Introduction session-3-b-guyanas_mrv_system.pdf
- 1. REGIONAL WORKSHOP ON REDD+ MRV IMPLEMENTATION AND DRIVERS OF DEFORESTATION Guyana Forestry Commission Guyana, South America December, 2013
- 2. Outline of Presentation • Background to MRV System Development • Developing the design of the MRV System (MRV Roadmap) • Implementation of work under MRV –Forest Area Change Assessment (FACA) –Forest Carbon Monitoring System (FCMS) • Reference Levels (REL/RL) • Key challenges and Lessons Learned • Next Steps in Guyana’s MRVS 2
- 3. Background to MRV System Development • Work on the development of the MRVS started in 2009 To enable the development of the MRVS, several key areas are identified to be addressed. • There needs to be established a framework of accepted principles and procedures of of accepted principles and procedures of estimation and reporting forest carbon emissions and removals at the national level as specified by the IPCC Good Practice Guidelines and Guidance for reporting on the international level. • As well as an outline of the REDD Implementation strategy for the MRVS. This will also entail the assessment of a reference emissions level
- 4. The Roadmap Approach to Building Guyana’s MRVS • A Road Map was developed, which outlined progressive steps over a 3 year period that will build towards a full MRVS being implemented. • Undertook a capacity building approach • Undertook a capacity building approach • The first year in the Roadmap starts at 2010 and requires for a number of initial reporting activities to commence which will assist in shaping the next steps planned for 2011 and 2012.
- 5. Implementation of work under MRV • The aim of the MRVS is to establish a comprehensive, national system to monitor, report and verify forest carbon emissions resulting from deforestation and forest degradation in Guyana. • With the development of the MRVS • With the development of the MRVS Roadmap, implementation of works begun in 2010 in two areas: – Forest Area Change Assessment – Forest Carbon Monitoring System • These activities determine the historical and current patterns of emissions coming forest, their drivers and the carbon stock present in the various pools.
- 6. Forest Area Change Assessment Activities Completed: 2011- Year 1 • Determining the forested area • Setting the 1990-2009 Change baseline • Accuracy of Mapping & Change 97% 2012 – Year 2 • Degradation process implemented • Batch processing of 300+ RE tiles to a • Batch processing of 300+ RE tiles to a change product • Accuracy of Mapping & Change 97% 2013 – Year 3 • 100% country coverage with RE • Integration of Shifting cultivation • Integration of Afforestation monitoring • Base mapping improvements / Automation • UNFCCC reporting run operationally
- 7. Year 3 Assessment • Reporting period was 01 January, 2012 to 31 December, 2012 • First version of the Report was released for a 1 month period (16th October to 16th November 2013) for general feedback November 2013) for general feedback • Version 2 is currently available on the GFC’s website and includes feedback from: – Norwegian Ministry of the Environment – TAAMOG – Ronald E. Mc Roberts
- 8. Year 3 Assessment • Forest change between 1 January 2012 and 31 December 2012, was determined using high resolution 5 m imagery for the whole of Guyana • The use of a national coverage of 5 m imagery • The use of a national coverage of 5 m imagery is a significant improvement over Year 2 which used a combination 5 m and 30 m imagery to achieve national coverage. • This improvement has allowed the boundaries and the drivers of change to be mapped with greater certainty.
- 9. Year 3 Assessment • The total forested area at the Benchmark period (30 September 2009) was estimated as 18.39 million hectares (ha) (with an indicative accuracy of 97.1%). • In 2012, as planned Guyana’s forest area was re-evaluated using RapidEye 5 m imagery. re-evaluated using RapidEye 5 m imagery. • This analysis has resulted in an increase in the forested area by approximately 110 000 ha to 18.5 million of which 15.5 million ha is administered by the State. • The revised 2012 forest area is used as the reference point from which the rate of change is calculated.
- 10. Findings • Forest change of forest to non-forest excluding degradation between 1 January 2012 and 31 December 2012 (12 months) is estimated at 14 655 ha. • Equates to a total deforestation rate of 0.08%. • Equates to a total deforestation rate of 0.08%. • This rate of change is higher than Year 2 period (15 months) which was reported as 0.054%. • The area of degradation as measured by interpretation of the 5 m RapidEye satellite imagery in the 2011 assessment was 5 467 ha. • This has reduced in 2012 to 1 963 ha.
- 11. Findings • The main deforestation driver for the current forest year reported (Year 3) is mining which accounts for 93% of the deforestation in this period. • It should be noted that the driver of mining, includes mining infrastructure. • A majority (83%) of deforestation is observed in the • A majority (83%) of deforestation is observed in the State Forest Area. • The temporal analysis of forest change post 1990 indicates that most of the change is clustered around existing road infrastructure and navigable rivers. • In year 3 the change has continued to follow this trend with further expansion relatively constrained. This is evident from the decrease in the area of degradation.
- 12. Forest Change Area by Period & Driver from 1990 to 2012 Driver Historical Period Year 1 2009-10 Year 2 2010-11 (15 months) Year 3 2012 1990 to 2000 2001 to 2005 2006 to 2009 Deforestation Degradation Deforestation Degradation Area (ha) Forestry (includes forestry infrastructure) 6 094 8 420 4 784 294 233 147 240 113 Agriculture (permanent) 2 030 2 852 1 797 513 52 N/A 440 0 Mining (includes mining infrastructure) 10 843 21 438 12 624 9 384 9 175 5 287 13 516 1 629 Infrastructure 590 1 304 195 64 148 5 127 13 Fire (deforestation) 1 708 235 32 58 28 184 208 Degradation (year 2) converted to deforestation 148 Amaila Falls development 225 Area Change 21 267 34 249 19 400 10 287 9 891 5 467 14 655 1 963 Total Forest Area of Guyana 18 473 394 18 452 127 18 417 878 18 398 478 18 388 190 18 502 531 Total Forest Area of Guyana Remaining 18 452 127 18 417 878 18 398 478 18 388 190 18 378 299 18 487876 Period Deforestation % 0.01% 0.04% 0.02% 0.056% 0.054% 0.079%
- 13. Historical &Year 3 Forest Change
- 14. Mining Spatial & Temporal Distribution Y1, Y2 & Y3
- 15. Forestry Spatial & Temporal Distribution Y1, Y2 & Y3
- 16. Infrastructure Roads Spatial & Temporal Distribution Years 2 & 3
- 17. Agriculture Development Spatial & Temporal Distribution Y1, Y2 & Y3
- 18. Biomass Burning - Fire Temporal and Spatial Distribution Y1, Y2 & Y3
- 19. Accuracy Assessment • Accuracy Assessment conducted by Durham University • A two-stage sampling with stratification of the primary units was adopted to provide precise estimates of forest area. • Two strata were selected according to “risk of • Two strata were selected according to “risk of deforestation”, that is, land proximal to settlements, roads, logging concessions and known mining dredge sites, and other low risk land area. • Interpretations of deforestation and degradation drivers were made from expert image interpretation of very high spatial resolution aerial imagery or high spatial resolution satellite imagery. • Accuracy Assessment (AA) dataset was captured using GeoVantage’s aerial imaging camera system.
- 20. Accuracy Assessment • For the Year 3 Forest–Non-forest map, the results show a correspondence (prevalence) of 99.76% between reference image interpretation and IAP/GFC mapping for all the 55,119 one-hectare plots sampled from both strata. • This demonstrates a very high level of correspondence between the MRV maps and the reference data: – 99.56% in High Risk stratum and – 99.89% in Low Risk stratum. • This compares with 94.5% in High Risk and 99.08% in Low Risk for Year 2.
- 21. Comparison of Forest Change Estimates Source Forest area remaining at the end of Year 3 (ha) Forest area change Year 3 (ha) Benchmark Rate (%) Year 3 Rate (%) GFC / Indufor GIS Map 18,392,782 14,655 0.021 0.08 GIS Map Estimate 18,392,782 14,655 0.021 0.08 Durham Sample-based Estimate 18,392,292 15,145 0.021 0.08
- 22. Comparative Resolution of the RapidEye and Aerial Imagery
- 23. Comparative Resolution of the RapidEye and Aerial Imagery RapidEye 2012 GeoVantage 2013
- 24. Forest Carbon Monitoring System (FCMS) • Aim is to design and implement a long-term, robust, and scientifically sound national forest carbon measurement and monitoring system (FCMS) (FCMS) • Data generated from C stock work will be linked to the forest area assessment effort to provide historic emissions (RL) and estimates of annual carbon emissions and removals (MRV)
- 25. Key outcome of FCMS: national lookup tables of emission factors to meet standards • Standards for level of uncertainty (e.g. precision of ground data) • Produce QA/QC plans for all data collection and analyses Change agent/Driver – Deforestation (stock change) Mining Infrastructure Logging Agriculture Fire Stratum Mining (>1 ha in size) (t CO2e ha -1 ) Infrastructure (t CO2e ha -1 ) Logging Infrastructure (t CO2e ha -1 ) Agriculture (t CO2e ha -1 ) Fire (t CO2e ha -1 ) Mixed forests high potential for change Mixed forest medium potential for change • Table will be filled in with EF based on ground data collection and analysis • It will be used with activity data to generate estimates of emissions of GHG
- 26. Stratification for Monitoring of Carbon • Based on preliminary carbon sampling data, the forest types identified in Guyana’s forest vegetation map did not appear to have different carbon stocks. • Analyses showed similar carbon stocks per forest type. Therefore, only stratification by anthropogenic factors was included in the final forest carbon sampling stratification methodology. stratification methodology. • A large portion of Guyana’s forest is not easily accessible and one of the goals in the design of the sampling stratification is to overcome some operational constraints, while maintaining the robust sampling results. Therefore, the factor of accessibility was also introduced in the sampling stratification methodology. • The final forest carbon sampling design stratifies the forests in Guyana by potential for change (high, medium and low) and by accessibility (more and less accessible).
- 27. Approach to Sampling • Guyana is implementing a three-phased approach for implementation of data collection as follows: • The FIRST phase of data collection includes high potential for change in includes high potential for change in more and less accessible strata. • The SECOND phase includes medium potential for change in more and less accessible strata. • The THIRD phase includes low potential for change in more and less accessible strata.
- 28. Forest Potential for Change Map
- 29. Forest Carbon Sample Design for 2013
- 30. Sampling Design • Randomly select number of grids in which to install plot clusters by high threat strata based on targeted precision (+/- Forest areas under high threat overlain with 10 km X 10 km grid targeted precision (+/- 10% mean) • Takes into account accessible versus less accessible forests in sampling design • Repeat process for medium and low threat in phased approach
- 31. Preliminary Data • Single Plots • Cluster Plots Carbon Pool Carbon Stock (t C ha-1) % of Total Aboveground tree biomass 192.9 ± 29.9 71.2 Belowground tree biomass 45.2± 7.0 17.2 Saplings* 7.0 ± 1.3 2.7 Dead wood (standing)# 1.1 ± 1.0 0.4 Dead wood (lying)# 17.3 ± 7.1 6.6 Total 279.3 ± 25.2 100 Carbon Pool Carbon Stock (t C ha-1) % of Total Aboveground tree biomass 190.6 ± 12.88 72.4 Belowground tree biomass 44.8± 3.0 17.0 Belowground tree biomass 44.8± 3.0 17.0 Saplings* 5.2 ± 0.6 2.0 Dead wood (standing)# 3.3 ± 1.4 1.3 Dead wood (lying)# 19.3 ± 3.1 7.3 Total 263.2 ± 9.3 100 a a a b 0 50 100 150 200 250 300 dakama mixed wallaba swamp mean tC/ha ±90% CI Forest type
- 32. What are Reference Levels? • Basis for calculating emission reductions • Reference Levels (RLs) refer to business– as-usual benchmarks • Ultimately compared to REDD+ Ultimately compared to REDD+ implementation captured by MRV • Derived from historical data and adjusted for national circumstances as appropriate • Set at the beginning of a fixed length period (e.g. 5 year period beginning in 2013)
- 33. Guyana's Reference Level Define Historical Period • Start dates: 1990 or 2001 • End dates: 2009 or 2010 OPTIONS • Combined Reference Level • Continuation of historical average • Continuation of historical trend • Adjustment for National Circumstances
- 34. Key challenges and Lessons Learned • Key Challenges – Cloud Cover in Satellite data – Building of Technical Capacity in key REDD+ areas – Overall operational Cost – Rules not definitively established at international level for MRVS • Lessons Learned – Cross Sectoral Approach – National context and appropriateness – Sustainability of approach achieved through capacity building – Efforts need to link to international processes, negotiation, bilateral arrangements, and international mechanisms – Moving ahead in absence of full capacity and historic data. – Priority setting and effective implementation strategies
- 35. Next Steps in Guyana’s MRVS • Next Steps – Year 4 FAA – Continuing of work on degradation – Initiation of special studies on specific areas as measurement of emissions areas as measurement of emissions from key drivers of deforestation & forest degradation – Ongoing capacity building for staff as well as key groups as the MRVS SC – Continued implementation of activities in the MRVS Road Map
- 36. Next Steps in Guyana’s MRVS • Development/demonstration priorities – Better integration of the GFC log tracking system and the satellite imagery in order to monitor compliance – Real-time mining deforestation (using Landsat/Modis). To monitor compliance. – Temporal study of shifting cultivation using historical data to better understand land cover change dynamics – Improvement of the national forest cover map using the – Improvement of the national forest cover map using the Geovantage aerial coverage as a reference layer to classify the RapidEye imagery – Integrated data sharing with other agencies to communicate mapping results to ensure improved enforcement – Assessment of the newly developed image processing routines that NSC and FAO are working on – Ongoing - Overflights using the same system as trialled this year. This would be used again for the accuracy assessment in Year 4.
- 37. Photo Credits GFC, R Thomas, FTCI, Fotonatura, B Hoffman, J van Essen, B.Lim Thank you Kaieteur National Park 37