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

A Sub-National RL Concept Note in TAL

18TH JUNE 2013

Terai Arc Landscape Program

In Technical Support of WWF

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 (tCO2e/ha) = tCO2e/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

Soil Carbon Herbaceous vegetation Wood products Branches Litter Dead wood Roots

Above Ground Biomass Below Ground Biomass Shrubs Litter Soil Organic Carbon

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
• n 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

• ver 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 R2 value
• f 0.92 and does not saturate

at all.

R2 = 0.92

AGC- LIDAR AND NDFI

• NDFI was correlated with

AGB estimated using the LiDAR model developed for TAL

• NDFI has an R2 value of

0.44 but saturates at 300 tons/ha

R2 = 0.44

LAMP RESULTS AT 1Ha RESOLUTION

R2 = 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
• f 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:

COMMENTS!