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Monitoring, reporting and verification (MRV) of
  activities for reducing forest related GHG
               emissions (REDD+)

                Martin Herold


                                      5. February 2013
Distribution of aboveground biomass
Introduction

  Monitoring key for management and tracking
  (positive) impact of activities
  Purpose: provide information balancing
  uncertainties, costs and benefits
Experiences and guidelines

 Monitoring of forest related GHG emissions:
    ● Regular reporting of all countries to the UN
      climate convention on land use change and
      forestry - IPCC good practice guidelines
    ● Kyoto-countries: annual reporting for targets
    ● Project experiences from voluntary market
    ● Research and development
 Varying data and capacity gaps exist in developing
 countries (for larger area monitoring)
REDD+ monitoring capacities vs. engagement




                                                     Capacity gap in REDD+
                                                     Engagement

Notes:
Capacity gap derived from Romijn et al., 2012, ESP
Engagement: UN-REDD, WB-FCPF, Norway NIFCI
Data for REDD+ monitoring
Examples of activity data
Examples of activity data
Change in forest areas remaining as forest (degradation)

                                                                 • Caused by:
                                                                    – Selective logging
                                                                    – Forest fires
                                                                    – Forest use (wood,
                                                                       agricuture)
                                                                    – ….
                                                                 • Creates a complex
                                                                   environment:
                                                                    – Undisturbed forests
                                                                    – Canopy gaps
                                                                    – Exposed soils
                                                                    – Dead vegetation
                                                                 • Can be precursor to:
                                                                    – Deforestation
                                                                    – Further disturbances

                                Ikonos Image – Paragominas, PA
      Souza Jr. and Roberts (2005) - IJRS
Global coverage of 5 m resolution data




                       eyefind.rapideye.com
Google Earth Engine

1.   Large satellite data catalogue
2.   Platform for scientists and analysts to implement
     and algorithms and upload own data
3.   Global-scale algorithm processing to implement
     mapping and monitoring (cloud)
4.   Tool for (non-) experts to run detailed remote
     sensing analysis
5.   http://earthengine.googlelabs.com
Data for REDD+ monitoring
Human induced disturbance
                                causing loss of forest: fire, clearing, selective extraction, …
               Primary forest
Carbon stock




                                                                                           Deforestation

                                                           Time
Estimating emission factors

 Considering changes in different carbon pools:
    ● Above- and belowground biomass
    ● Deadwood, litter and soil
 Main data sources:
    ● Ground measurements (forest inventory)
    ● Remote sensing (combining with ground data)
 Obtaining quality data on forest carbon stock change in
 efficient manner:
    ● Key category analysis
    ● Stratify to measure in areas of changes
How to estimate emission?


                       Use defaults (Tier 1)
                       Create a good carbon
                       stock estimate (i.e.
                       combining ground data
                       with RS) – Tier 2
                       Repeated measurements
                       with focus on (Tier 3):
                            ● Key C-pools
                            ● In and around
                             areas of changes
Carbon stock change from deforestation/degradation

Tiers (C pool change)                       Certainty                           REDD            Cost
1.Default values:




                                        Red. Em.
                                                                                 Simple &
 biomass in forest types by region                                            conservative
  and ecol. stratification, carbon                                             starting point
  fraction etc.
2. Country/regional data:




                                                       Conservative estimate
                                                                               Motivation to



                                        Red. Em.
 Inventories (date, focus)                                                      improve
 Ecological monitoring plots                                                   monitoring
 Project studies/field samples                                                system over
                                                                                   time
3. Full inventory of C stocks:                                                  Accurate &
                                        Red. Em.

 Comprehensive assessment                                                      established
 Consider different carbon pools                                                emissions
  and assessment for all associated                                             monitoring
  changes
                                      Conservative estimates:
                                      1) Incomplete: a pool (e.g. soil) may be omitted
                                      2) Uncertain: use confidence intervals
REDD+ monitoring: capacities & engagement

1. Institutional setup: coordination, roles,
   capacities:
    ● Clear, simple, and sustainable
2. Build upon what is already available
3. Who should/could be involved:
    ● National/provincial experts
    ● Local experts/REDD+ implementers
    ● International experts
Conclusions

1. Thorough experiences for monitoring &
   reporting forest-related GHG emission
2. Improvements in developing countries
   through REDD+ related capacity
   development
3. Approaches for handling uncertainties when
   linking to financial incentives
4. Technology is (usually) not a limiting
   factor; consider institutions and capacities
5. Focus should be on REDD+ activities
GOFC-GOLD REDD+ Sourcebook
      http://www.gofcgold.wur.nl/redd




    A sourcebook of methods and procedures for
monitoring and reporting anthropogenic greenhouse
gas emissions and removals caused by deforestation,
     gains and losses of carbon stocks in forests
         remaining forests, and forestation

    Latest version published for COP-18 in Doha

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Monitoring, reporting and verification (MRV) of activities for reducing forest related GHG emissions (REDD+)

  • 1. Monitoring, reporting and verification (MRV) of activities for reducing forest related GHG emissions (REDD+) Martin Herold 5. February 2013
  • 3. Introduction  Monitoring key for management and tracking (positive) impact of activities  Purpose: provide information balancing uncertainties, costs and benefits
  • 4. Experiences and guidelines  Monitoring of forest related GHG emissions: ● Regular reporting of all countries to the UN climate convention on land use change and forestry - IPCC good practice guidelines ● Kyoto-countries: annual reporting for targets ● Project experiences from voluntary market ● Research and development  Varying data and capacity gaps exist in developing countries (for larger area monitoring)
  • 5. REDD+ monitoring capacities vs. engagement Capacity gap in REDD+ Engagement Notes: Capacity gap derived from Romijn et al., 2012, ESP Engagement: UN-REDD, WB-FCPF, Norway NIFCI
  • 6. Data for REDD+ monitoring
  • 9. Change in forest areas remaining as forest (degradation) • Caused by: – Selective logging – Forest fires – Forest use (wood, agricuture) – …. • Creates a complex environment: – Undisturbed forests – Canopy gaps – Exposed soils – Dead vegetation • Can be precursor to: – Deforestation – Further disturbances Ikonos Image – Paragominas, PA Souza Jr. and Roberts (2005) - IJRS
  • 10. Global coverage of 5 m resolution data eyefind.rapideye.com
  • 11. Google Earth Engine 1. Large satellite data catalogue 2. Platform for scientists and analysts to implement and algorithms and upload own data 3. Global-scale algorithm processing to implement mapping and monitoring (cloud) 4. Tool for (non-) experts to run detailed remote sensing analysis 5. http://earthengine.googlelabs.com
  • 12. Data for REDD+ monitoring
  • 13. Human induced disturbance causing loss of forest: fire, clearing, selective extraction, … Primary forest Carbon stock Deforestation Time
  • 14. Estimating emission factors  Considering changes in different carbon pools: ● Above- and belowground biomass ● Deadwood, litter and soil  Main data sources: ● Ground measurements (forest inventory) ● Remote sensing (combining with ground data)  Obtaining quality data on forest carbon stock change in efficient manner: ● Key category analysis ● Stratify to measure in areas of changes
  • 15. How to estimate emission?  Use defaults (Tier 1)  Create a good carbon stock estimate (i.e. combining ground data with RS) – Tier 2  Repeated measurements with focus on (Tier 3): ● Key C-pools ● In and around areas of changes
  • 16. Carbon stock change from deforestation/degradation Tiers (C pool change) Certainty REDD Cost 1.Default values: Red. Em. Simple &  biomass in forest types by region conservative and ecol. stratification, carbon starting point fraction etc. 2. Country/regional data: Conservative estimate Motivation to Red. Em.  Inventories (date, focus) improve  Ecological monitoring plots monitoring  Project studies/field samples system over time 3. Full inventory of C stocks: Accurate & Red. Em.  Comprehensive assessment established  Consider different carbon pools emissions and assessment for all associated monitoring changes Conservative estimates: 1) Incomplete: a pool (e.g. soil) may be omitted 2) Uncertain: use confidence intervals
  • 17. REDD+ monitoring: capacities & engagement 1. Institutional setup: coordination, roles, capacities: ● Clear, simple, and sustainable 2. Build upon what is already available 3. Who should/could be involved: ● National/provincial experts ● Local experts/REDD+ implementers ● International experts
  • 18. Conclusions 1. Thorough experiences for monitoring & reporting forest-related GHG emission 2. Improvements in developing countries through REDD+ related capacity development 3. Approaches for handling uncertainties when linking to financial incentives 4. Technology is (usually) not a limiting factor; consider institutions and capacities 5. Focus should be on REDD+ activities
  • 19. GOFC-GOLD REDD+ Sourcebook http://www.gofcgold.wur.nl/redd A sourcebook of methods and procedures for monitoring and reporting anthropogenic greenhouse gas emissions and removals caused by deforestation, gains and losses of carbon stocks in forests remaining forests, and forestation Latest version published for COP-18 in Doha