A Sub-National RL Concept Note in TAL Terai Arc Landscape Program - PowerPoint PPT Presentation

A Sub-National RL Concept Note in TAL Terai Arc Landscape Program In Technical Support of WWF 18 TH JUNE 2013

WHAT IS RL/REL Forest Reference Emission Levels &/or Forest Reference levels:  Benchmarks for assessing a country’s performance in implementing REDD+ activities  Expressed in tons of CO2 eq/ year  Credible ones will be driven by historical data: any projections (while allowed) will receive substantial more scrutiny and criticism Benchmarks:  Moving from REDD+ readiness – Demonstration- Performance Based Payments .

WHAT REALLY IS RL The most important thing about a REDD+ RL:  Basis for determining whether a REDD program or policy is working. On REDD+, funding that is performance-based:  RLs are essential to know the starting point of forest cover change and emissions in an area.  RLs are a combination of empirical data, assumptions, and modeling.  RLs are being discussed at project levels, subnational levels, nationally, internationally (UNFCCC), multilaterally (e.g., World Bank).

BASIS OF REDD+ RL The basic math is: Activity Data (ha loss or ha degraded/per year) X Emissions Factors (tCO 2 e/ha) = tCO 2 e/year  Activity data will be based on satellite information (past) or assumptions (future)  Emission factors will be based on field measurements & Allometric equations – they will be net changes in forest carbon between the classes used in the activity data

CONCEPT NOTE

PROPOSAL Approach: Historical RL @ a sub-national scale  Base Year 1999  Project Area; 12 jurisdictional boundaries Tools: Img Tools (NDFI) and LiDAR (Arbo-LiDAR and LAMP)  Generate activity data (AGC) (1999 to 2011) and emissions factors (derived from plot data and NDFI)  Larger plots for calibration of LiDAR Allometric Equations  Chave et all, Moist Forest- Diameter Model- (Equation: 1.3)  Sharma and Pukkala

PROPOSAL: POOLS Above Ground Biomass Branches Below Ground Wood products Biomass Shrubs Litter Herbaceous vegetation Soil Organic Carbon Litter Soil Carbon Dead wood Roots

LIDAR • LAMP computes model-based estimates that take advantage of field plots, LiDAR, and satellite images like Landsat or RapidEye; • It produces an Above-ground biomass (AGB) map at high spatial resolution, from 1 ha upwards; • The AGB estimates are unbiased; • The estimates also preserve AGB variance present in LiDAR blocks; • The LAMP process does not depend on subjective expert opinion.

APPLYING IMG TOOLS FOR NDFI

NDFI: NORMALIZED DIFFERENTIAL FRACTION INDEX • Equations that combines Landsat’s wavelength returns into a single value to explain forests • A significant relationship between NDFI values and field derived estimates of carbon • We binned NDFI into forests with low, medium and high carbon values • These bins are the key pivot points for generating AGC values

VALUES Low: Bin I (1-90 NDFI) Mean C: 25tC/Ha Medium : Bin II (91-147 NDFI) Mean C: 59tC/Ha High: Bin III (148-199 NDFI) Mean C: 145tC/Ha

APPLYING NDFI and FOREST CHANGE  The forest change information  Deforestation (Bin II  Bin I, or Bin III  Bin I)  Degradation (Bin III  Bin II, Bin II-)  Regrowth (Bin I  Bin II, or Bin I  Bin III)  Enhancement (Bin II to Bin III)  Can be applied to : a. Available forest classification Sal, Mixed hardwood, Riverine etc. by overlapping available forest classification over the FCD Mapper b. Physiographic classification, such as Terai and Siwaliks

ANALYSIS: BOOKEND APPROACH: 1999-2011: (2.9 MT OF CO2 EQ/YR)

ANALYSIS: TIME SERIES APPROACH: (2.64 MT OF CO2 EQ/YR)

ACCURACY ASSESSMENT

AGC 1999

AGC 2011

CHANGE DECTECTION 1999-2011

CHANGE DETECTION 1999- 2011

CENTRAL TERAI IN 12 YEARS: RAUTAHAT & BARA

WESTERN TERAI IN 12 YEARS: BARDIYA

WESTERN TERAI IN 12 YEARS: KAILALI

WESTERN TERAI IN 12 YEARS: KANCHANPUR

FINANCING Current Emissions: 2.64 Mt of CO2/yr Performance: Reduce by 50% Rate: $7/Mt of CO2 eq Revenue: 46.2 million in 5 years

LIDAR AND AGC • LiDAR model was correlated with recently measured 48 field plots with 30m radius LiDAR model has an R 2 value • of 0.92 and does not saturate at all. R 2 = 0.92

AGC- LIDAR AND NDFI • NDFI was correlated with AGB estimated using the LiDAR model developed for TAL NDFI has an R 2 value of • 0.44 but saturates at 300 tons/ha R 2 = 0.44

LAMP RESULTS AT 1Ha RESOLUTION R 2 = 0.53

LEARNINGS IN THE PROCESS • NDFI has strong correlation with forest cover change, • LiDAR has strong capapcity to pick up AGC, • Incorporation of NDFI in LAMP will enhance the capacity of LAMP to detect change and estimate AGC. • Choice for Allometry Equations

Work in progress (LAMP) : Carbon difefrence map at 1 ha resolution between 1999 and 2011

FCPF • FCPF is still in the process of designing the framework • Many countries getting ready to line-up for Carbon Fund, but not many that will be viewed as being READY. • It is important for Nepal to not delay in getting an initial ER-PIN before the fund. Ideally, October meeting, which would require a late September submission to the FMT

UNFCCC/SB-38  DRAFT CONCLUSIONS: Adopted  NFMS: National Forest Monitoring Systems  MRV- ICA: Monitoring Reporting and Verifications- International Consultations and Analysis  RL: Reference Levels: 21 WEEKS REVIEW  NMBA: Non- Market Based Approaches  NCB: Non Carbon Benefits  SAFEGUARDS:  DRIVERS:  REDD FINANCE:

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