths of 1.0-2.5 mm in the soybean field. Compared with existing methods (e.g., dye tracing, resin impregnation, water breakthrough curve analysis, and computed tomography technique), the proposed method can provide more significant spatial structure information from an ecological perspective. Such information can help expand our understanding of the spatial structures of preferential flow paths and the underlying ecological formation processes in soil ecosystems. The method is also effective, convenient, rapid, and economical when used to the study the spatial structures of soil preferential paths at different field scales for soil management.

Scenario simulation and landscape pattern dynamic changes of land use in the Poverty Belt around Beijing and Tianjin: A case study of Zhangjiakou city, Hebei Province

Land use/cover change has been recognized as a key component in global change and has attracted increasing attention in recent decades. Scenario simulation of land use change is an important issue in the study of land use/cover change, and plays a key role in land use prediction and policy decision. Based on the remote sensing data of Landsat TM images in 1989, 2000 and 2010, scenario simulation and landscape pattern analysis of land use change driven by socio-economic development and ecological protection policies were reported in Zhangjiakou city, a representative area of the Poverty Belt around Beijing and Tianjin. Using a CLUE-S model, along with socio-economic and geographic data, the land use simulation of four scenarios–namely, land use planning scenario, natural development scenario, ecological-oriented scenario and farmland protection scenario–were explored according to the actual conditions of Zhangjiakou city, and the landscape pattern characteristics under different land use scenarios were analyzed. The results revealed the following: (1) Farmland, grassland, water body and unused land decreased significantly during 1989–2010, with a decrease of 11.09%, 2.82%, 18.20% and 31.27%, respectively, while garden land, forestland and construction land increased over the same period, with an increase of 5.71%, 20.91% and 38.54%, respectively. The change rate and intensity of land use improved in general from 1989 to 2010. The integrated dynamic degree of land use increased from 2.21% during 1989–2000 to 3.96% during 2000–2010. (2) Land use changed significantly throughout 1989–2010. The total area that underwent land use change was 4759.14 km2, accounting for 12.53% of the study area. Land use transformation was characterized by grassland to forestland, and by farmland to forestland and grassland. (3) Under the land use planning scenario, farmland, grassland, water body and unused land shrank significantly, while garden land, forestland and construction land increased. Under the natural development scenario, construction land and forestland increased in 2020 compared with 2010, while farmland and unused land decreased. Under the ecological-oriented scenario, forestland increased dramatically, which mainly derived from farmland, grassland and unused land. Under the farmland protection scenario, farmland was well protected and stable, while construction land expansion was restricted. (4) The landscape patterns of the four scenarios in 2020, compared with those in 2010, were more reasonable. Under the land use planning scenario, the landscape pattern tended to be more optimized. The landscape became less fragmented and heterogeneous with the natural development scenarios. However, under the ecological- oriented scenario and farmland protection scenario, landscape was characterized by fragmentation, and spatial heterogeneity of landscape was significant. Spatial differences in landscape patterns in Zhangjiakou city also existed. (5) The spatial distribution of land use could be explained, to a large extent, by the driving factors, and the simulation results tallied with the local situations, which provided useful information for decision-makers and planners to take appropriate land management measures in the area. The application of the combined Markov model, CLUE-S model and landscape metrics in Zhangjiakou city suggests that this methodology has the capacity to reflect the complex changes in land use at a scale of 300 m×300 m and can serve as a useful tool for analyzing complex land use driving factors.

耦合种群动态的生境格局变化分析粒度与景观因子选择——以盐城越冬丹顶鹤及其生境的变化为例

PDF HTML阅读 XML下载 导出引用 引用提醒 耦合种群动态的生境格局变化分析粒度与景观因子选择——以盐城越冬丹顶鹤及其生境的变化为例 DOI: 10.5846/stxb201412102450 作者: 作者单位: 南京农业大学 土地管理学院;College of Land Management;College of Land Management,南京农业大学 土地管理学院;College of Land Management;College of Land Management 作者简介: 通讯作者: 中图分类号: 基金项目: 江苏省青蓝工程项目 Grain size and landscape indices selection by coupling population dynamics and habitat pattern analysis: a case study of wintering red-crowned crane and its habitat in Yancheng Author: Affiliation: Nanjing Agriculture University,Nanjing agriculture university 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:选择盐城珍禽国家级自然保护区,以丹顶鹤越冬生境景观与种群动态这一格局-过程关系为切入点,尝试从丹顶鹤最小存活面积特征与种群动态视角探讨一下最佳粒度、景观格局变化分析的指数遴选方法。结果发现:根据丹顶鹤最小生存面积确定200m为最大转换粒度,综合景观指数随空间粒度变化的规律和粒度转换精度损失评价的结果,确定最佳分析粒度为70m。在众多景观因子中,运用Spearman秩相关分析,再利用逐步回归分析建立起景观与丹顶鹤数量指标间的联系,最终筛选出反映景观面积(CA)和空间格局(IJI,ENN_MN)的3种影响显著景观因子,其解释贡献率(累计R2)达到70.5%,且其所代表的生境景观的组成和结构信息较为客观地反映出研究区丹顶鹤种群动态分布的显示状态。与纯粹的景观指数分析相比,这种方法更能反应景观格局演变特征的特定生态学意义。 Abstract:Landscape pattern is scale-dependent. Thus, understanding landscape structure and functioning requires multiscale information. Scaling functions are the most precise and concise methods for explicitly quantifying multiscale characteristics. If landscape indices are ecologically relevant and reflect important attributes of spatial pattern, they can functionally link the dynamics of ecological processes to landscape structure. Therefore, the selection of appropriate scale (e.g., grain size) and landscape indices are critical to landscape pattern analysis. The major objective of this study was to explore how optimal grain size and landscape indices can be selected for landscape pattern analysis, to improve our understanding and prediction of ecological processes. For this, we conducted a case study on wintering Red-crowned crane and its habitat in Yancheng. To obtain the optimal grain size for landscape pattern analysis of the wintering habitat of the Red-crowned crane, we followed two steps. The first step was scale (grain) effect analysis, to find a grain size that the test metrics could detect in case of any variation (sensitivity). In this step, the minimum survival area for the species was considered for identifying the maximum grain size for scaling. The second step was accuracy test by evaluating the loss of landscape area and patch numbers in each grain size level. The optimal grain size was obtained by integrated analysis of the results from the above two steps. In landscape indices selection, 19 landscape metrics (computed at the optimal grain size) were subjected to Spearman rank correlation analysis to assess the independence. Then, step-wise regressions were performed to evaluate the effects of the spatial attributes (landscape indices with higher independence) at three hotspots on the abundance of cranes (based on population dynamics of the past 12 years[1]). Variables with significance level above 90% were selected as the optimal landscape indices for pattern analysis. The results showed the following: (1) on the basis of the minimum survival area of the red-crowned crane, 200 m was the highest obtained grain size, and 70 m was the optimal grain size identified by integrating the results of scale (grain) effect and accuracy after assessing the grain conversion area loss. (2) Effects of landscape patterns at the hotspots were analyzed using 8 pairs of landscape indices (results of metrics for the most suitable and supplement habitat types for cranes were computed) as the independent variables. Three landscape indices (CA, IJI, ENN_MN) of two habitat types were found to be significant (R2 = 70.5%). (3) The selected optimal landscape indices of the supplement habitat showed positive effect for isolation and negative effect for area size on population abundance. Our results imply that supplement habitat may provide complementary resource sites for cranes, but continued species concentration at these habitats may negatively affect crane abundance and distribution due to induced human disturbance. Our combined findings on optimal grain size and landscape indices proved to be satisfactory for landscape pattern analysis, suggesting that our approaches are reasonable. Further, compared to landscape pattern analysis by using random grain size and simple landscape metrics, the results obtained using our approaches, as shown in this case study, are ecological relevant. 参考文献 相似文献 引证文献

A computational framework for generalized moving windows and its application to landscape pattern analysis

Land cover products based on remotely sensed data are commonly investigated in terms of landscape composition and configuration; i.e. landscape pattern. Traditional landscape pattern indicators summarize an aspect of landscape pattern over the full study area. Increasingly, the advantages of representing the scale-specific spatial variation of landscape patterns as continuous surfaces are being recognized. However, technical and computational barriers hinder the uptake of this approach. This article reduces such barriers by introducing a computational framework for moving window analysis that separates the tasks of tallying pixels, patches and edges as a window moves over the map from the internal logic of landscape indicators. The framework is applied on data covering the UK and Ireland at 250m resolution, evaluating a variety of indicators including mean patch size, edge density and Shannon diversity at window sizes ranging from 2.5km to 80km. The required computation time is in the order of seconds to minutes on a regular personal computer. The framework supports rapid development of indicators requiring little coding. The computational efficiency means that methods can be integrated in iterative computational tasks such as multi-scale analysis, optimization, sensitivity analysis and simulation modelling.

Planning of Green Space Ecological Network in Urban Areas: An Example of Nanchang, China.

Green space plays an important role in sustainable urban development and ecology by virtue of multiple environmental, recreational, and economic benefits. Constructing an effective and harmonious urban ecological network and maintaining a sustainable living environment in response to rapid urbanization are the key issues required to be resolved by landscape planners. In this paper, Nanchang City, China was selected as a study area. Based on a series of landscape metrics, the landscape pattern analysis of the current (in 2005) and planned (in 2020) green space system were, respectively, conducted by using FRAGSTATS 3.3 software. Considering the actual situation of the Nanchang urban area, a “one river and two banks, north and south twin cities” ecological network was constructed by using network analysis. Moreover, the ecological network was assessed by using corridor structure analysis, and the improvement of an ecological network on the urban landscape was quantitatively assessed through a comparison between the ecological network and green space system planning. The results indicated that: (1) compared to the green space system in 2005, the planned green space system in 2020 of the Nanchang urban area will decline in both districts (Changnan and Changbei districts). Meanwhile, an increase in patch density and a decrease in mean patch size of green space patches at the landscape level implies the fragmentation of the urban green space landscape. In other words, the planned green space system does not necessarily improve the present green space system; (2) the ecological network of two districts has high corridor density, while Changnan’s ecological network has higher connectivity, but Changbei’s ecological network is more viable from an economic point of view, since it has relatively higher cost efficiency; (3) decrease in patch density, Euclidean nearest neighbor distance, and an increase in mean patch size and connectivity implied that the ecological network could improve landscape connectivity greatly, as compared with the planned green space system. That is to say, the planned ecological network would reduce landscape fragmentation, and increase the shape complexity of green space patches and landscape connectivity. As a result, the quality of the urban ecological environment would be improved.

Historical and recent fragmentation of temperate floodplain grasslands: Do patch size and distance affect the richness of characteristic wet meadow plant species?

Patch size and isolation are thought to have a large influence on the extinction risk of specialist plant species in grassland fragments in the modern agricultural landscape. We combined a re-sampling study in semi-permanent floodplain grassland plots with a GIS-based analysis of historical (1950s/1960s) and recent landscape patterns. Based on historical and recent vegetation maps and releves from six study areas (plus a protected reference area) covering 50–60 years of vegetation change following agricultural intensification, we aimed at analysing the importance of fragmentation on the diversity of potentially sensitive specialist species of wet floodplain meadows in northern Germany. On the plot scale, we found 30–66 % reductions in species richness of these characteristic wet meadow plant species over time and an associated increase in the fragmentation of grassland habitats. Distance to the nearest suitable habitat had a modest negative effect on modern plot-scale richness, while the other tested landscape metrics (total meadow area, mean patch size and landscape proximity index distribution) had no significant influence. There was also no evidence for a legacy of historical landscape structure on current richness of specialist species. Instead, management intensity and its change over the past decades, as indicated by altered Ellenberg indicator values for nutrients and moisture, had a strong influence on plot-scale diversity. The results suggest that fragmentation is not the proximate cause of impoverishment and point to habitat deterioration as a main driver. We conclude that conservation measures in Central-European floodplain meadows should not only focus on large continuous grassland areas, but should also consider small meadow patches if they remained species-rich.

Different bat guilds perceive their habitat in different ways: a multiscale landscape approach for variable selection in species distribution modelling

Context Unveiling the scale at which organisms respond to habitat features is crucial to understand how they are influenced by anthropogenic environmental changes. We implemented species distribution models (SDMs) based on multiple-scale landscape pattern analysis for four bat species representative of different foraging guilds: Nyctalus leisleri, Rhinolophus hipposideros, Myotis emarginatus and Pipistrellus pipistrellus. Objectives (a) to assess the environmental factors and the influence of scale on the habitat suitability of bats; (b) to develop an objective methodology to select the best performing variables from a large variable dataset. Methods We performed the study in central Italy (Tuscany): 381 variables were derived from topographical and habitat maps using a moving windows analysis set at three spatial scales (1, 5 and 10 km) that are ecologically meaningful for bats. For each species, weran381univariatemodelstoselectthevariables for multivariate SDMs. Results All the variables retained in the SDMs described spatial pattern indices underlining the importance of landscape structure for species distribution. Species reacted differently in terms of both scale and landscape pattern. P. pipistrellus only responded to variables at 10 km; N. leisleri and M.

Scenario-based land cover change modeling and its implications for landscape pattern analysis in the Neka Watershed, Iran

Land cover changes and urbanization cause destruction of natural habitats and threaten biodiversity. Land cover modeling is one of the most important procedures for evaluating this trend. This study was performed with the objective of comparing multi-layer perceptron (MLP) artificial neural network with logistic regression (LR) in predicting land cover change and quantifying future landscape change using landscape metrics in the Neka River Basin, a small part of the eastern Hyrcanian forest, in northern Iran. For this purpose, first, change analysis was carried out using satellite imagery, from 1987 to 2011. Then, transition potential modeling was conducted using MLP and LR in 5 different scenarios. A Relative Operating Characteristic (ROC) analysis was carried out to detect the degree of correlation between variables and transitions in LR. In addition, the accuracy rate for assessing the transition potential modeling using MLP was employed. Land cover change prediction was conducted using prediction for 2011 and 2017. The accuracy assessment model was determined by comparing the actual land cover map of 2011 with the predicted land cover map of 2011. Landscape indices for 1987, 2001, 2006, 2011, and 2017 were calculated and analyzed using Fragstats to determine the impact of land cover change on landscape fragmentation. The result showed that during 1987–2001, agriculture was the main contributor to the increased built-up area. The most important transition was the conversion of agriculture to orchard and residential, between 2001 and 2006. Forest regenerated from orchard and agricultural lands, between 2006 and 2011. The maximum and minimum amounts of Cramer's V were obtained for the empirical likelihood to change variable and distance from the river. Overall kappa obtained in the best scenario based on LR was 88%. Furthermore, the prediction results showed that major deforestation will occur in surrounding forest areas and most residential development is in the outskirts of the town of Neka. Increased fragmentation in the landscape will continue in 2017, more shape complexity will be observed, and habitats of the Neka Basin will become more diverse and abundant. The results of this study provide useful information for Reducing Emission from Deforestation and Forest Degradation (REDD) project.

Landscape sequences along the urban–rural–natural gradient: A novel geospatial approach for identification and analysis

Human influence on the environment differs in terms of distribution and intensity, thus producing a gradient of landscape modifications that translates into different landscape structures. Within this variety of landscapes, fringe areas represent complex spaces where dynamic processes and instable conditions can be observed. In this research Kernel Density Estimation, multivariate spatial analysis, landscape pattern analysis, and Principal Component Analysis (PCA) were combined to model and characterise landscape gradients, and to analyse the structural features of fringe areas. This methodology was applied to a rural area of central Italy, using density indicators associated with urbanisation, agriculture, and natural elements considered to be key components for the identification of landscape gradients. The results highlight not only specific “pillar” landscapes, which are dominated by said components, but also transitional landscapes, where the most relevant forms of interaction between land uses were identified. Characterisation of landscape structures along the gradient illustrated different trends in patch density, shape complexity and landscape diversity, demonstrating greater variability in fringe areas than in pillar landscapes. PCA revealed a partial overlap between the main structural characteristics of the agro-forestry matrix and the medium intensity agricultural landscapes, whereas urban fringes and semi-natural fringes were clearly separated. The discovery of the continuous landscape gradients and an understanding of the gamut of landscape types nested along them is crucial in allowing for more effective land-use planning in which also fringe areas become a relevant part of the process.