Spatial + Temporal Scope [MGD Sections]
Institutional arrangements and REDD+ decisions
UNFCCC decisions and requirements
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
Estimation methods for REDD+ activities
Integration frameworks for estimating emission and removals
Guiding principles – Methods and approaches
Remote sensing observations
Ground-based observations
Guiding principles – Remote sensing and ground-based observations
Activity data
Emissions/removals factors
Reporting and verification of emissions and removals
Financial considerations
Country examples – Tier 3 integration
Use of global forest change map data
UNFCCC decisions and requirements
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
Estimation methods for REDD+ activities
Integration frameworks for estimating emission and removals
Guiding principles – Methods and approaches
Remote sensing observations
Ground-based observations
Guiding principles – Remote sensing and ground-based observations
Activity data
Emissions/removals factors
Reporting and verification of emissions and removals
Financial considerations
Country examples – Tier 3 integration
Use of global forest change map data
REDD+ Activities [MGD Sections]
Institutions involved in measurement, reporting and verification
Measurement, reporting and verification processes
UNFCCC decisions and requirements
IPCC good practice guidance
Design decisions relevant to national forest monitoring systems
Estimation methods for REDD+ activities
Integration frameworks for estimating emission and removals
Reporting and verification of emissions and removals
Use of global forest change map data
Measurement, reporting and verification processes
UNFCCC decisions and requirements
IPCC good practice guidance
Design decisions relevant to national forest monitoring systems
Estimation methods for REDD+ activities
Integration frameworks for estimating emission and removals
Reporting and verification of emissions and removals
Use of global forest change map data
LULC Stratification Scheme [MGD Sections]
UNFCCC decisions and requirements
UNFCCC decisions and requirements
Design decisions relevant to national forest monitoring systems
Estimation methods for REDD+ activities
Integration frameworks for estimating emission and removals
Selecting an integration framework
Practical considerations in choosing an integration tool
Remote sensing observations
Global forest cover change datasets
Ground-based observations
Guiding principles – Remote sensing and ground-based observations
Activity data
Maps of forest/non-forest, land use, or forest stratification
Reporting and verification of emissions and removals
Guiding Principles – Reporting and verification of emissions and removals
Financial considerations
Sampling
UNFCCC decisions and requirements
Design decisions relevant to national forest monitoring systems
Estimation methods for REDD+ activities
Integration frameworks for estimating emission and removals
Selecting an integration framework
Practical considerations in choosing an integration tool
Remote sensing observations
Global forest cover change datasets
Ground-based observations
Guiding principles – Remote sensing and ground-based observations
Activity data
Maps of forest/non-forest, land use, or forest stratification
Reporting and verification of emissions and removals
Guiding Principles – Reporting and verification of emissions and removals
Financial considerations
Sampling
Forest Definition [MGD Sections]
Institutional arrangements and REDD+ decisions
UNFCCC decisions and requirements
IPCC good practice guidance
Design decisions relevant to national forest monitoring systems
Definition of forest
Land cover, land use and stratification
Forest reference emission levels and forest reference levels
Estimation methods for REDD+ activities
Remote sensing observations
Global forest cover change datasets
National forest inventories
Activity data
Reporting and verification of emissions and removals
UNFCCC decisions and requirements
IPCC good practice guidance
Design decisions relevant to national forest monitoring systems
Definition of forest
Land cover, land use and stratification
Forest reference emission levels and forest reference levels
Estimation methods for REDD+ activities
Remote sensing observations
Global forest cover change datasets
National forest inventories
Activity data
Reporting and verification of emissions and removals
Carbon Pools [MGD Sections]
IPCC good practice guidance
Significance and key category analysis
Design decisions relevant to national forest monitoring systems
Activity data x emission/removal factor tools
Fully integrated tools
Ground-based observations
Emissions/removals factors
Above- and belowground biomass
Dead wood and litter pools
Soil organic carbon
Emissions from prescribed fires and wildfires
National choices in emissions and removals factor estimation
Emission and removal factor uncertainties
Estimating total emissions/removals and its uncertainty
Guiding principles – Estimation and uncertainty
Financial considerations
Sampling
Country examples – Tier 3 integration
Brief review of the potential for estimation of biomass by remote sensing
mgd_Appendix_H
Significance and key category analysis
Design decisions relevant to national forest monitoring systems
Activity data x emission/removal factor tools
Fully integrated tools
Ground-based observations
Emissions/removals factors
Above- and belowground biomass
Dead wood and litter pools
Soil organic carbon
Emissions from prescribed fires and wildfires
National choices in emissions and removals factor estimation
Emission and removal factor uncertainties
Estimating total emissions/removals and its uncertainty
Guiding principles – Estimation and uncertainty
Financial considerations
Sampling
Country examples – Tier 3 integration
Brief review of the potential for estimation of biomass by remote sensing
mgd_Appendix_H
Approaches Methods + Tiers [MGD Sections]
Institutional arrangements and REDD+ decisions
IPCC good practice guidance
GHGI coverage, approaches, methods and tiers
Significance and key category analysis
Estimation methods for REDD+ activities
Integration frameworks for estimating emission and removals
Guiding principles – Methods and approaches
Activity data
Emissions/removals factors
Estimating total emissions/removals and its uncertainty
Guiding principles – Estimation and uncertainty
REDD+ requirements and procedures
Financial considerations
Sampling
Country examples – Tier 3 integration
Use of global forest change map data
IPCC good practice guidance
GHGI coverage, approaches, methods and tiers
Significance and key category analysis
Estimation methods for REDD+ activities
Integration frameworks for estimating emission and removals
Guiding principles – Methods and approaches
Activity data
Emissions/removals factors
Estimating total emissions/removals and its uncertainty
Guiding principles – Estimation and uncertainty
REDD+ requirements and procedures
Financial considerations
Sampling
Country examples – Tier 3 integration
Use of global forest change map data
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2.3.2 Land cover, land use and stratification
Although the terms land cover and land use may be used interchangeably they are not synonymous. Land cover can change temporarily without change in land use – e.g. tree cover may be temporarily removed but land remains in forest land use if replanting or other regeneration follows.
The GPG2003 ask that the land of a country be reported using the six land use categories previously identified in Table 3, namely Forest Land, Croplands, Grasslands, Wetlands Settlements and Other Land. In general reporting against the six IPCC land use categories and changes between them cannot be achieved on the basis of remote sensing observations alone but also requires rules for attribution based on spatially explicit location and auxiliary data (Table 6; Chapter 4, Section 4.2.3) e.g. climate, ecosystem, management type, accessibility and time-series analysis (Box 7), to distinguish for example whether forest cover loss is due to deforestation (change in land use) or is temporary (no change in land use because tree forest is expected to be replanted of regenerate). This can lead to nationally specific stratification schemes which are then categorized into the IPCC classes according to national definitions.
Attribution is the process of associating observed land-cover changes with underlying causes of disturbance. Knowledge of the cause of disturbance is needed for the estimating GHG emissions and removals because different disturbance types have different impacts on carbon stocks (Kurz et al., 2009).
Table 6: Examples of auxiliary data and possible assumptions that can help with classifying land use
Data | Source | Possible assumption |
Forest management plans | Forest agencies, stakeholders | That plans are implemented |
Maps of plantation establishment | Forest agencies, private sector | Plantation species will be established. |
Species (or natural/plantation splits) | Remote sensing (either the same or other sensors as used for the time series) | Plantation species will be established. Natural species will have been cleared for other uses |
Fire maps | Remote sensing Land management agencies | Change that occurs at the same time as fire is a fire |
National parks and protected areas | Land management agencies | Changes are natural, unless otherwise noted |
Climate or soils types | Resource agencies, meteorological agencies | Determine the types of crops and management that can occur in certain regions (e.g. no crops in a desert) |
Stratification is important for several reasons. It can
- in the use of resources in preparing emissions and removals estimates
- assist in the management of uncertainties
- allow greater flexibility in reporting of monitored data (for example effectiveness of policies tailored to specific strata (forest types, risk types))
- enable tailoring of specific methods or data collection processes in different strata (for example it is much more difficult to measure deforestation using traditional optical methods in fragmented dryland forests than contiguous moist tropical forests).
Where relevant, stratification can be undertaken to distinguish between managed and unmanaged land in the various categories to meet the requirement of including only anthropogenic emissions and removals using the managed land proxy(1). While this approach to separating natural and anthropogenic emissions and removals is a proxy, it is the only generally practicable approach. Settlements and cropland are by definition managed, and it may be that all land in other categories can be considered as managed.
Stratification does not necessarily entail the use of maps, although usually(2) spatially explicit data (e.g. georeferenced NFI plots) are used. It may be on the basis of ground data or remotely-sensed data, or both in combination. Strata need to be sufficiently distinct to be identifiable and the boundaries of strata can change over time e.g. if the frontier of disturbance moves into areas of previously undisturbed forest. Information such as stocking densities (e.g. volume, biomass or carbon) and specialized map layers such as soils, site class, topography, aspect, dominant tree species or species clusters are commonly used for stratification. Examples of the stratification process can be found in McRoberts et al., 2002 and Olofsson et al., 2013.
Estimation of forest degradation, and the 'plus' activities of REDD+(3) may require finer resolution data (both spatially and temporally) than are being used currently by countries. Development of national capacity will help take advantage of technical developments as they become available(4). For forest degradation auxiliary information on harvesting, whether legal or not, and other disturbances will help considerably.
Likelihood of human disturbance can also be the basis for stratification. Identification of areas at high risk of deforestation can assist in designing early warning and targeted monitoring processes. Data sources and tools are available to assist in this process (Chapter 4, Section 4.2.3). Box 20 and Chapter 5, Section 5.1 provide more information on stratification.
Box 7: Plantation management in Kenya
In Kenya the standard plantation management practice following harvest is to put crops on the land for 1-2 years before replanting. In this case the remote sensing program will correctly see that the cover has changed from forest to crop. The attribution process notes that this is a human induced change in cover (due to the harvest). However, it is noted that the harvest occurred in a plantation (determined through knowledge of the species and stand maps from the Forest Information system). The policy and reporting rule set by the Government of Kenya is that the short crop cycle is part of plantation management. Consequently the land use does not change, (that is, it remains forestland) and all emissions associated with the harvest and removals from subsequent replanting reported under forestland. However, there is also the chance that the land will have been cleared and will not be returned to trees. If the land cover does not return for forest within a specified number of years, then a land use change is considered to have occurred at the time of harvest and the land areas are updated accordingly in the next report.
(1) | IPCC 2010 Technical Paper Revisiting the Use of Managed Land as a Proxy for Estimating National Anthropogenic Emissions and Removals. ![]() |
(2) | Stratification is possible without spatially explicit data, e.g. based on frequencies of occurrences of various classes and guided by expert judgement and credible assumptions. |
(3) | Namely conservation of forest carbon stocks, sustainable management of forests and enhancement of forest carbon stocks. |
(4) | E.g. it is currently challenging to detect changes in canopy cover associated with degradation. In October 2013 GFOI and GOFC-GOLD held a workshop and published a report on technical developments in monitoring degradation ![]() |