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]

4.3   Guiding principles – Remote sensing and ground-based observations Previous topic Parent topic Child topic Next topic

  • In most cases estimates of emissions and removals associated with REDD+ activities will be made using a combination of remotely-sensed and ground based data.
  • Landsat satellites provide a time series of remotely sensed digital images spanning 40 years and are being used widely in monitoring activities such as deforestation, forest degradation and natural disturbances, and for estimating changes in biomass and carbon stocks.
  • Other types of remotely sensed data, such as SAR, LIDAR and high resolution optical data are increasingly available and helpful especially in extending the range of REDD+ activities for which operational methods are available.
  • Pre-processed data sets can be used as a basis for REDD+ estimation in conjunction with reference and auxiliary data to capture national circumstances.
  • Remotely sensed and auxiliary ground-based data in combination are likely to be useful for stratification in order to increase sampling efficiency.
  • If sufficient NFI data are available over space and time and at sufficient spatial resolution, NFIs can be used to estimate directly from repeated inventories stock changes associated with REDD+ activities. It will often be best to use NFIs in combination with remotely-sensed data.
  • Data from NFIs are also a potentially valuable source of information for REDD+ estimation using gain-loss methods, and for developing modelling approaches at Tier 3.
  • Detailed information generated at a fine scale at intensive monitoring sites can help address the difficulty of estimating stocks and stock changes for litter, dead wood and soil, by supporting development of model parameters, including emissions and removals factors.