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Living Rev Landscape Res 3 (2009) 1httpwwwlivingreviewsorglrlr-2009-1 in landscape research

RRRRLLLLL I V I N G REVIEWS

Landscape Metrics and Indices

An Overview of Their Use in Landscape Research

Evelin UuemaaDepartment of Geography Institute of Ecology and Earth Sciences University of Tartu

46 Vanemuise St Tartu Estonia 51014email kevelynutee

Marc AntropDepartment of Geography University of Ghent Krijgslaan 281 S8 9000 Gent Belgium

email MarcAntropUGentbe

Juri RoosaareUniversity of Tartu (see above)

email juriroosaareutee

Riho MarjaUniversity of Tartu (see above)

email rihomarjautee

Ulo ManderUniversity of Tartu (see above)

email ulomanderutee

Living Reviews in Landscape ResearchISSN 1863-7329

Accepted on 1 March 2009Published on 17 March 2009

Abstract

The aim of this overview paper is to analyze the use of various landscape metrics andlandscape indices for the characterization of landscape structure and various processes atboth landscape and ecosystem level We analyzed the appearance of the terms landscapemetricsindexesindices in combination with seven main categories in the field of landscapeecology [1) useselection and misuse of metrics 2) biodiversity and habitat analysis 3) waterquality 4) evaluation of the landscape pattern and its change 5) urban landscape patternroad network 6) aesthetics of landscape 7) management planning and monitoring] in thetitles abstracts andor key words of research papers published in international peer-reviewedscientific journals indexed by the Institute of Science Information (ISI) Web of Science (WoS)from 1994 to October 2008 Most of the landscape metrics and indices are used concerningbiodiversity and habitat analysis and also the evaluation of landscape pattern and its change(up to 25 articles per year) There are only a few articles on the relationships of landscapemetricsindicesindexes to social aspects and landscape perception

Keywords Biodiversity FRAGSTATS Landscape aesthetics Landscape ecology Landscapepattern Landscape planning

This review is licensed under a Creative CommonsAttribution-Non-Commercial-NoDerivs 30 Germany Licensehttpcreativecommonsorglicensesby-nc-nd30de

Imprint Terms of Use

Living Reviews in Landscape Research is a peer reviewed open access journal published by theLeibniz Centre for Agricultural Landscape Research (ZALF) Eberswalder Straszlige 84 15374Muncheberg Germany ISSN 1863-7329

This review is licensed under a Creative Commons Attribution-Non-Commercial-NoDerivs 30Germany License httpcreativecommonsorglicensesby-nc-nd30de

Because a Living Reviews article can evolve over time we recommend to cite the article as follows

Evelin Uuemaa Marc Antrop Juri Roosaare Riho Marja and Ulo ManderldquoLandscape Metrics and Indices An Overview of Their Use in Landscape Researchrdquo

Living Rev Landscape Res 3 (2009) 1 [Online Article] cited [ltdategt]httpwwwlivingreviewsorglrlr-2009-1

The date given as ltdategt then uniquely identifies the version of the article you are referring to

Article Revisions

Living Reviews supports two different ways to keep its articles up-to-date

Fast-track revision A fast-track revision provides the author with the opportunity to add shortnotices of current research results trends and developments or important publications tothe article A fast-track revision is refereed by the responsible subject editor If an articlehas undergone a fast-track revision a summary of changes will be listed here

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For detailed documentation of an articlersquos evolution please refer always to the history documentof the articlersquos online version at httpwwwlivingreviewsorglrlr-2009-1

Contents

1 Introduction 5

2 Methods 5

3 Results and Discussion 631 ldquoLandscape metricsrdquo vs ldquolandscape indicesrdquo 632 Use and selection of metrics 733 Biodiversity and habitat analysis 834 Estimating water quality 1135 Evaluation of landscape pattern and changes therein 1136 Urban landscape pattern road network 1337 Landscape aesthetics 1438 Management and planning 15

4 Conclusions 17

5 Acknowledgements 17

References 18

List of Tables

1 Correlations between various landscape metrics and biological variables indicatingbiodiversity and habitat features 9

2 Correlation between various landscape metrics and water quality parameters 123 Correlation between various landscape metrics and parameters characterizing land-

scape aesthetics 14

Landscape Metrics and Indices 5

1 Introduction

The quantification of spatial heterogeneity is necessary to elucidate relationships between ecologicalprocesses and spatial patterns (Turner 1990 Turner et al 2003) Therefore the measurementanalysis and interpretation of spatial patterns receive much attention in landscape ecology (Haines-Young and Chopping 1996) A great variety of metrics for landscape composition (eg the numberand amount of different habitat types) and configuration (the spatial arrangement of those classes)were developed for categorical data Software packages are widely used (eg FRAGSTATS seeMcGarigal and Marks 1995 McGarigal et al 2002) and many metrics have also been integratedinto existing geographic information system (GIS) software (eg Patch Analyst in ArcView andmodule Pattern in IDRISI)

Although spatial pattern analysis should be considered to be a tool rather than a goal in andof itself and the objectives or questions driving any analysis must include the qualities of thepattern to be represented and why there are many examples in the literature when this has notbeen correctly followed (Li and Wu 2004) Several issues associated with the interpretation oflandscape metrics are widely used by practitioners (Gustafson 1998 Haines-Young and Chopping1996 Li and Wu 2004 Turner et al 2003) Many metrics are sensitive to changes in the spatialresolution (grain size) of the data or the area (extent) of the landscape (Wickham and Riitters1995) and numerous correlations occur among landscape indices (Riitters et al 1995 Cain et al1997) The downscaling and upscaling of landscape metrics as functional and structural landscapeindicators at different scales still remains a challenge (Mander et al 2005)

On the other hand the common usage of the term ldquolandscape metricsrdquo mostly refers to indicesdeveloped for categorical map patterns (McGarigal et al 2002) but it is sometimes also used fortopographic measures (Iampietro et al 2005 Vivoni et al 2005) that characterize landscape or itmay also just refer to some combination of several characteristics that are important to a particularspecies (Schils 2006 Fernandez et al 2007)

The main aim of this paper is to give an overview of the development and state of the art ofthe applications for landscape metrics one of the classical landscape ecological tools and studyobjects that help us better understand the relationships between landscape pattern and processes

2 Methods

We analyzed papers published in international peer-reviewed journals that are indexed by theInstitute of Science Information (ISI) Web of Science (WoS) from 1994 to October 2008 Theterms ldquolandscape metricsrdquo ldquolandscape indexesrdquo and ldquolandscape indicesrdquo were searched as bothseparate items and in combination with the following terms

ldquobiodiversityrdquo ldquohabitatrdquo ldquourban landscaperdquo ldquoroad networkrdquo ldquowater qualityrdquo ldquowatershed(s)rdquoldquocatchment(s)rdquo ldquolandscape patternrdquo ldquolandscape structurerdquo ldquoFragstatsrdquo ldquoland userdquo ldquoland usechangerdquo ldquolandscape aestheticsrdquo and ldquoaesthetics of landscaperdquo ldquolandscape planningrdquo ldquolandscapemanagementrdquo

The appearance of these terms and combinations thereof in the titles abstracts andor keywords of papers was taken into account The overlapping issues (if the terms or combinationsappeared in the same paper) were not double-counted

Living Reviews in Landscape Researchhttpwwwlivingreviewsorglrlr-2009-1

6 Evelin Uuemaa Marc Antrop Juri Roosaare Riho Marja and Ulo Mander

3 Results and Discussion

There are 331 articles for the term ldquolandscape metricsrdquo 131 articles for the term ldquolandscapeindicesrdquo and 17 for ldquolandscape indexesrdquo in the ISI Web of Science literature database (October 142008) In fact some of the articles overlapped and a few articles were added by using the singularform of the two terms We therefore eventually reviewed 337 articles for the term ldquolandscapemetricsrdquo and 141 articles for the term ldquolandscape indicesrdquo and ldquolandscape indexesrdquo

31 ldquoLandscape metricsrdquo vs ldquolandscape indicesrdquo

The term ldquolandscape metricsrdquo appears more frequently but there are no definite rules or traditionsas to when one or the other term is used It seems that the term ldquolandscape metricsrdquo is used moreoften only for metrics calculated by Fragstats or by some of its developments in other programs(FRAGARC Fragstats for ArcView Patch Analyst etc) The term ldquolandscape indicesrdquo is morefrequently used in a broader sense ie metrics have similar or the same formulae as in Fragstatsbut are named differently Also in terms of the timeline of their use (Figure 1) it can be seenthat the term ldquolandscape indicesrdquo was more often used in the 1990s and now the term ldquolandscapemetricsrdquo is prevalent From here on we will only use the term ldquolandscape metricsrdquo

Figure 1 The use of the terms ldquolandscape metricsrdquo and ldquolandscape indicesrdquo in titles abstracts andorkey words of international peer-reviewed scientific papers The analysis has been performed on the basisof journal papers indexed by the ISI Web of Science from 1994 to October 2008

The usage of landscape metrics is very broad and can be grouped into seven general categoriesa) use and misuse selection of metrics b) biodiversity and habitat analysis c) estimating waterquality d) evaluation of landscape pattern and changes therein e) urban landscape pattern roadnetwork f) aesthetics of landscape g) management planning and monitoring Category e) isactually more like a subcategory of d) but since the human impact on landscapes is so importantand has been very widely explored we decided to analyze it separately Most of the studiespublished from 1994 ndash 2008 are on biodiversity and habitat analysis and the evaluation of landscapepattern and changes therein (up to 25 articles per year Figure 2) There are up to 15 articles peryear about the use and misuse selection of metrics The number of articles published each yearhas generally increased since 1994 but for example articles published on the relations betweenlandscape aesthetics relations and landscape metrics has been surprisingly low



Figure 2 The use of the following terms and their combinations in titles abstracts andor key words ofinternational peer-reviewed scientific papers a) use and misuseselection of metrics b) biodiversity andhabitat analysis c) estimating water quality d) evaluation of landscape pattern and changes therein e)urban landscape pattern road network f) landscape aesthetics g) management planning and monitoringThe analysis has been performed on the basis of journal papers indexed by the ISI Web of Science from1994 to October 2008

32 Use and selection of metrics

Many of the articles have been written on the use and misuse and selection principles of landscapemetrics As there are literally hundreds of landscape metrics many of the landscape metrics arecorrelated to each other which makes interpretation more difficult Riitters et al (1995) foundthat the first six factors explained about 87 of the variation in the 26 landscape metrics andthese factors were interpreted as composite measures of average patch compaction overall imagetexture average patch shape patch perimeter-area scaling the number of attribute classes andlarge-patch density-area scaling Cushman et al (2008) performed principal component analysis(PCA) and cluster analysis to identify independent components of landscape structure and groupthem and found that there were eight universal and consistent combinations of Fragstats met-rics that universally describe the major attributes of landscape structure at the landscape levelBotequilha Leitao and Ahern (2002) even proposed a core set of metrics that are most useful andrelevant for landscape planning and Schindler et al (2008) proposed set of metrics for establishinga landscape monitoring program to detect the local drivers of biodiversity in Mediterranean areaThe interpretation of some of the landscape metrics is also complicated because their behaviourhas not yet been evaluated (McGarigal et al 2002) In that field neutral landscapes are useful(see for example Neel et al 2004 Li et al 2005a)

Another important issue is that the results of spatial data analysis depend on data aggregationmethods and the zoning scheme Its general formulation is known as the modifiable areal unitproblem (MAUP) created by (Openshaw and Taylor 1981) MAUP in the context of landscapeecology consists of three related aspects how the grain size zoning and areal extent of investi-gation influence results and how to determine their optimal values for each particular case Thedependence of landscape metrics on grain size is studied by (Wickham and Riitters 1995 Uuemaaet al 2005 Buyantuyev and Wu 2007) Wickham et al (1997) Huang et al (2006) Langfordet al (2006) have studied the influence of map classification and Wu et al (2002) and Wu (2004)have studied the extent of the study area on the value of landscape metrics

Although there are already hundreds of landscape metrics several researchers have proposed



new landscape metrics Jaeger (2000) proposed a degree of landscape division (D) splitting index(S) and effective mesh size (m) which characterize the anthropogenic penetration of landscapesfrom a geometric point of view and are calculated from the distribution function of the remainingpatch sizes (He et al 2000) proposed new metric (aggregation index-AI) for measuring aggre-gation in landscape pattern AI is class-based and contrary to contagion it is independent ofcomposition All of these metrics are now also available in Fragstats The fact that researchers arestill working out new metrics indicates the need for measuring new aspects of landscape patternbut also researchersrsquo aspiration to overcome the collinearity in Fragstats metrics

33 Biodiversity and habitat analysis

The relationship between landscape metrics and bird species richness and their habitat preferenceshas been studied most extensively There are many studies that have been performed on therelationships between landscape parameters and specific species ndash owls (Carey et al 1992 Ribeet al 1998) sparrows (Perkins and Conner 2003) turkeys (Chamberlain et al 2000 Miller andConner 2007) woodpeckers (Wigley et al 1999) bobwhites (Guthery et al 2001 Twedt et al2007) grouses (Fearer and Stauffer 2003) pheasants (Clark et al 1999) and ducks (Stephenset al 2005) Different studies have shown that most bird species responded more strongly tothe composition of land-cover classes than to the configuration of the landscape (Table 1) Oflandscape configuration metrics patch size has given the most important relationships with birdspecies richness ie fragmentation plays an important role for birds

Landscape metrics have been used to determine the landscape preferences of raccoons (Henneret al 2004) gray wolves (Mladenoff et al 1995) wild hogs (Gaines et al 2005) moose (Maieret al 2005) deer (Foster et al 1997 Finder et al 1999 Kie et al 2002) black bears (Kindalland Van Manen 2007) ocelots (Jackson et al 2005) elk (Stubblefield et al 2006) possums (Eyreand Buck 2005) and bats (Limpert et al 2007) Different species provide different correlationswith landscape metrics depending on their landscape preferences ie large compact patches arepreferred by wild hogs (Gaines et al 2005) moose (Maier et al 2005) deer (Table 1 Fosteret al 1997 Plante et al 2004) and possums (Eyre and Buck 2005) while ocelots (Jackson et al2005) and gliders (Table 1 McAlpine and Eyre 2002) preferred areas that had a greater degree offragmentation (ie a larger number of patches of smaller size and with more edge)

Several studies have even shown the significance of landscape pattern (measured by landscapemetrics) on frog populations (Table 1 Knutson et al 1999 Pellet et al 2004) and on insectpopulation levels (Radeloff et al 2000 French et al 2004 Roschewitz et al 2005) The structureof the landscape may be important to explain and understand the epidemiology associated withinsects (Graham et al 2004) Overgaard et al (2003) studied the influence of landscape structureon Anopheline mosquito density and based on their results suggested that if landscape managementwere to be used for malaria control the large-scale reduction and fragmentation of forest coverwould be needed in the case of northern Thailand The risk of transmission of Lyme disease hasbeen found to be influenced by landscape structure and the spatial arrangement of land cover types(Turner 1989) Brownstein et al (2005) performed an analysis of the landscape pattern of forestpatches using satellite imagery and calculated landscape indices revealed a positive link betweenfragmentation and both tick density and the prevalence of infection in ticks Yang et al (2008)investigated ecological variability related to the distribution of Oncomelania hupensis the snailintermediate host of Schistosoma japonicum and found that the reduction of the heterogeneity ofthe landscape could reduce snail density

It is known that habitats composed of spatially heterogeneous abiotic conditions provide a greatdiversity of potentially suitable niches for plant species The scientific premises of landscape ecologysuggest that at a higher spatial level the composition and structure of the landscape mosaic alsoinfluences biotic processes and hence species richness (Honnay et al 2003) There are several



studies on the determining of relationships between landscape structure (estimated with landscapemetrics) and plant diversity (Table 1 Moser et al 2002 Burton and Samuelson 2008 Hernandez-Stefanoni and Dupuy 2008) A growing number of ecological studies have focused on alien plantsrsquoinvasive processes in order to predict further invasions and associated potentially negative effectsThe introduction of alien plants or plant species new to an area due to human activity and theirspread and establishment is thought to cause a decline in the diversity of native species (Williamson1999) Deutschewitz et al (2003) found that the species richness of native and alien plants increaseswith moderate levels of natural andor anthropogenic disturbances coupled with high levels ofhabitat and structural heterogeneity in urban riverine and small-scale rural ecosystems Kumaret al (2006) found that both native and non-native plant species richness were positively correlatedwith edge density Simpsonrsquos diversity index and the interspersionjuxtaposition index and werenegatively correlated with mean patch size (Table 1) Landscape metrics of watersheds have alsoproven to be useful for the identification of estuarine benthic conditions and degraded bottomcommunities (Hale et al 2004)

Table 1 Correlations between various landscape metrics and biological variables indicating biodiversityand habitat features Significance plt005 plt001 plt0001 plt00001

Taxa Landscape metrics Dependent vari-ables

Pearson r References

Amphibia Density of urban land-cover in a buffer of30 m around the pond

calling sites selectionby males of tree frog(Hyla arborea)

minus023 Pellet et al (2004)

Mammals log10 forest patch area carnivores species rich-ness

069 Michalski and Peres(2005)

primates species rich-ness

065

Mean woods patch size(log)

deer vulnerability toharvest (log)

minus075 Foster et al (1997)

Proximity index (log) minus076 Foster et al (1997)

mean woods patchshape (log)


Mean nearest neigh-bour distance

076 Foster et al (1997)

Number of patches Deer density 043 Plante et al (2004)

Edge density 037 Plante et al (2004)

Mean Patch Size Count of the Yellow-bellied Glider (Petau-rus australis)

minus025 McAlpine and Eyre(2002)

Edge density 029 McAlpine and Eyre(2002)

Contrast weightededge density

028 McAlpine and Eyre(2002)

Largest patch index Diversity of exudivorespecies


Shannonrsquos evennessindex




Table 1 ndash Continued



Contagion minus033 McAlpine and Eyre(2002)

Birds Agricultural land (ha) Number of hoodedcrane

079 Liu et al (2003)

Proportion forest Abundance of femalecowbirds

062 Fauth et al (2000)

Proportion forest Abundance of indigobuntings

minus077 Fauth et al (2000)

Proximity index minus035 Fauth et al (2000)

Edge density Abundance of woodthrushes


Insects Total area of hostpatches

Mean abundance of(Delphacodes kuscheli)

079 Grilli (2008)

Mean proximity index(host patches)

096 Grilli (2008)

Class area (maize) Total number of west-ern corn rootworm

091 Beckler et al (2004)

Number of patches(maize)


Proximity (maizepatches)


Edge density Mean jack pine bud-worm (Choristoneurapinus pinus)population levels

026 Radeloff et al (2000)

Corrected meanperimeter area ratio


Modified Simpsonrsquosdiversity index

Anopheline speciesdiversity (ShannonndashWeaver diversity in-dex)

minus074 Overgaard et al(2003)

Plants Forest cover () Riparian woody plantspecies richness

078 Burton and Samuelson(2008)

Shannonrsquos diversityindex

minus074 Burton and Samuelson(2008)

Number of patches Species richness ofvascular plants

061 Moser et al (2002)

Edge density 056 Moser et al (2002)

Mean shape index minus07 Moser et al (2002)

Number of patches Species richness ofbryophytes









Simpsonrsquos diversityindex

Native species richness 028 Kumar et al (2006)

Interspersion and jux-taposition index

031 Kumar et al (2006)

Patch richness density 035 Kumar et al (2006)


Non-native speciesrichness





34 Estimating water quality

Landscape structure is one of the most important factors influencing nutrient and organic matterrunoff in watersheds (Turner et al 2003 Wickham et al 2003 Uuemaa et al 2007) Thereforethere is increasing demand for indicators and methods that make it possible to evaluate the land-scape factors influencing water quality in freshwater management (Griffith 2002) Several studieshave attempted to determine the relationship between land useland cover structure and waterquality but most studies have largely relied on compositional landscape metrics (Kearns et al2005) It is however clearly important to understand not only the total area of sources and sinksin the landscape but also their spatial arrangement relative to flowpaths (Gergel 2005) Theimportance of the spatial arrangement of land cover within watersheds on water quality has beenstudied by Jones et al (2001) King et al (2005) Li et al (2005b) Snyder et al (2005) Xiao andJi (2007) Uuemaa et al (2005 2007) see Table 2

The spatial pattern of riparian zones is also an especially powerful landscape indicator forwater quality because the variation in length width and gaps of riparian buffers influences theireffectiveness as nutrient sinks (Gergel et al 2002) Weller et al (1998) developed and analyzedmodels predicting landscape discharge based on material release by an uphill source area the spatialdistribution of a riparian buffer along a stream and retention within the buffer and found averagewidth to be the best predictor of landscape discharge for unretentive buffers Baker et al (2006)quantified the effects of riparian buffers on watershed nutrient discharges by using in addition totraditional fixed-distance measures mean buffer width gap frequency and measures of variationin buffer width using both ldquounconstrainedrdquo metrics and ldquoflow-pathrdquo metrics constrained by surfacetopography

35 Evaluation of landscape pattern and changes therein

Land use changes are mostly caused by humans but also by natural disturbances For exampleLin et al (2006) used landscape metrics and spatial autocorrelation to assess how earthquakes andtyphoons affect landscape patterns and found that the disturbances produced variously fragmentedpatches interspersed with other patches and isolated from patches of the same type across the entireChenyulan watershed in Taiwan Results of fire disturbances studies Keane et al (1999) and Hudak



Table 2 Correlation between various landscape metrics and water quality parameters Significanceplt005 plt001 plt0001 plt00001

Landscape metrics Dependent variables Pearson r orSpearman ρ

References

Cropland () Log (NO3-N) 067 King et al (2005)

Canal line density Soluble reactive phos-phorus reduction

08 Li et al (2005b)

Canal connectivity 083 Li et al (2005b)

Canal circuity 085 Li et al (2005b)

Canal line density Total nitrogen reduction 084 Li et al (2005b)



Edge density (forest) Conductivity minus034 Xiao and Ji (2007)

Patch density 033 Xiao and Ji (2007)

Contagion minus049 Xiao and Ji (2007)

Edge density (forest) Total Cd minus053 Xiao and Ji (2007)

Edge density (forest) Total Zn minus049 Xiao and Ji (2007)


Patch density BOD7 (biological oxy-gen demand)

minus053 Uuemaa et al (2005)

Edge density minus047 Uuemaa et al (2005)

Patch density CODKMnO4 (chemicaloxygen demand)


Mean shape index 066 Uuemaa et al (2005)

Edge density Total-N minus056 Uuemaa et al (2005)

Mean shape index minus044 Uuemaa et al (2005)



et al (2004) found that fire creates more diverse fragmented and disconnected landscapes andKashian et al (2004) found that large stand-replacing fires may result in heterogeneous forestlandscapes rather than homogenous forests of uniform structure According to Viedma et al(2006) on the contrary fire had made the landscape less fragmented and more continuous

Teixido et al (2007) used landscape metrics to study the spatial patterns of the Antarcticbenthos in terms of the succession process after iceberg disturbance and found the first stagesof recovery to have low cover area low complexity of patch shape small patch size low diversityand patches that were poorly interspersed to samples from later stages with higher values of theseindices

Many studies have been done on the mapping of forest cover change Human influence alsocauses forest fragmentation that also affects species richness (Fuller 2001 Cayuela et al 2006Echeverrıa et al 2007 Altamirano et al 2007) Twentieth century management activities havesignificantly influenced the structure of the forest landscape (Wolter and White 2002 Lofman andKouki 2003) and altered spatial patterns of physiognomies cover types and structural conditionsand vulnerabilities to fire insect and pathogen disturbances (Hessburg et al 2000) Logging is oneof the main reasons for forest fragmentation and although it may change the landscape structureat a small spatial scale and not alter the structure of the entire forest mosaic (Leimgruber et al2002) it can be associated with dramatic changes in the structure and composition of the forests(Echeverrıa et al 2007) Etheridge et al (2006) also found using landscape metrics as an indicatorthat clearcuts result in the loss of large patches Zhang and Guindon (2005) used landscape metricsand cellular automata to analyze human impacts on forest fragmentation and showed that theobserved values of scalar landscape metrics and their interrelationships can only be understoodby taking into account the spatial pattern aspects associated with causal human drivers of thedeforestation process

36 Urban landscape pattern road network

Urbanization has significantly changed natural landscapes everywhere Urban growth and frag-mentation caused by urban sprawl have been extensively studied (Herold et al 2002 Ji et al2006 Tang et al 2006 Gonzalez-Abraham et al 2007) It has been shown that landscape pat-tern is more fragmented around city centres and along coastlines where urbanization and humaneconomic activities are more concentrated (Yang and Liu 2005) There are several possibilitiesas to how to use landscape metrics to detect spatial patterns caused by urbanization For exam-ple Seto and Fragkias (2005) calculated and analyzed landscape metrics spatiotemporally acrossthree buffer zones but another effective approach for analyzing systematically the effects of ur-banization on ecosystems is to studying the changes in ecosystem patterns and processes along anurban-to-rural gradient (McDonnell et al 1997) Studies of landscape pattern change along anurban-to-rural gradient focus on the identification of urban texture ndash whether urban landscapeshave unique ldquospatial signaturesrdquo that are distinguishable from other types of landscapes (Weng2007) In many studies only land use changes in space are considered (Luck and Wu 2002 Hahsand McDonnell 2006 Conway and Hackworth 2007) but landscape pattern also changes overtime Spatiotemporal gradient analysis makes it possible to determine how the urban centre hasshifted in space and time (Wu et al 2006 Xie et al 2006 Weng 2007)

Another critical issue is fragmentation caused by infrastructure and many studies have revealedthat road corridors in the urban landscape increased habitat fragmentation (Saunders et al 2002Zhu et al 2006 Hawbaker et al 2006 Jaeger et al 2007)



37 Landscape aesthetics

Human perception and intuition can strongly influence how we measure and interpret landscapepattern (DrsquoEon and Glenn 2000) Antrop and Van Eetvelde (2000) also emphasise the importanceof holism and found that summed entropy corresponds most closely to the landscape units definedby visual image interpretation and can be used as a quantitative characteristic of holisticallydefined landscape units (Franco et al 2003) also found strong explanatory relationship betweencitizensrsquo scenic beauty estimation and the Shannonrsquos diversity index (Table 3)

Table 3 Correlation between various landscape metrics and parameters characterizing landscape aesthet-ics Significance plt005 plt001 plt0001 plt00001


References

Shannonrsquos diversity index Scenic beauty estimation 082 Franco et al (2003)

Edge density Scenic beauty estimation 042 Palmer (2004)

Agricultural and open land 038 Palmer (2004)

Recreation 031 Palmer (2004)

Other urban minus045 Palmer (2004)

Waste minus033 Palmer (2004)

Wetland open water 033 Palmer (2004)

Largest patch index Neighbourhood satisfaction(0= not satisfied 6= verysatisfied)

018 Lee et al (2008)

Patch density minus013 Lee et al (2008)

Total core area 021 Lee et al (2008)

Mean Euclidean nearestneighbour distance

minus023 Lee et al (2008)

Area-weighted mean shapeindex

015 Lee et al (2008)

Mean shape index minus021 Lee et al (2008)

Cohesion 014 Lee et al (2008)

Shannonrsquos diversity index Preference scores (1= leastpreferred 5= most pre-ferred)

058 Dramstad et al(2006)

No of land types 053 Dramstad et al(2006)

No of patches 045 Dramstad et al(2006)

Percent open area minus045 Dramstad et al(2006)

Palmer (2004) investigated residentsrsquo perceptions of scenic quality in the Cape Cod communityof Dennis Massachusetts over a period of significant landscape change and used landscape metricsto predict residentsrsquo perception of scenic value for each time period The results indicated thatlandscape composition metrics were more closely related to scenic value than the configuration



metrics (Table 3) Scenic value was most positively related to the relative amount of agriculturaland related open lands and the most intensive urban land uses were negatively associated withscenic value From configuration metrics only edge density was positively related to scenic valueLee et al (2008) however found that residentsrsquo neighbourhood satisfaction was more likely to behigh when tree patches in neighbourhood environments were less fragmented less isolated andwell connected (Table 3) Dramstad et al (2006) also found that spatial configuration is relatedto peoplersquos landscape preferences and these may therefore be suitable as indicators for the visuallandscape (Table 3)

The embedding of the concept of valuable landscapes in legislation such as the European Land-scape Convention (Council of Europe 2004) has led to the need for an lsquoobjectiversquo assessment ofthese values and the potential impact of changes to them (Sang et al 2008) The visual characteris-tics of a landscape are some of the most widely experienced but also most difficult and controversial(Walker 1995) to define Sang et al (2008) investigated how well landscape metrics predict theresults on preference from the Visulands Pan European Survey (httpwwwesacptvisulands)and the implications of this for the role of preference metrics and visualisation methods in plan-ning processes such as landscape character assessment Furthermore Fry et al (2009) find thatlandscape metrics have a strong conceptual base in landscape ecological principles but for the vi-sual aspects of landscapes this conceptual base is often missing and thus hindering progress in thedevelopment of indicators Therefore they proposed hierarchical framework for establishing andstrengthening links between theory and indicator application

38 Management and planning

Landscape metrics are useful for the application of the concepts of landscape ecology to sustainablelandscape planning (Botequilha Leitao and Ahern 2002) and landscape monitoring (Herzog andLausch 1999) Lin et al (2007) combined a land use change model landscape metrics and awatershed hydrological model with an analysis of the impacts of future land use scenarios on landuse pattern and hydrology for a landscape management plan Landscape metrics also make itpossible to detect potential areas for greenways (Colantonio Venturelli and Galli 2006 Zhang andWang 2006) and assess habitat suitability (Holzkamper et al 2006 Kim and Pauleit 2007) forlandscape planning and management

Landscape metrics can be useful for assessing soil erosion on large territories (Li 2008) and helplandscape managers to indicate how well landscapes function to retain not ldquoleakrdquo vital systemresources such as rainwater and soil (Ludwig et al 2002)

Agricultural activities have major effect on floral and faunal species richness of anthropogeniclandscapes As European Union is providing subsidies to farmers for environmentally friendlyagricultural practices there is an urgent need to assess the effectiveness of these subsides Wrbkaet al (2008) investigated the agri-environmental measures in a parcel-wise manner and analyzedtheir effects on landscape values and biodiversity They found that reduction of agrochemicalsshowed positive effects on biodiversity of vascular plants in grassland and birds in arable land andtargeted measures that directly address threatened species were most effective but had much lesscoverage Wrbka et al (2008) also concluded that agri-environmental measures are currently nottargeted enough to effectively halt biodiversity losses Therefore we also find that researchers shouldaim for more specific guidelines to evaluate different management schemes For example (Greenhillet al 2003) determined typical ranges of the metrics in environmentally sustainable localities for anextensive suburban area on the southwest edge of London using multispectral IKONOS-2 imageryThe spatial distributions of the metrics provide new insight into landscape structure which canbe exploited in land use planning and in the construction of empirical spatial planning heuristicsfor sustainable urban development If researchers determine the critical values or ranges of thelandscape metrics where landscape retains its identity or there is positive effect on biodiversity



then landscape metrics can be extremely useful indicators for measuring the effectiveness of themanagement schemes



4 Conclusions

The landscape metrics is one of the hot topics of modern landscape ecological research Howeverthere is a decreasing trend since 2005 of the papers published in this particular field in high-qualityinternational scientific journals It indicates that researchers and also practitioners have begun touse pattern metrics more often skipping correlating ones and choosing only the most informativemetrics that truly indicate some relationships between patterns and processes Yet new metrics arebeing developed and this fact indicates that there are still some aspects of landscape pattern thatexisting metrics do not cover or there are problems with scale interpretability etc Neverthelessone should not underestimate the role of landscape metrics in determining the relations betweenlandscape pattern and process

The majority of papers using landscape metricsindicesindexes are dedicated to biodiversityand habitat analysis Also many articles analyze the relationship of landscape metrics with theevaluation of landscape pattern and changes therein On the other hand there are very few articlesrelated to social aspects and landscape perception and therefore one large potential research field isuncovered Likewise a lot of research is needed in order to determine landscape metrics useful forlandscape management and planning including specifying significant values and ranges of landscapemetrics depending on the planning or management purpose

5 Acknowledgements

This study has been supported by the Ministry of Education and Science of Estonia (grantsSF0182534s03 and SF0180127s08) and Estonian Science Foundation grants 6083 and 7527



References

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Antrop M Van Eetvelde V (2000) ldquoHolistic aspects of suburban landscapes visual imageinterpretation and landscape metricsrdquo Landscape and Urban Planning 50(1-3) 43ndash58 doi101016S0169-2046(00)00079-7 37

Baker ME Weller DE Jordan TE (2006) ldquoImproved methods for quantifying potential nutri-ent interception by riparian buffersrdquo Landscape Ecology 21(8) 1327ndash1345 doi101007s10980-006-0020-0 34

Beckler AA French BW Chandler LD (2004) ldquoCharacterization of western corn rootworm(Coleoptera Chrysomelidae) population dynamics in relation to landscape attributesrdquo Agricul-tural and Forest Entomology 6(2) 129ndash139 doi101111j1461-9563200400213x 1

Botequilha Leitao A Ahern J (2002) ldquoApplying landscape ecological concepts and met-rics in sustainable landscape planningrdquo Landscape and Urban Planning 59(2) 65ndash93 doi101016S0169-2046(02)00005-1 32 38

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Deutschewitz K Lausch A Kuhn I Klotz S (2003) ldquoNative and alien plant species rich-ness in relation to spatial heterogeneity on a regional scale in Germanyrdquo Global Ecology andBiogeography 12(4) 299ndash311 doi101046j1466-822X200300025x 33

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Etheridge DA MacLean DA Wagner RG Wilson JS (2006) ldquoEffects of Intensive ForestManagement on Stand and Landscape Characteristics in Northern New Brunswick Canada(1945ndash2027)rdquo Landscape Ecology 21(4) 509ndash524 doi101007s10980-005-2378-9 35

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Franco D Franco D Mannino I Zanetto G (2003) ldquoThe impact of agroforestry networks onscenic beauty estimation The role of a landscape ecological network on a socio-cultural processrdquoLandscape and Urban Planning 62(3) 119ndash138 doi101016S0169-2046(02)00127-5 37 3

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Gaines KF Porter DE Punshon T Brisbin Jr IL (2005) ldquoA Spatially ExplicitModel of the Wild Hog for Ecological Risk Assessment Activities at the Department of En-ergyrsquos Savannah River Siterdquo Human and Ecological Risk Assessment 11(3) 567ndash589 doi10108010807030590949654 33

Gergel SE (2005) ldquoSpatial and non-spatial factors When do they affect landscape indicators ofwatershed loadingrdquo Landscape Ecology 20(2) 177ndash189 doi101007s10980-004-2263-y 34

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Hernandez-Stefanoni JL Dupuy JM (2008) ldquoEffects of landscape patterns on species densityand abundance of trees in a tropical subdeciduous forest of the Yucatan Peninsulardquo ForestEcology and Management 255(11) 3797ndash3805 doi101016jforeco200803019 33

Herold M Scepan J Clarke KC (2002) ldquoThe use of remote sensing and landscape metricsto describe structures and changes in urban land usesrdquo Environment and Planning A 34(8)1443ndash1458 doi101068a3496 36

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Huang C Geiger EL Kupfer JA (2006) ldquoSensitivity of landscape metrics to clas-sification schemerdquo International Journal of Remote Sensing 27(14) 2927ndash2948 doi10108001431160600554330 32

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Iampietro PJ Kvitek RG Morris E (2005) ldquoRecent advances in automated genus-specificmarine habitat mapping enabled by high-resolution multibeam bathymetryrdquo Marine TechnologySociety Journal 39(3) 83ndash93 1

Jackson VL Laack LL Zimmerman EG (2005) ldquoLandscape Metrics Associated with Habi-tat Use by Ocelots in South Texasrdquo Journal of Wildlife Management 69(2) 733ndash738 doi1021930022-541X(2005)069[0733LMAWHU]20CO2 33

Jaeger JAG (2000) ldquoLandscape division splitting index and effective mesh size new measuresof landscape fragmentationrdquo Landscape Ecology 15(2) 115ndash130 doi101023A100812932928932

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Ji W Ma J Twibell RW Underhill K (2006) ldquoCharacterizing urban sprawl using multi-stageremote sensing images and landscape metricsrdquo Computers Environment and Urban Systems30(6) 861ndash879 doi101016jcompenvurbsys200509002 36

Jones KB Neale AC Nash MS Van Remortel RD Wickham JD Riitters KH OrsquoNeillRV (2001) ldquoPredicting nutrient and sediment loadings to streams from landscape metrics Amultiple watershed study from the United States Mid-Atlantic Regionrdquo Landscape Ecology 16(4) 301ndash312 doi101023A1011175013278 34

Kashian DM Tinker DB Turner MG Scarpace FL (2004) ldquoSpatial heterogeneity of lodge-pole pine sapling densities following the 1988 fires in Yellowstone National Park WyomingUSArdquo Canadian Journal of Forest Research 34(11) 2263ndash2276 doi101139x04-107 35

Keane RE Morgan P White JD (1999) ldquoTemporal patterns of ecosystem processes on simu-lated landscapes in Glacier National Park Montana USArdquo Landscape Ecology 14(3) 311ndash329doi101023A1008011916649 35

Kearns FR Kelly NM Carter JL Resh VH (2005) ldquoA method for the use of land-scape metrics in freshwater research and managementrdquo Landscape Ecology 20(1) 113ndash125doi101007s10980-004-2261-0 34

Kie JG Bowyer RT Nicholson MC Boroski BB Loft ER (2002) ldquoLandscape hetero-geneity at differing scales Effects on spatial distribution of mule deerrdquo Ecology 83(2) 530ndash544doi1018900012-9658(2002)083[0530LHADSE]20CO2 33

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King RS Baker ME Whigham DF Weller DE Jordan TE Kazyak PF Hurd MK(2005) ldquoSpatial Considerations for Linking Watershed Land Cover to Ecological Indicators inStreamsrdquo Ecological Applications 15(1) 137ndash153 doi10189004-0481 34 2



Knutson MG Sauer JR Olsen DA Mossman MJ Hemesath LM Lannoo MJ (1999)ldquoEffects of Landscape Composition and Wetland Fragmentation on Frog and Toad Abundanceand Species Richness in Iowa and Wisconsin USArdquo Conservation Biology 13(6) 1437ndash1446doi101046j1523-1739199998445x 33

Kumar S Stohlgren TJ Chong GW (2006) ldquoSpatial heterogeneity influences na-tive and nonnative plant species richnessrdquo Ecology 87(12) 3186ndash3199 doi1018900012-9658(2006)87[3186SHINAN]20CO2 33 1

Langford WT Gergel SE Dietterich TG Cohen W (2006) ldquoMap Misclassification CanCause Large Errors in Landscape Pattern Indices Examples from Habitat FragmentationrdquoEcosystems 9(3) 474ndash488 doi101007s10021-005-0119-1 32

Lee S-W Ellis CD Kweon B-S Hong S-K (2008) ldquoRelationship between landscape struc-ture and neighborhood satisfaction in urbanized areasrdquo Landscape and Urban Planning 85(1)60ndash70 doi101016jlandurbplan200709013 3 37

Leimgruber P McShea WJ Schnell GD (2002) ldquoEffects of Scale and Logging on LandscapeStructure in a Forest Mosaicrdquo Environmental Monitoring and Assessment 74(2) 141ndash166doi101023A1013881319390 35

Li HB Wu JG (2004) ldquoUse and misuse of landscape indicesrdquo Landscape Ecology 19(4)389ndash399 doi101023BLAND000003044115628d6 1

Li XZ He HS Bu RC Wen QC Chang Y Hu YM Li YH (2005a) ldquoThe adequacy ofdifferent landscape metrics for various landscape patternsrdquo Pattern Recognition 38(12) 2626ndash2638 doi101016jpatcog200505009 32

Li XZ Jongman RHG Hu YM Bu RC Harms B Bregt AK He HS (2005b)ldquoRelationship between landscape structure metrics and wetland nutrient retention func-tion A case study of Liaohe Delta Chinardquo Ecological Indicators 5(4) 339ndash349 doi101016jecolind200503007 34 2

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Limpert DL Birch DL Scott MS Andre M Gillam E (2007) ldquoTree Selection and Land-scape Analysis of Eastern Red Bat Day Roostsrdquo Journal of Wildlife Management 71(2) 478ndash486 doi1021932005-642 33

Lin YP Chang TK Wu CF Chiang TC Lin SH (2006) ldquoAssessing Impacts of Typhoonsand the Chi-Chi Earthquake on Chenyulan Watershed Landscape Pattern in Central TaiwanUsing Landscape Metricsrdquo Environmental Management 38(1) 108ndash125 doi101007s00267-005-0077-6 35

Lin YP Hong NM Wu PJ Wu CF Verburg PH (2007) ldquoImpacts of land use changescenarios on hydrology and land use patterns in the Wu-Tu watershed in Northern TaiwanrdquoLandscape and Urban Planning 80(1-2) 111ndash126 doi101016jlandurbplan200606007 38

Liu YB Nishiyama S Kusaka T (2003) ldquoExamining Landscape Dynamics at a WatershedScale Using Landsat TM Imagery for Detection of Wintering Hooded Crane Decline in YashiroJapanrdquo Environmental Management 31(3) 365ndash376 doi101007s00267-002-2785-5 1

Lofman S Kouki J (2003) ldquoScale and dynamics of a transforming forest landscaperdquo ForestEcology and Management 175(1-3) 247ndash252 doi101016S0378-1127(02)00133-0 35



Luck M Wu JG (2002) ldquoA gradient analysis of urban landscape pattern a case study fromthe Phoenix metropolitan region Arizona USArdquo Landscape Ecology 17(4) 327ndash339 doi101023A1020512723753 36

Ludwig JA Eager RW Bastin GN Chewings VH Liedloff AC (2002) ldquoA leakinessindex for assessing landscape function using remote sensingrdquo Landscape Ecology 17(2) 157ndash171 doi101023A1016579010499 38

Maier JAK Ver Hoef JM McGuire AD Bowyer RT Saperstein L Maier HA (2005)ldquoDistribution and density of moose in relation to landscape characteristics effects of scalerdquoCanadian Journal of Forest Research 35(9) 2233ndash2243 doi101139x05-123 33

Mander U Muller F Wrbka T (2005) ldquoFunctional and structural landscape indica-tors Upscaling and downscaling problemsrdquo Ecological Indicators 5(4) 267ndash272 doi101016jecolind200504001 1

McAlpine CA Eyre TJ (2002) ldquoTesting landscape metrics as indicators of habitat loss andfragmentation in continuous eucalypt forests (Queensland Australia)rdquo Landscape Ecology 17(8) 711ndash728 doi101023A1022902907827 33 1

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Miller DA Conner LM (2007) ldquoHabitat Selection of Female Turkeys in a Managed PineLandscape in Mississippirdquo Journal of Wildlife Management 71(3) 744ndash751 doi1021932005-738 33

Mladenoff DJ Sickley TA Haight RG Wydeven AP (1995) ldquoA Regional Landscape Anal-ysis and Prediction of Favorable Gray Wolf Habitat in the Northern Great Lakes RegionrdquoConservation Biology 9(2) 279ndash294 doi101046j1523-173919959020279x 33

Moser D Zechmeister HG Plutzar C Sauberer N Wrbka T Grabherr G (2002) ldquoLand-scape patch shape complexity as an effective measure for plant species richness in rural land-scapesrdquo Landscape Ecology 17(7) 657ndash669 doi101023A1021513729205 33 1

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Palmer JF (2004) ldquoUsing spatial metrics to predict scenic perception in a changing land-scape Dennis Massachusettsrdquo Landscape and Urban Planning 69(2-3) 201ndash218 doi101016jlandurbplan200308010 3 37

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Roschewitz I Hucker M Tscharntke T Thies C (2005) ldquoThe influence of landscape contextand farming practices on parasitism of cereal aphidsrdquo Agriculture Ecosystems amp Environment 108(3) 218ndash227 doi101016jagee200502005 33

Sang N Ode A Miller D (2008) ldquoLandscape metrics and visual topology in the analysis oflandscape preferencerdquo Environment and Planning B Planning and Design 35(3) 504ndash520doi101068b33049 37

Saunders SC Mislivets MR Chen JQ Cleland DT (2002) ldquoEffects of roads on landscapestructure within nested ecological units of the Northern Great Lakes Region USArdquo BiologicalConservation 103(2) 209ndash225 doi101016S0006-3207(01)00130-6 36

Schils T (2006) ldquoThe tripartite biogeographical index a new tool for quantifying spatio-temporal differences in distribution patternsrdquo Journal of Biogeography 33(4) 560ndash572 doi101111j1365-2699200501416x 1



Schindler S Poirazidis K Wrbka T (2008) ldquoTowards a core set of landscape metrics forbiodiversity assessments A case study from Dadia National Park Greecerdquo Ecological Indicators8(5) 502ndash514 doi101016jecolind200706001 32

Seto KC Fragkias M (2005) ldquoQuantifying Spatiotemporal Patterns of Urban Land-use Changein Four Cities of China with Time Series Landscape Metricsrdquo Landscape Ecology 20(7) 871ndash888 doi101007s10980-005-5238-8 36

Snyder MN Goetz SJ Wright RK (2005) ldquoStream health rankings predicted by satellitederived land cover metricsrdquo Journal of the American Water Resources Association 41(3) 659ndash677 doi101111j1752-16882005tb03762x 34

Stephens SE Rotella JJ Lindberg MS Taper ML Ringelman JK (2005) ldquoDuck NestSurvival in the Missouri Coteau of North Dakota Landscape Effects at Multiple Spatial ScalesrdquoEcological Applications 15(6) 2137ndash2149 doi10189004-1162 33

Stubblefield CH Vierling KT Rumble MA (2006) ldquoLandscape-Scale Attributes of Elk Cen-ters of Activity in the Central Black Hills of South Dakotardquo Journal of Wildlife Management 70(4) 1060ndash1069 doi1021930022-541X(2006)70[1060LAOECO]20CO2 33

Tang JM Wang L Yao ZJ (2006) ldquoAnalyzing Urban Sprawl Spatial Fragmentation Us-ing Multi-temporal Satellite Imagesrdquo GIScience amp Remote Sensing 43(3) 218ndash232 doi1027471548-1603433218 36

Teixido N Garrabou J Gutt J Arntz WE (2007) ldquoIceberg Disturbance and SuccessionalSpatial Patterns The Case of the Shelf Antarctic Benthic Communitiesrdquo Ecosystems 10(1)143ndash158 doi101007s10021-006-9012-9 35

Turner MG (1989) ldquoLandscape Ecology The Effect of Pattern on Processrdquo Annual Review ofEcology and Systematics 20 171ndash197 doi101146annureves20110189001131 33

Turner MG (1990) ldquoSpatial and temporal analysis of landscape patternsrdquo Landscape Ecology 4(1) 21ndash30 doi101007BF02573948 1

Turner RE Rabalais NN Justic D Dortch Q (2003) ldquoGlobal patterns of dissolved N Pand Si in large riversrdquo Biogeochemistry 64(3) 297ndash317 doi101023A1024960007569 1 34

Twedt DJ Wilson RR Keister AS (2007) ldquoSpatial Models of Northern Bobwhite Popu-lations for Conservation Planningrdquo Journal of Wildlife Management 71(6) 1808ndash1818 doi1021932006-567 33

Uuemaa E Roosaare J Mander U (2005) ldquoScale dependence of landscape metrics and theirindicatory value for nutrient and organic matter losses from catchmentsrdquo Ecological Indicators5(4) 350ndash369 doi101016jecolind200503009 32 34 2

Uuemaa E Roosaare J Mander U (2007) ldquoLandscape metrics as indicators of river waterquality at catchment scalerdquo Nordic Hydrology 38(2) 125ndash138 doi102166nh2007002 34

Viedma O Moreno JM Rieiro I (2006) ldquoInteractions between land useland cover changeforest fires and landscape structure in Sierra de Gredos (Central Spain)rdquo Environmental Con-servation 33(3) 212ndash222 doi101017S0376892906003122 35

Vivoni ER Teles V Ivanov VY Bras RL Entekhabi D (2005) ldquoEmbedding landscapeprocesses into triangulated terrain modelsrdquo International Journal of Geographical InformationScience 19(4) 429ndash457 doi10108013658810512331325111 1



Walker G (1995) ldquoRenewable energy and the publicrdquo Land Use Policy 12(1) 49ndash59 doi1010160264-8377(95)90074-C 37

Weller DE Jordan TE Correll DL (1998) ldquoHeuristic Models for Material Discharge fromLandscapes with Riparian Buffersrdquo Ecological Applications 8(4) 1156ndash1169 doi1018901051-0761(1998)008[1156HMFMDF]20CO2 34

Weng Y-C (2007) ldquoSpatiotemporal changes of landscape pattern in response to urbanizationrdquoLandscape and Urban Planning 81(4) 341ndash353 doi101016jlandurbplan200701009 36

Wickham JD Riitters KH (1995) ldquoSensitivity of landscape metrics to pixel sizerdquo InternationalJournal of Remote Sensing 16(18) 3585ndash3594 doi10108001431169508954647 1 32

Wickham JD OrsquoNeill RV Riitters KH Wade TG Jones KB (1997) ldquoSensitivity ofSelected Landscape Pattern Metrics to Land-Cover Misclassification and Differences in Land-Cover Compositionrdquo Photogrammetric Engineering amp Remote Sensing 63(4) 397ndash402 32

Wickham JD Wade TG Riitters KH OrsquoNeill RV Smith JH Smith ER Jones KBNeale AC (2003) ldquoUpstream-to-downstream changes in nutrient export riskrdquo Landscape Ecol-ogy 18(2) 193ndash206 doi101023A1024490121893 34

Wigley TB Sweeney SW Sweeney JR (1999) ldquoHabitat Attributes and Reproduction ofRed-Cockaded Woodpeckers in Intensively Managed Forestsrdquo Wildlife Society Bulletin 27(3)801ndash809 33

Williamson M (1999) ldquoInvasionsrdquo Ecography 22(1) 5ndash12 doi101111j1600-05871999tb00449x 33

Wolter PT White MA (2002) ldquoRecent forest cover type transitions and landscape struc-tural changes in northeast Minnesota USArdquo Landscape Ecology 17(2) 133ndash155 doi101023A1016522509857 35

Wrbka T Schindler S Pollheimer M Schmitzberger I Peterseil J (2008) ldquoImpact of theAustrian Agri-environmental scheme on diversity of landscapes plants and birdsrdquo CommunityEcology 9(2) 217ndash227 doi101556ComEc92008211 38

Wu JG (2004) ldquoEffects of changing scale on landscape pattern analysis scaling relationsrdquoLandscape Ecology 19(2) 125ndash138 doi101023BLAND000002171140074ae 32

Wu JG Shen WJ Sun WZ Tueller PT (2002) ldquoEmpirical patterns of the ef-fects of changing scale on landscape metricsrdquo Landscape Ecology 17(8) 761ndash782 doi101023A1022995922992 32

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Introduction

Methods

Results and Discussion

``Landscape metrics vs ``landscape indices

Use and selection of metrics

Biodiversity and habitat analysis

Estimating water quality

Evaluation of landscape pattern and changes therein

Urban landscape pattern road network

Landscape aesthetics

Management and planning

Conclusions

Acknowledgements

References

Imprint Terms of Use

Living Reviews in Landscape Research is a peer reviewed open access journal published by theLeibniz Centre for Agricultural Landscape Research (ZALF) Eberswalder Straszlige 84 15374Muncheberg Germany ISSN 1863-7329

This review is licensed under a Creative Commons Attribution-Non-Commercial-NoDerivs 30Germany License httpcreativecommonsorglicensesby-nc-nd30de

Because a Living Reviews article can evolve over time we recommend to cite the article as follows

Evelin Uuemaa Marc Antrop Juri Roosaare Riho Marja and Ulo ManderldquoLandscape Metrics and Indices An Overview of Their Use in Landscape Researchrdquo

Living Rev Landscape Res 3 (2009) 1 [Online Article] cited [ltdategt]httpwwwlivingreviewsorglrlr-2009-1

The date given as ltdategt then uniquely identifies the version of the article you are referring to

Article Revisions

Living Reviews supports two different ways to keep its articles up-to-date

Fast-track revision A fast-track revision provides the author with the opportunity to add shortnotices of current research results trends and developments or important publications tothe article A fast-track revision is refereed by the responsible subject editor If an articlehas undergone a fast-track revision a summary of changes will be listed here

Major update A major update will include substantial changes and additions and is subject tofull external refereeing It is published with a new publication number

For detailed documentation of an articlersquos evolution please refer always to the history documentof the articlersquos online version at httpwwwlivingreviewsorglrlr-2009-1

Contents

1 Introduction 5

2 Methods 5


4 Conclusions 17


References 18

List of Tables



scape aesthetics 14


1 Introduction





2 Methods







































065



























079 Liu et al (2003)










079 Grilli (2008)


096 Grilli (2008)



















































References



08 Li et al (2005b)


































References









018 Lee et al (2008)






015 Lee et al (2008)






















4 Conclusions



5 Acknowledgements




References






































































































































































Introduction

Methods










Conclusions

Acknowledgements

References

Contents

1 Introduction 5

2 Methods 5


4 Conclusions 17


References 18

List of Tables



scape aesthetics 14


1 Introduction





2 Methods







































065



























079 Liu et al (2003)










079 Grilli (2008)


096 Grilli (2008)



















































References



08 Li et al (2005b)


































References









018 Lee et al (2008)






015 Lee et al (2008)






















4 Conclusions



5 Acknowledgements




References






































































































































































Introduction

Methods










Conclusions

Acknowledgements

References


1 Introduction





2 Methods







































065



























079 Liu et al (2003)










079 Grilli (2008)


096 Grilli (2008)



















































References



08 Li et al (2005b)


































References









018 Lee et al (2008)






015 Lee et al (2008)






















4 Conclusions



5 Acknowledgements




References






































































































































































Introduction

Methods










Conclusions

Acknowledgements

References



































065



























079 Liu et al (2003)










079 Grilli (2008)


096 Grilli (2008)



















































References



08 Li et al (2005b)


































References









018 Lee et al (2008)






015 Lee et al (2008)






















4 Conclusions



5 Acknowledgements




References






































































































































































Introduction

Methods










Conclusions

Acknowledgements

References







079 Liu et al (2003)










079 Grilli (2008)


096 Grilli (2008)



















































References



08 Li et al (2005b)


































References









018 Lee et al (2008)






015 Lee et al (2008)






















4 Conclusions



5 Acknowledgements




References






































































































































































Introduction

Methods










Conclusions

Acknowledgements

References



























References



08 Li et al (2005b)


































References









018 Lee et al (2008)






015 Lee et al (2008)






















4 Conclusions



5 Acknowledgements




References






































































































































































Introduction

Methods










Conclusions

Acknowledgements

References














References









018 Lee et al (2008)






015 Lee et al (2008)






















4 Conclusions



5 Acknowledgements




References






































































































































































Introduction

Methods










Conclusions

Acknowledgements

References













4 Conclusions



5 Acknowledgements




References






































































































































































Introduction

Methods










Conclusions

Acknowledgements

References


References






































































































































































Introduction

Methods










Conclusions

Acknowledgements

References























































































































































Introduction

Methods










Conclusions

Acknowledgements

References

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