Uncertainty [MGD Sections]

UNFCCC decisions and requirements
IPCC good practice guidance
Relationship to UNFCCC
GHGI coverage, approaches, methods and tiers
Design decisions relevant to national forest monitoring systems
Land cover, land use and stratification
Forest reference emission levels and forest reference levels
Quality assurance and quality control
Guiding principles – Requirements and design decisions
Estimation methods for REDD+ activities
Integration frameworks for estimating emission and removals
Selecting an integration framework
Activity data x emission/removal factor tools
Fully integrated tools
Practical considerations in choosing an integration tool
Guiding principles – Methods and approaches
Remote sensing observations
Coarse resolution optical data
Medium resolution optical data
High resolution optical data
L-band Synthetic aperture radar
C-band and X-band SAR
LIDAR
Global forest cover change datasets
Ground-based observations
National forest inventories
Auxiliary data
Guiding principles – Remote sensing and ground-based observations
Activity data
Methods for estimating activity data
Maps of forest/non-forest, land use, or forest stratification
Detecting areas of change
Additional map products from remote sensing
Estimating uncertainty of area and change in area
Estimating total emissions/removals and its uncertainty
REDD+ requirements and procedures
Reporting forest reference emission levels and forest reference levels
Technical assessment of forest reference emission levels and forest reference levels
Reporting results of REDD+ activities
Technical analysis of the REDD+ annex to the BUR
Additional advice on REDD+ reporting and verification
Guiding Principles – Reporting and verification of emissions and removals
Financial considerations
Country examples – Tier 3 integration
Use of global forest change map data
Relative efficiencies
Developing and using allometric models to estimate biomass

Record Keeping [MGD Sections]

Integration + Estimation [MGD Sections]

Ground Based Observations [MGD Sections]

5.2.6.1   Method 1: Calculation of emissions/removals factors from spatially segregated strata Previous topic Parent topic Child topic Next topic

For the first method, two spatially segregated strata that differ in carbon density (A and B) can be independently sampled, with the mean emission/removal factor given by:
Equation 27
image80.svg
where image81.svgand image82.svgare the mean carbon densities for each stratum as calculated from the sample.
In this context stratum A could correspond to modified natural forest (MNF), and stratum B to primary forest (PF), with image83.svg therefore corresponding to the term [CBPF − CBMNF] in Equation 1 in Chapter 3, Section 3.1.2.
Because the sampling in each of the strata is independent, the uncertainty of image84.svg can be calculated as
Equation 28
image85.svg
Where image86.svg is the variance of the estimate of the respective mean (see also Section 5.1.5.1, Equation 2).
Note that image87.svg is often called the standard error, and when multiplied by the appropriate t0.95 statistic (usually taken to be 1.96) gives the 95% confidence interval. Equation 28 corresponds to Rule A of section 6.3 of GPG2000 Opens in new window(1), which is cross-referenced in section 5.2.2.1 Opens in new window of GPG2003 - although Rule A is expressed in terms of 95% confidence intervals, rather than variance.

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