1. Global Observation of Forest and Land Cover Dynamics Slides for Stephen Briggs Martion Herold

2. Global Observation of Forest and Land Cover Dynamics 0 Background UNFCCC

3. 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 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 http://www.gofc-gold.uni-jena.de/redd www.fao.org/gtos/topcECV.html Major investments in land monitoring, estimation and accounting

4. Observing land cover as ECV www.fao.org/gtos/

5. Global Observation of Forest and Land Cover Dynamics 1/2/3 Background REDD

6. Carbon Stock Sectoral Crediting Baselines Direct Barter Design positive incentives: Programatic or sectoral scale Similar to programmatic CDM Calculate historical and future baseline carbon stock – credits gained for performance below baseline Suriname Vanuatu PNG Solomon’s Bolivia Indonesia India Costa Rica China International incentive mechanisms need to work for all nations

7. Draft decision text for Copenhagen

8. 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.

9. 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 non- Annex 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

10. Variability in capacities for REDD monitoring 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 Capacity gap

11. Earth observation contribution to UNFCCC-REDD 2005 GOFC-GOLD working group est. COP11 Montreal GTOS submission I Subm. of view by parties I 1 st GOFC-GOLD workshop ED/GOFC SBSTA side event SBSTA 24 1 st SBSTA workshop GTOS/GOFC report COP12 Nairobi ESA/GOFC Side event + booth Subm. of view by parties II 2 nd SBSTA workshop SBSTA 26 2 nd GOFC-GOLD workshop ESA/GOFC- GOLD side event GTOS submission II COP13 Bali 1.+ 2. REDD Sourcebook draft WINROCK/ GOFC-GOLD side event 2006 20072008 2009 Subm. of view by parties III + IV GTOS submission III SBSTA 28 GTOS/GOFC -GOLD side event 3 rd GOFC-GOLD workshop COP14 Poznan 3 rd SBSTA workshop SBSTA 30 COP15 Copenhagen PNG / GOFC-GOLD side event Informal REDD workshop GOFC-GOLD side event 3. REDD Sourcebook version

12. REDD Sourcebook http://www.gofc-gold.uni-jena.de/redd

13. Global Observation of Forest and Land Cover Dynamics 4 Background forest monitoring from space

14. 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

15. JRC/FAO sampling in Central Africa – changes 1990-2000 degradation deforestation Source: F. Achard, EC-JRC

16. 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

17. Current availability of fine-scale satellite data sources and capacities for global land change observations Satellite observation system/program Technical observation challenges solved Access to information on quality of archived data worldwide Continuous observation program for global coverage Pre-processed global image datasets generated & accessible Image data available in mapping agencies for land change analysis Capacities to sustainably produce/use map products in developing countries OPTICALOPTICAL LANDSAT TM/ETM ASTEROn demand SPOT HRV (1-5)Commercially CBERS 1-3Regionally IRS / Indian programRegionally DMC programProbablyCommercially SARSAR ALOS/PALSAR + JERSRegionally ENVISAT ASAR, ERS 1/2Regionally TERRARSAR-XCommercially HR IKONOS, GEOEyeProbablyPotentially ICESAT/GLAS (LIDAR) (Note: dark gray=common or fully applicable, light gray=partially applicable/several examples, white=rare or no applications or examples) Increase usefulness through demonstration

18. Addressing technical challenges for remote sensing Mean annual cloud cover Seasonality Topography Country coverage of Landsat 5 receiving stations Mean annual cloud free country coverage with SPOT data 2006-08 Average internet download speed Percent Variability in cloud cover (%) Area with steep slopes (%)

19. GEO forest carbon tracking task Scope and work items to improve situation

20. Global Observation of Forest and Land Cover Dynamics 4 Evolving technologies different foci – degradation, carbon etc.

21. 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)

22. The role of LIDAR observations LIDAR (LIght Detection And Ranging) sensors: –directly measure three-dimensional distribution of vegetation canopy components and sub-canopy topography Tool for a range of forest inventory information –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

23. 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

24. 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

25. 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

26. 3.4 National carbon assessment through carbon budget model Components of the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3)

27. What is it? 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 Data collection at local level: Carbon assessment by communities

28. Global Observation of Forest and Land Cover Dynamics 5 Examples

29. Global Observation of Forest and Land Cover Dynamics Vanuatu – small remote state with very limited capacities

30. Satellite coverage for S-Pacific Island State of Vanuatu Landsat (1989/91) 18 scenes Landsat (2000/03) 14 scenes ASTER (1999/00) 14 scenes SPOT data (1990/92) 17 scenes ASTER (2005/07) 36 scenes

31. Hot spotsForest loss [ha]Tree canopy cover [%]

32. GSE Forest Monitoring Examples Cameroon and Bolivia

33. Biomass forest monitoring examples Christiane will provide slides

34. 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

35. 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

36. 6 GEO forest carbon tracking task

37. 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