Download presentation
Presentation is loading. Please wait.
1
OROMIA Forest Reference Level WHY a Regional Forest Reference Level (R-FRL)? Ethiopia submitted its National Forest Reference Level in 2016. A regional Forest Reference level will allow Oromia to assess progress on the outcomes of the policies and measures taken to mitigate climate change in the forestry sector for domestic reasons at subnational scale. The Oromia FRL document is currently under development using an approach coherent with the national. The narrative should be completed by ORCU and MEFCC under the supervision of REDD+ Secretariat and TA from FAO
2
OROMIA Forest Reference Level DATA Activity Data calculated per Biome after a sampling intensification (Region specific). The Emission Factors from NFI calculated per Strata and then weighted per Biome.
3
OROMIA Forest Reference Level SCOPE Activities: Deforestation & Afforestation Pools: AGB, BGB, deadwood (excluded with scientific justification, litter and soil) Gases: CO2 only
4
OROMIA Forest Reference Level
5
Forest Reference Level
OROMIA Forest Reference Level NFI Data collected from 67 Sample Units that fall in forest strata (a total of 268 plots in the forest strata) over a total of 204 SUs across the Oromia region (816 plots) Applied allometric equation: Chave et al., 2014 Conversion factors for C and for BGB from IPCC (2016) WD from Ethiopian Database
6
OROMIA Forest Reference Level NFI
7
OROMIA Forest Reference Level NFI
8
OROMIA Forest Reference Level NFI
9
OROMIA Forest Reference Level NFI
10
OROMIA Forest Reference Level AD
11
OROMIA Forest Reference Level PROPOSED FOREST REFERENCE LEVEL
12
OROMIA Forest Reference Level PROPOSED FOREST REFERENCE LEVEL
13
FOREST REFERENCE LEVEL
OROMIA Forest Reference Level PROPOSED FOREST REFERENCE LEVEL 5.06M tonCO2e/yr 0.735M tonCO2e/yr
14
FOREST REFERENCE LEVEL
OROMIA Forest Reference Level PROPOSED FOREST REFERENCE LEVEL
15
OROMIA Forest Reference Level Thank you!
16
OROMIA Forest Reference Level Some considerations about the trend analysis The precision of the method used for estimates is too low to achieve an significant trend. The trend for two periods will have overlapping confidence intervals, resulting in a insignificant trend. Lack of freely available very high resolution yearly imagery impeded the accuracy assessment of the yearly Hansen forest loss data Lack of freely available very high resolution data for earlier years limited collection of sample data for classifier training and validation. Lack of human resources for testing other methods
17
Hansen data forest loss 2012 and 2013
18
Ethiopian activity data 2000-2013
Similar presentations
© 2025 SlidePlayer.com. Inc.
All rights reserved.