Shades of green: Measuring the ecology of urban green space in … · 2010-12-25 · Shades of...

Shades of Green Measuring the Ecology of Urban Green Space in the Context

of Human Health and Well-BeingAnna Jorgensen and Paul H Gobster

ABSTRACTIn this paper we review and analyze the recent research literature on urbangreen space and human health and well-being with an emphasis on stud-ies that attempt to measure biodiversity and other green space concepts rel-evant to urban ecological restoration We first conduct a broad scaleassessment of the literature to identify typologies of urban green space andhuman health and well-being measures and use a research mapping exer-cise to detect research priorities and gaps We then provide a more in-depthassessment of selected studies that use diverse and innovative approaches tomeasuring the more ecological aspects of urban green space and we evalu-ate the utility of these approaches in developing urban restoration principlesand practices that are responsive to both human and ecological values

KEYWORDSbiodiversity green infrastructure proxy measures research mapping sce-nario manipulation urban ecological restoration

Western ideas about the benefits of nature to human health and well-being go back at least two centuries but until the emergence of land-scape perception and assessment research in the 1960s these benefitswere considered too subjective to measure Kaplan et al (1972) wereamong the first to measure peoplersquos preferences for natural over urbanscenes and before long investigators were developing models to pre-dict green space preferences based upon the biophysical psycholog-ical and artistic properties of vegetation and other landscape elements(Daniel 2001) These included psycho-evolutionary models that sug-gested that humans prefer savanna-like landscapes characterized byopen glades with smooth ground texture framed by clumps of maturetrees (eg Ulrich 1986) and that vegetation types associated withmore biodiverse landscapes such as rough ground cover woodlandedge or scrub were generally lower in preference (Parsons 1995) Nas -sauerrsquos (1995) work suggesting that preferences for ldquomessy ecosystemsrdquocould be enhanced by placing landscapes within ldquoorderly framesrdquo

Nature and Culture 5(3) Winter 2010 338ndash363 copy Berghahn Journalsdoi103167nc2010050307

helped to move the discussion on beyond the relative merits of sce-nic as opposed to ecological aesthetics

Research on urban green spaces and human health and well-being has steadily expanded beyond its original focus on landscapepreference and social scientists and public health researchers havebeen studying how various aspects of human health and well-beingare affected by exposure to green spaces (eg Bell et al 2008 Malleret al 2002 Tzoulas et al 2007) While the scope of this research hasbeen diverse the main focus has been on the human side of the equa-tion to understand the benefits and outcomes that green space has forpeople measured at psychological social and physiological levels ofconcern The green side of the equationmdashthe measurement of greenspace qualities and characteristicsmdashhas sometimes also been an im-portant part of this work but many questions remain about the natureof green space as it relates to human health and well-being (Frumkin2001 2006 Velarde et al 2007) What are the key green space char-acteristics that generate desired health and well-being outcomes Dodifferent characteristics of ldquogreenrdquo play differential roles with respectto various human benefits How can an enhanced understanding ofthese characteristics and their beneficial properties be integrated withother contemporary green space agendas including ecological res -toration and the creation of multifunctional green infrastructure

In this paper we take a first step in addressing these questions byexamining how researchers have measured predominantly urbangreen space in the context of human health and well-being with ref-erence to a broad spectrum of urban green spaces but especially themore structurally complex and biodiverse natural environments asso-ciated with ecological restoration Our approach relies on an assess-ment of recent research literature classifying the types of green spacemeasures that are being used and mapping them with measures of hu-man health and well-being also under consideration

As well as mapping the green space measures against humanhealth and wellbeing outcomes we go on to consider how effectivethese measures are in the context of an inter-disciplinary researchcontext Green spacemdashopen land and its vegetative cover1mdashforms thecentral part of urban ecosystems To enhance the function and sus-tainability of urban ecosystems ecologists and land managers arguethat green space must be more than the mown grass and ornamentaltree plantings that typifies managed green space in most cities Butwhile restoration provides a set of principles and practices for increas-ing the ecological values of urban green space those involved in ur-

MEASURING THE ECOLOGY OF URBAN GREEN SPACE

339

ban ecological restoration are becoming increasingly aware of theneed to also take into account its social values including the healthand well-being dimension (eg Ingram 2008) At the same time therehas been a growing focus on the ecological health of urban systemsmore generally and researchers in urban ecology urban ecologicalrestoration and other fields have developed concepts and practicesfor measuring and managing urban land cover to maintain hydrolog-ical function promote air quality regulate microclimate sequestercarbon and preserve species and habitat diversity (Nowak and Dwyer2007 see also Del Tredici this issue) A major obstacle connectingthese two lines of research has been the lack of suitable metrics tomea sure the characteristics of green spaces against the full range ofdesired human and ecological benefits (eg Fry et al 2009) If urbanenvironments are to deliver the fullest possible range of benefits it isessential that relevant and meaningful green space measures be found

Within this problem context the questions this paper seeks to an-swer are

1 How is urban green space conceptualized and measured in re-search directed at human health and well-being

2 How does the use of green space concepts and measures vary ac-cording to the particular human benefit and outcome measuresunder consideration

While these two questions relate most directly to the quantitativeldquodatardquo portion of our study and provide a broad picture of the currentstate of research a subset of this work is then examined at greater depthin a more qualitative way to address the following questions

3 Which of these approaches have the greatest potential to be usedin interdisciplinary research linking the social and natural sciencesand urban ecological restoration planning and management

4 What issues need to be overcome in developing holistic and trans-ferable conceptualizations of urban green space

Methods

Our literature review and assessment draws upon a sample of recentlypublished studies on urban green space and human health and well-being relationships As described earlier urban green spaces providemany human and environmental benefits and a recent review by Bellet al (2007) divided this literature into five broad categories health

ANNA JORGENSEN AND PAUL H GOBSTER

340

and well-being social and community economic values environmen-tal quality and planning and design (including perceptions and pref-erences) While the economic and environmental aspects are clearlycrucial in building a more holistic view of human-green space rela-tionships the other three categories identified by Bell et al seemed tocapture the appropriate breadth of literature for our focus

We developed a three-step strategy to identify the study sampleFirst we conducted an electronic search of the literature using theScopus database After some trial and error we developed the follow-ing query ldquo(TITLE-ABS-KEY(biodiversity OR greenspace OR ldquogreenspacerdquo) AND TITLE-ABS-KEY(urban) AND TITLE-ABS-KEY(health ORwell-being))rdquo and limited the search to articles published in journalsafter 1997 This generated a total of 189 items Our original intentionwas to repeat the Scopus search for the ldquosocial and communityrdquo andldquoplanning and designrdquo categories of Bell et alrsquos (2007) classificationbut this strategy soon proved unsatisfactory Not only did each itera-tion of the search generate an unmanageably large quantity of new lit-erature but we also found that some key studies we knew of were notbeing retrieved

Therefore as a second step in identifying our sample we adopteda more purposive approach We began by assembling a collection ofliterature we already knew about and then supplemented it by usingldquosnowballingrdquo techniques such as scanning reference lists of articlesfor promising citations This yielded an additional 241 publications

The final step in identifying a sample of the literature for furtheranalysis was to screen the set of 430 publications for those that con-formed to our specific study objectives We entered study citations andabstracts into a spreadsheet and coded the articles for key informationWe then eliminated from further analysis any articles that were notapplicable to urban green space issues were not empirical were notpublished in refereed journals or did not have measures of green spaceor human benefits sufficiently well described or central to our ownwork leaving a final sample of 182 items While this semi-systematicprocedure no doubt missed some articles we felt confident that theresulting sample of 182 articles used in our final analysis provided agood cross-section of the literature as well as a number of key articles2

To address research questions 1 and 2 of our study we developedinitial taxonomies for classifying green space and human health andwell-being measures We each read a portion of the sample studiesand for each paper wrote a short description of its green space andhuman measures along with coding classification We then discussed


341

the coding and adjusted our taxonomies until we felt comfortable thatthey were meaningful and could be used consistently These tax-onomies are set out in Tables 1 and 2 To help make sense of the find-


342

Table 1 Taxonomy of green space measures

Code Definition

None Green space is the focus of study but no attemptis made to measure vary or describe its characteristics

Urban versus Research design compares exposure to urban and natural natural settings

Descriptive Qualitative description of green space by research narrative participant without categorization

Inventory Multiple environmental characteristics includingvegetation and facilities many not relating to urban green space

AreaDistance Quantity or proximity of green space usuallywith reference to research participantsrsquo homesObjective measure or self-report

Biophysical Presencequantity of specific landscape elements(eg vegetation open land) or interventionswith different landscape outcomes (eg forestmanagement plans) Covers most physical mea -sures falling short of biodiversity Objectiveandor self-report May be inherent in the stimu-lus (eg vegetation manipulated in the researchdesign) or explicit in the measure (eg vegetationdensity within a given area)

Human Categorizations based on cultural constructsperceptual descriptorsvalues (eg quality of green space

naturalness (unless linked to a biodiversity mea -sure) openness) Landscape types May be inher-ent in the stimulus or explicit in the measure orboth Objective measure or self-report

Biodiversity Objective measure of plantanimal diversity (orclose proxy) or where the concept of ldquobiodiver-sityrdquo is being evaluated

ings from this taxonomic coding we used a variant of the researchmapping process described by Bell et al (2007) For this process cod-ing information for the studies was tabulated in a green space-by-human benefit matrix According to Bell et al examining the distri-bution of studies across the various cells of the matrix can help revealresearch priorities and gaps

To address research questions 3 and 4 we jointly selected 30studies from among the 182 that we felt represented diverse and in-novative approaches to measuring the more ecological aspects of ur-ban green space and conceptualizing the issues By reading anddiscussing these studies our aim was to highlight in a more qualita-tive way the major methodological approaches assess their successand limitations and suggest ways in which current and future workcan develop holistic measures that function in an interdisciplinary


343

Table 2 Taxonomy of human health and well-being measures

Code Definition

Preference Participants are asked to rate the attractiveness ofdifferent landscape scenes or scenarios or theirsuitability for a particular activity

Attitudes Spans a range of methodologies from quantitativemeanings in which participants are asked for their level of and values agreement with attitudinal statements to qualita-

tive approaches in which underlying meaningsand values are explored

Psychological Self-rated or objectively measured psychological benefits health or other psychological mea sure including

restoration and affective responses to landscape

Physical health Self-rated or objectively measured physicalhealth

Behavior Behavioral patterns or changes eg physical activity walking

Mixed Several human measures No overall focus onone aspect

Other Other human measure (eg socio-economic variables)

context to address both the social and ecological dimensions of urbangreen space

Finally ldquowell-beingrdquo as a term has been interpreted in differentways For example Bell et al (2007) have limited ldquohealth and well-beingrdquo literature to the health domain whereas in the MillenniumEcosystem Assessment (2003) model ldquowell-beingrdquo refers to a muchwider range of human benefits including cultural values to whichecosystem services contribute Thus except in relation to our searchstrategy outlined above when we refer to ldquohealth and well-beingrdquo inthis paper we include literature related to health and well-being so-cial and community health and well-being and perceptions and pref-erences under that description

Results

Research Mapping

The results of the research mapping exercise are set out in Table 3which suggests some clear associations between the green space andhuman health and well-being measures with each green space meas-ure mapping predominantly onto one or two closely-related humandomains

Studies without any green space measures (ldquononerdquo n=34) tendedto map with human measures of ldquoattitudes meanings and valuesrdquoWithin this grouping the emphasis was on understanding attitudes to-ward a range of issues both in relation to specific sites and to moregeneric conceptualizations of green space and nature For exampleByrne et al (2006) examined the spiritual traditions that Australianimmigrant groups have toward nature in the context of the GeorgesRiver park site in southwest Sydney Australia Bright et al (2002) as-sessed urban dwellersrsquo beliefs attitudes and awareness toward theidea of urban ecological restoration in Chicago USA and Herzog etal (2002) looked at how activities in nature were rated by students inrelation to other quotidian and leisure activities

The ldquourban versus naturalrdquo measures (n=20) were used mainly instudies of the ldquopsychological benefitsrdquo derived from exposure to envi-ronmental settings Across this sample of studies the dichotomy wasoperationalized in a variety of ways including comparing the bene-fits of running in urban or rural settings (Bodin and Hartig 2003) orindoors on a treadmill and outside in natural surroundings (Kerr et al2005) of being in rooms with tree views or no views (Hartig et al


344


345

Tabl

e 3

R

esea

rch

map

of g

reen

spa

ce b

y hu

man

hea

lth a

nd w

ell-

bein

g m

easu

res

full

stud

y se

t (N

=18

2)

Atti

tude

s

mea

ning

s

Psyc

holo

gica

l Ph

ysic

al

Mea

sure

sPr

efer

ence

and

valu

esbe

nefit

she

alth

Beh

avio

rM

ixed

Oth

erTo

tal

Non

e1

233

13

30

34

Urb

an v

ersu

s na

tura

l1

215

01

10

20

Inve

ntor

y1

03

03

20

9

Des

crip

tive

narr

ativ

e0

123

03

21

21

Are

adi

stan

ce0

21

114

13

22

Bio

phys

ical

144

20

20

224

Hum

an p

erce

ptua

l8

64

21

20

23

Bio

dive

rsity

1014

10

01

329

All

mea

sure

s35

6332

1417

129

182

2003) and exposure to urban as opposed to natural settings depictedin videos (Laumann et al 2003) or slides (Staats et al 2003)

ldquoInventoryrdquo measures were used in the least number of studies(n=9) and were spread across human measures of ldquopsychological ben-efitsrdquo and ldquobehaviorrdquo and in studies with ldquomixedrdquo measures They con-sisted of a somewhat eclectic list of items many of which did not relateto green space at all For example Sugiyama and Ward Thompson(2008) used a 26-item neighborhood open space scale (which includedldquotrees and plants are attractiverdquo) to identify neighborhood attributes thatpredicted the level of walking in people above the age of 65

We used the ldquodescriptivenarrativerdquo green space measure (n=21)to categorize qualitative studies where the green space measures orthemes were derived from the research participants rather than im-posed by the investigators Most studies using this type of green spacemeasure mapped with studies of ldquoattitudes meanings and valuesrdquoThe studies covered a wide range of research topics and consequentlythere was very little consistency in the themes reported

ldquoAreadistancerdquo (n=22) was used as a green space measure mainlyin studies examining peoplersquos ldquophysical healthrdquo and ldquobehaviorrdquo wherein this context behavior referred to physical activity especially walk-ing In this cluster of studies green space was measured either interms of its proximity to the residence of a research participant (egCochrane et al 2009 Takano et al 2002) or its quantity in terms ofarea or amount of green space within a given radius from onersquos resi-dence (eg De Vries et al 2003 Maas et al 2006 Maas et al 2009)or within an administrative district that included residences (Mitchelland Popham 2008) In some studies measures of area and distancewere combined (eg Neuvonen et al 2007)

ldquoBiophysical measuresrdquo (n=24) mapped predominantly to studiesof human ldquopreferencerdquo and to a lesser extent ldquoattitudes meaningsand valuesrdquo For studies coded in this green space category the focuswas on assessing preferences for or acceptability of specific ap-proaches and practices of landscape planning and management Bio-physical measures included the percentage of open land in the viewand size of landscape ldquoroomsrdquo in a study of landscape scale (Tveit2009) the spatial arrangement of trees in brownfield rehabilitationscenarios (Lafortezza et al 2008) and the specification of differentoptions for managing urban forests (Tyrvaumlinen et al 2003)

As in the case of ldquobiophysical measuresrdquo ldquohuman perceptualrdquomeasures of green space (n=23) mapped mainly to studies of ldquoprefer-encerdquo and ldquoattitudes meanings and valuesrdquo As cultural constructs of


346

physical green space characteristics human perceptual measureswere not objectively measured or systematically manipulated in theresearch design and for our sample of studies were either predefinedby the investigator (in the case of ldquopreferencerdquo studies) or identifiedby the investigator or the participant (in studies of ldquoattitudes mean-ings and valuesrdquo) These measures thus ranged from participant-de-fined and context-specific to more abstract and generalized Forexample Tyrvaumlinen et al (2007) mapped residentsrsquo perceptions of thequalities of their local woodlands (eg tranquility the feeling of beingin a forest and naturalness) and Simonic = (2003) asked participants torate photographs of different landscape types for preference and nat-uralness The more generalized investigator-defined measures in-cluded dimensions based on Kaplan and Kaplanrsquos (1989) preferencematrix (Herzog 1989 1992) Mozingorsquos (1997) principles for the aes-thetics of ecological design (Brzuszek and Clark 2007) and the pres-ence of human influence (Van den Berg and Vlek 1998) and signs ofcare in the landscape (Kaplan 2007)

Finally ldquobiodiversityrdquo green space measures (n=29) also mappedmainly to studies of ldquopreferencerdquo and ldquoattitudes meanings and val-uesrdquo Biodiversity included measures of actual plant and animal diver-sity (Asakawa et al 2004 Lindemann-Matthies and Bose 2007Nas sauer 2004a) as well as surrogate measures used in remote sens-ing such as NPP (Net Primary Productivity) as an indicator of speciesdiversity and biological productivity (Alessa et al 2008) and theNDVI (Normalized Differential Vegetation Index) as an indicator ofthe percentage of vegetated area per setting (Hur et al 2009) Otherproxies for biodiversity included structural complexity evaluated at asite level by Home et al (2010) to study preferences for green spacesaround social housing and landscape heterogeneity mapped byDramstad et al (2001) at a landscape scale using remote sensing tostudy aesthetic appreciationexperience and cultural heritage valuesAnother approach was to contrast preferences or attitudes toward var-ious scenarios for the enhancement of biodiversity in different con-texts such as the design of residential subdivisions in the UnitedStates (Nassauer 2004b) or business sites in the Netherlands (Snep etal 2009) A further approach was to assess the impact of levels ofstructural alteration in naturally-occurring vegetation communities onviewer preference (Purcell and Lamb 1998) and judgments of natural-ness (Lamb and Purcell 1990)

As applied to our sample of the literature the research mappingexercise provided a characterization of how urban green space has


347

been conceptualized and measured to address issues of human healthand well-being While our narrative focused on the dominant con-ceptual combinations in our sample the matrix in Table 3 also showsareas where there has been less research activity These gaps accord-ing to Bell et al (2007) can suggest priorities for future researchThere has for example been virtually no research into the impact ofbiodiversity in green spaces on psychological benefits including psy-chological restoration physical health or behavior with the notableexception of Fuller et al (2007)

Innovative approaches to measuring the ecology of urban green space

Out of our sample we selected for in-depth analysis a shortlist of 30studies that we felt used innovative approaches to address the ecolog-ical aspects of urban green space in the context of human health andwell-being or highlighted some of the key issues in using green spacemeasures in inter-disciplinary research As Table 4 demonstratesthese papers were dominated by ldquobiodiversityrdquo (n=18) measures of ur-ban green space but also included measures from the ldquobiophysicalrdquo(n=7) ldquohuman perceptualrdquo (n=4) and ldquodescriptivenarrativerdquo (n=1)domains In terms of the human measures they mapped mainly ontoldquopreferencerdquo and ldquoattitudes meanings and valuesrdquo The followingdiscussion focuses on how green space characteristics are measuredand how alternatives for green space design and management are rep-resented to people for evaluation

DIRECT AND PROXY APPROACHES TO MEASURING GREEN SPACE CHARACTERISTICS

In terms of the way biodiversity is measured in our shortlisted sampleof papers a rough distinction can be made between approaches thatseek to measure biodiversity on-site and those deploying landscapemetric proxies for biodiversity Examples of the former approach in-clude de la Maza et al (2002) in which 6 different measures of bio-diversity were used to study the association between biodiversity andthe income level of residents in the 36 metropolitan boroughs of San-tiago Chile Kinzig et al (2005) in which plant and bird diversitywere mapped against the income levels of residents of Phoenix Ari-zona USA and Fuller et al (2007) in which urban parks along atransect in Sheffield UK were sampled inter alia for plant and birdspecies richness to explore the links between biodiversity and the psy-chological benefits experienced by park users


348


349

Tabl

e 4

R

esea

rch

map

of g

reen

spa

ce b

y hu

man

hea

lth a

nd w

ell-

bein

g m

easu

res

sub

set o

f inn

ovat

ive

stud

ies

(N=

30)

Atti

tude

s m

eani

ngs

Ps

ycho

logi

cal

Mea

sure

Pref

eren

cean

d va

lues

bene

fits

Oth

erTo

tals

Des

crip

tive

Hea

d an

d M

uir

Nar

rativ

e(2

006)

(1)

1

Bio

phys

ical

Bje

rke

et a

l (2

006)

Han

ds a

nd

Bre

uste

(200

4) (

1)Li

and

Wen

g B

row

n (2

002)

Laf

orte

zza

et a

l (2

007)

(1)

(200

8) T

yrvauml

inen

et a

l (2

003)

V

an d

en B

erg

and

Kool

e (2

006)

(5)

7

Hum

an

Kap

lan

(200

7) (

1)D

e G

root

and

Van

Ko

rpel

a et

al

perc

eptu

alde

n B

orn

(200

3)

(200

8) (

1)Ouml

zgun

er a

nd K

endl

e (2

006)

(2)

4

Bio

dive

rsity

Dra

mst

ad e

t al

(200

1) L

inde

man

n-B

onne

s et

al

(200

7)

Fulle

r et

al

De

la M

aza

Mat

thie

s an

d B

ose

(200

7) L

inde

man

n-H

ur e

t al

(200

9)

(200

7) (

1)et

al

(200

2)

Mat

thie

s et

al

(201

0) N

assa

uer

Gyl

lin a

nd G

rahn

K

inzi

g et

al

(200

4a)

Nas

saue

r (2

004b

) O

de e

t al

(200

5) L

amb

and

(200

5) (

2)(2

009)

Pal

mer

(200

4) P

urce

ll an

d Pu

rcel

l (19

90)

Lee

Lam

b (1

998)

Sol

iva

and

Hun

zike

r et

al

(200

8) J

unke

r (2

009)

(9)

and

Buc

heck

er

(200

8) (

6)18

Tota

ls15

102

330

The main advantages of site-based biodiversity measures seem tobe accuracy and site specificity However there is no single readily-identifiable measure of biodiversity In human dimensions researchthere is an additional question as to which indicator or combinationof indicators has a measurable impact on humans This may be a ques-tion of scale if the measures are too fine (eg where the organismsunder investigation are too small too specialized or the sampling toolocalized) or too coarse (eg where the spatial unit of mea surement istoo big) they may be outside the scale of human comprehension(Bonnes et al 2007) Nassauer (2004a) found that wetland visitorsrsquo re-ports of the frequency with which they saw wildlife were highly cor-related with expert-based plant and bird species richness valuesFuller et al (2007) concluded that green space users were able to per-ceive species richness of well-known higher taxa but also hypothe-sized that users detect biodiversity indirectly ldquogross structural habitatheterogeneity might cue the perceptions and benefits of biodiversityrdquo(p 393) There is considerable support for this more broadly basedldquostructural heterogeneityrdquo hypothesis including Australian studieswhich have found that viewers (students and storekeepers) were ableto discriminate between different naturally-occurring structural vege-tation types and different forms of structural alteration within thosetypes (Lamb and Purcell 1990 Purcell and Lamb 1998)

Perhaps one of the greatest drawbacks of a site sampling approachto biodiversity measurement in social science research is its resourceintensiveness Fuller et alrsquos (2007) protocol for measuring herbaceousplant species richness involved sampling 15 green spaces using 20quadrats per habitat type up to a maximum of 7 habitat typesmdasha hy-pothetical maximum of 2100 quadrats Woody plant species weresampled using a similar protocol adding to the sampling load An-other limitation is that if landscape change is to be monitored thewhole sampling procedure has to be repeated

In contrast to on-site measures of biodiversity our shortlist also in-cluded a number of proxy approaches to biodiversity using remotesensing and GIS Some of these approaches have already been men-tioned in our findings on the full sample of studies (Alessa et al 2008Hur et al 2009) Other remote sensing approaches have used struc-tural heterogeneity or equivalent measures as key variables lendingadditional support to Fuller et alrsquos (2007) structural heterogeneity hy-pothesis Lee et al (2008) used the normalized difference vegetationindex (NDVI) method applied to IKONOS multispectral images tomea sure the impact of fragmentation distance permeability variabil-


350

ity and connectivity of tree patches on neighborhood satisfaction Inan ambitious multidisciplinary study Dramstad et al (2001) usedmapped landscape heterogeneity (ldquothe spatial variation of a land-scaperdquo p 260) as a proxy for biodiversity in assessing aesthetic andcultural heritage values in the landscape

While proxy approaches have obvious pragmatic advantages interms of being able to use remote sensing data that is often readilyavailable and regularly updated the Dramstad et al (2001) study alsohighlights two problems in using such approaches in interdisciplinarylandscape research The first is that of moving from a two-dimensionalmap-based world view to a ground-level representation that relates tothe normal human experience of landscape While landscape hetero-geneity and cultural heritage values may be mapped in two dimen-sions in the GIS human aesthetic landscape values derive from beingable to experience or at least see that landscape at a specific loca-tion The second problem is that while GIS can store and display com-plex information about large-scale spatially-related resources humanperception tends to operate at a much smaller scale and is con-strained by factors not ordinarily recognized in the GIS such as visualbarriers or structures affecting physical movement In the previously-mentioned study by Lee et al (2008) the authors state that not enoughis known about the critical scales at which humans experience theirresidential environment and the same critique can be extended tovirtually any environment

Dramstad et al (2001) attempted to address these problems byasking a small sample of students to evaluate the aesthetic value oftypical ground-level images of the landscapes included in the GISanalysis But the content of such images is clearly crucial and sam-pling must be done systematically or images must be digitally manip-ulated to ensure that the landscape is thoroughly and consistentlyrepresented The latter approach was taken by Ode et al (2009) whoused computer-generated visualizations of a hypothetical landscapecontaining pasture and broadleaved woodland to explore the rela-tionships between viewer preference and three landscape-level indi-cators of naturalness (level of succession number of woodland patchesand shape index of edges) Preference was strongly related to the levelof succession and number of woodland patches and more weaklywith the shape index of edges This work seems to address some ofthe difficulties in translating mapped landscape indicators into visu-ally comprehensible representations that people can respond to Pre-sumably if we can use remote sensing data and GIS to extract the


351

critical metrics of landscapes we can construct a virtual landscapebased on those metrics

SCENARIO ON-SITE AND SEMANTIC APPROACHES TO REPRESENTING GREEN SPACES

The work of Ode et al (2009) also exemplifies what may broadly betermed the scenario manipulation approach used frequently in ourshortlisted papers These scenarios used visual images to presentgreen space planning design and management alternatives to studyparticipants for evaluation (usually expressed in preference ratings)The scenarios ranged from highly structured alternatives like Ode etal where green space images were digitally manipulated in a system-atic way along one or more variables to less structured approachesthat presented people a range of real-world examples illustrating al-ternatives without systematic measurement or control of extraneousvariables Hands and Brown (2002) also used digitally altered imagesto assess employeesrsquo reactions to different ecological rehabilitationscenarios of their workplace in Niagara Falls Canada demonstratinghow visual images and biodiversity or biophysical measures can beused in a focused way to systematically study practical interventionsat a site level

Examples of a less structured photo-based approach includestudies by Kaplan (2007) who used 24 photographs to represent arough gradient of landscapes with differing naturalurban content anddifferent levels of management in a study of preference and attitudestoward quotidian landscapes around the workplace in Ann ArborMichigan USA and Tyrvaumlinen et al (2003) who used a set of 24photographs to represent different urban forest management optionsdemonstrating how the scenario manipulation approach may be usedin participatory planning in Helsinki Finland

Junker and Buchecker (2008) used a structured approach to com-pare expert ratings of ecological quality and public evaluation of vi-sual attractiveness in the context of river restoration The authorscomment on the ldquolack of suitable reference scales for varying states ofecological integrityrdquo (p 142) In this case they used the concept ofldquoeco-morphological qualityrdquo (essentially the structural state of riverreaches) an approach to river restoration based on the pre-existingldquomodule-step conceptrdquo (BUWAL 1998) as the basis for constructing aseries of digitally manipulated photographs depicting a river in an ar-tificial semi-artificial semi-natural and near-natural condition Thestudy is noteworthy for a number of reasons For one scenarios basedon this approach can be visualized more easily than if they were


352

based on a more abstract concept of biodiversity Also the differentlevels of restoration are established according to objective and replic-able criteria and relate directly to real-life scenarios in which theldquomodule-step conceptrdquo is to be used This study also lends weight toFuller et alrsquos (2007) hypothesis that biodiversity is detected by the laypublic by means of structural or morphological cues in the landscape

Junker and Bucheckerrsquos (2008) study highlights some of the diffi-culties inherent in representing spatially explicit ecological models astwo-dimensional visualizations and two of the studies in our sampledeveloped interesting solutions to this problem Lafortezza et al(2008) created digital simulations of four landscape rehabilitationscenarios involving soil remediation the addition of ground coverspecies and trees in different spatial configurations They also used aldquoCost Surface Modelingrdquo (CSM) approach which assigns a ldquofrictionvaluerdquo to each land cover type representing the permeability of thelandscape to forest passerines (songbirds) The different rehabilitationscenarios were assigned friction values as were the rest of the landcover types in the area and thus the CSM was able to demonstratehow the different remediation options would function at the land-scape scale This innovative approach however was compromised bythe use of very simplistic visual simulations and thus while study re-sults showed that the scenarios most favorable to bird dispersal werealso more visually preferable research participants might have re-acted less positively to more lifelike remediation scenarios

Another innovative approach is that of Nassauer (2004b) whoused digitally manipulated scenes to evaluate preferences for devel-opment scenarios of the urban-agricultural fringe The ecological im-plications of three different development scenarios (conventional andecologically beneficial residential development and existing agricul-ture) were evaluated by measuring stream health (presence of sus-pended materials chemical composition and invertebrate species rich-ness) at existing sites having land covers equivalent to those envisagedin the development scenarios The strengths of this research design liein its ability to bridge the spatial temporal and conceptual bound-aries of landscape planning and design by linking current measuresof ecological health to future development scenarios the study wasable to anticipate the ecological impacts that peoplersquos developmentpreferences could have across a landscape

Some of the scenario manipulation approaches in our samplealso examined cultural and demographic differences in preference asa function of vegetation density and biodiversity Bjerke et al (2006)


353

measured Norwegian urban residentsrsquo recreational preferences for ur-ban park landscapes using photographs varying in vegetation densityand examined preference variations as a function of demographic andenvironmental value orientations Soliva and Hunziker (2009) askedSwiss residents to rate visualizations of potential landscape develop-ments under four different scenarios representing a variety of biodi-versity management and reforestation options and to answer anumber of text items dealing with biodiversity concepts and valuesVan den Berg and Koole (2006) adopted a similar approach in rela-tion to Dutch nature development plans The advantage of these re-search designs is that they give additional insights into the culturaland demographic foundations of landscape preferences which helpsto build a picture of how such preferences map onto different sectorsof the population and how preferences are likely to change in re-sponse to social and biophysical landscape changes

While the majority of shortlisted studies relied on the developmentof structured and unstructured photographic scenarios to representgreen space ideas and management alternatives for public evaluationa few studies employed on-site visits andor semantic approaches ofrepresentation Three of our selected studies used actual sites and in-terestingly each was concerned with eliciting popular meanings ofbiodiversity nature or naturalness Oumlzguner and Kendle (2006) useda questionnaire to explore the attitudes and values of park visitors to-ward ldquonaturerdquo and ldquonaturalnessrdquo in two urban parks in Sheffield UKone naturalistic and one formal Gyllin and Grahn (2005) used se-mantic measures to assess attitudes to biodiversity in six different ar-eas characterized by varying management intensity representing astratified selection of park types common in southern Sweden AndHead and Muir (2006) used a qualitative ethnographic approach tostudy gardeners and their gardens in metropolitan Sydney Australiato reveal how notions of boundary making and nativeness expressedthrough gardening practices helped to define nature perceptions andinform ideas about the management of urban and rural landscapes

The final example in our shortlisted set of studies by De Groot andVan den Born (2003) relied entirely on textual description In the studya mail survey was used to elicit views about the types of nature thatpeople distinguish and the levels of naturalness ascribed to thesetypes of nature the images that people hold of the appropriate rela-tionship between people and nature and the level of adherence tothese images and peoplersquos preference of broadly defined landscapetypes This study fills a gap between landscape preference studies and


354

peoplersquos views of nature While at first glance the textual measuresused seem somewhat abstract like the study by Head and Muir (2006)this open-ended approach can help assess the complex cultural ldquovi-sions of naturerdquo that underpin green space preferences Their abstrac-tion allowed participants to introduce their own content into thedescriptions This technique may have wider applications in terms ofsituating peoplersquos green space preferences and values within a broadercultural context

Discussion

In this paper we have attempted to examine recent research on urbangreen space in the context of human health and well-being In thecontext of urban ecological restoration our analysis shows that whilea range of relatively sophisticated measures are being used to assessthe biophysical human perceptual and biodiversity characteristics ofurban green space most of this work has been focused on a relativelynarrow range of human health and well-being dimensions particu-larly in the areas of preference and attitudes meanings and valuesIn contrast most work on psychological and physical benefits andbehavior (especially studies of physical activity) have relied on rela-tively simple green space measures such as natural versus urban orareadistance Our map of the research (Table 3) confirms other recentanalyses of the green space literature by Nasar (2008) Van den Berget al (2007) and Velarde et al (2007)

According to Bell et al (2007) these gaps suggest priorities for fu-ture research and while we generally believe this to be a productivestrategy some green space measures applicable to issues in urbanecological restoration may not readily transfer across all domains ofhuman health and well-being For example De Vries et al (2003) ex-amined the relationship between human health urbanity and theamount of green space within one and three kilometers of peoplersquoshomes While some broad distinctions were made between differenttypes of green space (urban green agricultural green and forests andnature areas) only agricultural green was significant for all the healthindicators used in the study The authors surmise that this is not be-cause agricultural green is inherently better but because it exceededother forms of green in the study In other words it is the amount ofgreen space that may be crucial and not its particular characteristicsand even then the authors question whether the amount of green may


355

just be another way of measuring the natural versus urban dimensionThus it should not be assumed that all green space measures aresalient across the entire spectrum of human benefits

A more productive strategy for future research into these benefitdomains thus should seek to establish which types of green space pro-mote particular well-being outcomes and how interactions with differ-ent types of green space may be mediated by cultural and demographicfactors Indeed much of what may loosely be termed landscape re-search is concerned with the need for integration between researchdisciplines and between research and practice across the fields oflandscape planning design and management (Borgstroumlm et al 2006Morton et al 2009) Interdisciplinary collaboration between the so-cial and natural sciences involves the consideration of multiple pa-rameters and multiple scales across the dimensions of time spatialityand process (Tress et al 2003) and it therefore is unlikely that a sin-gle environmental measure would ever be capable of working effec-tively across the full range of these disciplines Thus the developmentof more complex models is called for and a number of authors in-cluding Fry et al (2009) and Tzoulas et al (2007) have made signifi-cant progress in this direction

Several of the shortlisted studies that we reviewed in-depth (Table4) suggest that structural landscape heterogeneity may be one of themost promising green space measures with the potential to integratedifferent disciplinary perspectives and scales The evidence suggeststhat structural heterogeneity may be the principle means by which hu-mans detect biodiversity in the landscapes around them (Fuller et al2007) in that it can be used to integrate the assessment of differentlandscape values at a landscape scale using a GIS (Dramstad et al2001) and be systematically represented in digital simulations to gaugepublic reaction to particular planning design or management out-comes (Junker and Buchecker 2008 Nassauer 2004b Ode et al2009) The creation or retrofitting of green infrastructure as the basisfor future sustainable urban development involves the establishmentof multifunctional green networks and it seems likely that structurallandscape heterogeneity could become one of the principal means bywhich their effectiveness is measured against multiple parametersHowever many of the studies that used a form of structural landscapeheterogeneity as an environmental measure were conducted in a ru-ral context and it may prove to be less effective in urban areas whereparcels of green space are smaller more fragmented and vegetationcommunities are more disturbed (Purcell and Lamb 1998)


356

To be truly effective such models need to accommodate a para-digm shift that sees humans not merely as ldquoan exogenous perturbingforce but as an interactive species on the landscape structuring theirsurroundings to achieve a particular suite of environmental ameni-tiesrdquo (Kinzig et al 2005 2) As these authors point out this involvesrecognizing that the social political economic administrative andcultural processes that have hitherto been considered separately fromthe ecology of the natural landscape are in fact deeply implicated inits development and change

As a final note both the studies included in the research mappingexercise and the final shortlist were predominantly quantitative intheir methodological approach and many relied on what we havecalled the scenario manipulation approach using mainly visual stim-uli This bias toward quantitative and visual studies was the outcomeof our emphasis on explicit green space measures which are oftenabsent from qualitative research In focusing on the former we acceptthat we have excluded from consideration some important aspects ofhuman health and well-being and methodological approaches thatrely on hands-on multi-sensory experiential interaction with greenspace (eg Gobster 2008)

Conclusion

Urban ecological restoration provides a set of ecologically-based con-cepts and practices that challenge managers to think of urban greenspace as more than ldquosimply greenrdquo By creating more structurallycomplex environments in a wider range of urban green spaces man-agers can address a number of issues that are at the forefront of urbanecology including sustainability biodiversity and the provision ofecosystem services (Ingram 2008 Nowak and Dwyer 2007) But thereis also an important human side to urban ecological restoration andas seen in this review of the recent literature studies of green spaceand human health and well-being are using a diverse range of waysto measure the green in green space in ways that are relevant andmeaningful to people Work on human-green space interactions hasgenerally shown a positive relationship between measures of biodi-versity and preference but it also shows important exceptions in dif-ferent contexts for different demographic and cultural groups and for different domains of human health and well-being Further cross-disciplinary research is needed as those working in urban ecological


357

restoration seek to integrate social concepts and practices with eco-logical ones

Acknowledgements

Support for this research came in part through a grant from the USNational Science Foundation (DEB-BE-0909451) ldquoCoupled Natural-Human Systems in the Chicago Wilderness Evaluating the Biodiversityand Social Outcomes of Different Models of Restoration Planningrdquo(Gobster)

Anna Jorgensen is a Lecturer with the Department of Landscape The Uni-versity of Sheffield Crookesmoor Building Conduit Road Sheffield Eng-land UK S10 1FL Her research deals with exploring and evidencing thevalues and benefits of ldquowilderrdquo urban landscapes ranging from woodland toderelict and marginal sites across different human well-being dimensions Email ajorgensenshefacuk (Corresponding author)

Paul Gobster is Research Social Scientist with the USDA Forest ServicersquosNorthern Research Station in Chicago and a member of the Nature+CultureEditorial Board His current research examines peoplersquos perceptions of nat-ural areas restoration and management the interface of aesthetic and eco-logical values in landscape and the design and provision of urban greenspaces to encourage healthy lifestyles Email pgobsterfsfedus

Notes

1 While green space is largely characterized by its vegetation it may also in-clude water features wildlife and built facilities that support use or other associatedfunctions

2 The full list of study citations is available from the authors upon request

References

Alessa Lilian N Andrew (Anaru) Kliskey and Gregory Brown 2008 ldquoSocialndashecological Hotspots Mapping A Spatial Approach for Identifying Coupled SocialndashEcological Spacerdquo Landscape and Urban Planning 85 (1) 27ndash39

Asakawa Shoichiro Keisuke Yoshida and Kazuo Yabe 2004 ldquoPerceptions of UrbanStream Corridors within the Greenway System of Sapporo Japanrdquo Landscapeand Urban Planning 68 (2-3) 167ndash182


358

Bell Simon Val Hamilton Alicia Montarzino Helen Rothnie Penny Travlou and Su-sana Alves 2008 Greenspace and Quality of Life A Critical Literature ReviewStirling UK Greenspace Scotland

Bell Simon Alicia Montarzino and Penny Travlou 2007 ldquoMapping Research Priori-ties for Green and Public Open Space in the UKrdquo Urban Forestry and UrbanGreening 6 (2) 103ndash115

Bjerke Tore Torbjoslashrn Oslashstdahl Christer Thrane and Einar Strumse 2006 ldquoVegetationDensity of Urban Parks and Perceived Appropriateness for Recreationrdquo UrbanForestry and Urban Greening 5 (1) 35ndash44

Bodin Maria and Terry Hartig 2003 ldquoDoes the Outdoor Environment Matter for Psy-chological Restoration Gained through Runningrdquo Psychology of Sport and Exer-cise 4 (2) 141ndash153

Bonnes Mirilia David Uzzell Guiseppe Carrus and Tanika Kelay 2007 ldquoInhabitantsrsquoand Expertsrsquo Assessments of Environmental Quality for Urban SustainabilityrdquoJournal of Social Issues 63 (1) 59ndash78

Borgstroumlm Sara T Thomas Elmqvist Per Angelstam and Christine Alfsen-Norodom2006 ldquoScale Mismatches in Management of Urban Landscapesrdquo Ecology andSociety 11(2) article 16 httpwwwecologyandsocietyorgvol11iss2art16 (ac-cesses 21 July 2010)

Bright Alan D Susan C Barro and Randall T Burtz 2002 ldquoPublic Attitudes towardEcological Restoration in the Chicago Metropolitan Regionrdquo Society and NaturalResources 15 (9) 763ndash785

Brzuszek Robert F and James Clark 2007 ldquoAre They Getting It Visitors Respond tothe Crosby Arboretumrsquos Ecological Aestheticrdquo Landscape Architecture 97 (5) 78ndash85

BUWAL 1998 Methoden zur Untersuchung und Beurteilung der FliessgewaumlsserModul-Stufen-Konzept vol 26 Bern Mitteilungen zum Gewaumlsserschutz

Byrne Denis Heather Goodall Stephen Wearing and Allison Cadzow 2006 ldquoEn -chanted Parklandsrdquo Australian Geographer 37 (1) 103ndash115

Cochrane Thomas Rachel C Davey Chris Gidlow Graham R Smith Jon FairburnChristopher J Armitage Hilde Stephansen and Svetlana Speight 2009 ldquoSmallArea and Individual Level Predictors of Physical Activity in Urban CommunitiesA Multi-Level Study in Stoke on Trent Englandrdquo International Journal of Environ-mental Research and Public Health 6 (2) 654ndash677

Daniel Terry C 2001 ldquoWhither Scenic Beauty Visual Landscape Quality Assessmentin the 21st Centuryrdquo Landscape and Urban Planning 54 (1ndash3) 267ndash281

De Groot W T and R J G van den Born 2003 ldquoVisions of Nature and LandscapeType Preferences An Exploration in The Netherlandsrdquo Landscape and UrbanPlanning 63 (2) 127ndash138

De la Maza Carmen Luz Jaime Hernaacutendez Horacio Bown Manuel Rodriguez andFrancisco Escobedo 2002 ldquoVegetation Diversity in the Santiago De Chile UrbanEcosystemrdquo Arboricultural Journal 26 347ndash357

De Vries Sjerp Robert A Verheij Peter P Groenewegen and Peter Spreeuwenberg2003 ldquoNatural EnvironmentsHealthy Environments An Exploratory Analysis ofthe Relationship between Greenspace and Healthrdquo Environment and Planning A35 1717ndash1731

Del Tredici Peter 2010 ldquoSpontaneous Urban Vegetation Reflections of Change in aGlobalized Worldrdquo Nature and Culture 5 (3) 299ndash315


359

Dramstad WE G Fry W J Fjellstad B Skar W Helliksen M-L B Sollund M STveit A K Geelmuyden and E Framstad 2001 ldquoIntegrating Landscape-BasedValues Norwegian Monitoring of Agricultural Landscapesrdquo Landscape and Ur-ban Planning 57 (3) 257ndash268

Frumkin Howard 2001 ldquoBeyond Toxicity Human Health and the Natural Environ-mentrdquo American Journal of Preventive Medicine 20 (3) 234ndash240

mdashmdashmdash 2006 ldquoThe Measure of Placerdquo American Journal of Preventive Medicine 31(6) 530ndash532

Fry G M S Tveit Aring Ode and M D Velarde 2009 ldquoThe Ecology of Visual Land-scapes Exploring the Conceptual Common Ground of Visual and EcologicalLandscape Indicatorsrdquo Ecological Indicators 9 (5) 933ndash947

Fuller Richard A Katherine N Irvine Patrick Devine-Wright and Kevin J Gaston2007 ldquoPsychological Benefits of Greenspace Increase with Biodiversityrdquo BiologyLetters 3 390ndash394

Gobster Paul H 2008 ldquoYellowstone Hotspot Reflections on Scenic Beauty Aesthet-ics and Ecologyrdquo Landscape Journal 27 (2) 291ndash308

Gyllin Mats and Patrik Grahn 2005 ldquoA Semantic Model for Assessing the Experienceof Urban Biodiversityrdquo Urban Forestry and Urban Greening 3 (3-4) 149ndash161

Hands Denise E and Robert D Brown 2002 ldquoEnhancing Visual Preference of Eco-logical Rehabilitation Sitesrdquo Landscape and Urban Planning 58 (1) 57ndash70

Hartig Terry Gary W Evans Larry D Jamner Deborah S Davis and Tommy Garling2003 ldquoTracking Restoration in Natural and Urban Field Settingsrdquo Journal of En-vironmental Psychology 23 (2) 109ndash123

Head Lesley and Pat Muir 2006 ldquoSuburban Life and the Boundaries of Nature Re-silience and Rupture in Australian Backyard Gardensrdquo Transactions Institute ofBritish Geographers 31 (NS) 505ndash524

Herzog Thomas R 1989 ldquoA Cognitive Analysis of Preference for Urban Naturerdquo Jour-nal of Environmental Psychology 9 (1) 27ndash43

Herzog Thomas R 1992 ldquoA Cognitive Analysis of Preference for Urban Spacesrdquo Jour-nal of Environmental Psychology 12 (3) 237ndash248

Herzog Thomas R Hong C Chen and Jessica S Primeau 2002 ldquoPerception of theRestorative Potential of Natural and Other Settingsrdquo Journal of EnvironmentalPsychology 22 (3) 295ndash306

Home Robert Claudia Keller Peter Nagel Nicole Bauer and Marcel Hunziker 2010ldquoCultural and Biological Determinants in the Evaluation of Urban Green SpacesrdquoEnvironment and Behavior 42 (4) 494ndash532

Hur Misun Jack L Nasar and Bumseok Chun 2009 ldquoNeighborhood SatisfactionPhysical and Perceived Naturalness and Opennessrdquo Journal of EnvironmentalPsychology 32 (1) 52ndash59

Ingram Mrill 2008 ldquoUrban Ecological Restorationrdquo Ecological Restoration 26 (3)175ndash177

Junker Berit and Matthias Buchecker 2008 ldquoAesthetic Preferences versus EcologicalObjectives in River Restorationsrdquo Landscape and Urban Planning 85 (3ndash4)141ndash154

Kaplan Rachel 2007 ldquoEmployeesrsquo Reactions to Nearby Nature at Their WorkplaceThe Wild and the Tamerdquo Landscape and Urban Planning 84 (1) 17ndash24

Kaplan Rachel and Stephen Kaplan 1989 The Experience of Nature A Psychologi-cal Perspective Cambridge UK Cambridge University Press


360

Kaplan Stephen Rachel Kaplan and John S Wendt 1972 ldquoRated Preference andComplexity for Natural and Urban Visual Materialrdquo Perception and Psycho -physics 12 (4) 354ndash356

Kerr John L Hakeui Fujiyama Atsuko Sugano Taito Okamura Milan Chang andFrancis Onouha 2005 ldquoPsychological Responses to Exercising in Laboratory andNatural Environmentsrdquo Psychology of Sport and Exercise 7 (4) 345ndash359

Kinzig Ann P Paige Warren Chris Martin Diane Hope and Madhusuan Katti 2005ldquoThe Effects of Human Socioeconomic Status and Cultural Characteristics on Urban Patterns of Biodiversityrdquo Ecology and Society 10 (1) 23

Lafortezza Raffaele Robert C Corry Giovanni Sanesi and Robert D Brown 2008ldquoVisual Preference and Ecological Assessments for Designed Alternative Brown-field Rehabilitationsrdquo Journal of Environmental Management 89 (3) 257ndash269

Lamb Richard J and Alan T Purcell 1990 ldquoPerception of Naturalness in Landscapeand Its Relationship to Vegetation Structurerdquo Landscape and Urban Planning 19(4) 333ndash352

Laumann Karin Tommy Garling and Kjell Morten Stormark 2003 ldquoSelective Atten-tion and Heart Rate Responses to Natural and Urban Environmentsrdquo Journal ofEnvironmental Psychology 23 125ndash134

Lee Sang-Woo Christopher D Ellis Byoung-Suk Kweon and Sung-Kwon Hong2008 ldquoRelationship between Landscape Structure and Neighborhood Satisfac-tion in Urbanized Areasrdquo Landscape and Urban Planning 85 (1) 60ndash70

Lindemann-Matthies Petra and Elisabeth Bose 2007 ldquoSpecies Richness StructuralDiversity and Species Composition in Meadows Created by Visitors of a Botani-cal Garden in Switzerlandrdquo Landscape and Urban Planning 79 (3-4) 298ndash307

Lindemann-Matthies Petra Xenia Junge and Diethard Matthies 2010 ldquoThe Influenceof Plant Diversity on Peoplersquos Perception and Aesthetic Appreciation of GrasslandVegetationrdquo Biological Conservation 143 195ndash202

Maas J R A Verheij P P Groenewegen S de Vries and P Spreeuwenberg 2006ldquoGreen Space Urbanity and Health How Strong Is the Relationrdquo Journal of Epi-demiology and Community Health 60 587ndash592

Maas J R A Verheij S de Vries P Spreeuwenberg F G Schellevis and P P Groe-newegen 2009 ldquoMorbidity Is Related to a Green Living Environmentrdquo Journal ofEpidemiology and Community Health 63 (12) 967ndash973

Maller Cecily Mardie Townsend Peter Brown and Lawrence St Leger 2002 HealthyParks Healthy People The Health Benefits of Contact with Nature in a Park Context A Review of the Literature Melbourne Deakin University and Parks Victoria

Millennium Ecosystem Assessment 2003 Ecosystems and Human Wellbeing AFramework for Assessment Washington DC Island Press

Mitchell Richard and Frank Popham 2008 ldquoEffect of Exposure to Natural Environ-ment on Health Inequalities An Observational Population Studyrdquo Lancet 3721655ndash1660

Morton S R O Hoegh-Guldberg D B Lindenmayer M Harriss Olson L HughesMT McCulloch S McIntyre H A Nix et al 2009 ldquoThe Big Ecological Ques-tions Inhibiting Effective Environmental Management in Australiardquo Austral Ecol-ogy 34 (1) 1ndash9

Mozingo Louise M 1997 ldquoThe Aesthetics of Ecological Design Seeing Science asCulturerdquo Landscape Journal 16 (1) 46ndash59


361

Nasar Jack L 2008 ldquoAssessing Perceptions of Environments for Active Livingrdquo Amer-ican Journal of Preventive Medicine 34 (4) 357ndash363

Nassauer Joan I 1995 ldquoMessy Ecosystems Orderly Framesrdquo Landscape Journal 14161ndash170

Nassauer Joan I 2004a ldquoMonitoring the Success of Metropolitan Wetland Restora-tions Cultural Sustainability and Ecological Functionrdquo Wetlands 24 (4) 756ndash765

Nassauer Joan I 2004b ldquoExurban Residential Subdivision Development Effects onWater Quality and Public Perceptionrdquo Urban Ecosystems 7 (3) 267ndash281

Neuvonen Marjo Tuija Sievaumlnen Susan Toumlnnes and Terhi Koskela 2007 ldquoAccess toGreen Areas and the Frequency of Visits A Case Study in Helsinkirdquo UrbanForestry and Urban Greening 6 (4) 235ndash247

Nowak David J and John F Dwyer Jr 2007 ldquoUnderstanding the Benefits and Costsof Urban Forest Ecosystemsrdquo Pp 25ndash46 in Urban and Community Forestry in theNortheast 2nd ed ed John E Kuser New York Springer

Ode Aringsa Gary Fry Mari S Tveit Pernette Messager and David Miller 2009 ldquoIndica-tors of Perceived Naturalness as Drivers of Landscape Preferencerdquo Journal of En-vironmental Management 90 (1) 375ndash383

Oumlzguumlner Halil and Anthony D Kendle 2006 ldquoPublic Attitudes Towards NaturalisticVersus Designed Landscapes in the City of Sheffield (UK)rdquo Landscape and UrbanPlanning 74 (2) 139ndash157

Parsons Russ 1995 ldquoConflict between Ecological Sustainability and EnvironmentalAesthetics Conundrum Canaumlrd or Curiosityrdquo Landscape and Urban Planning32 227ndash244

Purcell A Terrence and Richard J Lamb 1998 ldquoPreference and Naturalness An Eco-logical Approachrdquo Landscape and Urban Planning 42 (1) 57ndash66

Simonic= Tanja 2003 ldquoPreference and Perceived Naturalness in Visual Perception ofNaturalistic Landscapesrdquo Zb Bioteh Fak Univ Ljublj Kmet 81 (2) 369ndash387

Snep Robbert Ekko van Ierland E and Paul Opdam 2009 ldquoEnhancing Biodiversityat Business Sites What are the Options and Which of these do Stakeholders Pre-ferrdquo Landscape and Urban Planning 91 (1) 26ndash35

Soliva Reto and Marcel Hunziker 2009 ldquoHow do Biodiversity and Conservation Val-ues Relate to Landscape Preferences A Case Study from the Swiss Alpsrdquo Biodi-versity Conservation 18 (9) 2483ndash2507

Staats Henk Arenda Kieviet and Terry Hartig 2003 ldquoWhere to Recover from Atten-tional Fatigue An Expectancy-Value Analysis of Environmental Preferencerdquo Jour-nal of Environmental Psychology 23 (2) 147ndash157

Sugiyama Takemi and Catherine Ward Thompson 2008 ldquoAssociations betweenCharacteristics of Neighbourhood Open Space and Older Peoplersquos Walkingrdquo Ur-ban Forestry and Urban Greening 7 (1) 41ndash51

Takano T K Nakamura and M Watanabe 2002 ldquoUrban Residential Environmentsand Senior Citizensrsquo Longevity in Megacity Areas The Importance of WalkableGreen Spacesrdquo Journal of Epidemiology and Community Health 56 (12) 913ndash918

Tress Baumlrbel Gunther Tress Arnold van der Valk and Gary Fry eds 2003 Potentialand Limitations of Interdisciplinary and Transdisciplinary Landscape Studies Wa-geningen Delta Series 2


362

Tveit Mari Sundli 2009 ldquoIndicators of Visual Scale as Predictors of Landscape Prefer-ence A Comparison between Groupsrdquo Journal of Environmental Management90 2882ndash2888

Tyrvaumlinen Liisa Kirsi Makinen and Jasper Schipperijn 2007 ldquoTools for Mapping So-cial Values of Urban Woodlands and Other Green Areasrdquo Landscape and UrbanPlanning 79 (1) 5ndash19

Tyrvaumlinen Liisa Harri Silvennoinen and Osmo Kolehmainen 2003 ldquoEcological andAesthetic Values in Urban Forest Managementrdquo Urban Forestry and UrbanGreening 1 135ndash149

Tzoulas Konstantinos Kalevi Korpela Stephen Venn Vesa Yli-Pelkonen AleksandraKazmierczak Jari Niemela and Philip James 2007 ldquoPromoting EcosystemHealth and Human Health in Urban Areas Using Green Infrastructure A Litera-ture Reviewrdquo Landscape and Urban Planning 81 (3) 167ndash178

Ulrich Roger S 1986 ldquoHuman Responses to Vegetation and Landscapesrdquo Landscapeand Urban Planning 13 (1) 29ndash44

Van den Berg Agnes E Terry Hartig and Henk Staats 2007 ldquoPreference for Naturein Urbanized Societies Stress Restoration and the Pursuit of SustainabilityrdquoJournal of Social Issues 63 (1) 79ndash96

Van den Berg Agnes E and Sander L Koole 2006 ldquoNew Wilderness in the Nether-lands An Investigation of Visual Preferences for Nature Development Land-scapesrdquo Landscape and Urban Planning 78 (4) 362ndash372

Van den Berg Agnes E and Charles A J Vlek 1998 ldquoThe Influence of Planned-change Context on the Evaluation of Natural Landscapesrdquo Landscape and UrbanPlanning 43 (1) 1ndash10

Velarde M D G Fry and M Tveit 2007 ldquoHealth Effects of Viewing Landscapes ndashLandscape Types in Environmental Psychologyrdquo Urban Forestry and Urban Green-ing 6 (4) 199ndash212


363

helped to move the discussion on beyond the relative merits of sce-nic as opposed to ecological aesthetics

Research on urban green spaces and human health and well-being has steadily expanded beyond its original focus on landscapepreference and social scientists and public health researchers havebeen studying how various aspects of human health and well-beingare affected by exposure to green spaces (eg Bell et al 2008 Malleret al 2002 Tzoulas et al 2007) While the scope of this research hasbeen diverse the main focus has been on the human side of the equa-tion to understand the benefits and outcomes that green space has forpeople measured at psychological social and physiological levels ofconcern The green side of the equationmdashthe measurement of greenspace qualities and characteristicsmdashhas sometimes also been an im-portant part of this work but many questions remain about the natureof green space as it relates to human health and well-being (Frumkin2001 2006 Velarde et al 2007) What are the key green space char-acteristics that generate desired health and well-being outcomes Dodifferent characteristics of ldquogreenrdquo play differential roles with respectto various human benefits How can an enhanced understanding ofthese characteristics and their beneficial properties be integrated withother contemporary green space agendas including ecological res -toration and the creation of multifunctional green infrastructure

In this paper we take a first step in addressing these questions byexamining how researchers have measured predominantly urbangreen space in the context of human health and well-being with ref-erence to a broad spectrum of urban green spaces but especially themore structurally complex and biodiverse natural environments asso-ciated with ecological restoration Our approach relies on an assess-ment of recent research literature classifying the types of green spacemeasures that are being used and mapping them with measures of hu-man health and well-being also under consideration

As well as mapping the green space measures against humanhealth and wellbeing outcomes we go on to consider how effectivethese measures are in the context of an inter-disciplinary researchcontext Green spacemdashopen land and its vegetative cover1mdashforms thecentral part of urban ecosystems To enhance the function and sus-tainability of urban ecosystems ecologists and land managers arguethat green space must be more than the mown grass and ornamentaltree plantings that typifies managed green space in most cities Butwhile restoration provides a set of principles and practices for increas-ing the ecological values of urban green space those involved in ur-


339








Methods



340







341



342


Code Definition













343


Code Definition












Results

Research Mapping





344


345

Tabl

e 3

R

esea

rch

map

of g

reen

spa

ce b

y hu

man

hea

lth a

nd w

ell-

bein

g m

easu

res

full

stud

y se

t (N

=18

2)

Atti

tude

s

mea

ning

s

Psyc

holo

gica

l Ph

ysic

al

Mea

sure

sPr

efer

ence

and

valu

esbe

nefit

she

alth

Beh

avio

rM

ixed

Oth

erTo

tal

Non

e1

233

13

30

34

Urb

an v

ersu

s na

tura

l1

215

01

10

20

Inve

ntor

y1

03

03

20

9

Des

crip

tive

narr

ativ

e0

123

03

21

21

Are

adi

stan

ce0

21

114

13

22

Bio

phys

ical

144

20

20

224

Hum

an p

erce

ptua

l8

64

21

20

23

Bio

dive

rsity

1014

10

01

329

All

mea

sure

s35

6332

1417

129

182








346





347







348


349

Tabl

e 4

R

esea

rch

map

of g

reen

spa

ce b

y hu

man

hea

lth a

nd w

ell-

bein

g m

easu

res

sub

set o

f inn

ovat

ive

stud

ies

(N=

30)

Atti

tude

s m

eani

ngs

Ps

ycho

logi

cal

Mea

sure

Pref

eren

cean

d va

lues

bene

fits

Oth

erTo

tals

Des

crip

tive

Hea

d an

d M

uir

Nar

rativ

e(2

006)

(1)

1

Bio

phys

ical

Bje

rke

et a

l (2

006)

Han

ds a

nd

Bre

uste

(200

4) (

1)Li

and

Wen

g B

row

n (2

002)

Laf

orte

zza

et a

l (2

007)

(1)

(200

8) T

yrvauml

inen

et a

l (2

003)

V

an d

en B

erg

and

Kool

e (2

006)

(5)

7

Hum

an

Kap

lan

(200

7) (

1)D

e G

root

and

Van

Ko

rpel

a et

al

perc

eptu

alde

n B

orn

(200

3)

(200

8) (

1)Ouml

zgun

er a

nd K

endl

e (2

006)

(2)

4

Bio

dive

rsity

Dra

mst

ad e

t al

(200

1) L

inde

man

n-B

onne

s et

al

(200

7)

Fulle

r et

al

De

la M

aza

Mat

thie

s an

d B

ose

(200

7) L

inde

man

n-H

ur e

t al

(200

9)

(200

7) (

1)et

al

(200

2)

Mat

thie

s et

al

(201

0) N

assa

uer

Gyl

lin a

nd G

rahn

K

inzi

g et

al

(200

4a)

Nas

saue

r (2

004b

) O

de e

t al

(200

5) L

amb

and

(200

5) (

2)(2

009)

Pal

mer

(200

4) P

urce

ll an

d Pu

rcel

l (19

90)

Lee

Lam

b (1

998)

Sol

iva

and

Hun

zike

r et

al

(200

8) J

unke

r (2

009)

(9)

and

Buc

heck

er

(200

8) (

6)18

Tota

ls15

102

330





350





351







352






353





354


Discussion




355





356



Conclusion



357


Acknowledgements




Notes



References




358


















359





















360


















361



















362











363








Methods



340







341



342


Code Definition













343


Code Definition












Results

Research Mapping





344


345

Tabl

e 3

R

esea

rch

map

of g

reen

spa

ce b

y hu

man

hea

lth a

nd w

ell-

bein

g m

easu

res

full

stud

y se

t (N

=18

2)

Atti

tude

s

mea

ning

s

Psyc

holo

gica

l Ph

ysic

al

Mea

sure

sPr

efer

ence

and

valu

esbe

nefit

she

alth

Beh

avio

rM

ixed

Oth

erTo

tal

Non

e1

233

13

30

34

Urb

an v

ersu

s na

tura

l1

215

01

10

20

Inve

ntor

y1

03

03

20

9

Des

crip

tive

narr

ativ

e0

123

03

21

21

Are

adi

stan

ce0

21

114

13

22

Bio

phys

ical

144

20

20

224

Hum

an p

erce

ptua

l8

64

21

20

23

Bio

dive

rsity

1014

10

01

329

All

mea

sure

s35

6332

1417

129

182








346





347







348


349

Tabl

e 4

R

esea

rch

map

of g

reen

spa

ce b

y hu

man

hea

lth a

nd w

ell-

bein

g m

easu

res

sub

set o

f inn

ovat

ive

stud

ies

(N=

30)

Atti

tude

s m

eani

ngs

Ps

ycho

logi

cal

Mea

sure

Pref

eren

cean

d va

lues

bene

fits

Oth

erTo

tals

Des

crip

tive

Hea

d an

d M

uir

Nar

rativ

e(2

006)

(1)

1

Bio

phys

ical

Bje

rke

et a

l (2

006)

Han

ds a

nd

Bre

uste

(200

4) (

1)Li

and

Wen

g B

row

n (2

002)

Laf

orte

zza

et a

l (2

007)

(1)

(200

8) T

yrvauml

inen

et a

l (2

003)

V

an d

en B

erg

and

Kool

e (2

006)

(5)

7

Hum

an

Kap

lan

(200

7) (

1)D

e G

root

and

Van

Ko

rpel

a et

al

perc

eptu

alde

n B

orn

(200

3)

(200

8) (

1)Ouml

zgun

er a

nd K

endl

e (2

006)

(2)

4

Bio

dive

rsity

Dra

mst

ad e

t al

(200

1) L

inde

man

n-B

onne

s et

al

(200

7)

Fulle

r et

al

De

la M

aza

Mat

thie

s an

d B

ose

(200

7) L

inde

man

n-H

ur e

t al

(200

9)

(200

7) (

1)et

al

(200

2)

Mat

thie

s et

al

(201

0) N

assa

uer

Gyl

lin a

nd G

rahn

K

inzi

g et

al

(200

4a)

Nas

saue

r (2

004b

) O

de e

t al

(200

5) L

amb

and

(200

5) (

2)(2

009)

Pal

mer

(200

4) P

urce

ll an

d Pu

rcel

l (19

90)

Lee

Lam

b (1

998)

Sol

iva

and

Hun

zike

r et

al

(200

8) J

unke

r (2

009)

(9)

and

Buc

heck

er

(200

8) (

6)18

Tota

ls15

102

330





350





351







352






353





354


Discussion




355





356



Conclusion



357


Acknowledgements




Notes



References




358


















359





















360


















361



















362











363







341



342


Code Definition













343


Code Definition












Results

Research Mapping





344


345

Tabl

e 3

R

esea

rch

map

of g

reen

spa

ce b

y hu

man

hea

lth a

nd w

ell-

bein

g m

easu

res

full

stud

y se

t (N

=18

2)

Atti

tude

s

mea

ning

s

Psyc

holo

gica

l Ph

ysic

al

Mea

sure

sPr

efer

ence

and

valu

esbe

nefit

she

alth

Beh

avio

rM

ixed

Oth

erTo

tal

Non

e1

233

13

30

34

Urb

an v

ersu

s na

tura

l1

215

01

10

20

Inve

ntor

y1

03

03

20

9

Des

crip

tive

narr

ativ

e0

123

03

21

21

Are

adi

stan

ce0

21

114

13

22

Bio

phys

ical

144

20

20

224

Hum

an p

erce

ptua

l8

64

21

20

23

Bio

dive

rsity

1014

10

01

329

All

mea

sure

s35

6332

1417

129

182








346





347







348


349

Tabl

e 4

R

esea

rch

map

of g

reen

spa

ce b

y hu

man

hea

lth a

nd w

ell-

bein

g m

easu

res

sub

set o

f inn

ovat

ive

stud

ies

(N=

30)

Atti

tude

s m

eani

ngs

Ps

ycho

logi

cal

Mea

sure

Pref

eren

cean

d va

lues

bene

fits

Oth

erTo

tals

Des

crip

tive

Hea

d an

d M

uir

Nar

rativ

e(2

006)

(1)

1

Bio

phys

ical

Bje

rke

et a

l (2

006)

Han

ds a

nd

Bre

uste

(200

4) (

1)Li

and

Wen

g B

row

n (2

002)

Laf

orte

zza

et a

l (2

007)

(1)

(200

8) T

yrvauml

inen

et a

l (2

003)

V

an d

en B

erg

and

Kool

e (2

006)

(5)

7

Hum

an

Kap

lan

(200

7) (

1)D

e G

root

and

Van

Ko

rpel

a et

al

perc

eptu

alde

n B

orn

(200

3)

(200

8) (

1)Ouml

zgun

er a

nd K

endl

e (2

006)

(2)

4

Bio

dive

rsity

Dra

mst

ad e

t al

(200

1) L

inde

man

n-B

onne

s et

al

(200

7)

Fulle

r et

al

De

la M

aza

Mat

thie

s an

d B

ose

(200

7) L

inde

man

n-H

ur e

t al

(200

9)

(200

7) (

1)et

al

(200

2)

Mat

thie

s et

al

(201

0) N

assa

uer

Gyl

lin a

nd G

rahn

K

inzi

g et

al

(200

4a)

Nas

saue

r (2

004b

) O

de e

t al

(200

5) L

amb

and

(200

5) (

2)(2

009)

Pal

mer

(200

4) P

urce

ll an

d Pu

rcel

l (19

90)

Lee

Lam

b (1

998)

Sol

iva

and

Hun

zike

r et

al

(200

8) J

unke

r (2

009)

(9)

and

Buc

heck

er

(200

8) (

6)18

Tota

ls15

102

330





350





351







352






353





354


Discussion




355





356



Conclusion



357


Acknowledgements




Notes



References




358


















359





















360


















361



















362











363



342


Code Definition













343


Code Definition












Results

Research Mapping





344


345

Tabl

e 3

R

esea

rch

map

of g

reen

spa

ce b

y hu

man

hea

lth a

nd w

ell-

bein

g m

easu

res

full

stud

y se

t (N

=18

2)

Atti

tude

s

mea

ning

s

Psyc

holo

gica

l Ph

ysic

al

Mea

sure

sPr

efer

ence

and

valu

esbe

nefit

she

alth

Beh

avio

rM

ixed

Oth

erTo

tal

Non

e1

233

13

30

34

Urb

an v

ersu

s na

tura

l1

215

01

10

20

Inve

ntor

y1

03

03

20

9

Des

crip

tive

narr

ativ

e0

123

03

21

21

Are

adi

stan

ce0

21

114

13

22

Bio

phys

ical

144

20

20

224

Hum

an p

erce

ptua

l8

64

21

20

23

Bio

dive

rsity

1014

10

01

329

All

mea

sure

s35

6332

1417

129

182








346





347







348


349

Tabl

e 4

R

esea

rch

map

of g

reen

spa

ce b

y hu

man

hea

lth a

nd w

ell-

bein

g m

easu

res

sub

set o

f inn

ovat

ive

stud

ies

(N=

30)

Atti

tude

s m

eani

ngs

Ps

ycho

logi

cal

Mea

sure

Pref

eren

cean

d va

lues

bene

fits

Oth

erTo

tals

Des

crip

tive

Hea

d an

d M

uir

Nar

rativ

e(2

006)

(1)

1

Bio

phys

ical

Bje

rke

et a

l (2

006)

Han

ds a

nd

Bre

uste

(200

4) (

1)Li

and

Wen

g B

row

n (2

002)

Laf

orte

zza

et a

l (2

007)

(1)

(200

8) T

yrvauml

inen

et a

l (2

003)

V

an d

en B

erg

and

Kool

e (2

006)

(5)

7

Hum

an

Kap

lan

(200

7) (

1)D

e G

root

and

Van

Ko

rpel

a et

al

perc

eptu

alde

n B

orn

(200

3)

(200

8) (

1)Ouml

zgun

er a

nd K

endl

e (2

006)

(2)

4

Bio

dive

rsity

Dra

mst

ad e

t al

(200

1) L

inde

man

n-B

onne

s et

al

(200

7)

Fulle

r et

al

De

la M

aza

Mat

thie

s an

d B

ose

(200

7) L

inde

man

n-H

ur e

t al

(200

9)

(200

7) (

1)et

al

(200

2)

Mat

thie

s et

al

(201

0) N

assa

uer

Gyl

lin a

nd G

rahn

K

inzi

g et

al

(200

4a)

Nas

saue

r (2

004b

) O

de e

t al

(200

5) L

amb

and

(200

5) (

2)(2

009)

Pal

mer

(200

4) P

urce

ll an

d Pu

rcel

l (19

90)

Lee

Lam

b (1

998)

Sol

iva

and

Hun

zike

r et

al

(200

8) J

unke

r (2

009)

(9)

and

Buc

heck

er

(200

8) (

6)18

Tota

ls15

102

330





350





351







352






353





354


Discussion




355





356



Conclusion



357


Acknowledgements




Notes



References




358


















359





















360


















361



















362











363




343


Code Definition












Results

Research Mapping





344


345

Tabl

e 3

R

esea

rch

map

of g

reen

spa

ce b

y hu

man

hea

lth a

nd w

ell-

bein

g m

easu

res

full

stud

y se

t (N

=18

2)

Atti

tude

s

mea

ning

s

Psyc

holo

gica

l Ph

ysic

al

Mea

sure

sPr

efer

ence

and

valu

esbe

nefit

she

alth

Beh

avio

rM

ixed

Oth

erTo

tal

Non

e1

233

13

30

34

Urb

an v

ersu

s na

tura

l1

215

01

10

20

Inve

ntor

y1

03

03

20

9

Des

crip

tive

narr

ativ

e0

123

03

21

21

Are

adi

stan

ce0

21

114

13

22

Bio

phys

ical

144

20

20

224

Hum

an p

erce

ptua

l8

64

21

20

23

Bio

dive

rsity

1014

10

01

329

All

mea

sure

s35

6332

1417

129

182








346





347







348


349

Tabl

e 4

R

esea

rch

map

of g

reen

spa

ce b

y hu

man

hea

lth a

nd w

ell-

bein

g m

easu

res

sub

set o

f inn

ovat

ive

stud

ies

(N=

30)

Atti

tude

s m

eani

ngs

Ps

ycho

logi

cal

Mea

sure

Pref

eren

cean

d va

lues

bene

fits

Oth

erTo

tals

Des

crip

tive

Hea

d an

d M

uir

Nar

rativ

e(2

006)

(1)

1

Bio

phys

ical

Bje

rke

et a

l (2

006)

Han

ds a

nd

Bre

uste

(200

4) (

1)Li

and

Wen

g B

row

n (2

002)

Laf

orte

zza

et a

l (2

007)

(1)

(200

8) T

yrvauml

inen

et a

l (2

003)

V

an d

en B

erg

and

Kool

e (2

006)

(5)

7

Hum

an

Kap

lan

(200

7) (

1)D

e G

root

and

Van

Ko

rpel

a et

al

perc

eptu

alde

n B

orn

(200

3)

(200

8) (

1)Ouml

zgun

er a

nd K

endl

e (2

006)

(2)

4

Bio

dive

rsity

Dra

mst

ad e

t al

(200

1) L

inde

man

n-B

onne

s et

al

(200

7)

Fulle

r et

al

De

la M

aza

Mat

thie

s an

d B

ose

(200

7) L

inde

man

n-H

ur e

t al

(200

9)

(200

7) (

1)et

al

(200

2)

Mat

thie

s et

al

(201

0) N

assa

uer

Gyl

lin a

nd G

rahn

K

inzi

g et

al

(200

4a)

Nas

saue

r (2

004b

) O

de e

t al

(200

5) L

amb

and

(200

5) (

2)(2

009)

Pal

mer

(200

4) P

urce

ll an

d Pu

rcel

l (19

90)

Lee

Lam

b (1

998)

Sol

iva

and

Hun

zike

r et

al

(200

8) J

unke

r (2

009)

(9)

and

Buc

heck

er

(200

8) (

6)18

Tota

ls15

102

330





350





351







352






353





354


Discussion




355





356



Conclusion



357


Acknowledgements




Notes



References




358


















359





















360


















361



















362











363



Results

Research Mapping





344


345

Tabl

e 3

R

esea

rch

map

of g

reen

spa

ce b

y hu

man

hea

lth a

nd w

ell-

bein

g m

easu

res

full

stud

y se

t (N

=18

2)

Atti

tude

s

mea

ning

s

Psyc

holo

gica

l Ph

ysic

al

Mea

sure

sPr

efer

ence

and

valu

esbe

nefit

she

alth

Beh

avio

rM

ixed

Oth

erTo

tal

Non

e1

233

13

30

34

Urb

an v

ersu

s na

tura

l1

215

01

10

20

Inve

ntor

y1

03

03

20

9

Des

crip

tive

narr

ativ

e0

123

03

21

21

Are

adi

stan

ce0

21

114

13

22

Bio

phys

ical

144

20

20

224

Hum

an p

erce

ptua

l8

64

21

20

23

Bio

dive

rsity

1014

10

01

329

All

mea

sure

s35

6332

1417

129

182








346





347







348


349

Tabl

e 4

R

esea

rch

map

of g

reen

spa

ce b

y hu

man

hea

lth a

nd w

ell-

bein

g m

easu

res

sub

set o

f inn

ovat

ive

stud

ies

(N=

30)

Atti

tude

s m

eani

ngs

Ps

ycho

logi

cal

Mea

sure

Pref

eren

cean

d va

lues

bene

fits

Oth

erTo

tals

Des

crip

tive

Hea

d an

d M

uir

Nar

rativ

e(2

006)

(1)

1

Bio

phys

ical

Bje

rke

et a

l (2

006)

Han

ds a

nd

Bre

uste

(200

4) (

1)Li

and

Wen

g B

row

n (2

002)

Laf

orte

zza

et a

l (2

007)

(1)

(200

8) T

yrvauml

inen

et a

l (2

003)

V

an d

en B

erg

and

Kool

e (2

006)

(5)

7

Hum

an

Kap

lan

(200

7) (

1)D

e G

root

and

Van

Ko

rpel

a et

al

perc

eptu

alde

n B

orn

(200

3)

(200

8) (

1)Ouml

zgun

er a

nd K

endl

e (2

006)

(2)

4

Bio

dive

rsity

Dra

mst

ad e

t al

(200

1) L

inde

man

n-B

onne

s et

al

(200

7)

Fulle

r et

al

De

la M

aza

Mat

thie

s an

d B

ose

(200

7) L

inde

man

n-H

ur e

t al

(200

9)

(200

7) (

1)et

al

(200

2)

Mat

thie

s et

al

(201

0) N

assa

uer

Gyl

lin a

nd G

rahn

K

inzi

g et

al

(200

4a)

Nas

saue

r (2

004b

) O

de e

t al

(200

5) L

amb

and

(200

5) (

2)(2

009)

Pal

mer

(200

4) P

urce

ll an

d Pu

rcel

l (19

90)

Lee

Lam

b (1

998)

Sol

iva

and

Hun

zike

r et

al

(200

8) J

unke

r (2

009)

(9)

and

Buc

heck

er

(200

8) (

6)18

Tota

ls15

102

330





350





351







352






353





354


Discussion




355





356



Conclusion



357


Acknowledgements




Notes



References




358


















359





















360


















361



















362











363


345

Tabl

e 3

R

esea

rch

map

of g

reen

spa

ce b

y hu

man

hea

lth a

nd w

ell-

bein

g m

easu

res

full

stud

y se

t (N

=18

2)

Atti

tude

s

mea

ning

s

Psyc

holo

gica

l Ph

ysic

al

Mea

sure

sPr

efer

ence

and

valu

esbe

nefit

she

alth

Beh

avio

rM

ixed

Oth

erTo

tal

Non

e1

233

13

30

34

Urb

an v

ersu

s na

tura

l1

215

01

10

20

Inve

ntor

y1

03

03

20

9

Des

crip

tive

narr

ativ

e0

123

03

21

21

Are

adi

stan

ce0

21

114

13

22

Bio

phys

ical

144

20

20

224

Hum

an p

erce

ptua

l8

64

21

20

23

Bio

dive

rsity

1014

10

01

329

All

mea

sure

s35

6332

1417

129

182








346





347







348


349

Tabl

e 4

R

esea

rch

map

of g

reen

spa

ce b

y hu

man

hea

lth a

nd w

ell-

bein

g m

easu

res

sub

set o

f inn

ovat

ive

stud

ies

(N=

30)

Atti

tude

s m

eani

ngs

Ps

ycho

logi

cal

Mea

sure

Pref

eren

cean

d va

lues

bene

fits

Oth

erTo

tals

Des

crip

tive

Hea

d an

d M

uir

Nar

rativ

e(2

006)

(1)

1

Bio

phys

ical

Bje

rke

et a

l (2

006)

Han

ds a

nd

Bre

uste

(200

4) (

1)Li

and

Wen

g B

row

n (2

002)

Laf

orte

zza

et a

l (2

007)

(1)

(200

8) T

yrvauml

inen

et a

l (2

003)

V

an d

en B

erg

and

Kool

e (2

006)

(5)

7

Hum

an

Kap

lan

(200

7) (

1)D

e G

root

and

Van

Ko

rpel

a et

al

perc

eptu

alde

n B

orn

(200

3)

(200

8) (

1)Ouml

zgun

er a

nd K

endl

e (2

006)

(2)

4

Bio

dive

rsity

Dra

mst

ad e

t al

(200

1) L

inde

man

n-B

onne

s et

al

(200

7)

Fulle

r et

al

De

la M

aza

Mat

thie

s an

d B

ose

(200

7) L

inde

man

n-H

ur e

t al

(200

9)

(200

7) (

1)et

al

(200

2)

Mat

thie

s et

al

(201

0) N

assa

uer

Gyl

lin a

nd G

rahn

K

inzi

g et

al

(200

4a)

Nas

saue

r (2

004b

) O

de e

t al

(200

5) L

amb

and

(200

5) (

2)(2

009)

Pal

mer

(200

4) P

urce

ll an

d Pu

rcel

l (19

90)

Lee

Lam

b (1

998)

Sol

iva

and

Hun

zike

r et

al

(200

8) J

unke

r (2

009)

(9)

and

Buc

heck

er

(200

8) (

6)18

Tota

ls15

102

330





350





351







352






353





354


Discussion




355





356



Conclusion



357


Acknowledgements




Notes



References




358


















359





















360


















361



















362











363








346





347







348


349

Tabl

e 4

R

esea

rch

map

of g

reen

spa

ce b

y hu

man

hea

lth a

nd w

ell-

bein

g m

easu

res

sub

set o

f inn

ovat

ive

stud

ies

(N=

30)

Atti

tude

s m

eani

ngs

Ps

ycho

logi

cal

Mea

sure

Pref

eren

cean

d va

lues

bene

fits

Oth

erTo

tals

Des

crip

tive

Hea

d an

d M

uir

Nar

rativ

e(2

006)

(1)

1

Bio

phys

ical

Bje

rke

et a

l (2

006)

Han

ds a

nd

Bre

uste

(200

4) (

1)Li

and

Wen

g B

row

n (2

002)

Laf

orte

zza

et a

l (2

007)

(1)

(200

8) T

yrvauml

inen

et a

l (2

003)

V

an d

en B

erg

and

Kool

e (2

006)

(5)

7

Hum

an

Kap

lan

(200

7) (

1)D

e G

root

and

Van

Ko

rpel

a et

al

perc

eptu

alde

n B

orn

(200

3)

(200

8) (

1)Ouml

zgun

er a

nd K

endl

e (2

006)

(2)

4

Bio

dive

rsity

Dra

mst

ad e

t al

(200

1) L

inde

man

n-B

onne

s et

al

(200

7)

Fulle

r et

al

De

la M

aza

Mat

thie

s an

d B

ose

(200

7) L

inde

man

n-H

ur e

t al

(200

9)

(200

7) (

1)et

al

(200

2)

Mat

thie

s et

al

(201

0) N

assa

uer

Gyl

lin a

nd G

rahn

K

inzi

g et

al

(200

4a)

Nas

saue

r (2

004b

) O

de e

t al

(200

5) L

amb

and

(200

5) (

2)(2

009)

Pal

mer

(200

4) P

urce

ll an

d Pu

rcel

l (19

90)

Lee

Lam

b (1

998)

Sol

iva

and

Hun

zike

r et

al

(200

8) J

unke

r (2

009)

(9)

and

Buc

heck

er

(200

8) (

6)18

Tota

ls15

102

330





350





351







352






353





354


Discussion




355





356



Conclusion



357


Acknowledgements




Notes



References




358


















359





















360


















361



















362











363





347







348


349

Tabl

e 4

R

esea

rch

map

of g

reen

spa

ce b

y hu

man

hea

lth a

nd w

ell-

bein

g m

easu

res

sub

set o

f inn

ovat

ive

stud

ies

(N=

30)

Atti

tude

s m

eani

ngs

Ps

ycho

logi

cal

Mea

sure

Pref

eren

cean

d va

lues

bene

fits

Oth

erTo

tals

Des

crip

tive

Hea

d an

d M

uir

Nar

rativ

e(2

006)

(1)

1

Bio

phys

ical

Bje

rke

et a

l (2

006)

Han

ds a

nd

Bre

uste

(200

4) (

1)Li

and

Wen

g B

row

n (2

002)

Laf

orte

zza

et a

l (2

007)

(1)

(200

8) T

yrvauml

inen

et a

l (2

003)

V

an d

en B

erg

and

Kool

e (2

006)

(5)

7

Hum

an

Kap

lan

(200

7) (

1)D

e G

root

and

Van

Ko

rpel

a et

al

perc

eptu

alde

n B

orn

(200

3)

(200

8) (

1)Ouml

zgun

er a

nd K

endl

e (2

006)

(2)

4

Bio

dive

rsity

Dra

mst

ad e

t al

(200

1) L

inde

man

n-B

onne

s et

al

(200

7)

Fulle

r et

al

De

la M

aza

Mat

thie

s an

d B

ose

(200

7) L

inde

man

n-H

ur e

t al

(200

9)

(200

7) (

1)et

al

(200

2)

Mat

thie

s et

al

(201

0) N

assa

uer

Gyl

lin a

nd G

rahn

K

inzi

g et

al

(200

4a)

Nas

saue

r (2

004b

) O

de e

t al

(200

5) L

amb

and

(200

5) (

2)(2

009)

Pal

mer

(200

4) P

urce

ll an

d Pu

rcel

l (19

90)

Lee

Lam

b (1

998)

Sol

iva

and

Hun

zike

r et

al

(200

8) J

unke

r (2

009)

(9)

and

Buc

heck

er

(200

8) (

6)18

Tota

ls15

102

330





350





351







352






353





354


Discussion




355





356



Conclusion



357


Acknowledgements




Notes



References




358


















359





















360


















361



















362











363







348


349

Tabl

e 4

R

esea

rch

map

of g

reen

spa

ce b

y hu

man

hea

lth a

nd w

ell-

bein

g m

easu

res

sub

set o

f inn

ovat

ive

stud

ies

(N=

30)

Atti

tude

s m

eani

ngs

Ps

ycho

logi

cal

Mea

sure

Pref

eren

cean

d va

lues

bene

fits

Oth

erTo

tals

Des

crip

tive

Hea

d an

d M

uir

Nar

rativ

e(2

006)

(1)

1

Bio

phys

ical

Bje

rke

et a

l (2

006)

Han

ds a

nd

Bre

uste

(200

4) (

1)Li

and

Wen

g B

row

n (2

002)

Laf

orte

zza

et a

l (2

007)

(1)

(200

8) T

yrvauml

inen

et a

l (2

003)

V

an d

en B

erg

and

Kool

e (2

006)

(5)

7

Hum

an

Kap

lan

(200

7) (

1)D

e G

root

and

Van

Ko

rpel

a et

al

perc

eptu

alde

n B

orn

(200

3)

(200

8) (

1)Ouml

zgun

er a

nd K

endl

e (2

006)

(2)

4

Bio

dive

rsity

Dra

mst

ad e

t al

(200

1) L

inde

man

n-B

onne

s et

al

(200

7)

Fulle

r et

al

De

la M

aza

Mat

thie

s an

d B

ose

(200

7) L

inde

man

n-H

ur e

t al

(200

9)

(200

7) (

1)et

al

(200

2)

Mat

thie

s et

al

(201

0) N

assa

uer

Gyl

lin a

nd G

rahn

K

inzi

g et

al

(200

4a)

Nas

saue

r (2

004b

) O

de e

t al

(200

5) L

amb

and

(200

5) (

2)(2

009)

Pal

mer

(200

4) P

urce

ll an

d Pu

rcel

l (19

90)

Lee

Lam

b (1

998)

Sol

iva

and

Hun

zike

r et

al

(200

8) J

unke

r (2

009)

(9)

and

Buc

heck

er

(200

8) (

6)18

Tota

ls15

102

330





350





351







352






353





354


Discussion




355





356



Conclusion



357


Acknowledgements




Notes



References




358


















359





















360


















361



















362











363


349

Tabl

e 4

R

esea

rch

map

of g

reen

spa

ce b

y hu

man

hea

lth a

nd w

ell-

bein

g m

easu

res

sub

set o

f inn

ovat

ive

stud

ies

(N=

30)

Atti

tude

s m

eani

ngs

Ps

ycho

logi

cal

Mea

sure

Pref

eren

cean

d va

lues

bene

fits

Oth

erTo

tals

Des

crip

tive

Hea

d an

d M

uir

Nar

rativ

e(2

006)

(1)

1

Bio

phys

ical

Bje

rke

et a

l (2

006)

Han

ds a

nd

Bre

uste

(200

4) (

1)Li

and

Wen

g B

row

n (2

002)

Laf

orte

zza

et a

l (2

007)

(1)

(200

8) T

yrvauml

inen

et a

l (2

003)

V

an d

en B

erg

and

Kool

e (2

006)

(5)

7

Hum

an

Kap

lan

(200

7) (

1)D

e G

root

and

Van

Ko

rpel

a et

al

perc

eptu

alde

n B

orn

(200

3)

(200

8) (

1)Ouml

zgun

er a

nd K

endl

e (2

006)

(2)

4

Bio

dive

rsity

Dra

mst

ad e

t al

(200

1) L

inde

man

n-B

onne

s et

al

(200

7)

Fulle

r et

al

De

la M

aza

Mat

thie

s an

d B

ose

(200

7) L

inde

man

n-H

ur e

t al

(200

9)

(200

7) (

1)et

al

(200

2)

Mat

thie

s et

al

(201

0) N

assa

uer

Gyl

lin a

nd G

rahn

K

inzi

g et

al

(200

4a)

Nas

saue

r (2

004b

) O

de e

t al

(200

5) L

amb

and

(200

5) (

2)(2

009)

Pal

mer

(200

4) P

urce

ll an

d Pu

rcel

l (19

90)

Lee

Lam

b (1

998)

Sol

iva

and

Hun

zike

r et

al

(200

8) J

unke

r (2

009)

(9)

and

Buc

heck

er

(200

8) (

6)18

Tota

ls15

102

330





350





351







352






353





354


Discussion




355





356



Conclusion



357


Acknowledgements




Notes



References




358


















359





















360


















361



















362











363





350





351







352






353





354


Discussion




355





356



Conclusion



357


Acknowledgements




Notes



References




358


















359





















360


















361



















362











363





351







352






353





354


Discussion




355





356



Conclusion



357


Acknowledgements




Notes



References




358


















359





















360


















361



















362











363







352






353





354


Discussion




355





356



Conclusion



357


Acknowledgements




Notes



References




358


















359





















360


















361



















362











363






353





354


Discussion




355





356



Conclusion



357


Acknowledgements




Notes



References




358


















359





















360


















361



















362











363





354


Discussion




355





356



Conclusion



357


Acknowledgements




Notes



References




358


















359





















360


















361



















362











363


Discussion




355





356



Conclusion



357


Acknowledgements




Notes



References




358


















359





















360


















361



















362











363





356



Conclusion



357


Acknowledgements




Notes



References




358


















359





















360


















361



















362











363



Conclusion



357


Acknowledgements




Notes



References




358


















359





















360


















361



















362











363


Acknowledgements




Notes



References




358


















359





















360


















361



















362











363


















359





















360


















361



















362











363





















360


















361



















362











363


















361



















362











363



















362











363











363

Shades of green: Measuring the ecology of urban green space in … · 2010-12-25 · Shades of...

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Transcript of Shades of green: Measuring the ecology of urban green space in … · 2010-12-25 · Shades of...