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


Simple

Quantifable

Repeatable

Transferable

Representative

http://www.zsl.org/science/research-projects/lpi,1162,AR.html

WWF - Living planet database





Simple

Quantifiable

Repeatable

Transferable

Representative

Accurate

Cheap

Aerodata

International

10 cm

imagery -

Google

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

http://www.wmo.int/pages/prog/gcos/index.php?name=EssentialClimateVariables


















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

11

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!

12

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:




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:




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 -

Google

Dutch

topographic

map

1:25000


























MEASUREMENTS OF SUSTAINABILTY SHOULD BE: ACCURATE AND CHEAP – FOREST AROUND ENSCHEDE

Netherlands




JRC Forest Map

2006

(FMAP2006)

IRS-P6

Aerodata

International

10 cm air

photo -

Google

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)

Documents

Remote sensing for sustainable landscapes