Remote Sensing For Assessing
Environmental Impacts Based On
Sustainability Indicators
John C. Trinder
School of Surveying and SIS
UNSW
Sydney, Australia
1st Vice President ISPRS
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IMPACT OF HUMAN DEVELOPMENT
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Humans are modifying the energy and mass
exchanges that occur between the atmosphere,
oceans and biota
The resulting changes may be beyond the
resilience of the Earth’s environment to absorb
them
Sets of compatible global data are required for
analysis of key terrestrial variables
WSSD declaration includes the three ‘pillars’ of
Sustainable Development: economic, social and
environmental protection
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SUSTAINABLE DEVELOPMENT
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Sustainable Development:
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Adoption of practices of environmental use and management
which provides for a satisfactory standard of living today,
and which will not impair the capacity to provide for future
generations.
Development that meets the needs of the present without
foreclosing the needs or options of future generations
It requires equilibrium between production and the
consumption of energy
Achieving a sustainable society cannot be divorced
from issues of equity, welfare, lifestyle and standards
of living
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SUSTAINABILITY IN TERMS OF
ECOLOGICAL ECONOMICS
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Need to take into consideration economical, ecological
and sociological issues
Ecological economics – based on transformation of
‘Natural Capital’ into ‘Man-Made Capital’
Optimal growth occurs when marginal cost of natural
capital transformation equals marginal benefits to
mankind
There is a limit to the extent of natural capital
When development involves transformation above
optimum, it is unsustainable
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TOWARDS A SUSTAINABLE FUTURE
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Scenarios for developing a sustainable human society
(Gallopin & Raskin 2002) :
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market forces
policy reform
eco-communalism
muddling through
Ecosocial market (Rademaker 2004 )
consensus, and respect for civil rights and human equity
 human behaviour is agreed globally by social contract
Decisions based on inputs from all stakeholders (Azapagic
2005)
Economic, social and ecological issues must be considered
when developing sustainable society
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Sustainable Development Indicators (SDI)
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developed to monitor progress and assess the impact of
policies on natural resource development
exact measures of single factors and their combination
into meaningful parameters
compresses information on a relatively complex
process, trend or state into a more readily
understandable form
may be application specific
should be unbiased
sensitive to changes
convenient to communicate and collect.
separate SDIs for economic, social and ecological
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Development of SDIs
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Many examples on SDIs
OECD - 23 indices based on natural sciences,
policy performance, accounting framework and
synoptic indices.
IISD – International Institute for Sustainable
Development
UN – DSD
World Bank
Alliance for a Sustainable Atlanta
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Environmental and Sustainability Indicators for
Canada (NRTEE) (2003)
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National natural and human capital indicators
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Supplementing existing economic indicators will
provide a more robust picture of the state of the
national capital
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Air quality
Fresh water
Green house gas emissions
Forest cover
Wetlands
Human capital (Education attainment)
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Typical SDIs for Land Practices
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Sustainable land practices:
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nutrient balance, yield trend and variability, land use diversity
and land cover
amount of tree cover
impact on soil and/or water
conservation of native habitats.
Agriculture
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yield trends, coefficients for limited resources, material and
energy flows and balances, soil health, modelling and bioindicators
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Analysis and Combination of SDIs
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Multiple SDIs cause difficulties in assessing
sustainability
Methods suggested to combine multiple SDIs to
produce a measure of sustainability
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Rule based system
Fuzzy logic analysis
Principal component analysis
Concept is still being researched – is it
appropriate?
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SDI FRAMEWORKS
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Simple approach to developing SDIs inadequate
New approach - frameworks for SDIs which include
linkages between the three areas:Typical conceptual frameworks recommended by authors:
domain-based, issue-based, goal-based
Olalla-Tárraga (2006)
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hierarchical concept
economic, social and ecological each subdivide into ‘area’,
‘objective’, ‘attribute’, and ‘indicators’
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Dimension
Area
Objective
Environment
Sustainable
Development
Social
Attribute
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D
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C
A
T
O
R
S
Economic
Hierarchical framework of indicator system.
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Characteristics of Sustainability Indicators
(Becker 1997)
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Criteria
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Scientific Quality
Ecosystem relevance
Data Management
Sustainability Paradigm
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Scientific Quality
Indicator really measures what it is supposed
to detect
Indicator measures significant aspect
Problem specific
Distinguishes between causes and effects
Can be reproduced and repeated over time
Uncorrelated, independent
Unambiguous
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Ecosystem relevance
Changes as the system moves away from equilibrium
Distinguishes agro-systems moving away from
sustainability
Identifies key factors leading to unsustainability
Warning of irreversible processes
Proactive in forecasting future trends
Covers full cycles through time
Corresponds to aggregation level
Highlights links to other system levels
Permits trade-off detection and assessment between
system components and levels
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Remote Sensing for Sustainable Development
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Identify parameters measurable by remote
sensing sensors
Relate them to sustainability indicators
Typical parameters:
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Vegetation stress
Agricultural
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Yield estimates
Soil condition and erosion
Land subsidence due to mining or water withdrawal
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Vegetation stress
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Effects of stress on vegetation caused by withdrawal of
underground water has been studied in Florida
Vegetation - pond-Cyprus
Laboratory scans in NIR and mid infrared regions of the
spectrum of dried milled branch tips
Chemical changes in the vegetation revealed in the data
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An indicator of unsustainable withdrawal of water from the
aquifers
Similar studies of stress on vegetation due to lack of water have
been made on red gum plantations in Australia
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Agricultural yield estimates
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Remote sensing data, combined with agrometeorological data, can provide daily, weekly and
annual information on crop condition and status
This data can also be used to generate yield
estimates and comparisons of annual production
trends
Similar measurements made in Canada
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Soil condition and erosion
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Remote sensing input - direct and indirect indicators may
be derived through spectral characterisation of the soil (if
exposed) or of vegetation conditions (if covered)
changes of the soil surface composition over time are
indicators of land degradation, salinity and erosion
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Mapping surface expression of salinity in south western Australia
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Land subsidence due to mining or water
withdrawal
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Differential interferometric SAR (DInSAR) is a
precise for measuring mine subsidence
Can detect illegal mines by surface subsidence
Subsidence of surface due to withdrawal of
underground water
Permanent scatterers over built-up areas –
PSInSAR can give very high precisions of ground
subsidence.
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Typical Plan View
of Longwall Panels
Coal remaining
Goaf
Direction
of mining
Goaf
Remaining chain pillars
between longwall panels
Longwall
shearer
Coal face
Development
headings to
create new
longwall panels
Solid coal
Extracted
longwall
panel
Current
longwall
panel
Future
longwall
panel
Main Headings
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(typically a slice of 1 metre
width is removed), the
shearer, conveyor and
hydraulic roof supports are
pushed forward allowing
further collapse of the
strata behind the supports
into the goaf.
shearing and cracking of
the stata depends upon the
strata geology, the longwall
width, the seam thickness
and the depth of cover.
Cross Section of a Typical
Longwall Face
Goaf
Coal Seam
Hydraulic
roof supports
Longwall
shearer
& conveyor
Direction
of mining
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Mine subsidence in 24 Hours
– ERS Tandem DInSAR
Subsidence
• Master: 29 October
1995, ERS-1; Slave: 30
October 1995, ERS-2;
• Remarkable result of
subsidence in 24 hours
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PSInSAR
result of
ground
subsidence in
Perth
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Trend of
groundwater level
1995 - 2004
(CSIRO)
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REVIEW - TOWARDS A SUSTAINABLE
FUTURE
Scenarios for developing a sustainable human
society
Ecosocial market (Rademaker 2004 )
Decisions based on inputs from all stakeholders
(Azapagic 2005)
Economic, social and ecological issues must be
considered when developing sustainable society
Remote sensing deals primarily with ecological issues
Linking to economic and social issues is essential
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Linking Remote Sensing to Social Sciences and
Economics
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Remote sensing determines ‘what’ and ‘where’
of changes
Social sciences aim to determine ‘why’ and
‘who’
Economics deals with ‘how’ and ‘who’
Relating data from social sciences and
economics to remote sensing presents
considerable difficulties.
The reason for suggesting frameworks
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where & what
why & who
how & who
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where & what
why & who
how & who
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Conclusions
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Definitions of sustainable development have been
given
Assessment of sustainability should be based on
appropriate indicators - SDIs
There is still a lot to be learned about SDIs to ensure
sustainability of development
The SDIs must consider relationships within the three
areas of sustainability – economic, social and
environmental
Examples demonstrate how remote sensing can
contribute to developing SDIs
There is still significant unexplored potential for
remote sensing to contribute to further the
development of SDI
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