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
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]

4.2   Ground-based observations Previous topic Parent topic Child topic Next topic

Ground-based observations are needed for the estimation of carbon and non-carbon dioxide GHG emissions and removals for REDD+ activities, regardless of the sampling or inferential method used. Ground-based observations are used to estimate emissions and removals factors, establish growth models for different types of forests, to parameterise Tier 3 models and as reference data for estimating activity data. Although availability will differ from country to country, examples relevant ground-based observations include:
  • NFIs, subnational forest inventories, and forest assessments based on plot or transect measurements;
  • growth and yield studies, harvested wood removals, and models for converting these to biomass;
  • auxiliary spatial data on land use, management, disturbance history, soil type which can be used to guide the selection and application of emissions and removals factors ;
  • research data that can be used to estimate emissions and removals in above- and below ground biomass, litter, deadwood and soils;
  • field observations which can be converted to emission/removal factors for non-CO2 GHGs from soils and fire.
For REDD+, emissions and removals estimates can be developed using data from NFIs and related intensive monitoring sites and auxiliary data. In general it will be efficient for the NFMS to collate relevant existing information (Chapter 4) prior to commencing any further sampling, and to conduct a gap analysis to determine the most efficient sampling strategy. Access to original data sets, data collection protocols employed as well as documentation of data quality checks undertaken are important for transparent reporting and assessment of generated estimates. To maintain representativeness, consistency of definitions and protocols, data generally need to be stratified according to forest type, soil and climatic conditions, topography, and the nature of forest disturbances induced by anthropogenic or natural factors (Chapter 2, Section 2.3.2).