Transparent monitoring in practice:
Supporting post-Paris land use sector mitigation
(TransMoni)
Project activities and expected outcomes in Ethiopia
By: Stibniati Atmadja (s.atmadja@cgiar.org), Manuel Boissière, Niki De Sy, Robert
Masolele
Scoping workshop, ILRI, Addis Ababa, Ethiopia, 30 July 2021

Monitoring GHGs under the Paris Agreement
Project goal
• Developing, testing and approving good practice guidance, for national accountable
implementation of TM approaches
• Contribute with improved data to increase monitoring capacities
• Supporting the uptake of the guidance in the international processes, including in the
context of the UNFCCC negotiations.
• Develop good practice methodologies for monitoring approaches that assist countries
with limited resources and data in implementing improved monitoring in the land use
sector
o tool-neutral and bottom-up guidance for open source datasets/tools
o based on case studies in several countries
o testing opensource data/tools (e.g., FAO’s OpenForis, Global Forest Watch, Geo-Wiki)
International Context
• The Paris Agreement emphasizes the land use sector’s importance for mitigating
climate change.
o “In order to build mutual trust and confidence and to promote effective implementation, an enhanced
transparency framework [ETF] for action and support, with built-in flexibility which takes into account Parties’
different capacities and builds upon collective experience is hereby established.” (Art 13:1 Paris Agreement)

Introduction of the project
• Project title: Transparent monitoring in practice: Supporting post-Paris land
use sector mitigation (TransMoni)
• Country Partners
o REDD+ Secretariat (Ethiopia)
o SEPREDD (Côte d’Ivoire)
o National Forest Authority (Papua New Guinea)
o Ministry of Environment (MINAM) (Peru)
• International Partners:
o Oeko-Institut e.V. (Germany) (Lead)
o CIFOR (Indonesia) (Co-Lead)
o UN-FAO (Italy)
o IIASA (International Institute for Applied Systems Analysis) (Austria)
o National Wildlife Federation (NWF) (USA)
o Wageningen University (Netherlands)
• Duration: 3 years (start date Dec 2020)
• Main donor: International Climate Initiative (IKI) of the German Federal
Ministry for the Environment, Nature Conservation, and Nuclear Safety
(BMU)

Project expected outcomes in Ethiopia
• Ethiopia’s national MRV system is better
aligned with the Paris Agreement’s Enhanced
Transparency Framework (ETF), by improving
processes and information quality for future
submissions

Overview of proposed activities in Ethiopia
1. Improve community
participation in MRV
2. Improve multilevel
MRV collaboration
O2. Improved national data on
forest/land use change in light
of the ETF (WUR + REDD Sec)
O1. Improved a/reforestation
MRV practices (CIFOR + REDD
Sec)
3. Improve information on
drivers of forest change by
using national and global
open-source datasets and
methods

3. Open-source data on drivers of
forest change : Federal
2. Multilevel MRV: BGRS,
Oromia Regional State, Federal
1. Participatory MRV: BGRS
Assosa Zone
Project geographical intervention (Ethiopia)

Outcome 1: Improved a/reforestation MRV practices
Afforestation / Reforestation
• one of the main sources of emission reductions in Ethiopia’s NDC and REDD+
implementation plan (RIP):
• Important climate change adaptation in dry forest biomes
• Produces carbon and non-carbon benefits
A/reforestation main technical challenges
• Difficult to monitor using remote sensing
• Safeguards and non-carbon information still fragmented.
• Data availability and flow between sectors and levels not yet well-understood
• Planted and maintained by communities, but they are not data provider or
validator
• Data burden falls on woreda forest expert

Outcome 1: Improved a/reforestation MRV practices
• Better collaboration across levels can improve data quality,
usefulness and ownership
• MRV on benefits and burdens of reforestation can help
understand reasons of reforestation fails/success
o Benefits: jobs, income, more access to fuelwood, timber, NTFPs.
o Costs: labor, cash, reduced income, conflicts
• Feedback from national to local can help
o Communities/woreda experts to know how well they are doing compared
to others
o Transparent benefit sharing and grievance redress mechanisms

1. Improving community participation in reforestation
MRV (CIFOR)
Background
• Research on participatory MRV (PMRV)
o Role of local actors in MRV: plant the
trees, give data.
o Participatory MRV can improve data
quality, but benefits to local actors are
unclear
o Cost of PMRV: time, ‘illegal’ livelihoods in
jeopardy
o Benefit of MRV for local actors?
 Feedback? Legitimacy? Access to
information?
o Sustainability and legitimacy of MRV
compromised

Activities: literature review, interviews and focus group discussions with MRV-
related practitioners and community members engaged in reforestation, about
• The current and potential role of communities in reforestation MRV
• Perceptions, motivations and worries in participating in reforestation MRV
• Potential costs and benefits of reforestation MRV at the community,
woreda and Kebele levels
Outputs: Report and workshop (national and regional) on the potential of
integrating communities in reforestation MRV; guidance on TM for Ethiopia
Relevant actors:
• Government institutions at federal level (EFCCC),
• Government institutions at regional/local levels (woreda, kebele),
• Local communities involved in restauration initiatives
• CSOs (EWNRA, FarmAfrica, GLAD), academics (CIAT, CIFOR, WGCFNR)
1. Improving community participation in reforestation
MRV (CIFOR)

2: Improving multilevel collaboration in reforestation MRV
Background
• Research on transformational change
in land use and climate change
o Multi-level, multi-sector linkages
essential to achieve change
o Shared learning, information
exchange, transparency
• Research on REDD+ MRV in Ethiopia
o MRV is multi-level, multi-sector issue
o Non-carbon data not well-integrated
o Actors at every level
o Need to bring data and actors together
How and why data is shared is as
important as what data is shared

• Activities: Desk-based study, key informant interview and workshop
series about
o data availability of carbon and non-carbon REDD+ benefits for MRV
o challenges/opportunities of data exchange and collaboration across levels.
• Output: Report and workshop (national and regional) on multilevel
MRV for reforestation; Guidance on TM for Ethiopia
• Relevant actors:
o Federal: EFCCC+ REDD+ Secretariat, other ministerial level agencies, Federal
data managers (e.g. CSA, EMA, EBI), academics (e.g. EEFRI, WGNR, CIFOR-
ICRAF, CIAT)
o Regional (Oromia, BG): Government bureaus, REDD+ actors (Oromia REDD+
Coordination Unit, OFWE), CSOs with REDD+/restoration activities (Farm
Africa, SOS Sahel, World Vision)
o Zone/woreda/kebele (BG): local forestry expert & government
administration, local restoration initiatives (Coordinate with outcome #1)
2: Improving multilevel collaboration in reforestation MRV

Outcome 2: Improved national data on forest/land use
change in light of the ETF
• Better understanding of land use change dynamics
o Updated assessment of land use following deforestation in Ethiopia is
essential for REDD+ implementation and not routinely available as a
national dataset
o Open-source tools such as SEPAL and Open FORIS could be leveraged to
assess forest/land use change based on satellite time series data, in
combination with high resolution images that can be used to support
calibration and validation
• Preparing for the Enhanced Transparency Framework (ETF) in GHG
accounting
o Explore match between country-reported data and global datasets, and
work towards understanding of differences and (if needed) harmonization
 E.g. harmonization of classes, and consideration of spatial and temporal differences
in datasets.
o Need to understand uncertainties in datasets
o Need trained staff

Background
• PhD candidate Robert Masolele
• Pantropical case study
• AI/deep learning models using
spatial and temporal information
from dense Landsat time-series
to predict land use activities
driving deforestation
• Open source platform in SEPAL
and GEE
3. Open-source datasets and information on drivers of forest change

Way forward
• Adapt deep learning model to
Ethiopian context
• Land use classes
• Method
o SEPAL
o Forest loss 2010 – 2014
o Land use following deforestation
2016
o Planet data, Landsat & Sentinel 2
o Other open-source data for
calibration and validation
Follow-up land use classes
Agriculture
Large-scale croplands
Small-scale cropland
Pasture/free grazing
Coffee crops
Mining
Infrastructure Roads
Buildings and dams
Plantation forest
Other land with tree cover
3. Open-source datasets and information on drivers of forest change

• Activities: develop reproducible open-source method in SEPAL for assessing
direct drivers of forest loss for Ethiopia with
o Close collaboration with EFCCC and FAO/SEPAL
o Exploring the match between (open-source) national and global
datasets, and work towards understanding of differences and (if
needed) harmonization
o Integration of high-resolution imagery to calibrate and validate existing
assessment of land use change
o Possibility of regular updates in the future by Ethiopia partners (and
other countries)
• Output
o Methodology for assessing drivers of forest change for Ethiopia
implemented in SEPAL
o Joint report on forest and land use change for Ethiopia
o Experiences as input to TM guidance for Ethiopia and beyond
3. Open-source datasets and information on drivers of forest change

cifor.org
blog.cifor.org
ForestsTreesAgroforestry.org