Download - Remote sensing for sustainable landscapes
REMOTE SENSING FOR SUSTAINABLE LANDSCAPES ANDREW SKIDMORE
SUSTAINABLE LANDSCAPES
Protected areas: 10-15%
land surface
>100,000 ha
0.12 ha/capita
>1,000,000 ha
0.08 ha/capita
Wilderness area is
larger than protected
areas
http://www.cbd.int/gbo1/chap-05.shtml
SUSTAINABLE FOOD SUPPLY CHAINS
Characteristics of a sustainable
food supply chain?
“lean & green”
“indefinite” production
no negative impact on
“nature” or “biodiversity”
How to measure with remote sensing?
MONITORING LANDSCAPE SUSTAINABILITY COVER TYPES - FOREST OR AGRICULTURE?
Teak inter-planted with sweet potato
Native cypress pine and grazing
Walnut and cherry interplanted with
rapeseed and beans France
http://archive.iwlearn.net/www.sprep.org/www.sprep.org/SLM/Linkages-SLM.htm
PLANT TRAITS
Plant traits may be measured
from EO or in situ
LAI or canopy cover
Biomass & yield
Productivity – fAPAR
Specific leaf area
From plant traits derive land
cover and plant functional types
Cover type
Ecosystem distribution
Leaf life span
Cornelissen, J. H. C. et al. (2003)
(Reich et al. 1992)
TRAITSCLASSES (not vice versa)
MEASURES OF SUSTAINABILITY SHOULD BE:
Simple
Quantifiable
Repeatable
Transferable
PTs = LAI, biomass, productivity, specific leaf area
MEASURES OF SUSTAINABILITY SHOULD BE:
Simple
Quantifable
Repeatable
Transferable
Representative
http://www.zsl.org/science/research-projects/lpi,1162,AR.html
WWF - Living planet database
MEASURES OF SUSTAINABILITY SHOULD BE:
Simple
Quantifiable
Repeatable
Transferable
Representative
Accurate
Cheap
Aerodata
International
10 cm
imagery -
VARIABLES TO MEASURE SUSTAINABILITY PROPOSED BY SCIENTIFIC COMMUNITIES
Essential climate variables
Essential biodiversity variables
Essential ocean variables
GLOBAL CLIMATE OBSERVING SYSTEM ESSENTIAL CLIMATE VARIABLES (ECV)
50+ GCOS Essential Climate
Variables (ECVs) (2010)
Land cover, fAPAR, LAI,
biomass, (fire) disturbance,
soil moisture, soil carbon
Domain GCOS Essential Climate Variables
Atmospheric
(over land, sea
and ice)
Surface:[1] Air temperature, Wind speed and direction, Water vapour,
Pressure, Precipitation, Surface radiation budget.
Upper-air:[2] Temperature, Wind speed and direction, Water vapour, Cloud
properties, Earth radiation budget (including solar
irradiance).
Composition: Carbon dioxide, Methane, and other long-lived greenhouse
gases[3], Ozone and Aerosol, supported by their
precursors[4].
Oceanic
Surface:[5] Sea-surface temperature, Sea-surface salinity, Sea level, Sea
state, Sea ice, Surface current, Ocean colour, Carbon
dioxide partial pressure, Ocean acidity, Phytoplankton.
Sub-surface: Temperature, Salinity, Current, Nutrients, Carbon dioxide partial
pressure, Ocean acidity, Oxygen, Tracers.
Terrestrial
River discharge, Water use, Groundwater, Lakes, Snow cover, Glaciers and ice
caps, Ice sheets, Permafrost, Albedo, Land cover (including vegetation type),
Fraction of absorbed photosynthetically active radiation (FAPAR), Leaf area
index (LAI), Above-ground biomass, Soil carbon, Fire disturbance, Soil
moisture.
http://gosic.org/ios/MATRICES/ECV/ECV-matrix.htm
10
ESSENTIAL BIODIVERSITY VARIABLES
Allelic richness
Phylogenic diversity
Gene diversity
Functional attributes (diet,
breeding system, body mass)
Co-ancestry
Number and frequency of key
traits
Turnover (beta-diversity)
Degree of protection
Use rate by humans
Use benefits to humans
(economic, spiritual, cultural
…)
Non-use benefits (existence,
aesthetic…)
Which may not be measured with IS or EO
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ESSENTIAL BIODIVERSITY VARIABLES
Species occurrence
Population abundance
Population structure
Number and frequency of
varieties/breeds
Phenology (PhiX)
Movement patterns
Life history and demography
Physiological characteristics
Ancillary attributes
Structural type
Disturbance regime
Ecosystem extent (type)
Cover (biomass, LAI, height)
Ecosystem distribution
Carbon sequestration
(balance and storage)
Photosynthetic activity (GPP =
fAPAR = LUE)
Respiration (NPP)
Allocation of biomass
(functional type)
Leaf Nitrogen content
Leaf phosphorus limitation
Secondary products
PROXIES FOR LANDSCAPE SUSTAINABILITY – EASY TO MEASURE!
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ESSENTIAL (BIODIVERSITY AND CLIMATE) VARIABLES IN AGRICULTURE
Biomass
fAPAR
Phenology
Crop yield
Crop growth
Crop development
Agricultural land is usually managed for the provision of food,
fiber, and fuel, often at the expense of other ES
What are the main tools used at present?
Remote sensing derived data products
Crop Yield Forecasting System
ECOSYSTEM SERVICES FROM AGRICULTURAL LAND PROVISION OF FOOD, FIBER AND FUEL
ECOSYSTEM SERVICES FROM AGRICULTURAL LAND REMOTE SENSING DERIVED DATA PRODUCTS
Meteosat 2nd generation
5 km resolution
JRC Monitoring Agricultural
Resources (MARS)
Used in the MARS crop yield
forecasting system (MCYFS)
ECOSYSTEM SERVICES FROM AGRICULTURAL LAND
CROP YIELD FORECASTING SYSTEM
JRC
Monitoring
Agricultural
resources
(MARS)
http://mars.jrc.ec.europa.eu/mars/About-us/AGRI4CAST/MARS-Bulletins-for-Europe
PHENOLOGY AND CROP DEVELOPMENT
Phenology is about the timing of periodic natural events
Satellite time series evaluate variability and trends
Used for studies on food security & biodiversity
Provisioning of ecosystem services from agricultural land
Recognize 3 crops
from their time series
BARLEY (R-Sq=75%)
ECOSYSTEM SERVICES FROM AGRICULTURAL LAND
CROP AREA – FROM SPACE DATA TO LANDSCAPE LEVEL
Sunflower (R-Sq=96%)
WHEAT (R-Sq=98%)
Ecosystem services at farm/local scale:
soil nitrogen & water supply
fragmentation & biodiversity
OTHER ECOSYSTEM SERVICES FROM AGRICULTURAL LANDSCAPES
Ecosystem services at farm/local scale:
soil nitrogen & water supply
fragmentation & biodiversity
OTHER ECOSYSTEM SERVICES FROM AGRICULTURAL LANDSCAPES
NITROGEN FERTILIZER APPLICATION
FOLIAR NITROGEN – INPUT TO SOIL NITRATE MODELS
Operationalization of European
Water Framework Directive
Detecting soil and foliar
nitrogen http://onlinelibrary.wiley.com/doi/10.1002/eet.446/abstract
Foliar nitrogen
grasses
Geology
Possible ecosystem services from farms cooperating at a
landscape scale:
soil nitrogen & water supply
fragmentation & biodiversity
OTHER ECOSYSTEM SERVICES FROM AGRICULTURAL LANDSCAPES
BAT BIODIVERSITY IN LOWER SAXONY
Pond bat
Hollow trees/roofs
Near threatened
Western Barbastelle
Old growth forest
Near threatened
NABU project on improved
monitoring of bats in Lower Saxony,
SUSTAINABILITY BOSWELLIA PAPYRIFERA –18,000 KM2 PROBABILITY OF TREE OCCURRENCE - FRANKINCENSE PRODUCTION
CRETAN WALL-LIZARD (PODARCIS ERHARDII)
15 m resolution farm level
ASSESSING SPECIES FROM IMAGE SPECTROSCOPY ARE SPECIES BEING SUSTAINED IN A LANDSCAPE OVER TIME?
27 salt marsh species could be discriminated based on their spectra
Possible to compare species extent and change over time
80% map accuracy
Schmidt and Skidmore 2002
27
API 30% map
accuracy
FIRE SALAMANDER (SALAMANDRA SALAMANDRA)
Original field observations
from 1996 in Lower Saxony
2014
2002
2014
2014
2014
habitat
change
suitable
habitat
FRAGMENTATION
Entire panda population in China, at least 30 fragmented populations exist, in which many fewer than 50 individuals.
In Qinling Mountains, at present, there are 4 isolated sub-populations. Research and monitoring shows there no communications between them.
GIANT PANDA MOVEMENT
GIANT PANDA AND VEGETATION
RPDi = (NDVIi – NDVImin) / (NDVImax - NDVImin)
16 days composition of MODIS-NDVI
Wang et al. 2010, Photogrammetric Engineering and Remote Sensing
SUSTAINABLE LANDSCAPE? HABITAT FRAGMENTATION CRESTED IBIS AND WINTER FLOODED RICE FIELDS
(BLI)
SPECIES DISTRIBUTION MODELS ANIMAL TRACKING, CLIMATE CHANGE AND FRAGMENTATION
2010
2050
Species probability of occurrence Species distribution change
due to climate change
Species distribution change
due to fragmentation
MEASUREMENTS OF SUSTAINABILTY SHOULD BE: ACCURATE AND CHEAP – FOREST AROUND ENSCHEDE
Netherlands
http://upload.wikimedia.org/wikipedia/commons/f/fe/Enschede-topografie.jpg
http://www.earthzine.org/2012/07/25/pan-european-forest-maps-derived-from-optical-satellite-imagery/
http://forest.jrc.ec.europa.eu/download/data/google-earth-overlays/
JRC Forest Map
2006
(FMAP2006)
IRS-P6
Aerodata
International
10 cm air
photo -
Dutch
topographic
map
1:25000
MEASUREMENTS OF SUSTAINABILTY SHOULD BE: ACCURATE AND CHEAP – FOREST AROUND ENSCHEDE
Netherlands
http://upload.wikimedia.org/wikipedia/commons/f/fe/Enschede-topografie.jpg
http://www.earthzine.org/2012/07/25/pan-european-forest-maps-derived-from-optical-satellite-imagery/
http://forest.jrc.ec.europa.eu/download/data/google-earth-overlays/
JRC Forest Map
2006
(FMAP2006)
IRS-P6
Aerodata
International
10 cm air
photo -
Dutch
topographic
map
1:25000
GLOBCOVER
ENVISAT
MERIS 300m
TO SUMMARIZE
1. Use simple and repeatable metrics to assess sustainability
2. Remote sensing can measure landscape sustainability metrics:
biomass, crop yields, soil nitrate, keystone and flagship species
3. Operational EU systems are at a regional/continental scale
4. Remote sensing is a perfect tool for assessing and monitoring
sustainable landscapes for agricultural industry, farmers and
conservation e.g. landscape fragmentation
5. Need to incorporate finer resolution data and analysis for
monitoring ecosystem services and biodiversity
6. Set up an operational biodiversity observation network (like the
MARS system)