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]

Appendix E   Relative efficiencies Previous topic Parent topic Child topic Next topic

This appendix contains the results and the literature references supporting the conclusions summarized in the dot points in Box 19.

Table 22: Relative efficiency of using the national versus UMD GFC based F/NF and change maps for Gabon

Country: Gabon
Type of reference data: independent interpretation of satellite imagery
Type of map/remotely sensed data
Biome/type of forest
Target variable
Relative efficiency of using national vs global map
% reduction in sample size
UMD GFC tree cover with 30% cover threshold F/NF 1 ha MMU map
Tropical rainforest
Forest area
9.5
89.4
UMD GFC tree cover with 30% cover threshold F/NF no MMU map
Tropical rainforest
Forest area
9.2
89.1
UMD GFC tree cover with 70% cover threshold F/NF 1 ha MMU map
Tropical rainforest
Forest area
3.8
73.6
UMD GFC tree cover with 70% cover threshold F/NF no MMU map
Tropical rainforest
Forest area
3.8
73.8
UMD GFC tree cover with 30% cover threshold F/NF 1 ha MMU map
Tropical rainforest
Net forest change area
2.0
49.7
UMD GFC tree cover with 30% cover threshold F/NF no MMU map
Tropical rainforest
Net forest change area
2.6
61.0
UMD GFC tree cover with 70% cover threshold F/NF 1 ha MMU map
Tropical rainforest
Net forest change area
4.6
78.3
UMD GFC tree cover with 70% cover threshold F/NF no MMU map
Tropical rainforest
Net forest change area
2.6
61.6
Reference:
Sannier, C., McRoberts, R. E., & Fichet, L. (2016). Suitability of Global Forest Change data to report forest cover estimates at national level in Gabon. Remote Sensing of Environment. 173:326–338.

Table 23: Relative efficiency of using the national and UMD GFC based F/NF and change maps against sample data for Gabon

Country: Gabon
Type of reference data: independent interpretation of satellite imagery
Type of map/remotely sensed data
Biome/type of forest
Target variable
Relative efficiency of using map
% reduction in sample size
National F/NF Map
Tropical rainforest
Forest area
57.7
98
UMD GFC tree cover with 30% cover threshold F/NF 1 ha MMU map
Tropical rainforest
Forest area
6.1
83.6
UMD GFC tree cover with 30% cover threshold F/NF no MMU map
Tropical rainforest
Forest area
6.3
84.0
UMD GFC tree cover with 70% cover threshold F/NF 1 ha MMU map
Tropical rainforest
Forest area
15.3
93.4
UMD GFC tree cover with 70% cover threshold F/NF no MMU map
Tropical rainforest
Forest area
15.1
93.4
National F/NF Map
Tropical rainforest
Net forest change area
2.66
62.4
National F/NF Map
Tropical rainforest
Net forest change area
1.12
10.9
UMD GFC tree cover with 30% cover threshold F/NF 1 ha MMU map
Tropical rainforest
Net forest change area
0.57
n/a
UMD GFC tree cover with 30% cover threshold F/NF no MMU map
Tropical rainforest
Net forest change area
0.44
n/a
UMD GFC tree cover with 70% cover threshold F/NF 1 ha MMU map
Tropical rainforest
Net forest change area
0.24
n/a
UMD GFC tree cover with 70% cover threshold F/NF no MMU map
Tropical rainforest
Net forest change area
0.43
n/a
Reference:
Sannier, C., McRoberts, R. E., & Fichet, L. (2016). Suitability of Global Forest Change data to report forest cover estimates at national level in Gabon. Remote Sensing of Environment. 173:326–338.
Desclée, B., Mayaux, P., Hansen, M., Lola Amani, P., Sannier, C. Mertens, B., Haüsler T., Ngamabou Siwe, R., Poilvé, H., Gond, V., Rahm,M., Haarpainter, J., Kibambe Lubamba, J.P. (2014) Evolution of forest cover area at a national and regional scale and drivers of change in The forests of the Congo basin—State of the forest 2013. Eds : deWasseige C., Flynn J., LouppeD., Hiol Hiol F.,Mayaux Ph. – 2014.Weyrich. Belgium. 328 p.

Table 24: Relative efficiency of using the national and UMD GFC based F/NF against sample data for Tanzania

Country: Tanzania
Type of reference data: National inventory of ground plots (first 6 cases; photo interpretation of visual images (cases 7 and 8)
Type of map/remotely sensed data
Biome/type of forest
Target variable
Relative efficiency of using map
% reduction in sample size
UMD global map (tree cover and Landsat digital numbers from mosaics).
Calibrated to local forest definition.
Miombo woodlands
Forest area
1.4
29%
UMD global map. Tree cover with 10% cover threshold.
Miombo woodlands
Forest area
1.0
0%
UMD global map. Tree cover with 20% cover threshold.
Miombo woodlands
Forest area
1.2
17%
Global ALOS PALSAR forest/non forest map. Calibrated to local forest definition.
Miombo woodlands
Forest area
1.7
41%
Global ALOS PALSAR forest/non forest map.
Miombo woodlands
Forest area
1.5
33%
RapidEye optical satellite images. Calibrated to local forest definition.
Miombo woodlands
Forest area
2.0
50%
UMD global map (tree cover). Calibrated to local forest definition.
Miombo woodlands
Forest area
1.8
44%
RapidEye optical satellite images. Calibrated to local forest definition.
Miombo woodlands
Forest area
1.7
41%
Reference:
Næsset, E., Ørka, H.O., Solberg, S., Bollandsås, O.M., Hansen, E.H., Mauya, E., Zahabu, E., Malimbwi, R., Chamuya, N., Olsson, H. & Gobakken, T. 2016. Mapping and estimating forest area and aboveground biomass in miombo woodlands in Tanzania using data from airborne laser scanning, TanDEM-X, RapidEye, and global forest maps as auxiliary information: A comparison of estimated precision. Remote Sensing of Environment, 175: 282-306. Ørka, H.O. 2015. Accuracy assessment of global forest maps and high-resolution satellite imagery for forest area estimation in a first phase of MRV for REDD+. Report to the Norwegian Space Centre, 29 June 2015, unpublished, 19 pp.