MEETING AGENDA
Estimating Greenspace Exposure and Benefits
for Cumulative Risk Assessment Applications
4-5 May 2015
Room AG-30, U.S. Environmental Protection Agency
26 Martin Luther King Drive West, Cincinnati, OH 45220
Meeting Purpose
The role of ecosystem services, including access and exposure to greenspace, may have
beneficial effects on population health. There is some uncertainty as to which mechanisms (e.g.,
social connectedness, psychological well-being from exposure to nature) associations between
greenspace and health outcomes are acting through. Given that greenspace may be a marker of
non-chemical stressors or an exposure modifier, it is a good candidate to examine in a
cumulative risk context, which could help determine its use and effectiveness as an ecosystem
service and potential risk management practice. To this end, EPA's National Center for
Environmental Assessment in Cincinnati is hosting a technical meeting to evaluate various
measures and roles of greenspace from a cumulative risk assessment (CRA) perspective. The
technical group will review existing greenspace exposure measures and methods used across
different fields of study, with a focus on which measures are useful for different health outcomes
and cumulative risk applications. The meeting discussion and outputs will inform methods for
evaluating environmental health risks and benefits associated with greenspace (GS).
Driving Questions
• How can existing cumulative risk assessment frameworks consider greenspace as it relates to
exposure assessment for human health?
• How is greenspace conceptualized across disciplines?
• What health outcomes are relevant to greenspace prevalence and access?
• Which evidence-based measures of greenspace provide the most applicable, reliable, and
replicable estimates for greenspace exposure in urban settings?
• What are the specific mechanisms for certain health benefits and can these be used to inform
biologic plausibility of reported associations with greenspace?
Key Objective
Identify and qualify approaches and appropriate data sources for measuring greenspace and
evaluating the distribution of health benefits (i.e., across socioeconomic status, sensitive
populations), including risk reductions, from a cumulative risk assessment perspective, with
attention to bias and uncertainty in reporting and measurement.
1. Evaluate key pathways and methods for estimating greenspace exposure.
2. Evaluate key health outcomes and/or benefits and related methods and data sources for
quantifying health outcomes related to greenspace.
3. Determine appropriate applications for greenspace measures, outcomes, and benefits within
existing cumulative risk assessment frameworks.
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APPENDIX B:
MEETING AGENDA AND TECHNICAL PRESENTATIONS
The meeting agenda material shared with participants is presented in the first section of
this report. The technical presentations provided by the invited experts follow the agenda, in the
order listed.
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Technical Fields and Focus Areas
Urban tree cover Air quality Reproductive health
Parks and recreation Physical activity Respiratory health
Built environment/neighborhood planning Socioeconomic disparities (environmental and/or health) Cardiovascular disease
Regional planning Exposure and risk assessment Obesity and diabetes
Ecosystem services Psychological health
Schedule at a Glance
Sun 3 May
Optional Activities (meet in hotel lobby for each, at 2:45 pm for Greenspace Tour 1)
5:00-5:30pm Greenspace Tour 2
6:00- 7:00 pm Social hour
7:00 pm Dinner option
Mon 4 May
Greenspace Metrics and Exposure Assessment
Tues 5 May
Greenspace and Health
9:00-9:15
Welcome and meeting overview
9:00-9:45
Respiratory effects
9:15-9:30
Group process; shared data sets for GS metrics
9:45-10:25
Reproductive effects
9:30-10:20
Exposure assessment approaches
Break
Break
10:35-11:15
Obesity and physical activity
10:30-11:10
Tree cover measurements
11:15-12:00
Cardiovascular disease and mortality
11:10-12:00
Access to greenness
Lunch
Lunch
1:00-1:40
Neurological/neurodevelopmental effects
1:00-1:40
Built enviromnent
1:40-2:40
Psychosocial effects
1:40-2:30
Design and enviromnental psychology
2:40-3:20
Attention restoration/cognitive effects
2:30-3:20
Specific populations, exposure considerations
Break
Break
3:30-4:10
Economic and community benefits
3:30-4:20
Exposure metrics, links to health
4:10-4:40
Specific populations, health considerations
4:20-5:10
Key points for exposure
4:40-5:00
Refine conceptual diagrams of GS/CRA
5:10-5:30
Wrap-up of Day 1, review of plan for Day 2
5:00-5:30
Key points for health; meeting wrap-up
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II
Mon 4 May
Greenspace Metrics and Exposure Assessment
• How is greenspace conceptualized across disciplines? What is being measured, and what needs to be measured for accurate assessments?
• Which evidence-based measures of greenspace provide the most applicable, reliable, and replicable estimates for greenspace exposure in urban settings?
• What are accepted methods for quantifying exposure to greenspace?
• Considerations of multiple routes of greenspace exposure
8:30-9:00
Arrival
9:00-9:15
Welcome and meeting overview
R. Gernes
9:15-9:30
Group process; shared data sets for greenspace metrics
T. Miller
9:30-10:20
Exposure assessment approaches (U.S. and international)
L.Jackson M. Nieuwenhuijsen M. A. van den Bosch
10:20-10:30
Break
10:30-11:10
Tree cover measurements (NDVI, regional-local UTC)
G. Donovan P. Hystad
11:10-12:00
Access to greenness
R. Mitchell M. Kondo M. A. van den Bosch
12:00-1:00
Lunch
1:00-1:40
Built environment
P. Hystad Y. Michael
1:40-2:30
Design and environmental psychology
J. Africa R. Mitchell W. Sullivan
2:30-3:20
Specific populations, exposure considerations
R. Mitchell A. Hipp Y. Michael
3:20-3:30
Break
3:30-4:20
Exposure metrics, links to health (attention restoration example)
W. Sullivan Y. Michael
4:20-5:10
Key points for exposure
T. Miller
5:10-5:30
Wrap-up of Day 1, review plan for Day 2
T. Miller R. Gernes
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Tues 5 May
Greenspace and Health
• How can existing CR4 frameworks consider greenspace as it relates to health?
• What health outcomes are relevant to greenspace prevalence and access?
• What are the specific mechanisms for certain health benefits, and can these be used to inform biologic plausibility of reported associations with greenspace?
• Considerations of community' and individual level outcomes.
8:30-9:00
Arrival
9:00-9:45
Respiratory effects
P. Ryan
G. Donovan
9:45-10:25
Reproductive effects
P. Hystad
G. Donovan Y. Michael
10:25-10:35
Break
10:35-11:15
Obesity and physical activity
M. A. van den Bosch
A. Hipp
11:15-12:00
Cardiovascular disease and mortality
P. Hystad
M. Nieuwenhuijsen
12:00-1:00
Lunch
1:00-1:40
Neurological/neurodevelopmental effects
M. Nieuwenhuijsen
P. Ryan
1:40-2:40
Psychosocial effects
M. Kondo
M. A. van den Bosch J. Africa
2:40-3:20
Attention restoration/cognition effects
A. Hipp
L. Jackson
3:20-3:30
Break
3:30-4:10
Economic and community benefits
M. Kondo
G. Donovan
4:10-4:40
Specific populations, health considerations
R. Mitchell
P. Ryan
4:40-5:00
Refine conceptual diagrams of greenspace/CRA
T. Miller
5:00-5:30
Key points for health; meeting wrap-up
T. Miller
R. Gernes
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TECHNICAL PRESENTATIONS
Day 1 -Mon 4 May
Greenspace Metrics and Exposure Assessment
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Day 1-Exposure assessment approaches (U.S. and international)
EnviroAtlas is...
An online decision support tool for viewing, analysing, and
downloading geospatial data related to ecosystem services
> Maps, data, tools and information
about the supply, demand,
drivers, and social benefits of
ecosystem services
> Population and climate scenarios
> Reference data (e.g., boundaries,
land cover, soils, hydrography,
impaired water bodies, wetlands,
demographics)
> Analytic and interpretive tools
> Free & open access
Version 1 Released May, 2014
International "Ecosystem Services" Framework
ECOSYSTEM SERVICES
Provisioning
FOOD
FRESH WATER
WOOD AND FIBER
Fua
Supporting
NUTRIENT CYCLING
SOIL FORMATION
PRIMAHY PRODUCTION
Regulating
CLIMATE REGULATION
FLOOO REGULATION
DISEASE REGULATION
WATER PURIFICATION
AESTHETIC
SPtRfTUAL
EDUCATIONAL
RECREATIONAL
CONSTITUENTS OF WELL-BEING
Security
PERSONAL SAFETY
SECURE RESOURCE ACCESS
SECURITY FROM DISASTERS
UFE ON EARTH - BIODIVERSITY
ARROW S COLOR Al f OV. WIDTH
Potential for mediation by Intensity of linkages between ecosystem
socioeconomic factors services and human well-being
Basic material
(or good life
ADEQUATE LIVELIHOODS
SUFFICIENT NUTRITIOUS FOOD
SHELTER
ACCESS TO GOOOS
Health
STRENGTH
FEELING WELL
ACCESS TO CLEAN AIR
AND WATER
Good social relations
SOCIAL COHESION
MUTUAL RESPECT
ABILITY TO HELP OTHERS
Freedom
of choice
and action
OPPORTUNITY TO BE
ABLE TO ACHIEVE
WHAT AN IN DIVIDUAL
VALUES DOING
AND BEING
Source Mtanraum Ecosystem Assessment
: Medium
I Slrong
Related concepts:
"benefits from nature," "green infrastructure," "our life-support system,"
"positive environmental exposures"
Ecosystem
Services
Drivers of change
Developed through cooperative effort
among multiple Federal agencies,
universities, and other organizations
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Day 1-Exposure assessment approaches (U.S. and international)
Ecosystem Services & Health:
Unrealized Assets = Unintended Consequences
Approach: Demonstrate Multiple
Benefits of Green Infrastructure,
• Clean air
• Clean & plentiful water
• Natural hazard mitigation
• Climate stabilization
• Recreation, culture & aesthetics
• Food, fiber & materials
• Biodiversity conservation
...and How They Relate to Human
Health & Well-Being
> Air and water pollutants removed by
neighborhood tree cover
> Homes and schools near busy
roadways
> Extreme heat events
> Opportunities for physical exercise,
social engagement, outdoor
experience, and play
> Distributions of vulnerable populations
How Does EnviroAtlas Conceptualize Green Space
as Ecosystem Services? (Goods not addressed today)
Buffers for Natural and Anthropogenic Hazards
¦ Extreme heat mitigation
¦ Stormwater runoff absorption
¦ Polluted runoff filtration
¦ Storm energy dissipation
¦ Air pollutant reduction
Opportunities for Healthful Behaviors
¦ Engagement with nature
¦ Social interaction
¦ Physical activity
Supporting Functions
¦ Carbon sequestration and storage
¦ Soil retention
¦ Wildlife habitat provision
Ecosystem dis-services are
not currently emphasized
in EnviroAtlas
- Pests
- Disease
- Physical dangers
- Pollen
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Day 1-Exposure assessment approaches (U.S. and international)
Map Legend
p"Po«tland. ME Omogtapfuct
Population wim income below twice
tr»e US poverty level
o 3-180
O 181-291
O »2-500
O »'•'«<>
Natural Hazard Mitigation ¦ PorUand. ME
** raoe reducfron in nighftme
amb>ent temperature (Celsius)
00-03
B 0.3-0.4
¦ 0.4-06
B 0.6-0.7
¦ 0.7-10
EnviroAtlas is Multi-Scaled
300+ map layers available online
National: Wall-to-wall coverage for
coterminous US; summarized by
~90,000 drainage basins
(12-digit HUCs). 160+ data layers
Community: High resolution component
for 50 populated places; summarized by
US census block group. 100+ data layers
Pictured: Greater Portland, ME
http://enviroatlas.epa.gov/
op Map Legend
^Recreation, Culture, and Aesthetics
Percent medium natural areas
0-81 (500-25,OOOac)
¦ 82-67 2
¦ 67 3-90.5
¦ 905-99.2
¦ 992-100
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Day 1-Exposure assessment approaches (U.S. and international)
"Clean and Plentiful Water
Data not shown
Percent natural land cover in oufler
0-54
P 54-80
B 80-94
¦ 94-99
¦ 99-100
"Biophysical Data
Connectivity. Natural Land Cover
2006, Water Ignored
| | Background
[~~| Branch
¦ Edge
m Perforation
| islet
i ¦ c°™
g| Bridge
I m Bridge in Edge
B Bridge in Perforation
} ~ Loop
I | Loop In Edge
m Loop in Perforation
[~| Missing
'Natural Hazard Mitigation
Percent forest on wet areas
(wetness index » 550)
0-0.1
¦ 01-39
1 3.9-194
B 19 4-439
B 43 9-100
Community Information to Assist Decision-Making
e.g., health interventions, public infrastructure, social equity
Estimated reductions in adverse
respiratory health eventsdue to
ambient air filtration by trees
m ' V ^
Mr f ;i i iMB
Potential to improve school
performance through cognitive
restoration & stress reduction
activity, engagement with nature,
& social interaction
Pictured: Greater Durham-Chapel Hill, NC
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Day 1-Exposure assessment approaches (U.S. and international)
Population
Precise maps of tree cover
along local roads & streams
Heat maps
All Data are Downloadable & Accessible via Web Services
(incl. fact sheets for general users and technical metadata)
Downscaled (30-meter) U.S. Census
population grid
Indicators of Public Health and Well-Being
Types of EnviroAtlas-Community Metrics
• Green space, tree cover, & impervious surface measures
• Walking distance to park entrances
• Air pollutants removed by tree cover
• Health & economic benefits of air pollutants removed
• Reduced runoff, water pollution from tree cover
• Temperature reduction, carbon storage by tree cover
• Presence/absence of tree cover along walkable & major roads
• Population living along busy roads
• Residences with limited window views of trees
• Schools & day care centers with limited views of green space
• Intersection density, housing & employment metrics
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Day 1-Exposure assessment approaches (U.S. and international)
Legend
2013 Communities
Seattle, WA
Portland, OR
Portland, ME
Fresno, GA
St. Louis, MO
Memphis, TN
Durham, NC
Birmingham, AL
Graphics Bsedtrptrniiuo." Cowng>il©28tJ£»* Aiin^h
sew* b* twa*4. ueik tiaw-
EnviroAtlas Communities
(Planned through 2015)
New Bedford, MA
* New Haven, CT
f Green Bay, Wl
. . Minneapolis/St. Paul, MN
J 1 1 ioi6| l
Salt L^ke City, UT Woodbine, IA Milwaukee, Wl Pittsburgh PA * New York,"NY
"• ¦ ,A 1 . Paterson, NJ
Des Moines, IA n-if *
/ - | Baltimore, MD
4HIAaf.^M^Penver co \ t /
Austin, TX
I 2014 Communities
2015 Proposed Communities
s
LandScope
ANRCS © SUSGS
The Eco-Health Relationship Browser
4 ecosystems:
• Forests
• Urban Ecosystems
• Wetlands
• Agro-Ecosystems
6 Ecosystem Services:
Health promotional services
• Aesthetics & Engagement with Nat re
• Recreation & Physical Activity
Buffering services
• Clean Air
• Clean Water
• Heat Hazard Mitigation
• Water Hazard Mitigation
Incl. extensive bibliography (n ~ 300)
30+health outcomes:
• Asthma
•ADHD
• Cancers
• Cardiovascular diseases
• Heat stroke
• Healing
• Low birth weight
• Obesity
• Social relations
• Stress
... many more
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Day 1-Exposure assessment approaches (U.S. and international)
Landcover Composition in Residential Buffers
as Indicators of Healthful Exposures
Radius Indicates potential for Mechanism(s)
50m Window views and Engagement w/natural features;
peridomestic activities Social interaction
500m Walkable neighborhood Promotion of physical activity;
Engagement w/ natural features;
Social interaction
1-3 km Local green destinations Promotion of physical activity;
Engagement w/ natural features;
Social interaction
Landcover Composition by City Block
50m moving windows Green views along Promotion of physical activity;
along road centerlines walkable roads Engagement w/natural features;
Social interaction
Landcover Composition in Residential Buffers
as Indicators of Effect Modification
Radius Indicates potential for Mechanism(s)
50m Window views and Mitigation of extreme heat, air
peridomestic activities pollution, noise, night light
300m Near-roadway buffers Absorption/dilution of vehicular
pollutants
400 - Walkable neighborhood Mitigation of extreme heat, air
1000m pollution
Landcover Composition by City Block
8.5m width pedestrian zones Shade along walkable Mitigation of extreme
along road edges roads heat
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Day 1-Exposure assessment approaches (U.S. and international)
Ecosystem Services Deliver "Co-Benefits/'
Facilitate Systems-Level Solutions
%
I'RHANA
I > Tf*» Prn(p«m
Urban Tree Benefit
Provide
habitat* for
wildlife
property
values
'rovtde « «en«
of place And
community
y Provide ^
shade and 1
reduce ambient I
k temperature A
Lower levrL
of noiae
and dust
Encourages
walking
Produce
Reduces
oxygen and
reduce carbon
k dtoxide A
W Umvratf Ave
WfU* , _
Reduces
• — * ¦ surface Hood
Lwalrr ruii-ollj
Evaluating Cumulative Benefits
under Alternate Tree-Planting Scenarios
Use Case by City of Durham, IMC
90%
Maximize: Roads Stormwater Optimize A Optimize B Vulnerability Walkability
Strategy scenarios
¦ Roads ¦ Vulnerability ¦ Walkability ¦Stormwater
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Day 1-Exposure assessment approaches (U.S. and international)
The Parma Commitments, WHO 2010
"We aim to provide each child by 2020 with
access to healthy and safe environments and
settings of daily life in which they can walk
and cycle to kindergartens and schools, and
to green spaces in which to play and
undertake physical activity."
Urban Green Space Indicator
• Define urban green spaces
• Identify GIS-definition
• Specify population distribution data in GIS and specificity
requirements (census or individual data)
• GIS-analysis, software, script
2
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Day 1-Exposure assessment approaches (U.S. and international)
European Environment Agency (EEA):
http://www.eea.europa.eu/data-and-maps/data/urban-atlas
Urban Atlas
Satellite data
Navigation data
Topographic maps
Field observations
Soil sealing
Coordinate system:
LAEA/ETRS89
(EU standard)
Land use data from Urban Atlas
http://www.eea.europa.eu/data-and-maps/data/urban-atlas
). AnlfcUlMMfKI
"Green Urban Areas":
Urban Atlas: 1.4.1.
Vector code: 14100
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Day 1-Exposure assessment approaches (U.S. and international)
Definition of urban green in Urban Atlas
Included are:
• MinMU 0.25 ha, Minimum width: 10 m
• Recreational use such as gardens, zoos, parks, castle parks.
• Suburban natural areas that have become and are managed as urban parks.
• Forests or green areas extending from the surroundings into urban areas
• Urban areas when at least two sides are bordered by green urban areas and
structures, and traces of recreational use are visible.
Not included are:
• Private gardens within housing areas ->class 1.1;
• Cemeteries ->class 1.2.1;
• Buildings within parks, such as castles or museums ->class 1.2.1;
• Patches of natural vegetation or agricultural areas enclosed by built-up areas
without being managed as green urban areas ->class 1
Case study Malmo
Sweden's 3rd city (n= 306 074)
Green space unevenly distributed and availability below Swedish average
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Day 1-Exposure assessment approaches (U.S. and international)
Population data
• Local, Malmo municipality
• Individual and aggregated (looxioom grids)
European population data:
Population density disaggregated dataset (EEA). Eurostat (2001) och
CORINE (2000)
Buffer analysis, 300 & 200 m
200m, 1 ha
300m, 1 ha
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Day 1-Exposure assessment approaches (U.S. and international)
UGSI, 200m, Malmo, Kaunas, Utrecht: various sizes
UGSI
¦ Kaunas
Utrecht
UGSI
•<300 m
•> 1 ha
•or suffix, e.g. UGSI (200, 2.5)
•full script for use by urban planners and
municipality officers
•policies and guidelines
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Day 1-Exposure assessment approaches (U.S. and international)
Issues
• Linear distance vs walking distance
• Optimal size
• Quality, amenities
• Comparability
• Non-EU countries
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Day 1-Exposure assessment approaches (U.S. and international)
GREEN SPACE AND HEALTH:
THE PHENOTYPE PROJECT
Mark J NieuwenhuijsenPhD
CREAL
22 Sept / La Pedrera, Barcelona
Generalitat
de Catalunya
SB"
U NI V E R SI TAT
POMPEU F A 8 R A
PHENOTYPE
• FP7 Theme ENV.2011,1.2.3-2; Positive effects of natural environmentfor human
health and well-being. Grant Agreement 282996
• 1st January 2012-31st December 2015
• EC contribution^ 3.499.403
• Beneficiaries:
— FundacioCentre de Recerca en Epidemiologia Ambiental-Spain (C)
— RijksinstituutvoorVolksgezondheiden Milieu-Netherlands
— Staffordshire University- United Kingdom
— Vytauto Didziojo Universitetas- Lithuania
— Universite de Geneve - Switzerland
— Vereniging voor Christelijk Hoger Onderwijs, WetenschappelijkOnderzoek en
Patientenzorg- Netherlands
— Veiligheids-en Gezondheidsregio Gelderland Midden- Netherlands
— University of California, Berkeley Campus - United States
II
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Day 1-Exposure assessment approaches (U.S. and international)
Open Access
BMJ Open Positive health effects of the natural
outdoor environment in typical
populations in different regions
in Europe (PHENOTYPE): a study
programme protocol
Mark J Nieuwenhuijsen,1,2,3 Hanneke Kruize,4 Christopher Gidlow,5
Sandra Andnjsaityte,6 Josep Maria Anto,1,2,3,7 Xavier Basagaha,1,2,3 MartaCirach,1,2,3
Payam Dadvand,12,3 Asta Danileviciute,6 David Donaire-Gonzalez,1,2,3
Judith Garcia,1,2,3 Michael Jerrett,8 Marc Jones,5 Jordi Julvez,1,2,3,7 Eiise van Kempen,4
Irene van Kamp,4 Jolanda Maas,9 Edmund Seto,8 Graham Smith,5
Margarita Triguero,1,2,3 Wanda Wendel-Vos 4 John Wright,10 Joris Zufferey,11
Peter Jan van den Hazel,12 Roderick Lawrence," Regina Grazuleviciene6
To cile: Nieuwenhuijsen MJ.
Kruize H. Gidlrw C. era/,
ftisiliw /ealtti etfects of the
natural outdoor environment in
typical populations in different
regions in furope
(PHENOTYPE): a study
programme protocol - BMJ
«)0/!2O14;4:eOO4951.
doi:10.1136/bmjopen-2014-
004951
ABSTRACT
Introduction: Growing evidence suggests that close
contact with nature brings benefits to human health and
well-being, but the proposed mechanisms are still not
well understood and the associations with health remain
uncertain. The Arcitive Health ftfects of the Afctural
Outdoor environment in Typical ftpulations in different
regions in furope (PHENOTYPE) project investigates the
interconnections between natural outdoor environments
and better human health and well-being.
Strengths and limitations of this study
The fbsrtive ttalth Effects of the fetural
ftitdoor environment in Typical fbpulations in
different regions in furope (PHENOTYPE) project
is the largest European project on green space
and health.
The PHENOTYPE project examines simultan-
eously the possible underlying mechanisms
fstress reduction/restorative function, phvsical
PHENOTYPE
Project Structure
Land use planning
and natural environment
Management (WPS)
Small studies (n=4*20-40)
T herapeutic studies
{WP-i)
Cardiovascular, respiratory and
cancer morbidity and mortality
Epidemiological studies
(WP3)
Obesity
Medium size studies (n=4'1000)
Environ me rial pollutants
Inclusive subgroups
Implications, including health impact assessment and application(WP5)
Policy involvement and Dissemination, including stakeholders (WP 6)
Natural environment:
Quantitative and quality characteristics (amount, type)
Different levels of urbanity (WP2)
? m
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Day 1-Exposure assessment approaches (U.S. and international)
PHENOTYPE - WP2
The characterisation of natural environments is reported at three levels:
LEVEL 1 » Basic Measures: Using Europe-wide, secondary data (e.g., Urban Atlas; NDVI)
LEVEL 2 » Detailed Measures: Using locally held secondary data (City Council, etc.) for a
more detailed classification of environments
AUDITS » Environment Quality: Primary data collection using a Streetscape Audit and
Neighbourhood Green Space Tool to report environmentquality data.
Classification of Natural Environments
Olher
(e o. mountains)
Rural and
ognarflural land
Marine / coastal
Freshwater
(including
beaches)
Other natural
features (e g
street trees)
Reiwavo-s
Ponds / Pods
(at standing
Canals
(linear water
features)
CMc spaces
(school tieUs.
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Day 1-Exposure assessment approaches (U.S. and international)
LEVEL 1 » Basic Measures (I)
This is the broad distinction between 'green' and 'blue' environments.
The basic indicators are being produced using routinely available data such as Urban Atlas and LandSat
derived NDVI.
These are designed to be generally representative of the amount of natural environment available within
a neighbourhood and can also be applied in other cities in Europe for comparability.
• NDVI
Source
Indicator
Distance
NDVI
(Landsat 30m - representative of WP2
data collection period - best available
data from April to August)
Average NDVI within exposure
buffer.
100m, 300m, 500m
Proportion of buffer area
classified within 6 NDVI ranges
100m, 300m, 500m
LEVEL 1 » Basic Measures (I)
Barcelona NDVI map
Landsat 8 (2013)
0 NDVI
~ NDVI
¦1
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Day 1-Exposure assessment approaches (U.S. and international)
LEVEL 1 » Basic Measures (I)
NDVI EXPOSURES WITHIN CENSUS AREAS IN BARCELONA
Within census area Within census area + 300m buffer
LEVEL 1 » Basic Measures (I)
10,000"
8,000-
6.000-
4,000"
2,000-
Barcelona
1 1
Stoke-on-Trent Doetinchem
100m Mean NDVI
300m Mean NDVI
~ 500m Mean NDVI
O o
8 8
Kaunas
City
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Day 1-Exposure assessment approaches (U.S. and international)
LEVEL 1 » Basic Measures (II)
• URBAN ATLAS (green)
Source
Indicator
Distance
Urban Atlas - green space
Straight line distance to nearest space > 5,000m2
Closest
Street network distance to nearest space > 5,000m2
Closest
Number of spaces within a street network distance
300m, 500m, 1000m
Total area of spaces (all) within buffer (network
distance)
300m, 500m, 1000m
Network distance to nearest space by size - 0.5 to 2,
2 to 5,5 to 20,20 plus hectares
300m, 500m, 1000m
3000m, 5000m (5 to 20, 20
plus only)
Number of spaces with street network distance by
size - 0.5 to 2,2 to 5,5 to 20,20 plus hectares
300m, 500m, 1000m
3000m, 5000m (5 to 20, 20
plus only)
LEVEL 1 » Basic Measures (III)
• URBAN ATLAS (blue)
Source
Indicator
Distance
Urban Atlas - blue space
Straight line distance to nearest space >
5,000m2
Closest
Street network distance to nearest space >
5,000m2
Closest
Number of spaces within a street network
distance
300m, 500m, 1000m
Total area of spaces (all) within a (network
distance)
300m, 500m, 1000m
Presence of Blue (Y/N)
300m, 500m, 1000m
Bl-26
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Day 1-Exposure assessment approaches (U.S. and international)
LEVEL 1 » Basic Measures (III)
Barcelona Major Green and Blue space (> 0.5ha)
Urban Atlas
AMOUNT OF MAJOR GREEN SPACES
Within census area Within census area + 300m buffer
Bl-27
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Day 1-Exposure assessment approaches (U.S. and international)
PERCENTAGE OF NATURAL ENVIRONMENT
Within census area Within census «rea ~ 300m buffer
LEVEL 2 » Detailed Measures
The detailed indicators are produced using locally held secondary data (City Council, etc.).
This data represents the best available data for each study area.
To make the data comparable a common classification of environments is applied to the local data in each study
area.
This classification is used to assign spaces to subsets of environments that will be used to produce the indicators
associated with a particular mechanism.
This is the level required to conduct the mechanism assessment in WP2. However, indicators are not produced for
individual categories but are grouped together to form sub-groups appropriate to the mechanism being
assessed:
' Stress reduction & restorative- All natural environments are included apart from agricultural land not
associated with urban areas and derelict urban space which is assumed not to be providing a 'pleasant'
environment for people to access or to view.
• Physical Activity-All natural environments that can be accessed and are large enough to support some
level of physical activity. The minimum size required is 0.5 hectares unless the space provides a dedicated
physical activity opportunity such asa playgroundorsports field.
• Social Interaction / Cohesion - All natural environments that can be accessed are included. Size is not seen
as important.
• Exposure to Environmental Hazards-All natural spaces are important. There is insufficient data to attempt
to match spaces to particulartypes of environmental hazard thatthey mitigate.
Bl-28
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Day 1-Exposure assessment approaches (U.S. and international)
LEVEL 2 » Detailed Measures
Barcelona Natural Environments map for Level 2
0 Nat Environments
Tipology
~ Parte
I I Semi-natural (Urban)
~ Amenity space
~ Country park
~ Derelict/ vacant
~ Formal recreation
¦ Functional
¦ Natural/Green corridor
EZ3 River / stream /canal
EH Coastal
LEVEL 2 » Detailed Measures
Barcelona Natural Environments map for Level 2 i
0 Nat Environments
Tipology
~ Parks
~ Semi-natural (Urban)
~ Amenity space
~ Country park
~ Derelict/ vacant
~ Formal recreation
Hi Functional
B Natural/Green corridor
EI River / stream /canal
Is! Coastal
4y/
yj
f
Bl-29
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Day 1-Exposure assessment approaches (U.S. and international)
LEVEL 2 » Detailed Measures
Level 1
Level 1.1
Level 2
Level 2.2
Mechanism subset
1 Stress
reduction
&
restorativ
e
2.
Physical
Activity
3. Social
Interaction
Cohesion
4 Exposure
to
Environment
al Hazards
Green
Urban Green Space
Parks
Urban parks
Y
Y
Y
Y
Semi-natural / natural
Biodiversity areas,
conservation areas,
nature reserves,
protected areas, heritage
sites?
Y
Y-
access
Y - access
Y
Formal Recreation
Playgrounds and sports
fields (not within parks)
Y
Y
Y
Y
Amenity space
Squares. Gardens,
Y
Y - size
>0.5ha
Y
Y
Functional
Allotment, Cemetery,
Civic Spaces. Institutional
(school, hospital grounds
etc.)
Y
Y
Y
Y
Natural / green corridor
Traffic free / natural.
Pathways, Trails and
cycle paths
Y
Y-
access
Y - access
Y
Derelict / vacant
Disused natural areas, no
LEVEL 2 » Detailed Measures
Mechanism Subset
Indicator
Distance
1. Stress reduction &
restorative - Green
Straight line distance to nearest
space
Closest
Street network distance to
nearest space
Closest
Number of spaces within a
street network distance
300m, 500m, 1000m
Total area of spaces (all) within
buffer (network distance)
300m, 500m, 1000m
Network distance to nearest
space by size - <0.5, 0.5 to 2, 2
to 5, 5 to 20, 20 plus hectares
300m, 500m, 1000m
3000m, 5000m (5 to 20, 20 plus
only)
1. Stress reduction &
restorative - Blue
Straight line distance to nearest
space
Closest
Street network distance to
nearest space
Closest
Number of spaces within a
street network distance
300m, 500m, 1000m
Total area of spaces (all) within
a (network distance)
300m, 500m, 1000m
Presence of Blue (Y/N)
300m, 500m, 1000m
Bl-30
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Day 1-Exposure assessment approaches (U.S. and international)
LEVEL 2 » Detailed Measures
2. Physical Activity - Green
Street network distance to
nearest space
Closest
Number of spaces within a
street network distance
300m, 500m, 1000m
Total area of spaces (all) within
buffer (network distance)
300m, 500m, 1000m
Network distance to nearest
space by size - 0.5 to 2, 2 to 5, 5
to 20, 20 plus hectares
300m, 500m, 1000m
3000m, 5000m (5 to 20, 20 plus
only)
2. Physical Activity - Blue
Street network distance to
nearest space
Closest
Number of spaces within a
street network distance
300m, 500m, 1000m
Total area of spaces (all) within
a (network distance)
300m, 500m, 1000m
Presence of Blue (Y/N)
300m, 500m, 1000m
LEVEL 2 » Detailed Measures
Mechanism Subset
Indicator
Distance
3. Social Interaction
Cohesion - Green
Street network distance to
nearest space
Closest
Number of spaces within a
street network distance
300m, 500m, 1000m
Total area of spaces (all) within
buffer (network distance)
300m, 500m, 1000m
Network distance to nearest
space by size - <0.5, 0.5 to 2, 2
to 5, 5 to 20, 20 plus hectares
300m, 500m, 1000m
3000m, 5000m (5 to 20, 20 plus
only)
3. Social Interaction
Cohesion - Blue
Street network distance to
nearest space
Closest
Number of spaces within a
street network distance
300m, 500m, 1000m
Total area of spaces (all) within
a (network distance)
300m, 500m, 1000m
Presence of Blue (Y/N)
300m, 500m, 1000m
Bl-31
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Day 1-Exposure assessment approaches (U.S. and international)
LEVEL 2 » Detailed Measures
Mechanism Subset
Indicator
Distance
4. Exposure to
Environmental Hazards-
Green
Straight line distance to nearest
space
Closest
Number of spaces within a
straight distance
300m, 500m, 1000m
Total area of spaces (all) within
straight-line buffer
300m, 500m, 1000m
4. Exposure to
Environmental Hazards-
Blue
Straight line distance to nearest
space
Closest
Number of spaces within a
straight-line distance
300m, 500m, 1000m
Total area of spaces (all) within
a straight-line distance
300m, 500m, 1000m
AUDITS » Environment Quality
In PHENOTYPE, for every selected neighborhood, we have audited:
- the streets/streetscape, and
-natural outdoor spaces in these neighborhood
Nat Env audittool was comprised of 59 items grouped into eight main domains:
Domains
Items (summarised)
Items
1. Access
2. Recreational
Facilities
Entrance points; busy/minor surrounding roads; pedestrian crossings; links areas;
walking paths (amount and quality); car parking
Playground equipment; Grass pitches; Courts; Skateboard ramp(s); Other sports or
fitness facilities
7
7
3. Amenities
Seating/benches; Litter bins; Dog mess bins (or equivalent); Public toilets; Cafe /
kiosk; Shelter/shade - man-made; Shelter/shade - from trees; Barbeques; Picnic
tables; Drinking fountains
10
4a. Aesthetics
(Natural features)
Area on the foreshore of a beach, nver or large lake; OTHER water features WITHIN
area. % area occupied by the water feature(s); Good view points, vistas, scenic
views; %of area occupied by trees; Primary surface quality; Flower beds / planters /
wild flowers. Other planted trees / shrubs I plants
8
4b. Aesthetics
(Non-natural)
Water fountain (decorative); Other public art; Histonc/attractive buildings/structures;
Public attractions (e.g.. zoo, other)
4
5. Incivilities
General litter. Evidence of alcohol use' Evidence of drug taking; Graffiti. Broken glass;
Vandalism; Noise (e g . traffic, industry); Unpleasant smells
9
6. Safety (social)
Lighting within area; Visibility of surrounding roads (from centre of area);
Visibility of surrounding houses (from centre of area)
3
7. Useage
(suitability for...)
Sport Informal games; Walking/running; Children's play; Conservation/biodiversity;
Enjoying landscape/visual qualities; Meeting, socialising; Relaxing/unwinding;
Cycling; Water sport; Fishing
11
TOTAL 59
Bl-32
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Day 1-Exposure assessment approaches (U.S. and international)
AUDITS » Environment Quality
Distribution of Natural Environment tipology audited by city
Typology"
City
Total
Barcelona
Doetinchem
Stoke-on-
Trent
Kaunas
Park
37
63
56
4
160
Natural/semi-natural
14
15
10
12
51
Amenity/public open space
8
4
6
1
19
Natural/green corridor
0
0
10
0
10
Lake, reservoir, pond, pool
0
0
2
0
2
River, stream, canal
0
2
6
0
8
Total
59
84
90
17
250
AUDITS » Environment Quality
Bar graph showing the relative contribution of Mechanism scores to each Typology
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
¦
:
¦ CycWallk
¦ Natural
¦ Relaxation
¦ Social
¦ PA
^ / 4
-C> \Q
J
J
/
V
/
r
/
f if
/¦
4>
Bl-33
-------
Day 1-Exposure assessment approaches (U.S. and international)
AUDITS » Environment Quality
Next steps:
Derive final scores for all audited spaces and
•Calculate neighbourhood-level aggregate scores
•Link individual space scores to relevant survey items about specific spaces
visited
Initial results WP3
Bl-34
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Day 1-Exposure assessment approaches (U.S. and international)
PHENCTYPE „. ,
—Birth outcomes
Articles
Population and outcome
NDVI
Access (Distance)
Use
Dadvand et al
2012
2393
4 Spanish birth cohorts
Birth weight
Gestational age
500 m IQR
44.2 (20.2-68.2)*
0.0 (-0.9, 0.9)
nd
nd
Dadvand et al
2012
8246 births Barcelona
Birth weight g
Gestational age d.
100 m in low SES:
436.3(43.1, 829.5)*
-19.8 (-67.6, 28.1)
-0.3 (-1.9, 1.4)
500 m in low SES:
189.8 (23.9, 355.7)*
-15.8 (-36.3, 4.8)
-0.4 (-1.1, 0.3)
nd
Dadvand et al
2014
10780 births
Bradford
Birth weight g
250 m IQR
in white British
26.2 (3.1- 49.3)*
Pakistani
6.5 (-16.4- 29.5)
300 m
4.8 (-12.5, 22.1)
nd
Grazuleviciene
et al 2015
3292 births
Kaunas
Birth weight, g
Gestational age d.
100 m
13.2 (-3.7-30.2)
-0.2 (-0.77-0.35)*
1000 m park
-6.43 (-45.2-32.4)
-0.21 (-0.39—0.04)
nd
Children health
Articles
Population and outcome
NDVI
Access (Distance)
Use
Dadvand
et al 2014
3178 9-12 yrs Sabadell
Sedentary behaviour
Obesity
Asthma
100 m IQR
0.85 (0.77, .93)**
0.83 (0.75, .93)**
1.00 (0.82, 1.21)
Parks 300m
0.91 (0.76, 1.09)
0.90 (0.74, 1.09)
1.60 (1.09, 2.36)**
Forest
0.61 (0.45, 0.83)**
0.75 (0.54, 1.03)*
1.02 (0.56, 1.87)
Nd
Amoly et al 2014
2,111 7-10 years
Barcelona
Total difficulties
Emotional symptoms
Peer relationship problems
Hyperactivity
NDVI 100m
-3.6 (-6.6-0.6)**
-1.4 (-5.9-3.2)
-2.4 (-8.7-4.3)
-6.0 (-11.3- -0.2)**
Distance 300 m
-1.3 (-8.2-6.2)
1.9 (-8.7-13.8)
-5.1 (-19.1-1.3)
1.8 (-11.6-17.3)
Playing time
Green/Blue spaces
-4.8 (-8.6 -.9)**
/-3.9 (-7.2, -0.4)**
-8.2 (-13.9 -2.2)**
/-3.9 (-9.1, 1.6)
-15.4 (-22.7-.4J**
/-16.8 (-23.4-9.7)**
-1.6 (-9.0-6.4)
/-O.l (-6.7-6.9)
Balseviciene et al
2014
1468 4- 6 years Kaunas
(Low SES 296) SDQ
300m (beta coefficient) in
high SES
Parks (beta coefficient) in
low SES
nd
Total Difficulties
0.069*
Peer problems
0.023*
Conditional problems
0.901*
0.026*
Hyperactivity
0.026*
Prosocial behavior
-1.104*
-0.029
31
Bl-35
-------
Day 1-Exposure assessment approaches (U.S. and international)
PHENCTYPE
Adults mental health
Articles
Population and
outcome
NDVI
Access (Distance)
Use
Reklaitiene
etal 2014
6944 45-72 yrs
Kaunas
Depressive
symptoms
Nd
>300 m parks
1.04 (0.91-1.19)
Use <4 h/week
1.17 (1.01-1.37)
Triguero-
Mas et al
2015
8793 adults
Catalonia
Perceived
depression
General health
300 m
0.79 (0.71, 0.88)*
0.80 (0.71, 0.91)*
300 m
0.86 (0.76, 0.98)*
0.87 (0.72, 1.05)
nd
32
PHENiTYPE
HMVttwneuWflttn
Cardiovascular health
Articles
Population and outcome
NDVI
Access (Distance)
Use
Grazuleviciene
etal 2014
3416 women
Kaunas, blood pressure
mmHg
High normal <139/89
Hypertension >140 or > 90
nd
>1000 m park
1.74(1.14-2.66)*
1.18 (0.79-1.77)
nd
Tamosiunas et
al2014
5112 45-72 yrs
Kaunas
Cardiovascular morbidity
and mortality
nd
Distance 3rd tertile
Total CVD
1.36 (1.03-1.80)*
Total sample
Non- fatal CVD
1.66 (1.01-2.73)*
Bl-36
-------
Day 1-Exposure assessment approaches (U.S. and international)
GREEN SPACE MANAGEMENT
INDICATORS
Indicators
-Quantitative
-Qualitative
1. Ownership
Blue and
Green Spaces
Ownership
Health Effects
Distinction public vs. private (hinterland, region, city, neighbourhood)
Communal/collective/ shared vs. private or public
m
PHENSTYPE
www. phenotype.eu
UHERII. IJ.Al.l 11 | XAUKMU
Square PLANCIION
VILUE dc MONiritlllR
Bl-37
-------
Day 1-Exposure assessment approaches (U.S. and international)
2. Size/shape
Blue and
Green Spaces
Size/ Shape
Health Effects
Classification of parks by size and shape
LSI 101
Jo
WI4-
I.S1-U2
A,. >9390
kr ¦ IIW'9
I 51 I +*
(On
(VmrTtcr - WW M
LSI - 4 7*
Area lrt*K?7M
I M ' -f
A rem M67173
foiiarta Nttl ?)
LSI -2 03
Vca «*»MJ *0 m
Pwim«W( !236 II in
5 O
p
{:*
C M
II
> O
It
2 <°
»5
PHENCTYPE
HaiWikrraiabch
www.phenotype eu
3. Biological characteristics
Health Effects
Blue and
Green Spaces
Biological
Characteristics
Land cover, biodiversity, presence of water, vegetation structure and
type
PHENCTYPE
HEC*itcnTai*afcfch
v/ww phenotype eu
Bl-38
-------
Day 1-Exposure assessment approaches (U.S. and international)
4. Functional uses
Health Effects
Blue and
Green Spaces
Functional Uses
Ecosystem services, human-made facilities, aesthetic and design,
human uses (leisure, restoration, social contact, physical activity)
PHEN®TYPE
Hecim torn aigae n
www phenotype.eu
5. Localisation
Blue and
Green Spaces
Localisation
Health Effects
Distance to blue and green spaces, quietness/ proximity of
nuisances, accessibility, connection with other blue and green
spaces
GOALS FOR 2015
90% Of COPENHAGENRS MUSI BE
AW F TO WAI K TO A PARK. A F.FACH
Oft A SCA SWnMING POOL IN
UNDER 15 MINUTES.
rOPFNHAGFNFRS WTII VISIT THF
CI I Y*S PARKS. NAI URAL AKtAS, StA
SWIMMING POOI SAND RFACHFS
IWICL As Ol ILNAS IIILY DO
TODAY.
PHENiTYPE
htolhtomaMfcln
www.phenotype.eu
Bl-39
-------
Day 1-Exposure assessment approaches (U.S. and international)
6. Management
Blue and
Green Spaces
Management
Health Effects
Maintenance (cleanliness, horticultural and landscape
management), sense of security, time of opening/closing, entrance
fees, codes of conduct (rules)
PHENCTYPE
www phenotype eu
7. Community identity
Blue and
Green Spaces
Community
Identity
Health Effects
Identity, history, culture, presence of local people/ethnic communities,
artistic, educational, sporting and tourist interests
m
im
Park life!
music, art,
dancing and
dining in
London's
green spaces
Time Out
London July
ITt' f\ AWwftk'iliO'yj
PHENvTYPE
www phenotype eu
Bl-40
-------
Day 1-Exposure assessment approaches (U.S. and international)
8. Climate/Weather
Blue and
Green Spaces
Climate/ Weather
Health Effects
Climate, weather conditions, seasonal change
PHEN€TYPE
HectfftfcrrOLtofcfch
www phenotype eu
Bl-41
-------
Day 1-Tree cover measurements (NDVI, regional-local UTC)
NDVI and Tree Cover
Measurements
Geoff Donovan and Perry Hystad
a
¥
\ ,¦ v-.. r,. .
*' • \'H4
• 5f •
Uoand
1 ¦¦ >1
•*» . : pWnut3 * ^JP 4r w
** imK!
\.i - V— v
A number of different GIS
methods can be used to assess
NDVI and tree cover for large
populations/areas
Bl-42
-------
Day 1-Tree cover measurements (NDVI, regional-local UTC)
Satellite Vegetation Indices
• Chlorophyll strongly absorbs visible
light (from 0.4 to 0.7 pm) for use in
photosynthesis.
• The cell structure of the leaves
strongly reflects near-infrared light
(from 0.7 to 1.1 pm).
• The more leaves a plant has,
the more these wavelengths of
light are affected.
NDVI
• Most common index using in health research is the
Normalized Difference Vegetation Index (NDVI).
• NDVI ranges from -1 to 1 (however, no green leaves gives a
value close to zero).
NDVI = (NIR — VIS)/(NIR + VIS)
(p.SO - 0.06)
Near infrared (AVHRff Channel 2. 725-1.1 urn)
Visible Light (AVHRR Channel 1. 56- 68 pm)
fwS
Bl-43
-------
Day 1-Tree cover measurements (NDVI, regional-local UTC)
Landsat NDVI
• Landsat NDVI (1972 onwards)
- Daily measurements
- Some processing/calculations of NDVI needed
1 HB
andsai-7
DOCC 3u
tm 'S$( 79 m 4 band |
m TM130/120 m 7 band)
CD ETMMI&OOftpm. abend)
~ Landtat 8 (1S/3Q90 m 9 band)
[ Um»Mf #
1 Hunched If F*
* tou
2 mo jom
I 1 Commercial optation*
I I Government opefabon*
Landsat NDVI
Bl-44
-------
Day 1-Tree cover measurements (NDVI, regional-local UTC)
Pereiraetal. (2012). The association between
neighborhood greenness and cardiovascular
disease: an observational study
• Walkable network area rather
than circular buffer
• Mean or Variation in
Greenness?
MODIS NDVI or EVI
Spatial Resolution
250m, 500m, 1km
Temporal Resolution
Daily, 8-day, 16-day, monthly, quarterly, yearly
(2000-present)
Data Format
Hierarchal Data Format - Earth Observing System
Format (HDF-EOS)
Spectral Coverage
36 bands (major bands include
Red, Blue, IR, NIR, MIR)
Bands 1-2: 250m
Bands 3-7: 500m
Bands 8-36: 1000m
Bl-45
-------
Day 1-Tree cover measurements (NDVI, regional-local UTC)
EVI
Enhanced Vegetation Index (EVI) was designed to improve
upon the quality of the NDVI product (available from the
MODIS sensor).
Corrects for some distortions in the reflected light caused by
the particles in the air as well as the ground cover below the
vegetation.
Improves on the saturation of NDVI at very high greenness
levels.
Maximum
Left 80% Right 80%
Start of
Right 20%
Right Minimum
l«t Minimum
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
MOOIIQI > Ik.dam .NOVI I %<<•««• I
v** •>%.
.I".
•• —¦ f"" f
3 2004 NOtk 2000 WO/
©I 7002
Bl-46
-------
Day 1-Tree cover measurements (NDVI, regional-local UTC)
U.S. Forest Change Assessment Viewer
(ForWarn)
Three types of products:
' Forest Change Products
' Basic Phenology Products
- Derivative Phenology Products
° l_1 • 1 ¦. HH. — rrmi—mmmm "• ——
http://forwarn.forestthreats.org
Use of ForWarn: 2013 Gypsy Moth Defoliation
in New York and Pennsylvania
06/01/2013 06/09/2013 06/17/2013
06/25/2013 07/03/2013 007/11/2013
Bl-47
-------
Day 1-Tree cover measurements (NDVI, regional-local UTC)
Leaf Area Index
• Ratio of leaf area to ground area.
• Computed daily at 1km from MODIS spectral reflectance's for
all vegetated land surface globally.
MODIS Leaf Area Index
Composite March 24 - April 8, 2000
Land Cover Maps
Landsat Image of Lake Tahoe Landcover map of Lake Tahoe
Bl-48
-------
Day 1-Tree cover measurements (NDVI, regional-local UTC)
Landsat Derived Land Cover Products
• United States
- National Land Cover Database (NLCD)
- GAP Analysis
- LANDFIRE
• Global
- Global Land Cover Network (FAO)
- Forest Change Products (Amazon Basin, Central
Africa, Paraguay) and Landsat Tree Cover (GLCF)
A
N
Classes
Tree Canopy
Grass/Shrub
Bare Soil
Water
Buildings
Roads/Railroads
Other Paved Surfaces
12 Miles
New York City Landcover 2010
Bl-49
-------
Day 1-Tree cover measurements (NDVI, regional-local UTC)
Central Park, New York Cityj
Landcover 2010
Classes
Tree Canopy
Grass/Shrub
| Bare Soil
Water
Buildings
Roads/Railroads
Other Paved Surfaces
A
Classes
HTree Canopy
Grass/Shrub
| Bare Soil
Water
Buildings
Roads/Railroads
^ Other Paved Surfaces
Liberty Island, New York City
Landcover 2010
SH '
Bl-50
-------
Day 1-Tree cover measurements (NDVI, regional-local UTC)
Assessing Change
• Land cover change
from 1992 to 2010
in the Pacific
Northwest.
Landsat Tree Cover
source: glcf.umd.edu
Global Land Cover Facility
www.iandcover.org
Landsat Tree Cover a I
Global Land Cover Facility (GLCF)
http://glcf.umd.edu/data/landsatTreecover/
> Landsat Tree Cover layers estimate the percent of tree cover per 30m pixel area (includes
stems, branches, leaves greater than 5 meters in height)
> Derived from all seven bands of Landsat 5-TM and Landsat ETM
r Landsat Tree Cover product represents 2000, 2005
Bl-51
-------
Day 1-Tree cover measurements (NDVI, regional-local UTC)
LiDAR
• LIDAR (Light Detection and Ranging) is a remote
sensing method that uses light in the form of a
pulsed laser to measure distances to the Earth.
• Generates precise, three-dimensional information
about the shape of the Earth and its surface
characteristics.
Example of LiDAR data - Canopy Cover
B1-52
-------
Day 1-Tree cover measurements (NDVI, regional-local UTC)
> V.IT"1 '
'&J<- **53881
Buildings Trees Ground Vegetation
Figure 2.2,2: A city block in study area that displays a) resulting building polygons from the LiDAR extraction technique, and b) result-
ing building polygons after post-processing to simplify polygon shapes, remove secondary structures, and separate buildings by land
parcel boundaries.
tree canopy loss
along the
1-75 corridor
canopy loss
tree canopy!
created by Stephen Hendrickson
B1-53
-------
Day 1-Tree cover measurements (NDVI, regional-local UTC)
0 10 20 Km
1 i I
Other Applications Applications
• Separate vegetation index by trees and
grass using LIDAR.
• Integrate cooling impacts of vegetation.
• Cost distance.
Cost Distance
Cost Ratio
500 m
Cost distance
... with trees
Without trees
Distance (m)
BI -54
-------
Day 1-Tree cover measurements (NDVI, regional-local UTC)
Enhancing NDVI and Tree Cover
"Exposure" Assessment
• Start with the specific exposure construct in which we want to
examine:
Outcomes May
Enhancing NDVI and Tree Cover
"Exposure" Assessment
• Include both objective and subjective measurements.
• Collect information on use of greenspace.
• Assess greenspace using GPS and accelerometer data with
momentary assessments of greenspace?
• Greenspace and tree exposure assessmentfrom a human
view (rather than birds eye view).
• Etc...
B1-55
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Day 1-Access to greenness
Access to greenness
Rich Mitchell, Michelle
Kondo, Matilda Van Den
Bosch
Day 1
Estimating Greenspace Exposure & Benefits for
Cumulative Risk Assessment Applications
Technical Working Group Meeting
May 4-5,2015
U.S. Environmental Protection Agency
26 Martin Luther King Drive West, Cincinnati, OH 45220
What kind of nature? Often, we're focused on urban nature (parks, woodlands,
river corridors etc.).
B1-56
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Day 1-Access to greenness
An example of very detailed landcovermapping
Glasgow: Kelvinbridge and Botanical Gardens
Ordnance Survey MasterMap (OSMM)
Master Map ©Crown Copyright/ database right 2009. An Ordnance Survey/EDINA supplied service Google imagery© Google
We extract 'green' areas based on land cover
Glasgow: Kelvinbridge and Botanical Gardens
Ordnance Survey MasterMap (OSMM)
IDowanhill;
[Univ.
MasterMap & 150000 Map ©Crown Copyright 2009. An Ordnance Survey/EDINA supplied service Google imagery© Googlec
B1-57
-------
Day 1-Access to greenness
Scotland's greenspace map
• The Map was compiled in 2011 from greenspace data provided by all
32 Scottish Councils.
• The local datasets were produced using greenspace mapping
characterisation.
• This involved using GIS maps and aerial photography to categorise
greenspaces into 23 different open space types; these include public
parks, play areas, allotments, amenity greenspace, private gardens.
Primary and secondary codes are used to capture multi-functional
greenspaces, for example, play areas or woodland within larger public
parks
5
Scotland's Greenspace
Primary Classification
| Oth«f Ikmctionalgreenspace egc
CMC space
Secondary Classification
Socoodary Greenspace Piowot
Scotland's Greenspace rr. x
<- C A www.snh.gov.uk/planriing-and-development/advice-for-planners-and-developers/greenspace-and-outdoor-access/scotlands-greenspace/dataset/
Apps Q UNIT4 Agresso HB BBC News - Home Elsevier Editorial
The project to develop the Scotland's Greenspace Map was led By greenspace Scotland with support from Scottish Government. Scottish Natural Heritage and Forestry
Commission Scotland; all 32 Scottish Councils actively supported the project and provided information. You can find out more about how Scotland's Greenspace Map was
developed at the greenspace Scotland website c?
B1-58
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Day 1-Access to greenness
These can then be buffered to give a 'distance to green space'
measure
Google Map
Distance buffer
uca£-:
Ek^pl cyf
Google imagery © Google. GUA data © EEA, Copenhagen, (2001) OS 150000 map, © Crown Copyright, An OrdnanceSurvey / EDINA supplied service
Or the proportion of land cover within an areal unit that is
green can be calculated
Google Map
Hybrid
y I nfmv
r~7
B1-59
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Day 1-Access to greenness
Some remotely sensed data sets capture only larger green spaces
Glasgow: Kelvinbridge and Botanical Gardens
Google Map
EEA CORINE
Keltflnside
i
Mu$eutr»
&sm
¦*s=ca
or k lull
CORINE data © EEA, Copenhagen, (2001). Google imagery © Google. OS 150000 map, © Crown Copyright. An OrdnanceSurvey / EDINA supplied service
Comparison of 'neighbourhood greenness' in Glasgow, from different data sets
Hybrid
OS Master Map
% Green space
o%-10%
10.1% -20%
1%- 30%
1% - 40%
1% - 50%
1% - 60%
1% - 70%
1% - 80%
Thisworicis based on data pra/ided through EDINA UKBORDERSwith the support oftheESRCandJISC and uses boundary material which is copyright of the
Crown and the Post Office. Master Map ©Crown Copyright/database right 2009. An Orctiance Suivey/EDINA supplied service. CORINE (c) EEA. Copenhagen, (2001)
Bl-60
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Day 1-Access to greenness
Scale matters here - these are 'city level' greenness measures, from National Land Cover
Database for 2001, in the US.
(a) Male
°, 2000 -
~ 1500
2
>
£ 1000 -
£ 500 -
• Las Vegas, NV
• Tucson, AZ
• • •
• • • 1* •
• • w m— i
•
10 20 30 40 50 60 70 80
city greenness (% area)
Richardson EA, Mitchell R, Hartig T, de Vries S, Astell-Burt T, Frumkin H. Green cities and health: a question of scale? Journal of Epidemiology and Community Health. 2011
doi:10.1136/jech.2011.137240
Bl-61
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Day 1-Access to greenness
Definition of greenness - what about viewsheds? This is Edinburgh
But if you look at how 'green' that part of the city is, different data sets tell you different thinj
Edinburgh: Holyrood Park
EEA's Green Urban Areas (GUA) data EEA'sGUA data, with CORINE
BailnwbahUS
.^Meadowbank^
jIacv" oi
l»ousc
Q £fcupcl ' VJ
^ . »'\v
1 \ ¦}
fill ' S ' V < ± > 9
wc i NB y
Salisbury Holyroo^J^rk—^D'
3f\ ^v, » larV L
CORINE & GUA data © EEA, Copenhagen, (2001).150000 OS map© Crown Copyright. An Ordnance Survey/ EDINA supplied service
Bl-62
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Day 1-Access to greenness
More problems
• Distance/walking time or °/o coverage are not the same as exposure in
at least two more important ways
• We don't know if the space is accessible to our population of interest
• We don't know if the space is accessed by our population of interest
• Co-location or spatial proximity * exposure
This lovely park in Dowanhill is private
Google Imagery © Google
Bl-63
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Day 1-Access to greenness
agricultural grassland
agricultural grassland
STATE HIGHWAY 74
Park
ley Golf
In our work in New Zealand, we were
able to use land registry data to
distinguish public and private, or
accessible and non accessible space.
We found different levels of access,
of different kinds of space, for
different social groups
Greenspace type Road network
| Non greenspace * Highway
Usable Other road
Non-usable
Non-usable (bluespace)
Richardson E. PearceJ. Mitchell R, DayP, Kingham S. The association between green space and cause-specific mortality in urban New Zealand: an ecolog ical ana tysisof green space utility. Bmc Public Health. 2010;10(1):240.
How do we do this?
(1) Relate the health of everyone in a
neighbourhood to how much green space there
is (comparing neighbourhoods)
Mortality data from GROS & ONS (2001-2005)
Bl-64
Estimates of the % land area in a
neighbourhood that is green space
www.cresh.org.uk
-------
Day 1-Access to greenness
How do we do this?
,JdP
)CrzJ/, nfmy
JXJa U&iS?t'
^?ne.
Uhiv
Mlllil
Estimates of the % land area in a
neighbourhood that is green space
www.cresh.ore.uk
(2) Relate the health of individuals to how much
green space they have in their neighbourhood &/or
whether they visit green spaces (comparing
individuals in different neighbourhoods)
Scottish Health Survey 2008
How do we do this?
...jit
QOt
*****
\je
-------
Day 1-Access to greenness
Using GPS to capture
environmental exposure
: All o t
Gdns
Wa
o
Schools
Eaton
GPS Locations and Activity Levels
Sedentary to light activity
Moderate to vigorous activity
Source: Andy Jones, Uni of East Anglia
Time + environment = exposure
tion -
GPS Locations and Activity Levels
Sedentary to light activity
Moderate to vigorous activity
Source: Andy Jones, Uni of East Anglia
B1 -66
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Day 1-Access to greenness
Ambient greenness, house plants,
etc
• Much research is focused on natural spaces, outside.
• Good evidence that indoor nature, pictures of nature, viewing nature
in other ways has health benefits (esp mental health)
• We are very bad at capturing this kind of exposure at a population
level.
Vacant spaces
Zoom in for details
* Chettei
Narberth
Cinnaminson
Cherry
Hill
Leaflet 1 Map data C OpcnSUeotMap contributors. Imagery C Mapbox
# public
# private
# in use
I QzsQ
Conshohocken
Radnor
Marple
aper
•idence
Bl-67
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Day 1-Access to greenness
Vacant lot greening
2003: Pennsylvania Horticultural Society & City of
Philadelphia launched Philadelphia LandCare
2015: PLC has "cleaned and greened" ~7,600 of
Philadelphia's approximately 40,000 vacant parcels
Studies document influence of vacant lot greening
on physiology (heart rate; South et al 2015) & social
life (violent crimes; Branas et al. 2011; Kondo et al
in review) in neighborhoods
¦i
r"
a» «fa><
i H Ij i:
w
— -r
Before
25
Vacant lot survey: Do residents access greened lots?
Physical survey of random 300 lots
(Pre-greening) focus groups and (post-
greening) interviews
X\V>
\ 3 it 4
** *
•> ..**
v.**
-0
Parks and Open Space
Surveyed Lots
~ Use Detected
• No Use Detected
.A °
Heckert, M.; Kondo. M. Surveyed Uses and Perceptions of "Cleaned-and-Greened" Vacant Lots
(under review)
26
Bl-68
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Day 1-Access to greenness
Are greened lots used by residents?
• 10% of lots showed signs of use
• Few noticed the greening, or were
not sure how to interact with the
lots, remaining vacant lots
remained problems
• Signs-of-use lots not statistically
different in terms of density,
playground proximity
Heckert, M., Kondo. M. Surveyed Uses and Perceptions of "Clearied-and-Greened" Vacant Lots
(under review)
Vacant lot greening & greenspace exposure
• Definition of greenspace:
• Do overgrown lots count as green space?
• Exposure effects for who?
• For nearby residents or outsiders?
• How should accessibility be measured and does
it equate to health effect?
• Can we have health benefits without accessibility?
• Does community involvement modify effect?
Bl-69
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Day 1-Built environment
Built Environment and Open Space:
Key Concepts and Metrics
Perry Hystad, Yvonne Michael
May 4, 2015
Built Environment and Health
rw
James F. Sallis et al. Circulation. 2012;125:729-737
American
Heart
Association. Copyright © American Heart Association, Inc. All rights reserved.
Bl-70
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Day 1-Built environment
Built Environment and Natural
Amenities
• Built environment determined by implementation of local
land use plans through zoning and design guidelines.
• Increasing interest in policies to promote urban development
that includes access to natural amenities and limits "grey
space"
- From parks, trails, and open space to green roofs and
green storm water infrastructure
3
Zoning
¦ Zoning ordinances commonly include designations for:
• Public
• Open Space
• Agricultural
• Residential
• Commercial
• Industrial
• Mixed Use
Courtesy of: public health law & policy
Bl-71
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Day 1-Built environment
Green roof
Urban Parks
fHHF1
.1
; ~~~
Green Storm water infrastructure
|T_^!-"rr-
tr^rrr-wrTrrir,
www.facilities.upenn.edu
http://www.uswaterallia
nce.org/
Urban Open Space
Blighted urban vacant land to be transformed into green space
http://www.na.fs.fed.us/
http://axisphilly.org/
Bl-72
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Day 1-Built environment
Health, Safety, and Greening Vacant
Urban Space in Philadelphia
• Across 4 sections of Philadelphia, 4,436 vacant lots totaling
over 7.8 million square feet (about 725,000 m2) were greened
from 1999 to 2008.
• "Before" and "after" outcome differences among treated
vacant lots compared with matched groups of control vacant
lots that were eligible but did not receive treatment.
• Outcomes assessed through Household Health Survey
conducted 1998-2008.
Methods
6 Lots in Northeast
Section
17,717 Lots With 1
or More Open Code
Violations
1,803 Lots in
Northeast Section
49,690 Not
Greened
47,887 Lots in
Other 4 Sections
4,442 Greened
13,308
Randomly
Selected
Control Lots #2
13,308
Randomly
Selected
Control Lots #1
4,436 Eligible
Greened Lots
54,132 Vacant
Lots in
Philadelphia,
1999-2008
25,164 Lots Within
660 Feet (202 m)
of a School,
Recreation Center,
Park, or Business
District
Bl-73
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Day 1-Built environment
Results
• Vacant lot greening was associated with:
- Reductions in gun assaults across all 4 sections of
the city
- Consistent reductions in vandalism in 1 section of
the city
- Residents' reporting less stress and more exercise
Measurement of Green Space in
Built Environment Studies
Objective measures
• Residential proximity to natural environment
— Distance to closest open space, park
• Percent green space
— Land use data
— NDVI
— Google Earth - may also be useful for evaluating quality with
trained assessors
• Street-level audits, including tree audits
Perceived measures via survey
• Quality and presence of amenities including parks and
other public/private recreation facilities
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Day 1-Built environment
Complex Relationships!
• Can we examine
greenspace and
health without
controlling for
other built
environment
factors?
James et al. (2015)
Part pfommity
nrian
Traffic
Park
proximity
GrNnness
NDV1100m
Air pollution
Air Pollution (N0,N02, PM2 5, BC)
Greenness
Noise (Traffic and
Bl-75
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Day 1-Built environment
Urban trees and the risk of poor birth
outcomes (Portland)
Table 1
Selected individual and neighborhood characteristics overall and by tree canopy within 50 m.
Variable
Overall
Tree canopy within 50 m
Tree canopy within 50 m
below median
above median
2007 real market value (S)
268000
260000*
276 000*
Mother did not graduate high school (%)
9.7
10.0
9.4
Mother non-Hispanic white [%)
71.1
73.3*
69.0*
Mother's age (years)
30.3
30.1*
30.6*
Married (%)
78.1
77.1
79.0
Total births
1.80
1.76*
1.83*
Gestational age (weeks)
39.0
39.0
39.1
Birth weight (g)
3425
3407
3443
Delivery cost paid by private insurance (%)
742
73.6
74.8
House age (years)
66.3
64.9*
67.7*
Distance to nearest private open space (m)
300S
2948*
3070*
Distance to nearest public transit stop (m)
679
682
676
Violent crimes within 200 m (2006 and 2007)
1.59
1.60
1.59
' Overall p-value < 0.05 comparing characteristics by level of tree canopy within 50 m of mother's residence.
Miro-Features of the Built
• Architectural
features that
facilitate visual
and social
contacts may be
a protective
factor for elders'
physical
functioning.
Brown et al. 2008 http://ehp.niehs.nih.gov/11160/
Environment
Baseline
12 months
24 months
Self-reported
Gait
Grip
health
speed
strength
Prebaselne
(2000-2002)
Front
entrance
Physical
functioning
Psychological
Ground floor
parking
Support Support
satisfaction satisfaction
Small
setback
Anxiety Depressive
^¦faMSymptoms
B1-76
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Day 1-Built environment
Objective vs. Subjective Measures
UrbanGems: Crowdsourcing Quiet, Beauty and Happiness
change am**, Which place makes you happier?
What percentage of people would agree with you?
Picture Info
CanlTrt
Picture Info
http://urbangems.org/
Findings
• Analyzed the scenes with ratings using image
processing tools.
• Amount of greenery in any given scene is
associated with all the three attributes.
• Urban design elements that increase human
interactions were associated with all three
attributes, especially happiness.
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Day 1-Built environment
Happy
Beauty
Quiet
Key Questions
• How is the built environment and open space conceptualized
and evaluated across disciplines?
• How is greenspace characterized within the definition of the
built environment?
• What is being measured, and what needs to be measured for
accurate estimates of the quality of the built environment?
• What are accepted methods for quantifying exposures related
to the built environment?
• Consideration of the intersection of socioeconomic context
and social behavior with built environment features, quality
and public use.
Bl-78
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Day 1-Design and environmental psychology
Design features — EPA Day 1
Julia Kane Africa
iafrica@hsph.harvard.edu
!HARVARD
SCHOOL OF PUBLIC HEALTH
Center lor Health
and the Clobal Environment
Context: etiology and pathology of stress
Social context
Personality
Design benefits
would likely be
seen in the
appraisal of
demandsand
adaptive
capacities
Environmental Demands (stressors/1 ife events)
Appraisal of Demands and of Adaptive Capacities
% 4 *
Perceived Stress Benign Appraisal
Negative Emotional Responses
Physiological or Behavioral Responses
I
Increased Risk of Physical disease
*
Increased risk of Psychiatric Disease
(feedback)
Cohen etal 1995
Bl-79
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Day 1-Design and environmental psychology
Theory: Introducing Biophilia
'^Biophilia
Hypothesis
Biophilia was released in 1984, and has since generated a design ethos (including much of what underlies
Biomimicry). E. 0. Wilson defines biophilia as 'the innate tendency [in human beings] to focus on life and
lifelike process. To an extent still undervalued in philosophy and religion, our existence depends on this
propensity, our spirit is woven from it, hopes rise on its currents.'
MNrtfteMvAM A* j—
(BioplilifU
EDWARD O. WILSON
Tbc hiinun !««*! «*»** »fKx»ci
What does a restorative environment feel like?
movement, variability, periodicity, and stimuli forthe five senses
Restorative landscapes rapidly evoke positive emotions and hold attention, displacing or restricting
negative thoughts and allowing a reduction in arousal that had been heightened by stress.
BI -80
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Day 1-Design and environmental psychology
Fractal and Fibonacci sequences
d
T
2f
~
1
y
1
kM
oi
c
tl MR
01
Ml IM Is
s r
~
W' x
BE
¦
d
2
SB
Why do we like what we like?Whosayswe like what we like?
B1-81
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Day 1-Design and environmental psychology
Natural Soundscapes
h8o://labs.hbgusa.com/web/animalorchestra/lEARLYS(
"The argument here is that the ambient sounds of an environment mimics a modern-ehy orchestra: the
voice of each creature has its own frequency, amplitude, - mbre, and dura-on, and occupies a unique
niche among the other musicians. This "animal orchestra" or biophony represents a unique sound
grouping for any given biome and sends a clear acous- cal message". - Bernie Krause
B 1-82
-------
Day 1-Design and environmental psychology
Singapore's Nature Pyramid: nature at every scale
National
Monthly
Regional
Weekly
Scale
Frequency, Duration
Intensity of Immersion
International
Yearly, Bi-Yearly. Longer duration,
More intense
"Cultural evolution
and the production
of architecture co-
evolve with the natural systems
of the world: all the works of
humans are "natural", and in
makingthe artifacts of civilization
overthe lastten thousand years we
have changed nature.The understanding
of the natural world - the very conception of
nature isculturallyproduced."
Michael Weinstock, Hypernatural
B1 -83
-------
Day 1-Design and environmental psychology
NATURE IN THE SPACE
1. Visual Connection writh Nature
2. Non-Visual Connection with Nature
3 Non-Rhythmic Sensory Stimuli
4. Thermal & Airflow Variability
Presence of Water
Dynamic & Diffuse Light
Connection With Natural Systems
NATURALANALOGUES
8. Biomorphic Forms & Patterns
g. Material Connection with Nature
10. Complexity & Order
NATURE OFTHE SPACE
11 Prospect
12. Refuge
13. Mystery
14. Peril
NY TIMES BIRCH GARDEN. PHOTO CREDIT: HUBERT I. STEED
HOK/Biomimicry Institute: Nature as mentor, model and measure
k
•rp ms>
w
1. What is the function of the
design?
2. In nature, whose survival depends
on solving a similar problem?
3. Identify operating parameters of
the biome:
-dimate conditions (wet, cold, hot,
low/high pressure, high/low UV)
- Mitrient conditions (poor, rich)
- Social conditions (competitive,
cooperative)
- Temporal conditions (dynamic,
static, aging)
4.Through pattern recognition,
emulate these relevant species-or
biome-specific design principles for
literal, abstracted or conceptual
applications.
Recognizing that the fluid mechanics of a bird's bill in water
and bullet train in air are similar
h8p://bit.ly/llW5h97
B1-84
-------
Day 1-Design and environmental psychology
B1-85
-------
Day 1-Design and environmental psychology
Designing with nature and natural design cues
B1-86
-------
Day 1-Specific populations, exposure considerations
Specific populations,
exposure considerations
Richard Mitchell, Yvonne
Michael, Aaron Hipp
May 4
Estimating Greenspace Exposure & Benefits for
Cumulative Risk Assessment Applications
Technical Working Group Meeting
May 4-5, 2015
U.S. Environmental Protection Agency
26 Martin Luther King Drive West, Cincinnati, OH 45220
1
Why specific populations?
• If access to nature is salutogenic (or pathogenic)
• Potential to increase inequalities in health
• Potential to decrease inequalities in health (equigenic)
• What would vary by population sub group?
• Differential exposure or access
• Environmental (in)justicedetermining proximity/quality
• Culture/ behaviour determining visits
• Culture / behaviour determining activities and perceptions
• Differential susceptibility
• Particularly positive or adverse impacts
• Which populations should we care about and why?
• Vulnerable groups, with particular health problems
• Groups where we suspect social, cultural and environmental processes work very differently
to the majority
• We should never assume 'one size fits all' in our science. Often the exceptions are those
which teach us most.
2
B1-87
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Day 1-Specific populations, exposure considerations
Gender
It's unlikely that residential location for men and women is responsible for
differential access to nature (residential segregation by sex is...rare)
Yet, evidence suggests that women are less likely to access natural
environments, where available, than men, particularly urban parks.
• Some evidence that some aspects of quality are more important to women
Evidence is mixed over whether women who do access green spaces use
them in different ways or with different frequencies.
Do we need to measure exposure differently for men and women?
• Perhaps this is about being sensitive to different aspects of exposure; for example
the proximity=exposure relationship may be very different from men and women,
but once they are within a space, activity/interaction may be similar
Who uses their green space? (data from Scotland n=cl000)
Women about 80% more likely
than men to be low or no users.
likiiii
Every day Several times Once a week Several times Once a month Less often Not at all
a week a month
¦ Men Women
Mitchell R. Paper in preparation. Data from the Scottish Social Attitudes Survey 2009
Bl-88
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Day 1-Specific populations, exposure considerations
Men and women who do use their green spaces, use them for similar things.
Just to pass through
Somewhere to take children/
grandchildren
To walk the dog
Somewhere to go with family or
friends
For meeting people
For relaxation
For fresh air
For exercise (including walking)
% Who use green space
Socio-economic position / race
• Many studies looking at inequitable access to nature, where access is defined by
proximity or landcover
• Dominated, numerically at least, by studies on race and nature from the USA. European
and Australasian studies have tended to focus more on socio-economic position
• Typically use conventional measures of access / availability & then explore whether these
vary by SEP / ethnic group (either at neighbourhood or individual level)
• Mixed results, but generally evidence for environmental injustice in terms of proximity &
quality, some suggestion of differences in terms of biodiversity too
• Also evidence for lower levels of use among more deprived, vulnerable and non-white
groups, even where green spaces are available
• Evidence that spaces are perceived differently (as being for white or dominant groups for
example)
• Do we need to measure exposure differently for these groups?
• Again, questions the 'proximity=exposure' relationship
• We must better understand that proximity/exposure relationship!
6
Women
B1-89
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Day 1-Specific populations, exposure considerations
Socio-economic differences in
50 -I
AIR
~ CORINE
¦ OSMM
~ Hybrid
1 (richest)
5 (poorest)
Income deprivation
Who uses their green space?
S 40
Once a week 3-4 times per 1-2 times per Once every 2 Once or twice Less often
or more month month to 3 months peryear
-AB «C1 C2 ¦ DE
Source: K Ord, PhD thesis 2014. n=1516
Bl-90
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Day 1-Specific populations, exposure considerations
1
Does inequality in use of green space reduce when it is readily available?
J
2.5
ID
¦ | 1-5
0.5
~ 2nd Tertile
¦ Bottom Tertile
<25%
25-<50% 50-<75%
Green Space Availability
75%+
Figure 7.12 Income related inequality in participating in green physical activity by green
space availability. Odds ratios given relative to the reference group (Top Income Tertile,
Odds Ratio = 1.00) and bars indicate 95% confidence interval (n=1209). The interaction
effect did not reach significance (x2 = 6.76, P = 0.3437) 1 •go, and income
Source: K Ord, PhD thesis 2014
Does inequality in use of green space reduce when it is readily available?
s ~
ro >
.9- 13
€ «
2. S
0.5
<25%
~ 2nd Tertile
¦ Bottom Tertile
w if i
25-<50% 50-<75%
Green Space Availability
75%+
Figure 7.12 Income related inequality in participating in green physical activity by green
space availability. Odds ratios given relative to the reference group (Top Income Tertile,
Odds Ratio = 1.00) and bars indicate 95% confidence interval (n=1209). The interaction
effect did not reach significance (x2 = 6.76, P = 0.3437) 1 ad>"»,ed»9e and
Source: K Ord, PhD thesis 2014
Bl-91
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Day 1-Specific populations, exposure considerations
Life Course Approach
DEVELOPMENTAL
ENVIRONMENT
WORK, EXPERTISE
& EXPERIENCE
SKILLS &
KNOWLIDGL
PRENATAL INEANCY CHILDHOOD ADOLESCENCE ADULTHOOD OLD AGE
Parental support &
early years education
Education, Employment & Professional development
Secure, safe & supportive environment
Services for well-being, health, prevention & care
Influences
and Actions
along the Life
Course.
Model
developed as
part of the
Fair Society,
Healthy Lives
report (2011)
11
Relative
Magnitude
of Influence
Age (years)
FIGURE 2: INFLUENCE OF HEALTH STATUS ACROSS THE LIFE COURSE. Across the life course, the health status of individuals is a
function of endogenous factors (genetic, physiological, psychological), family influences, and a range of influences from the immediate
community (school and workplace), and the larger community (neighborhood, city, and nation). As illustrated in figure 2. the relative influence of
these factors changes as a function of age Adapted from Nordio S. 1078. Needs in Child and Maternal Care. Rational Utilization and Sooal-
Medical Resources Rn/iats Italians dt Rediatrsa 4:3-20.
From Neal Halfon
Bl-92
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Day 1-Specific populations, exposure considerations
Age Cohort and Green space
Differential exposure/access
• Children's independent mobility to local urban green space is limited by
distance to closest park, perceived safety, and parenting social norms
• Mobility limitations may keep older adults homebound, with limited access
to green space
• Older adults and teens less frequent users of green space
Differential susceptibility
• Allergic sensitization may vary by age
• Risk of chronic conditions and co-existing geriatric impairments increase with
age
Christian et al, Journal of Physical Activity & Health, 2015; Rosso et al, Journal of Aging Research 2011
13
Relative to other age groups,
seniors and teens use parks less
35
30
25
(SI
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Day 1-Specific populations, exposure considerations
Relative to their numbers in l-mi
radius, children/teens use parks more
0.1
c
o
ju 0.05
3
Q.
O
Q_
O
4-»
O
0
Children Teens Adults Seniors
Ratio of Park Users to Local Population in a 1-mile Radius cohenda, et ai,
Some general weaknesses
• We know very little about how / whether susceptibility to the benefits
(harms) of contact with nature varies by population sub-group (more on
this tomorrow)
• This is because few experimental studies are designed to explore these
differences
• The conventional measures of exposure - particularly those based on
proximity to green spaces or distance, rarely include measures of actual
visits!
• Yet, to work at a population level (i.e. millions of people), we need those
conventional measures.
• We know that some groups live further from, or appear to have worse
access to, natural spaces, but we tend not to know how this affects their
use of those spaces.
16
Female
Bl-94
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Day 1-Specific populations, exposure considerations
Discussion Questions
• Do we need to measure exposure differently for specific populations,
e.g., by gender, SEP/race, age?
• Does relevant type of exposure vary by group?
• Is duration or frequency different?
• Is exposure pathway different?
• How do we incorporate a life course perspective into our exposure
assessment?
17
Bl-95
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Day 1-Specific populations, exposure considerations
Why do these effects occur?
Bl-96
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Day 1-Specific populations, exposure considerations
-------
Day 1-Specific populations, exposure considerations
Experimental evidence: field
ParV3.-jimtsi*i f.OwtwiT,hpwiT. Th« c**5'CO|>tN<*V
-------
Day 1-Specific populations, exposure considerations
Experimental evidence: field
•ECORO
(ct Walking in the City Area (d) Watching the Landscape in the City Area
Ft
Fig. 1 CNanpr in salivary
cir.
ceimcxl etmccmrjiKa after
~
•. KTVriii|" juiiI ur.ill.iilg.
¦£i,,
Mkiji ± -J imJn-iJ ck'vhjiiim
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iSDfc ** p < O.CH;p tiilue
e
hy i tu'ii
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2
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=
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Environ Health Prtv Med (2010) 15:15-26
Bl-99
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Day 1-Specific populations, exposure considerations
Bl-100
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Day 1-Specific populations, exposure considerations
For whom are the woods scary? Who doesn't benefit?
v ki l jj
¦
Bl-101
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Day 1-Specific populations, exposure considerations
Why aren't rural areas, where nature is pervasive, super-
healthy? Is it the change in environment that matters?
Bl-102
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Day 1-Exposure metrics, links to health (Attention restoration example)
GREEN SPACE, ART & SRT
William Sullivan, University of Illinois
ATTENTION RESTORATION THEORY
d
ATTENTION RESTORATION THEORY
1 f&nti"
1 ft • ¦
jjfm i MM
ATTENTION RESTORATION
THEORY
Attention
ATTENTION RESTORATION
THEORY
Attention
Invduntary
ATTENTION RESTORATION
THEORY
Involuntary
Directed
(Paying Attention)
Bl-103
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Day 1-Exposure metrics, links to health (Attention restoration example)
ATTENTION RESTORATION
THEORY
Attention
Effort
Involuntary
Directed
(Paying Attention)
ATTENTION RESTORATION
THEORY
Attention
Effort
Involuntary
No
Directed
(Paying Attention)
ATTENTION RESTORATION
THEORY
Attention
Effort
Involuntary
No
OJrcctcc
(Paying Attention J
Yes
Bl-104
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Day 1-Exposure metrics, links to health (Attention restoration example)
ATTENTION RESTORATION
THEORY
Attention
Effort
Fatigue
Involuntary
No
Directed
(Paying Attention)
Yes
ATTENTION RESTORATION
THEORY
Attention
Effort
Fatigue
Involuntary
No
No
Directed
(Paying Attention)
Yes
ATTENTION RESTORATION
THEORY
Attention
Effort
Fatigue
Involuntary
No
No
Directed
(Paying Attention)
Yes
Yes
ATTENTION FATIGUES
# ~ —
PAYING ATTENTION
Matters for everything we care about
• Learning
• Problem solving
• Planning, initiating & carrying out tasks
• Self monitoring & self regulation
• Effective social functioning
Bl-105
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Day 1-Exposure metrics, links to health (Attention restoration example)
SYMPTOMS OF MENTAL
FATIGUE
Inattentiveness
SYMPTOMS OF MENTAL
FATIGUE
Impulsiveness
MAIZE BOOKS
ATTENTION RESTORATION
Bl-106
SYMPTOMS OF MENTAL
FATIGUE
Irritability
ATTENTION RESTORATION
Environments impact attention
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Day 1-Exposure metrics, links to health (Attention restoration example)
DONGYING LI
EVIDENCE
Bl-107
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Day 1-Exposure metrics, links to health (Attention restoration example)
f
M uud«tts
ACADEMIC ACTIVITIES
> 5 nmmAm ipwth
• Pnwf
~ SutMnctna {4029>I3)
ATTENTION MEASURES
• Dcfte* farvmrrH
• Dtfita bacicwKttia
• Stroof) color wot d
Blue
Yeilow Red Bine
Bl-108
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Day 1-Exposure metrics, links to health (Attention restoration example)
PHYSIOLOGICAL MEASURES
Measures of EKG, BVP, SC and
11
DO VIEWS TO TREES MPROVE LEARN NG7
EFFECT OF WINDOW VIEW ON
_ ATTENTION.
After classroom casks After break in room
EFFECT OF WINDOW VIEW ON
_ ATTENTION _
H No Wnd* Bimr ¦
6.
K
J"
13
u
l 5
J
CO
*i 4.5
5b
b
After classroom tasks After break in room
CLASSROOM WINDOW & ATTENTION
hi I Ccurr. h Color Slroop les:
Bl-109
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Day 1-Exposure metrics, links to health (Attention restoration example)
DO VIEWS TO TREES IMPACT STRESS?
n»<=
m
CLASSROOM WINDOW & STRESS RECOVERY
$
.J
p j 11
§si
r®
HOW MUCH NATURE?
Low Medium High
Concentration of Nature
PARTICIPANTS
60 fiea thy adults
Age 8 31 years old, M=21
Gender: 8 females, 79 ma es
PROCEDURE
tobodurtlon 3' rest
3' r®st Stsvty
Bl-110
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Day 1-Exposure metrics, links to health (Attention restoration example)
PROCEDURE
Introduction 3' rest
5-minute speech
5-minutes of subtraction
PROCEDURE
Introduction 3' rest
53E.
3' rest Suivqr
EXAMPLES FROM VIDEOS
EXAMPLES FROM VIDEOS
-------
Day 1-Exposure metrics, links to health (Attention restoration example)
EXAMPLES FROM VIDEOS
TEN 3-D VIDEOS
RANDOM ASSIGNMENT
MULTIPLE MEASURES
CORTISOL 3-TIMES
STRESS RESPONSE
SKIN CXNOUCTANCT
Bl-112
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Day 1-Exposure metrics, links to health (Attention restoration example)
MULTIPLE MEASURES
I Subjective
Introduction
3' rest
Stress 6 nature
3' rest Survey
Visual Analog Scale (VAS)
Anxiety
Not at all | ^ 1 Extremely
Tension
Not at all | 1 Extremely
Not at all | || 1 EMremely
Narratives survey: stress recovery experience
Create stress?
Change in Cortisol
H=
Change in Skin Conductance
Baseline After Stressor
Skin Conductance
Bl-113
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Day 1-Exposure metrics, links to health (Attention restoration example)
EXAMPLES FROM VIDEOS
DOSE-RESPONSE CURVE
NARRATIVES
Bl-114
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Day 1-Exposure metrics, links to health (Attention restoration example)
Bl-115
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