Transcript Reducing emissions from deforestation - uni

Global Observation of Forest and Land Cover Dynamics
Slides for Stephen Briggs
Martion Herold
Global Observation of Forest and Land Cover Dynamics
0 Background UNFCCC
Current focus: Land monitoring and the UNFCCC
Observing essential climate variables (ECV)
 Reduce uncertainties in monitoring the
global climate system
 Land cover, biomass and fire as key variables
 Development of standards and prepare
implementation programmes
www.fao.org/gtos/topcECV.html
Reducing emissions from deforestation and
forest degradation (REDD)
 Stronger mitigation role of developing
countries in post-2012 agreement
 Remote sensing capabilities to build national
forest carbon monitoring systems
Major investments in land monitoring,
estimation and accounting
http://www.gofc-gold.uni-jena.de/redd
Observing land cover as ECV
www.fao.org/gtos/
Global Observation of Forest and Land Cover Dynamics
1/2/3 Background REDD
Design positive incentives:
Carbon Stock
Suriname
Sectoral Crediting Baselines
Vanuatu
International
incentive mechanisms
Direct Barter
need to work for all nations
PNG
Programatic
Solomon’s
Bolivia
Indonesia
or sectoral scale
Similar to programmatic CDM
Costa Rica
China
Calculate historical and
India future baseline carbon
stock – credits gained for performance below
baseline
Draft decision text for Copenhagen
Foundations for REDD monitoring
1. Guidance for monitoring and implementation provided
under the UNFCCC;
2. Monitoring should be part of the national REDD
implementation strategy and objectives;
3. Knowledge in the use and application the methods of IPCC
LULUCF good practice guidelines;
4. Existing national forest monitoring capabilities;
5. Expertise in estimating terrestrial carbon dynamics and
related human-induced changes;
6. The consideration of different capabilities for monitoring
forest changes in the historical and for the future.
IPCC principles and developing country capacities
1. Consistency: use of heterogeneous data sources rather
than a systematic and consistent monitoring
2. Transparency: expert opinions, independent assessments
or model estimations are commonly used as data
3. Comparability: few countries have experience in using the
IPCC GPG as common estimation and reporting format
4. Completeness: lack of suitable forest data in many nonAnnex I countries is evident for both area change and
changes carbon stocks
5. Accuracy: limited information on the uncertainty and error
sources of estimates by countries and approaches to
analyze, reduce, and deal with them for international
reporting
Variability in capacities for REDD monitoring
Capacity gap
Consideration of factors:
1. Requirements for monitoring forest carbon on national level (IPCC GPG)
2. Existing national capacities for national forest monitoring
3. Progress in national GHG inventory and engagement in REDD
4. REDD particular characteristics: importance of forest fires, soil carbon,
deforestation rate etc.
5. Specific technical challenges (remote sensing): cloud cover, seasonality,
topography, remote sensing data availability and access procedures
Earth observation contribution to UNFCCC-REDD
GOFC-GOLD
working group est.
GTOS/GOFC
report
1.+ 2. REDD
Sourcebook draft
2nd GOFC-GOLD
workshop
1st GOFC-GOLD
workshop
3. REDD
Sourcebook version
3rd GOFC-GOLD
workshop
ED/GOFC
ESA/GOFC ESA/GOFC- WINROCK/ GTOS/GOFC PNG /
SBSTA
Side event +
GOLD
GOFC-GOLD
-GOLD GOFC-GOLD GOFC-GOLD
side event
side event
booth
side event side event
side event side event
GTOS
GTOS
GTOS
submission II
submission I
submission III
COP11
Montreal
SBSTA 24
COP12
Nairobi
1st SBSTA
workshop
COP13
Bali
2nd SBSTA
workshop
Subm. of view
by parties II
Subm. of view
by parties I
2005
SBSTA 26
2006
2007
SBSTA 28
COP14
Poznan
SBSTA 30
3rd SBSTA
workshop
Informal REDD
Subm. of view by workshop
parties III + IV
2008
2009
REDD Sourcebook
http://www.gofc-gold.uni-jena.de/redd
Global Observation of Forest and Land Cover Dynamics
4 Background forest
monitoring from space
Landsat-calibrated change estimates for Humid Tropics biome 2000-2005
27.2 Mha lost equaling 2.36% of year 2000 forest
cover, 47.8% of total in Brazil
Source: Matt Hansen
JRC/FAO sampling in Central Africa – changes 1990-2000
degradation
deforestation
Source: F. Achard, EC-JRC
Fine-scale land cover/use change
• Suite of national / regional experiences:
– National monitoring programs (i.e. CORINE, Australia)
– UNFCCC Kyoto reporting on LULUCF/AFOLU
• UNFCCC process on reducing emissions from
deforestation in developing countries:
– National case studies (GSE forest monitoring)
– Readiness activities in evolution (Worldbank, UN-REDD)
• Projects with global/large scale focus:
– EU/JRC: TREES 3 (sampling approach)
– UMD/SDSU: combined MODIS/Landsat approach
– GLOBCOVER and ECV monitoring
• FAO-Forest Resources Assessment 2010
Current availability of fine-scale satellite data sources and capacities for
global land change observations
Satellite observation
system/program
Image data Capacities to
Access to
Continuous Pre-processed
Technical
available in sustainably
information observation global image
observation
mapping
produce/use
on quality of program for
datasets
challenges
agencies for map products
archived data
global
generated &
land change in developing
solved
worldwide
coverage
accessible
analysis
countries
LANDSAT TM/ETM
O
P
T
I
C
A
L
ASTER
On demand
SPOT HRV (1-5)
Commercially
CBERS 1-3
Regionally
IRS / Indian program
Regionally
DMC program
ALOS/PALSAR + JERS
S
A ENVISAT ASAR, ERS 1/2
R
TERRARSAR-X
HR IKONOS, GEOEye
Probably
Commercially
Increase usefulness through
demonstration
Regionally
Regionally
Commercially
Probably
ICESAT/GLAS (LIDAR)
(Note: dark gray=common or fully applicable, light gray=partially
applicable/several examples, white=rare or no applications or examples)
Potentially
Addressing technical challenges for remote sensing
Mean annual cloud cover
Country coverage of Landsat 5
receiving stations
Seasonality
Mean annual cloud free country
coverage with SPOT data 2006-08
Percent
Variability in
cloud cover (%)
Topography
Area with steep
slopes (%)
Average internet download speed
GEO forest carbon tracking task
•
Scope and work items to improve situation
Global Observation of Forest and Land Cover Dynamics
4 Evolving
technologies different
foci – degradation,
carbon etc.
Monitoring carbon stock change in degraded forests
1. Inventory based approaches and long-term field observations
2. Remote sensing to detect degraded area:
 Direct detection of degradation (i.e. canopy damage)
 Indirect approaches (detection of human infrastructure)
3. Operational fire monitoring systems
Country objectives and importance of degradation:
1. Changes in forests remaining forests as key category?
2. Monitoring forest degradation important to avoid
displacement of emissions from reduced deforestation
3. Country aiming to claim credits on reduced emissions from
forest degradation (which processes)
The role of LIDAR observations
•
LIDAR (LIght Detection And Ranging) sensors:
–
•
Tool for a range of forest inventory information
–
•
•
directly measure three-dimensional distribution of
vegetation canopy components and sub-canopy
topography
primarily for estimation of tree/stand heights, also
volume, crown closure and biomass
Most operational examples using airborne
systems (footprint size of 0.1 – 2 m)
Global space-borne ICESAT/GLAS with
limitations caused by 70 m footprint diameter
Synthetic Aperture Radar (SAR) observations
•
•
•
•
•
•
•
Active system independent of atmosphere
Data of several space-borne systems archived
ALOS L-band global observations strategy since
2007
Requirements and
status of preprocessing
Baseline forest mapping
Cloudy areas
Project case studies
Source: Josef Kellndorfer, WHRC
Remote sensing support for carbon estimation
Direct biomass mapping from space remains a challenge
Existing capabilities:
 Satellite observation may help to map some specific forest
types (i.e. mangroves, plantations etc.)
 Targeted remote surveys to support carbon monitoring:
• Very high resolution satellite or airborne data of air-photo
quality to assist field surveys
• Sensitivity of LIDAR and long-wave RADAR observations
(few regional examples)
• Integration of in-situ and satellite data for large scale
biomass mapping
• Direct estimation of emissions from fire radiative power
 Technologies are not operational globally but evolving
National carbon assessment through carbon budget model
Choice of methods depends on national circumstances
which include available data and their
characteristics
– Two forest inventories (Sweden, US)
– One forest inventory plus area change - empirical
yield-data driven modeling (Canada)
– Limited Inventory – process modeling (Australia)
– Mixed approaches
Convergence of methods can be expected
3.4 National carbon assessment through carbon budget model
Components of the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3)
Data collection at local level: Carbon assessment by communities
What is it?
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•
•
•
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With very little training and support,
local people can accurately assess
basic properties of the forest:
Species, tree count, dbh
Measurements are part of forest
management aimed at local income
generation from forest resources
Low-intensity traditional forest
inventory to be used for quality
control and conversion to biomass
Data is processed by professional
staff, communicated locally
Correlation can be made with satellite
imagery
– Areas without sampling
– Quality control
Global Observation of Forest and Land Cover Dynamics
5 Examples
Global Observation of Forest and Land Cover Dynamics
Vanuatu – small
remote state with very
limited capacities
Satellite coverage for S-Pacific Island State of Vanuatu
Landsat
(1989/91)
18 scenes
SPOT data
(1990/92)
17 scenes
ASTER
(1999/00)
14 scenes
Landsat
(2000/03)
14 scenes
ASTER
(2005/07)
36 scenes
Hot spots
Forest loss [ha]
Tree canopy cover [%]
GSE Forest Monitoring Examples
•
Cameroon and Bolivia
Biomass forest monitoring examples
•
Christiane will provide slides
GOFC-GOLD biomass working
group
www.fao.org/gtos/gofc-gold
www.gofc-gold.uni-jena.de
Global Observations of Forest Cover and Land Dynamics
Initial set of goals and objectives
1. Establish a platform for coordination and cooperation for
biomass monitoring
2. Develop a community-consens framework for monitoring
biomass globally
3. Dedicated contributions to key international activities:





Consensus framework on how to observe biomass as ECV and support
of evolving programs
GOFC-GOLD contribution to GEO tasks
GOFC-GOLD technical REDD sourcebook
Support of space agencies and plans for dedicated missions
(BIOMASS, Desdiny etc.)
Integrate activities with other ECV observation products (land cover and
fire)
4. Foster comparison and synergy among existing
datasets
6 GEO forest carbon
tracking task
Web resources
• GOFC-GOLD:
– http://www.fao.org/gtos/gofc-gold/
• GOFC-GOLD land cover project office:
– http://www.gofc-gold.uni-jena.de/
• GOFC-GOLD REDD sourcebook:
– http://www.gofc-gold.uni-jena.de/redd
• IPCC background paper on use of remote sensing
in LULUCF sector (GOFC-GOLD 33):
– http://www.fao.org/gtos/gofc-gold/series.html
• UNFCCC/SBSTA technical paper on costs of
monitoring for REDD
– http://unfccc.int/resource/docs/2009/tp/01.pdf