城市化景观格局对本土植物多样性的多尺度影响——以北京市顺义区为例

景观格局对植物多样性的影响已经在很多研究中得到了验证,但有关城市景观的影响仍然知之甚少。为了探究城市化景观格局对植物多样性的影响及其尺度效应,本研究在北京市顺义区调查了105个样地,计算每个样地的α和β多样性指数;并以100 m为步长,分析了100～1000 m范围内的10个尺度43个城市的景观格局指数。结果表明: 在所有尺度上,城市景观面积指数、核心类指数和边缘指数与本土植物多样性均呈负相关;形状复杂性指数在小尺度内有利于植物多样性,而面积加权复杂性指数则在较大尺度上影响明显。其他指数如城市斑块的连接性、邻近性、内聚性、破碎性和散布并列指数与本土植物多样性之间的关系轻微且不稳定。城市化强度与尺度呈负相关,与各个尺度的植物多样性呈负相关。合理将城市区域分为许多边缘简单的小斑块,能够更好地保护本土植物多样性。该研究提出了保护城市植物多样性的景观格局建议,为生态城市建设提供参考。     

Evaluating the effectiveness of landscape metrics in quantifying spatial patterns

The effectiveness of landscape metrics in quantifying spatial patterns is fundamental to metrics assessment. Setting 36 simulated landscapes as sample space and focusing on 23 widely used landscape metrics, their effectiveness in quantifying the complexity of such spatial pattern components as number of patch types, area ratio of patch types and patch aggregation level, were analyzed with the application of the multivariate linear regression analysis method. The results showed that all the metrics were effective in quantifying a certain component of spatial patterns, and proved that what the metrics quantified were not a single component but the complexity of several components of spatial patterns. The study also showed a distinct inconsistency between the performances of landscape metrics in simulated landscapes and the real urban landscape of Shenzhen, China. It was suggested that the inconsistency resulted from the difference of the correlation among spatial pattern components between simulated and real landscapes. After considering the very difference, the changes of all 23 landscape metrics against changing of number of patch types in simulated landscapes were consistent with those in the real landscape. The phenomenon was deduced as the sign effect of spatial pattern components on landscape metrics, which was of great significance to the proper use of landscape metrics.     

景观指数耦合景观格局与土壤侵蚀的有效性

景观格局分析是景观生态学中揭示景观变化及其生态效应的主要方法,而景观指数是景观格局分析中广泛使用的工具。土壤侵蚀是土壤物质在景观中的迁移和再分配过程,受地形、植被和人类活动及其空间格局的调控。运用景观格局分析揭示景观格局变化特别是土地利用/覆被格局变化对土壤侵蚀的影响是土壤侵蚀研究中应用景观生态学原理和方法的典型。在当前的研究中,斑块-廊道-基质范式下建立的景观指数对侵蚀过程的解释能力不断受到质疑,建立筛选适用的景观指数的原则和方法十分必要。以延河流域碾庄沟小流域为例,利用WATEM/SEDEM模型模拟多个年份流域侵蚀产沙和输沙量;基于土地利用/覆被数据,利用Fragstat4.2软件,计算了相应年份流域斑块、边界密度、形状、集聚与分散和斑块类型多样性4个方面的代表性景观指数。在此基础上,分析了景观指数与流域侵蚀产沙和输沙之间的关系,讨论了景观指数在土壤侵蚀研究中的有效性,在景观和斑块类型水平上分析了景观指数表达"源"、"汇"两大类景观类型的空间格局与侵蚀产沙和输沙之间的关系的一致性。结果表明:斑块-廊道-基底范式下发展的景观指数在指示景观格局的土壤侵蚀效应时存在局限。相对而言,斑块类型尺度的景观指数更能有效表达景观格局与土壤侵蚀的关系。基于景观类型在土壤侵蚀过程中的"源"、"汇"功能,提出了在土壤侵蚀研究中筛选适用的景观指数的原则:(1)对"源"、"汇"两类景观类型,景观指数与土壤侵蚀状况表征变量的相关系数符号相反;(2)对同为"源"或"汇"景观类型的多个景观类型,景观指数与土壤侵蚀表征变量的相关系数应具有符号一致性。尽管景观指数在斑块类型水平上具有一定的有效性,但用其预测景观格局变化的侵蚀效应有很大的不确定性。因此,基于土壤侵蚀过程与景观格局的作用机制发展新型的景观指数是增强景观格局分析预测土壤侵蚀过程的能力的途径。     

景观格局-土壤侵蚀研究中景观指数的意义解释及局限性

景观格局分析是景观生态学研究的重要组成部分。景观指数是景观格局分析的有力工具。近年来,景观格局与土壤侵蚀关系的相关研究增多,常规景观格局指数得到应用。但针对土壤侵蚀过程的景观指数意义解释不足,景观指数在刻画景观格局-土壤侵蚀过程关系存在局限。选择了连接性、多样性、边界/斑块密度、形状4个方面的12个常用景观指数,对这些指数在景观格局-土壤侵蚀过程关系研究中的意义进行阐述,对指数应用的局限性及其原因进行了分析。景观数据属性、景观指数本身性质和土壤侵蚀过程的复杂性使得常规景观格局指数在景观格局-土壤侵蚀关系研究中存在不足。这3方面的影响使得常规景观格局指数与土壤侵蚀表征变量之间不存在确定的关系,从而难以通过景观指数来表征景观土壤侵蚀特征。缺乏土壤侵蚀过程基础是常规景观指数在土壤侵蚀研究应用中存在局限的主要原因。因此,构建基于土壤侵蚀过程的景观指数是景观格局-土壤侵蚀关系研究的需要和新的发展方向。     

Towards a core set of landscape metrics for biodiversity assessments: A case study from Dadia National Park,Greece

Spatial heterogeneity has an important influence on a wide range of ecological patterns and processes, and many landscape metrics in GIS environment are used to facilitate the investigation of the relation between landscape structure and biodiversity. Data reduction analyses have been applied to tackle the problem of highly correlated indices, but valid landscape predictors for fine scale Mediterranean forest-mosaics are still missing. Therefore, we analyzed the landscape structure of Dadia National Park, Greece, a Mediterranean forest landscape of high biodiversity, characterized by pine, oak and mixed woodland. By distinguishing nine land cover classes, 119 variables were computed and factor analysis was applied to detect the statistical dimensions of landscape structure and to define a core set of representative metrics. At landscape level, diversity of habitats, fragmentation and patch shape and at class level dominance of mixed forest and the gradient from one pure forest type to another turned out to be the crucial factors across three different scales. Mapping the encountered dimensions and the representative metrics, we detected that the pattern of landscape structure in Dadia National Park was related to dominating habitat types, land use, and level of protection. The evaluated set of metrics will be useful in establishing a landscape monitoring program, to detect the local drivers of biodiversity, and to improve management decisions in Dadia NP and similar mosaic-landscapes.     

基于景观格局的城市热岛研究进展

首先对城市热岛效应的研究历史、大气城市热岛(AUHI)和地表城市热岛(SUHI)等概念、以及数据获取方式等方面进行简要地概述;随之着重综述从景观格局角度对城市热岛效应进行的研究。统计描述、传统景观格局指数分析和模型模拟法是目前该方向研究的主要方法,统计和景观格局指数分析的研究方法相似,主要统计地表参数或地表景观格局指数与地表温度的相关关系,在SUHI的研究中用得较多;AUHI和SUHI的数据源和机理不尽相同,其研究方法也不同;AUHI一般使用固定气象站点的数据和精细的局部移动气象站数据,较难和景观格局指数结合;模型模拟法则既可以使用地表温度也可以使用大气温度,其结果具体可靠,但目前模型模拟中涉及的景观格局参数,尤其是二维或多维的格局参数并不多;最后从数据源和景观格局参数的参与两个角度讨论了该方向研究存在的问题并提出今后研究的重点,包括(1)针对研究目标,选取或生产最合适的高质量数据;(2)深入从景观格局角度模拟城市热岛效应的研究,尤其是二维和三维景观格局的模拟,并发展多维度的景观格局指数;(3)中尺度上充分利用多光谱遥和热红外遥感数据,结合小尺度的测量和模拟,建立基于机理的景观模型或格局指数以评价中尺度的城市热岛效应;(4)多领域数据的融合和多学科方法的交叉研究和应用。     

徐州城市景观格局对绿地植物多样性的多尺度影响

城市地表景观的变化导致城市生物栖息地的损坏、破碎和丧失,致使城市生物多样性下降.为探讨城市景观格局变化对植物多样性的影响,本研究以徐州市绕城高速公路内的城区为对象,采用布朗布伦奎特(Braun-Blanquet)盖度等级法对36块城市绿地植物群落进行调查,并对不同绿地植物群落的物种多样性进行了分析.同时,以研究区2005和2015年的Landsat ETM遥感影像作为基础数据源,在Erdas、GIS、Fragstats软件的支持下,以每块调查样地为中心,分别建立9个不同半径的缓冲区,计算各缓冲区内表征斑块形状、破碎度和连通性共3类39个景观指数,在此基础上,运用冗余分析(RDA)筛选出不同幅度下对城市绿地植物多样性有显著影响的景观格局指数.结果表明: 植物多样性对景观整体格局和景观要素的响应具有明显的时间和空间尺度效应.2005年,未利用地和农田的破碎度、形状指数在800 m半径的缓冲区内能更好地解释植物多样性,建筑用地的破碎度和连通性指数在800～2000 m范围内对植物多样性有重要影响;2015年,草地和林地景观在800 m缓冲区内可更好地解释植物多样性,而建筑用地和未利用地在1000～2000 m范围内对植物多样性有显著影响;研究区当前植物多样性受2005年类型水平景观指数的影响更显著,说明研究区植物多样性对周边景观格局变化的响应存在一定的时间滞后;景观水平的格局指数与类型水平指数特征较为一致,说明物种与空间尺度的相互作用更多依赖于景观类型.     

浑善达克沙地中部斑块格局影响植物多样性及功能性状

景观格局与植物多样性之间的关系已被广泛研究,然而,斑块格局如何影响植物多样性,以及这些影响的边缘类型差异尚不清楚。为从植物功能性状角度揭示斑块格局影响植物多样性的机制,该研究采用不同边缘类型的斑块,利用两年调查的705个样方数据,结合遥感卫星图像解译和空间信息分析,根据植物群落的空间位置和斑块格局,按照向内、向外、向内成核和向外成核4种边缘类型将浑善达克沙地中部的斑块进行分类,采用Duncan新复极差法比较了4种边缘类型斑块格局与植物功能性状多样性关系的差异,应用Pearson相关系数和冗余分析(RDA)法量化了斑块格局对植物多样性的影响。结果发现,植物丰富度和多样性指数与斑块格局密切相关,这些关系存在着边缘类型的显著差异,表现出不同的功能性状。对于向内边缘,边缘指数与丰富度负相关,和C₄植物比例正相关;对于向外边缘,边缘指数与C₄植物比例正相关;对于向内成核边缘,边缘密度与多年生植物和虫媒植物比例正相关;对于向外成核边缘,边缘角度和指数与物种Shannon-Wiener指数和Simpson指数正相关,与Pielou指数、丰富度和动物传播植物...     

流域景观格局变化对洪枯径流影响的SWAT模型模拟分析

为了进一步揭示流域景观格局变化的水文效应,以晋江流域为研究区,基于SWAT模型分别模拟1985年和2006年两种景观格局下,2002—2010年气象条件时的日径流过程;应用景观格局分析法和Pearson相关分析法,定量分析了景观格局变化对洪枯径流的影响,探讨了影响机制。研究表明:(1)SWAT模型能够较精确模拟晋江流域的日径流过程;(2)2002—2010年气象条件时,与1985年景观格局相比,在2006年景观格局下晋江流域年平均最大1 d和连续最大5 d径流深分别增加5.46%和4.97%,年平均最小1 d和连续最小7 d径流深分别减少3.79%和2.55%;(3)洪水径流与景观格局相关性最显著,最大1 d和连续最大5 d与林地景观面积呈显著负相关,相关系数分别为-0.764和-0.721;最大1 d与Shannon多样性指数和Shannon均匀度指数呈显著正相关,相关系数分别为0.721和0.736;与最大斑块指数和蔓延度呈显著负相关,相关系数分别为-0.61和-0.596,说明林地景观面积的减少降低了流域对强降水的截留能力;景观类型均衡化分布,连通性降低,降低了水分在流域的内部循环能力,导致洪峰流量的增加;(4)景观格局指数与最小1 d和连续最小7 d的相关性不显著,说明景观格局变化对枯水径流的直接影响较小。     

粒度变化对上海市景观格局分析的影响

采用1989年上海市1∶50 000彩红外航空遥感影像解译的土地利用数据,系统分析了粒度变化对中心城区、郊区和城郊结合部3类景观格局分析的影响.结果表明:景观格局指数对粒度具有尺度依赖性,随粒度的变粗,格局指数的变化可归为单调下降、阶梯上升或单峰变化以及不规则变化3类;景观格局指数随粒度变化的曲线存在多个拐点,并对应于合适的景观格局分析尺度,上海城市景观格局分析的合适尺度为10～20 m;不同城市景观类型对景观格局指数的粒度效应具有较大影响,景观格局指数在城郊结合部表现出与城区和郊区不同的变化趋势.     

基于GIS的上海市景观格局梯度分析

 定量分析景观格局及其变化对于监测和评价城市化的生态后果十分重要。该研究应用基于GIS的梯度分析与景观指数相结合的方法定量分析了上海市城市化的空间格局。沿一条自西向东64 km长6 km宽和另一条自南向北66 km长6 km宽的样带,应用移动窗口计算了一系列景观指数。结果表明,城市化的空间格局可以用梯度分析与景观指数来定量,不同的土地利用类型沿景观格局梯度确实表现出明显的“空间特征”。多项景观指数可准确地、定量地指示上海地区东西和南北发展轴线上城市化的前沿和城市景观梯度分异的特征。城市化的总体格局是随着城市化程度增加,景观在组分上更多样化,形状上更为复杂以及生态学上更破碎化。此外,该文显示的上海市城市化景观格局比较符合同心圆论的城市发展理论,研究结果支持斑块密度随城市化程度而增加,斑块大小和景观连接度则下降的假说,但与随人类干预程度增强,斑块形状变得更规则的假说不相符和,因此,需要进一步研究来证实该发现。     

Interactions between landcover pattern and geospatial processing methods: Effects on landscape metrics and classification accuracy

Remote sensing data is routinely used in ecology to investigate the relationship between landscape pattern as characterised by land use and land cover maps, and ecological processes. Multiple factors related to the representation of geographic phenomenon have been shown to affect characterisation of landscape pattern resulting in spatial uncertainty. This study investigated the effect of the interaction between landscape spatial pattern and geospatial processing methods statistically; unlike most papers which consider the effect of each factor in isolation only. This is important since data used to calculate landscape metrics typically undergo a series of data abstraction processing tasks and are rarely performed in isolation. The geospatial processing methods tested were the aggregation method and the choice of pixel size used to aggregate data. These were compared to two components of landscape pattern, spatial heterogeneity and the proportion of landcover class area. The interactions and their effect on the final landcover map were described using landscape metrics to measure landscape pattern and classification accuracy (response variables). All landscape metrics and classification accuracy were shown to be affected by both landscape pattern and by processing methods. Large variability in the response of those variables and interactions between the explanatory variables were observed. However, even though interactions occurred, this only affected the magnitude of the difference in landscape metric values. Thus, provided that the same processing methods are used, landscapes should retain their ranking when their landscape metrics are compared. For example, highly fragmented landscapes will always have larger values for the landscape metric “number of patches” than less fragmented landscapes. But the magnitude of difference between the landscapes may change and therefore absolute values of landscape metrics may need to be interpreted with caution. The explanatory variables which had the largest effects were spatial heterogeneity and pixel size. These explanatory variables tended to result in large main effects and large interactions. The high variability in the response variables and the interaction of the explanatory variables indicate it would be difficult to make generalisations about the impact of processing on landscape pattern as only two processing methods were tested and it is likely that untested processing methods will potentially result in even greater spatial uncertainty.     

千岛湖生态保护与建设对景观格局的影响研究

生态保护和生态建设过程对景观格局产生影响并使之发生变化,这种变化又会影响景观的生态过程。应用3s技术和景观指数分析了39年(1964-2003年)内千岛湖库区土地利用和土地覆盖格局的变化。结果显示,斑块总数和景观破碎度基本保持不变,但是各斑块类型的斑块数量、面积和优势度变化非常显著。最优势斑块类型由荒山(占陆地面积的47．44％)演变为马尾松( Pinus massoniana)林(占陆地面积的52．8l％),研究区域内森林植被覆盖率增加。研究还发现景观多样性指数略微下降。景观多样性是对土地利用和覆盖类型丰富度和均匀度的概要度量,并不一定总是和景观功能呈正相关关系。上述变化归因于多项生态保护措施的实施使得自然演替得以实现。景观格局的优化使生态系统的生态功能得到提高,包括生境恢复、生物多样性增加、水土流失减少。森林植被恢复以后,马尾松林斑块的单一化趋势应在今后的生物多样性保护、生态规划和可持续发展中得到重视。     

粒度变化对城市热岛空间格局分析的影响

尺度是景观格局和生态过程研究中的关键问题。综合目前城市热岛效应研究来看,景观格局指数的引入极大推进了热岛格局的定量研究,然而其尺度效应仍未得到重视。由于热岛空间格局与形成过程的复杂性和人类认识的局限性,对其尺度问题有待深入讨论。基于Landsat TM影像反演地表温度,采用均值-标准差分类方法划分热力等级,对珠三角城市热岛格局特征的粒度效应进行了研究。结果显示:随粒度增加,弱势热力斑块类型下降,向相邻斑块转移;景观指数在类型水平和景观水平均受空间粒度影响明显,"临界粒度"现象明显;总体而言,粒度150 m是城市热岛格局特征的临界粒度,对热岛格局进行景观指数计算的适宜粒度范围为30—150 m;不同景观指数粒度效应曲线有所差异,其中斑块密度和平均分维数在两个水平指数上都有较强的规律性;根据各景观指数变化特征,研究区尺度域主要在(30 m,150 m),表明在该尺度范围内构建的热岛效应预测模型可经简单推绎后使用。分析热岛格局随空间粒度变化特征对了解热岛格局的形成机制及进行尺度推绎具有重要意义。     

基于模拟景观的城市森林景观格局指数选取

基于现实的沈阳城市森林景观,模拟了4个景观格局梯度,并选取了1个与之相应的现实景观格局梯度,分析了28个景观格局指数在各梯度对景观破碎化和景观斑块形状复杂性的反映,从而筛选出描述这两种景观格局特征的适宜景观格局指数.结果表明：斑块密度（PD）和平均斑块面积（AREA_MN）在城市森林景观破碎化方面表现出较规律的变化趋势,斑块密度随破碎化程度的增加而增加,平均斑块面积随破碎化程度的增加而减小;面积加权平均周长面积比（PARA_AM）在描述景观斑块形状复杂性方面与景观格局梯度相吻合,且随斑块形状复杂性的增加而增加,能够较为准确地描述景观斑块形状的复杂性.     

On using landscape metrics for landscape similarity search

Landscape similarity search involves finding landscapes from among a large collection that are similar to a query landscape. An example of such collection is a large land cover map subdivided into a grid of smaller local landscapes, a query is a local landscape of interest, and the task is to find other local landscapes within a map which are perceptually similar to the query. Landscape search and the related task of pattern-based regionalization, requires a measure of similarity – a function which quantifies the level of likeness between two landscapes. The standard approach is to use the Euclidean distance between vectors of landscape metrics derived from the two landscapes, but no in-depth analysis of this approach has been conducted. In this paper we investigate the performance of different implementations of the standard similarity measure. Five different implementations are tested against each other and against a control similarity measure based on histograms of class co-occurrence features and the Jensen–Shannon divergence. Testing consists of a series of numerical experiments combined with visual assessments on a set of 400 3 km-scale landscapes. Based on the cases where visual assessment provides definitive answer, we have determined that the standard similarity measure is sensitive to the way landscape metrics are normalized and, additionally, to whether weights aimed at controlling the relative contribution of landscape composition vs. configuration are used. The standard measure achieves the best performance when metrics are normalized using their extreme values extracted from all possible landscapes, not just the landscapes in the given collection, and when weights are assigned so the combined influence of composition metrics on the similarity value equals the combined influence of configuration metrics. We have also determined that the control similarity measure outperforms all implementations of the standard measure.     

流域景观格局与河流水质的多变量相关分析

流域内的景观格局改变是人类活动的宏观表现,会对河流水质产生显著影响,因此明确影响水质变化的关键景观因子,对于深入了解景观对水质的影响机制具有重要的研究价值。选择广东省淡水河流域为研究对象,以2007年ALOS卫星影像以及水质监测数据为基础,运用空间分析和多变量分析方法,分析淡水河流域景观格局与河流水质的相关关系。用包括流域和河岸带尺度的景观组成和空间结构信息的景观指数表征景观格局,用Spearman秩相关分析、多元线性逐步回归模型和典型相关分析(CCA)研究景观指数和水质指标的相关关系。研究结果表明:林地、城镇用地和农业用地占淡水河流域总面积超过90%,其中城镇用地超过20%。多元线性逐步回归分析和CCA结果说明水质指标受到多个景观指数的综合影响,反映了景观格局对水质的复杂影响机制。流域景观格局对河流水质有显著影响,流域尺度的景观指数比河岸带尺度的景观指数对水质影响更大。城镇用地比例是影响耗氧污染物和营养盐等污染物浓度最重要的景观指数,林地和农业用地对水质的影响较小。另外,景观破碎化对pH值、溶解氧和重金属等水质指标有显著影响。CCA的第一排序轴解释了景观指数与水质指标相关性的54.0%,前两排序轴累积能解释景观指数与水质指标相关性的87.6%,前两轴分别主要表达了城市化水平和景观破碎化水平的变化梯度。淡水河流域的景观格局特征从上游到下游呈现出城市—城乡交错—农村的景观梯度,水质变化也对应了这个梯度的变化,说明人类活动引起的流域土地覆盖及土地管理措施变化会对水质变化产生显著影响。     

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。     

Scale dependence of landscape metrics and their indicatory value for nutrient and organic matter losses from catchments

We investigated scale dependence of landscape metrics and the relationship between land use parameters and FRAGSTATS-based landscape metrics (edge density (ED), patch density (PD), mean shape index (SHAPE_MN), mean euclidean nearest neighbor index (ENN_MN), contagion (CONTAG), patch richness density (PRD), and Shannon's diversity index (SHDI)) and nutrient/organic-matter-based water quality indicators (BOD₇ and COD_KMnO4 values, total-N and total-P concentrations in water) in 24 catchments with various land use patterns in Estonia. We used the Basic Map of Estonia (1:10,000), the Base Map of Estonia (1:50,000) and the CORINE Land Cover Map (1:100,000). In scale analysis, we calculated landscape metrics on artificial and real landscapes. Scale analysis showed that responses of landscape metrics to changing grain size vary among landscapes and metrics. Analysis of artificial landscapes showed that mean euclidean nearest neighbor distance and contagion are directly dependent on grain size and should therefore be used carefully. When finding relationships between landscape metrics and water quality indicators, significant differences between the relationships derived from the Base Map and the CORINE Land Cover Map were found. In the case of the Base Map, landscape metrics correlated strongly with land use and showed no expected relationships with water quality data. This underlines the importance of land use classification in such kind of analysis. Correlation between the landscape metrics calculated on the basis of the CORINE Land Cover Map and water quality data was stronger than in the case of the Base Map. The COD_KMnO4 value significantly correlated with all land use types. For instance, the COD_KMnO4 values are higher when fens and natural areas form a higher proportion of the catchments’ land use. Except for the BOD₇ value, all the water quality indicators showed significant correlation with urban land use proportions. Strong relationship between the patch density and the COD_KMnO4 value is most likely caused by the fact that both parameters were significantly correlated with the proportion of natural areas. As the landscape metrics depend on pixel size, topographic scale, and land use classification, and as the effect of land use on water quality in catchments is the most significant of the factors, it was impossible to separate the influence of land use pattern from the influence of FRAGSTATS-based landscape metrics.