1 UNFCCC Workshop on Reducing Emissions from Deforestation in Developing Countries 30/08-01/9/2006, Rome, Italy Overview of scientific, socio- economic, technical and methodological issues Sandra Brown

2 Much progress in the last 10 years….  Remote sensing data at various scales readily available and methods and tools have been developed and for estimating and monitoring carbon emissions from tropical deforestation and degradation  Change in land cover for most tropical regions can be measured from space with confidence, but measuring forest degradation from satellites is more technically challenging  Peer reviewed tools and methods available using field measurements to estimate carbon stocks in forests with high confidence.  Methods for estimating net and gross emissions from deforestation/degradation are available in existing IPCC reports (1996, 2003, 2006)

3 Forest Definition: (annex to decision 16/CMP.1 of Kyoto Protocol) Minimum forest area: 0.05 – 1 ha Minimum tree height: 2 – 5 m Minimum crown cover: 10 – 30 % Degradation (from IPCC): Direct, human-induced, long-term loss [persisting for X years or more] or at least Y% of forest carbon stocks since time T [not qualifying as deforestation] Deforestation: Direct, human-induced conversion of forested land to non-forested land 2-5 m ha 10-30%Definitions

4 Application of definitions 80%30% 10% 0% Carbon stocks in t C/ha 40 Crown cover Deforestation ΔC= 80 Deforestation ΔC= % 10% Degradation Devegetation

5 Drivers of deforestation and degradation as reported in national communications to the UNFCCC

6 Steps involved in a C monitoring system for deforestation DeFries et al Forest inventories In-situ/plot data-projects Targeted remote surveys— e.g. Lidar and aerial imagery FAO statistics IPCC-GPG / AFOLU

7 Monitoring change in forest cover  Remote sensing data available for many land cover changes and many developing countries since 1990s and deforestation can be measured from space with confidence  Not all areas covered; cloud cover issues for some key tropical countries  Identification of secondary forests—not “easy”  Identification of degraded forests developing  Identification of selectively logged forest developing  Development of new technology and new analytical methods in RS field progressing for addressing these challenges and likely to be available for future monitoring

8 Monitoring carbon stocks  Need to match estimates of carbon stocks with changes in land cover to improve accuracy and precision of emission estimates  Current operational optical satellites cannot remotely sense biomass carbon  Optical satellites have difficulty in distinguishing secondary from mature forests, yet carbon stocks can differ greatly because of effects of age and ecological zone

9 How are forest biomass C stocks in the tropics presently assessed?  Robust tools exist for converting traditional, statistically designed forest inventory data to carbon stocks in trees; use defaults for other pools (IPCC GPG Ch. 3; FAO)  Majority of tropical countries have no recent national forest inventories  Research plots generally insufficient as not from population of interest and designed for other purposes

10 CountryBiomass EstimationYear Brazil Scientific studies with small, non-stratified plots : Malaysia Volume to biomass using GPG (2003) and expansion factors from Brown (1997); extrapolated to Sabah and Sarawak 1993, 2004 Indonesia Volume (year 2000 estimated for various species) to biomass using expansion factor from Brown (1997) 1992, 1998, 2000 Peru Volume inventories, not converted to biomass 1995,2000 Bolivia Volume (humid forest only) to biomass using expansion factors, default values for roots and dead wood from IPCC Dem Rep. of Congo Volume to biomass using average wood density for Africa and BEF from Brown (1997) 1999 Cameroon 1990 volume (assumed constant for 2000 and 2005) to biomass using density and expansion factors (sources not listed) 1990 Central African Republic Partial inventory only. Volume (constant from ) to biomass using average wood density for Africa and expansion factors from Brown (1997) and FAO (2004) Directives 1996, 1997 Republic of Congo Volume (assumed constant for ) to biomass using average wood density for Africa and BEF from IPCC GPG 2004 Tanzania Volume (by vegetation classes) to biomass using average density for Africa and expansion factors (sources not listed) 1999

11  Traditional inventory approach:  Can be done in smaller countries and at project scale  Requires large resources at national level  Cost-prohibitive for large countries and not practical  Need remote means that are:  Cost-effective  Low uncertainty (high precision)  Transparent and repeatable  Acceptable to policy makers How to measure carbon stocks ?

12 Future trends in measuring and monitoring carbon stocks for DD  Build on existing techniques—regular “inventories” done by sampling  Need remote means  Not necessary for wall-to-wall mapping but statistical sampling approach  New remote technology developing—  Lidar already shown to measure changes in forest structure –height is a good indicator of forest biomass change  High resolution digital imagery combined with new field data on key metrics of forest carbon-crown area and tree height

13 Conclusions  Analysis of airborne or satellite remotely sensed data is the only practical approach to measure changes in DD at national and international scales.  Since the early 1990s, tools and methods exist to measure changes in forest area from space with confidence.  Measuring forest degradation from satellites is more technically challenging but methods are becoming available.  There are no accepted standard practices for measuring forest carbon stocks using RS data; instead they are estimated from traditional forest inventories or from default data.  Investments are required to expand inventories of forest carbon stocks so that reliable carbon estimates can be applied to deforested and degraded areas interpreted from RS imagery.  New technologies and approaches are developing for monitoring changes in carbon stocks with confidence using a combination of satellite and airborne imagery.

14 Conclusions (cont.)  Methods for estimating net and gross emissions from areas with measurable DD are available in existing IPCC 1996 GHG inventory methods, the 2003 GPG-LULUCF and the pending IPCC AFOLU.  Reliable and transparent results from application of these methods are hampered by capacity, availability, and access to data on both change in forest cover and, more critically, by change in carbon stocks  NEXT STEPS  Development of standard protocols for interpreting and analyzing remote sensing data at various scales, including which data to collect and use, how to analyze the data, and acceptable levels of accuracy to attain, etc (akin to GPG for C stocks for LULUCF)  Development of standard protocols for estimating carbon stocks of forests undergoing change at national scales, building on existing methods given in IPCC reports, and decisions on acceptable levels of accuracy and precision to attain.