Using a sub-pixel mapping model to improve the accuracy of landscape pattern indices

The assessment of landscape spatial patterns is a key issue in landscape management. Landscape pattern indices (LPIs) are tools appropriate for analyzing landscape spatial patterns. LPIs are often derived from raster land cover maps that are extracted from remotely sensed data through hard classification. However, pixel-based hard classification methods suffer from the mixed pixel problem (in which pixels contain more than one land cover class), making for inaccurate classification maps and LPIs. In addition, LPIs generated by hard classification methods are characterized by grain sizes (the sampling unit sizes) that limit the derived landscape pattern to a certain scale. Sub-pixel mapping (SPM) models can enable fine-scale estimation of the spatial patterns of land cover classes without requiring additional data; hence, this is an appropriate downscaling method for land cover mapping. The fraction images generated by soft classification estimate the area proportion of each land cover class within each pixel, and using these images as input enables SPM models to alleviate the mixed pixel problem. At the same time, by transforming fraction images into a finer-scaled hard classification map, SPM models can minimize the influence of grain size on LPIs calculation. In this research, simulated landscape thematic patterns that can provide different landscape spatial patterns, eight commonly used LPIs and a SPM model that maximizes the spatial dependence between neighbouring sub-pixels were applied to assess the efficiency of deriving LPIs from sub-pixel model maps. Results showed that the SPM model can more precisely characterize landscape patterns than hard classification methods can. Landscape fragmentation, class abundance, the uncertainty in SPM, and the spatial resolution of the remotely sensed data influenced LPIs derived from sub-pixel maps. The largest patch index, landscape division, and patch cohesion derived from remotely sensed data with different spatial resolutions through the SPM model were suitable for inter-comparison, whereas the patch density, mean patch area, edge density, landscape shape index, and area-weighted mean shape index derived from the sub-pixel maps were sensitive to the spatial resolution of the remotely sensed data.     

What is the Value of a Good Map? An Example Using High Spatial Resolution Imagery to Aid Riparian Restoration

Riparian areas contain structurally diverse habitats that are challenging to monitor routinely and accurately over broad areas. As the structural variability within riparian areas is often indiscernible using moderate-scale satellite imagery, new mapping techniques are needed. We used high spatial resolution satellite imagery from the QuickBird satellite to map harvested and intact forests in coastal British Columbia, Canada. We distinguished forest structural classes used in riparian restoration planning, each with different restoration costs. To assess the accuracy of high spatial resolution imagery relative to coarser imagery, we coarsened the pixel resolution of the image, repeated the classifications, and compared results. Accuracy assessments produced individual class accuracies ranging from 70 to 90% for most classes; whilst accuracies obtained using coarser scale imagery were lower. We also examined the implications of map error on riparian restoration budgets derived from our classified maps. To do so, we modified the confusion matrix to create a cost error matrix quantifying costs associated with misclassification. High spatial resolution satellite imagery can be useful for riparian mapping; however, errors in restoration budgets attributable to misclassification error can be significant, even when using highly accurate maps. As the spatial resolution of imagery increases, it will be used more routinely in ecosystem ecology. Thus, our ability to evaluate map accuracy in practical, meaningful ways must develop further. The cost error matrix is one method that can be adapted for conservation and planning decisions in many ecosystems.     

遥感主体图的准确度对景观生态学研究的影响

用各种案例系统地解释了遥感数据分类误差对景观指数误差的必然影响。一方面 ,遥感数据在各种时间和空间尺度上为景观生态学研究提供必需的土地类型数据 ;另一方面 ,遥感技术的灵活性和复杂性可以产生出各种质量的土地类型数据。但景观生态学方面的用户对土地类型数据基本上是没有选择地使用 ,甚至是不知好坏地使用 ,所以景观生态学的发现和结论具有不可避免的任意性。总结了在各种情况下景观指数的变动区间 ,指出了现实较低的遥感数据的分类准确度会引起更低的景观指数的准确度 ,当进行景观变化分析时 ,这种误差的放大效应将更加明显。当前 ,人们对除面积以外的景观指数的误差仍然束手无策 ,尽可能地提高遥感数据的分类准确度是唯一力所能及的办法。     

Mountain vegetation change quantification using surface landscape metrics in Lancang watershed,China

Land cover and vegetation change are among the most important aspects of environmental change. Vegetation change can be quantified by landscape pattern indices (LPI). Landscape indices are routinely calculated using planar land use/land cover (LU/LC) maps, obtained by the projection of a non-flat landscape surface into a two-dimensional Cartesian space. Especially in mountainous areas, quantification on planar maps can lead to underestimation of vegetation and land cover changes. Hoechstetter et al. (2008) developed a method to compute LPIs in a surface structure by calculating landscape patch surface area and surface perimeter from digital elevation models (DEM). As yet there have been no applications of these surface landscape indices on land use/land cover and vegetation change quantification. The objectives of this study are to (1) choose a LPI method (surface metrics pattern analysis or common planimetric metrics pattern analysis) for vegetation change quantification; and (2) employ the selected surface LPI method to assess vegetation pattern change in two mountainous areas of the Lancang watershed, Yunnan Province, China. The results show that the surface approach to estimate changes of class area (CA), mean patch area (MPA), and mean Euclidean Near-Neighbor distance (MENN) may obtain more accurate results for quantifying vegetation change in steep mountain areas. Forest fragmentation increased significantly over time in the two different mountainous study areas. The patches of two land cover classes, (i) agricultural land and (ii) low density forest and tall shrubs, became more aggregated in the northern (temperate) study area. In the southern (tropical) study area, rubber plantations increased considerably in size and became more aggregated.     

区域农田景观格局对麦蚜种群数量的影响

明确农田景观格局对麦田蚜虫种群的影响,是开展区域性害虫生态调控的重要理论依据之一。以区域性小麦种植区为研究对象,基于遥感影像与土地覆盖分类数据以及田间调查的蚜虫种群数据,计算景观格局指数,使用负二项分布的广义线性模型从农田景观、非作物生境景观和区域景观3个方面分析了区域农田景观格局对麦田蚜虫种群的影响。结果表明,蚜虫种群的数量与草地的平均斑块面积和最大斑块指数显著正相关,与县域的平均几何最邻近距离和面积加权平均斑块面积显著负相关,与耕地的面积加权平均斑块面积显著负相关,与耕地的斑块密度显著正相关。草地斑块面积的增大、区域景观与耕地的破碎化、区域景观的聚集会促进蚜虫种群数量的增加。使用草地的斑块面积和最大斑块指数、区域景观的平均几何最邻近距离可以预测蚜虫种群的发生量。非作物生境草地的斑块面积、耕地的破碎化、区域景观的空间分布及破碎化是影响麦田蚜虫种群发生的重要景观因素。     

广州市帽峰山森林公园森林景观多样性分析

城市森林对改善和美化城市景观起着重要作用.文中在景观分类的基础上,应用景观生态学原理,选取多样性指数、优势度、分离度和斑块密度指数四个指标,从景观的类型多样性、格局多样性和斑块多样性三个方面,对广州市帽峰山森林公园森林景观进行多样性分析.结果表明,经济果林、竹林破碎化程度较高;阔叶混交林类型保持完好,分离度也最小,黎葫林分离度最大;景观类型比例分布最不均衡,组成帽峰山森林公园的各景观类型所占比例差异小于广州地区.     

三江平原流域湿地景观破碎化过程研究

以流域为研究单元,利用历史图件和遥感数据资料及GIS技术,系统分析了该区典型流域50年来湿地景观的破碎化过程.结果表明,该区湿地景观破碎化在斑块个体和空间结构两方面变化极大.景观斑块个体变化主要表现为最大斑块、平均斑块面积不断缩小,斑块密度不断增大,斑块形状破碎化指数不断增大,景观内部生境面积破碎化指数不断上升;空间结构变化主要表现为湿地景观由初始基质景观逐渐变为河岸带景观;同时,随着农田面积逐渐扩大,隔离湿地斑体数量不断上升,隔离度不断增大;景观空间分布模式由“大陆-岛屿模式”向“卫星型模式”转变,最后变化为“完全隔离型模式”.导致该区湿地景观破碎化的主导因素是大规模的农业开发,反映了人类活动对湿地景观的巨大影响.     

景观指数之间的相关分析

应用辽宁省1997~1998年的TM 5影像数据,编制了景观类型图,以78个县市区为单位,分割成78个景观,共计算39个景观格局指数,对它们进行了相关分析。总面积是最基本的景观指数,它决定景观总边界长度、斑块数、类型密度等基本指数,同时与多个指数有显著的相关关系(相关系数绝对值大于0.75)。形状指数的独立性强,极少数指数与其它指数有显著的相关关系;多样性指数和蔓延度指数之间信息重复量最多,都表示景观的异质性,但多样性指数以面积百分比表示景观异质性,而蔓延度指数以类型之间相邻边界的百分比表示景观异质性。研究发现,如果两个指数之间存在显著的相关关系,而由它们两个构成的指数与它们之间没有显著的相关关系。如果指数平均值之间存在显著的相关关系,则它们的变异系数之间不存在显著的相关关系。景观指数间的相关系数不仅与景观格局本身有关,还与空间尺度,分类系统、计算公式及其参数、计算单元和生态学意义关系密切。指数之间影响因子的相同之处越多,它们之间存在显著相关关系的概率越大。     

Performance of partial statistics in individual‐based landscape genetics

Individual‐based landscape genetic methods have become increasingly popular for quantifying fine‐scale landscape influences on gene flow. One complication for individual‐based methods is that gene flow and landscape variables are often correlated with geography. Partial statistics, particularly Mantel tests, are often employed to control for these inherent correlations by removing the effects of geography while simultaneously correlating measures of genetic differentiation and landscape variables of interest. Concerns about the reliability of Mantel tests prompted this study, in which we use simulated landscapes to evaluate the performance of partial Mantel tests and two ordination methods, distance‐based redundancy analysis (dbRDA) and redundancy analysis (RDA), for detecting isolation by distance (IBD) and isolation by landscape resistance (IBR). Specifically, we described the effects of suitable habitat amount, fragmentation and resistance strength on metrics of accuracy (frequency of correct results, type I/II errors and strength of IBR according to underlying landscape and resistance strength) for each test using realistic individual‐based gene flow simulations. Mantel tests were very effective for detecting IBD, but exhibited higher error rates when detecting IBR. Ordination methods were overall more accurate in detecting IBR, but had high type I errors compared to partial Mantel tests. Thus, no one test outperformed another completely. A combination of statistical tests, for example partial Mantel tests to detect IBD paired with appropriate ordination techniques for IBR detection, provides the best characterization of fine‐scale landscape genetic structure. Realistic simulations of empirical data sets will further increase power to distinguish among putative mechanisms of differentiation.     

中性景观模型与真实景观的一致性

采用RULE和SimMap中性景观模型,使其形成模拟景观的图幅大小、景观内各类型数目以及各类型之间的比例等项与真实景观相同,通过不同景观指标对中性模型系列的反应,看其在多大程度上代替真实景观．研究发现,中性景观模型在斑块数、斑块周长、聚集度、蔓延度以及孔隙度等指标所反映的格局特征方面,能很好地代替真实景观,而在校正斑块周长面积比、分维数以及边界分布均匀度等指标所反映的格局特征方面,并不能很好地代替真实景观,说明中性景观模型只能在一定的范围内可以代替真实景观。而不能完全取而代之.     

黄土高原人口密集区城镇扩张对生境质量的影响——以兰州、西安-咸阳及太原为例

快速城镇化过程极大改变了区域生境的空间格局和功能要素,深刻影响生境斑块之间的物质流和能量流,同时对生境和生物多样性造成严重威胁.本研究采用InVEST模型、景观指数及多元线性回归,系统分析了1990-2018年黄土高原全域及人口密集区城镇化对生境质量影响的时空格局特征与因素.结果表明:黄土高原城镇扩张显著影响生境质量,...     

黄土丘陵区生物结皮空间分布的代表性景观指数

景观指数可量化表征生物结皮的分布特征,但景观指数存在数量众多、冗余度较高的问题。本研究以位于典型黄土丘陵区的陕西省吴起县合沟小流域不同分布格局的58个样方的生物结皮为对象,计算其15个常用景观格局指数,基于相关分析、因子分析和敏感性分析,筛选出可描述生物结皮景观格局、具有特定生态学意义的代表性景观指数,并以陕西省定边县杨井镇鹰窝山涧小流域退耕地不同盖度的生物结皮为例,检验所选景观格局指数的可靠性和合理性。结果表明: 15个景观指数中,10个指数之间具有显著相关关系,而边缘长度(TE)和边缘密度(ED)分别与斑块数量(NP)、斑块密度(PD)、丛生度(CLUMPY)和散布与并列指数(IJI)无显著相关性。斑块占景观比例(PLAND)、ED、斑块连结度(COHESION)和分离度(SPLIT),分别从盖度、长度、连通度和破碎度方面描述了生物结皮空间分布特征,其代表的3个公因子在刻画生物结皮空间分布格局时累计贡献率达91.6%。本研究确定了可量化生物结皮空间分布复杂性的代表性景观指数,为研究生物结皮格局变化及其与生态过程的关系提供了理论依据。     

遥感影像空间分辨率及粒度变化对城市景观格局分析的影响

尺度是景观生态学和遥感领域的重要问题,已有研究主要考虑景观的粒度效应,很少涉及遥感影像空间分辨率对景观格局,尤其是对城市景观格局的影响.基于2000年和2002年分别由ETM 和IRS-PAN影像解译得到的土地利用图,从景观和类型两个层次分析了不同粒度下上海市一城市化样带的景观格局.结果表明,城市景观有明显的尺度效应,空间分辨率和粒度变化都会影响城市景观格局,而道路等线性廊道对尺度变化的敏感则是造成这一影响的主要原因.斑块密度、边界密度、平均斑块分维度、景观聚集度和最大斑块指数的粒度效应比较明显,而景观比例、Shannon多样性指数对粒度变化并不敏感.高分辨率影像适用于城市景观格局,尤其是破碎度的分析,其用于分析的合适粒度是5～10m.     

近30年来白洋淀湿地景观格局变化及其驱动机制

湿地是水陆相互作用形成的独特生态系统,其景观格局极易受到气候变化和人类活动的影响。利用1984—2014年的11期遥感影像数据,综合运用GIS技术和景观格局指数方法,对白洋淀湿地景观格局变化特征及其驱动力机制进行了分析。结果表明,1984—2014年期间,挺水植物和沉水植物呈减少趋势,农田和居民点持续快速增长,纯水体为"增加—减少—再增加"的趋势,林地和裸土地变化幅度不大。其中挺水植物一直是白洋淀最主要的景观类型,占研究区总面积比例达到37%—61%。农田的平均斑块面积最大,挺水植物的最大斑块指数和分维度指数最高,挺水植物和农田的聚集度指数最大,居民点、林地和裸土地空间分布离散,破碎化程度高,连通性差。1989—2004年白洋淀景观多样性指数呈减少趋势,景观格局趋于不稳定,同期聚集度指数上升,湿地连通性增加;1984—1989年和2004—2014年期间白洋淀多样性指数上涨,聚集度指数逐年下降,景观异质性增加。人口和社会经济发展是影响白洋淀景观格局变化的主要因素。     

Fusing multidimensional hierarchical information into finer spatial landscape metrics

One of the core issues of ecology is to understand the effects of landscape patterns on ecological processes. For this, we need to accurately capture changes in the fine landscape structures to avoid losing information about spatial heterogeneity. The landscape pattern indicators (LPIs) can characterize the spatial structures and give some information about landscape patterns. However, researches on LPIs had mainly focused on the horizontal structure of landscape patterns, while few studies addressed vertical relationships between the levels of hierarchical landscape structures. Thus, the ignorance of the vertical hierarchical relationships may cause serious biases and reduce LPIs'' representational ability and accuracy. The hierarchy theory about the landscape pattern structures could notably reduce the loss of hierarchical information, and the information entropy could quantitatively describe the vertical status of landscape units. Therefore, we established a new multidimensional fusion method of LPIs based on hierarchy theory and information entropy. Here, we created a general fusion formula for commonly used simple LPIs based on two‐grade land use data (whose land use classification system contains two grades/levels) and derived 3 fusion landscape pattern indicators (FLIs) with a case study. The results show that the information about fine spatial structure is captured by the fusion method. The regions with the most differences between the FLIs and the traditional LPIs are those with the largest vertical structure such as the ecological ecotones, where vertical structure was ignored before. The FLIs have a finer spatial representational ability and accuracy, not only retaining the main trend information of first‐grade land use data, but also containing the internal detail information of second‐grade land use data. Capturing finer spatial information of landscape patterns should encourage the application of fusion method, which should be suitable for more LPIs or more dimensional data. And the increased accuracy of FLIs will improve ecological models that rely on finer spatial information.     

二维与三维景观格局指数在山区县域景观格局分析中的应用

景观格局指数是景观格局分析中常用的定量分析工具,而传统二维景观格局指数却忽略了地形对景观的影响,在定量描述山区景观格局时可能存在一定局限.本文以典型山地丘陵区山东栖霞市为研究区,在地形结构分析的基础上,选择面积/密度(类型面积、平均斑块大小)、边缘/形状(边缘密度、景观形状指数、平均斑块分维数)、多样性(香农多样性指数、香农均匀度指数)、聚散性(聚集度)4个方面的8个景观格局指数,比较分析传统二维景观格局指数与三维景观格局指数对山区景观格局及其动态变化定量描述的差异.结果表明:三维类型面积、平均斑块大小和边缘密度与其相应二维指数差异显著,三维景观形状指数、平均斑块分维数、香农多样性指数和香农均匀度指数与其相应二维指数差异不显著,三维聚集度与二维聚集度无差别.由于采用斑块表面面积和表面周长计算三维景观格局指数,采用各斑块的投影面积和投影周长计算二维景观格局指数,所以在描述山区景观面积、密度、边界等指标时三维景观格局指数相对精确,但在测定景观形状、多样性和聚散性等指数时,则与传统的二维景观格局指数差异不显著.三维景观格局指数引入了地形特征,对景观格局及其动态变化的反映相对精确.     

区域城市扩张对森林景观破碎化的影响——以粤港澳大湾区为例

森林生境丧失与景观破碎化是引起生物多样性下降,生态系统功能降低的重要原因。量化森林景观破碎化的时空特征及其与城市扩张格局的关系是开展区域生态修复与功能提升的重要基础。本文以快速城市化的典型区域——粤港澳大湾区为研究对象,基于遥感解译的1980年、1990年、2000年、2010年和2018年土地覆盖/利用专题图,通过多尺度的景观格局分析和统计分析,定量解析森林景观破碎化的时空演变特征及其与城市扩张格局间的关系。研究结果显示：1）1980-2018年,大湾区林地覆盖面积缩减1,274 km²,林地转变为建设用地的面积占林地丧失总面积的比例从1980-1990年的11%增长至2010-2018年的42%,表明城市扩张已成为林地丧失的主导因素;2）森林景观破碎化程度加剧,表现为林地斑块密度提高,平均斑块面积减小,但破碎类型与程度具有地域差异;3）城市扩张幅度与空间格局显著影响林地破碎化,其中,城市扩张幅度对林地破碎化的影响更为重要。基于森林景观破碎化与城市扩张的现状,落实城市增长边界划定、关键斑块-廊道识别与生态网络构建等措施,有助于保护与连通重要生态空间,保障和提升生态功能。     

景观生态学:两栖动物生态学研究的新途径

全球两栖动物正以远超过自然灭绝的高速率灭绝,这与生境丧失和景观破碎化有着直接关系。生境丧失导致两栖动物的生存空间减少,使局部种群消失,而景观破碎化则导致两栖动物种群之间的隔离度增加,不利于动物的繁殖和扩散。但两者往往是同时出现,相互作用。复合种群、景观连接度、景观遗传学及景观模型模拟等理论和方法的发展,为在生境丧失与破碎化景观下两栖动物的种群结构、组成和动态变化研究提供了理论基础和技术方法。同时景观生态学中特别重视研究的尺度,生境破碎化是发生在景观尺度下的生境变化过程,因此对生境破碎化的影响应该从现有的主要集中在斑块尺度和斑块-景观尺度转变到景观尺度上来。     

陕北黄土高原景观破碎化及其土壤裸露效应

破碎化是黄土高原典型的景观特征 ,深刻影响着区域的景观格局与功能。为深入探讨黄土高原景观破碎化的格局特征及其生态效应 ,选择陕北黄土高原为研究区 ,结合景观格局指数与主成分分析对破碎化程度进行量化 ,并针对研究区相应的景观格局特征、造成破碎化的景观类型及土壤裸露程度 ,进行组成、分布及动态分析。研究结果发现陕北黄土高原景观格局中的斑块密度特征对破碎化有较强的指示意义 ,其次则是景观的空间构型特征。草地和农地等与人为活动关系较为密切的景观类型是造成研究区景观破碎化的主要原因 ,且高破碎化区域的土壤裸露值明显高于低破碎化区域     

2D与3D景观指数测定山区植被景观格局变化对比分析

植被和土地覆盖变化是环境变化的一个重要因素,同时也是引起景观和生态系统变化的重要原因。景观指数是定量分析植被和土地覆盖变化的重要研究方法之一。以滇西北高山峡谷区为案例区,比较分析传统2D景观指数和3D景观指数进行植被变化定量测定的差异。研究主要选取了基于斑块面积和周长几个常用指数来进行比较分析。研究结果表明在斑块层次上,除了分维数指数,其他指数的三维方法计算值显著地高于二维方法计算值;在类型层次上,三维的类型面积指数、平均斑块面积指数、平均最小邻近距离指数测定的变化值显著大于二维的相应指数测定变化值,但是二维和三维平均形状指数和分维指数测定的植被斑块的平均形状变化结果没有显著差异;在景观层次,只有三维的平均斑块面积和最小邻近距离指数测定的变化结果显著高于二维的平均面积和最小邻近距离指数测定的变化结果,其它指数如形状指数、分维指数、多样性指数和均一度指数等测定出两个不同时期的植被图格局变化结果均无显著差异,主要由于这些指数是采用面积和周长的对数或者比值计算得出,从而缩小了斑块表面面积与平面面积,表面周长与平面周长之间的差异。总体而言,利用二维景观指数在进行定量分析山区植被格局变化时,往往低估了其类型面积、平均斑块面积、斑块邻近距离等指数变化量,而三维景观指数得到相对较精确的变化值。