Challenges for forest monitoring indeveloping countries:
global and national data experiencesin UN-REDD capacity building
Dr. Inge Jonckheere
FAO of the UN, ForestryJuly 2016
Lima, PeruUN-REDD Programme• Supports countries benefit from REDD+ (UNFCCC)– National REDD+ Strategies and Readiness• Established in 2008 by FAO, UNDP & UNEP
– Response to UN Framework Convention Climate

Change (UNFCCC) Bali Action Plan 2007
• Offers UN Joint Program: Delivering as One UN• Agreed delivery platform with Forest Carbon Partnership(FCPF) and Forest Investment Programme (FIP)• Current contributions: US$ about 300 million (withoutpledges) from donors Norway, Denmark and Spain

6 UN-REDD Work Areas

REDD+ Strategies

MRV and Monitoring

REDD+ Governance
Stakeholder Engagement
Multiple Benefits of forests/REDD+Transparent Equitable Accountable
Management of REDD+ Payments
REDD+ as Catalyst of Green Economy

Lead Implementation Role
MRV in the NP: FAO
Monitoring (M) & Measurement, reporting,verification (MRV)– Cornerstone for carbon monitoring• national communications to UNFCCC• one starting point for FR(E)L establishment• supports national / sub-national implementation of incentivesystems– Support to policy formulation and feedback• knowledge of drivers of change• information on multiple benefits

FAO’S RESPONSE- main outputs
Country support (64)COMBINED PROJECTS AND EFFORTS
UN-REDD (Norway, CE, Denmark, Spain, Japan, Luxemburg)

18 pilot countries

UN-REDD (Norway, CE, Denmark, Spain, Japan, Luxemburg)

32 countries

FAO-Finland (Finland)

5 countries

NFMA (Sweden, Finland, USA, Brazil, Angola, FAO TCP, GEF)

19 countries* Several countries are supported by more than one programme (e.g. Vietnam)

NFMSRM
Activity Data
Satellite Land Monitoring
SystemEmission Factors
National Forest Inventory

2005

VUNFCCC
Expert Reviews

GHGs Inventories

LULUCF
Inventory

UNFCCCInventorycompilation
QA/QC

Emission
Inventory
DatabaseMRV: Measurement

The IPCC’s methodological approach to calculate anthropogenic GHG emissions by sources and removals
by sinks related to forest land.

MRV: Measurement•••

Measurements of area change (Activity Data) and forest
carbon stock changes (Emission Factors)
This information provides the basis to compile a GHG
inventory

Emission factors– Forest carbon change– Assessment of biomass, carbon stocks and emission factors– Data are obtained from a national forest inventory (NFI)•2005

Activity data
– Area / forest cover change data (hectares per year)– Achieved using a satellite land representation system (SLMS)•ACTIVITY DATA
Satellite Land
Representation Systemx
EMISSION FACTORSNational ForestInventory

GHG Inventory– GHG assessment to determine national mitigation performance– Based on the data collected from the NFI and SLMS
– UNFCCC templates available=GHG Inventory

Information, Monitoring and MRVDevelopment through the 3 REDD+ Phases
REDD+ PHASES

Phase I

Capacity building& development

Year 2- Positive
incentive forverifiedperformance- Implementation ofP&Ms anddemonstration
activities- Readiness- Development of P&Ms

Year 1

Phase III

Phase II

Year 3

Year ...

Year ...

Year ...

REDD+ Safeguards
Information System

REDD+ Safeguards
Information System

Monitoring System

Monitoring System

SLRS

SLMS:
AD

NFI:
EF

GHG-I:CO2e

MRV System

Year ...

Monitoring Systems•To assess whether REDD+ is resulting in net positive
outcomes, i.e. results-based•

In Phase 2 of REDD+– To monitor the outcomes of demonstration
activities•In Phase 3 of REDD+– To monitor the outcomes of national policies andmeasures on all the national territory•

Technical requirements– Satellite Land Monitoring System (operationalremote sensing)– Web-GIS interface (for transparency, open access)Phase 3Phase 2

National forest monitoring systems
REDD+
MONITORINGSYSTEM
REMOTE SENSINGWEB INTERFACE Satellite data to monitor REDD+
activities at sub-national(demonstration) and national level Disseminated over internet
through a web-GIS interface

COMMUNITY
MONITORINGACTIVITY DATA
Satellite Land
Representation System2005

 Measurements of area change(Activity Data)Fitting the Systems Together

NATIONAL FOREST MONITORING SYSTEM

REDD+ SAFEGUARDSINFORMATIONSYSTEMLOCAL
ENGAGEMENT

REDD+MONITORINGSYSTEM

MRV SYSTEMMEASUREMENTREMOTE SENSINGREPORTING

COMMUNICATIONWEB INTERFACEDOCUMENTATIONCOMMUNITY
MONITORING

VERIFICATIONRS data used in countries• Main use:-training: both in-country, HQ and INPE (so free access needed)-AD: forest area detection (changes LULC)-NFI design (multisource inventory design and stratification)-Other: R(E)L, Location of households for surveys (HR), Use of HR for field plot
location, Mapping of co-benefits, Biodiversity (& other safeguards mapping)• Main RS data needs from countries:-data availability and cost analysis-data acquisition (actual purchase)-data (pre)processing-generation of statistics-accuracy assessment-web dissemination

Activity data
Mainly through RS for deforestation
No common approach yet for forest degradation,
several countries experimenting
Deforestation:

Degradation:

••
•
•
•

•
•

Medium-resolution
imagery (Landsat)
High-resolution imagery
Land registry (cadaster)•High-resolution imagery
Testing Landsat-NDVI combination
Need for time series
Timber records or management plans(volume harvested, species, collateral
damage, skid trails, …), drones
Fuelwood extraction statistics

Methodologies and technology for NFMS
z to technology and tools to generate their own
Countries require easy and inexpensive access
ADExperience Access to technology is quite limited,particularly for remote-sensing
technologies and data The basics are often missing (e.g. steadyelectricity, high-speed internet,
performing computers, software
packages) Certain technologies are costly (e.g. HR
images, Lidar, commercial software
packages), limiting large-scale
deployment and sustainability
 Ownership of data is crucial
FAO Forestry

Lessons learned
 Not promote specific tools/data sets but
provide overview of available options
 Help governments make informed decisions
 Support country decisions and tailor best
available approaches while maintaining
consistency and comparability of results
 Heavy reliance on complex & costly
technology may not be in all developing
countries’ best interest
 Open source, free software and global or
nation data sets that meet REDD+
requirements are available. If not, new tools
can be developed

Use of global data for national use•

Global data in the REDD+ context :1) Is available, so countries can use it when there is no other data available;
2) The quality of the data at national/local scales might vary3) Countries have the choice to use them as––––a) their national product without modification,b) their national product with some modification,c) an input to their national product,d) a validation dataset for their national product•Map with quantitative accuracy assessment yield statistically valid estimates of land coverclasses and changes. However, cartographically CORRECT maps are, however, more useful forland management and yield lower standard errors when making estimates.

•FAO Forestry promotes use of Landsat data for generating estimates of LCLU change atnational scales. The results we get from our assistance to National counterparts should be atleast similar in nature to those obtained by global products with a bit more focus on land use(instead of only land cover).

•FAO Forestry promotes quantitative assessments of all products intended for use as activity
data inputs. This includes performing accuracy assessments and area adjustments to provide
estimates on LC/LU and change.

FAO approach• Seeking best way to use available data
• Combine data with local knowledge to produce national
appropriate estimates• Building national ownership in the results and capacity• Range of level of engagement with global datasets:some only for comparison, some as training input, somewill only use global datasets• Use of global datasets– as training points for a supervised classification of change atnational level within the Google Earth Engine-API: examples
Kenya, ROC, Ethiopia, DRC– For mapping , carrying out an accuracy assessment to produce
adjusted area estimates with CI: Angola

Open source toolsImplementation with R, OFGT, GDAL, SEPAL

www.r-project.org

www.openforis.org

www.gdal.org• Free and open: independent versus commercial software• Reproducible: methods can be redone using the scripts•Transparent : maximum transparency: all scripts available
and guidance documents

SEPAL Cloud computing structure(SEPAL)http://www.openforis.org• This work was done in collaboration withFAO as a prototyping for the OpenForissystem• SEPAL  Amazon Web Services (AWS)• Cloud-based data processing
workflow
FAO / Norway SEPAL Progress Report
17/09/2015

SEPAL• Improve connection between data / users /information products for REDD+• Increase production speed of products required forMRV• Open, flexible system for rapid and standardized
image processing• Building national capacity for autonomous creationof national statistics: used now in 9 countries• Cloud-based and desktop functionality• Dense Landsat time series processing (collaborationwith WUR)

New openForis modules• OpenSARKit• Command line tools for quasi-fully automatic
preprocessing of nationwide SAR mosaics• Up to date: ALOS Palsar FBD data
• 30m output resolution• Output Stack: Backscatter values, Ratio,
Texture measures, DEM + aspect + slope

Collect Earth is a tool that enables data collection
through Google Earth with a sampling approach. In conjunction
with Google Earth, Bing Maps and Google Earth Engine, users
can analyse high and very high resolution satellite imagery for awide variety of purposes, including :• Activity data assessments of the Land Use, Land Use Changeand Forestry (LULUCF) for GHG Inventories• Assessment of the land use and land use change historical
trends for REL/RL• Support multi-phase National Forest Inventories• Monitoring agricultural land and urban areas• Validation of existing maps
• Collection of spatially explicit socio-economic data
• Quantifying deforestation, reforestation and desertification

Collect Earth System Overview

Google Earth
3D GIS for point-based, LULUCF sampling

Bing Maps
Geo-link with multiple image
repositories• Access to free, very
high resolution
imagery• Full integration withSaiku, for mining dataand generating chartsand other graphics

Google Earth Engine API
Trend visualization with vegetation indices

Google Earth EngineMulti-temporal analysis with 40 years of Landsat data

Saiku
Fast, intuitive and flexible data analysis

Collect Earth System Overview

FAO-INPE collaboration

FAO-INPE collaboration
Implementation of TerraAmazon in developing countries:• Free-of-charge and supported by analysis and programming
teams in Brazil (Funcate) and FAO HQ• Training on software utilities and Brazilian national forest
monitoring techniques at INPE CRA Amazonia, Belem, Brazil• Close collaboration BMU ICI, UN-REDD and INPE– 2015: Plug-ins in TerraAmazon• Training material for radar training in development• Follow-up and country implementation in FAO-HQ/country

Web portal development
For transparent, real-time access to forest dataand information, satellite images and forest
cover change, monitoring of the implementationand impact of REDD+ policies and measures• Completed: Paraguay, Ecuador• Under development: meso American platform

The NFMS development by UN-REDD

Audience
Country citizens are able to get acquainted about forest status
without read long technical reports
Policy makers can use this tool to support their legislative
initiatives

International GIS-RS experts can use the platform to have aglance on the overall forest dataset available

Supported countries
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See more at http://slms4redd.org

Democratic Republic of congo
Congo Republic
Paraguay
Ecuador
Papua New Guinea
ZambiaArgentina
BoliviaPerù
Congo
Cambodia
Pacific Islands
VietNamBangladesh
Sri Lanka
MyanmarBhutanNFMS is an Open data portal
End users browse national maps, display charts, read papers
related to forest assessment and redd+ initiatives

FA FOREST COVER 2010

“REDD+ Academy”
A package of 12 modules developed by all three
UN-REDD agency partners , covering all aspects ofREDD+ under the UNFCCC• Regional pilot “REDD+ Academy” event:
Yogyakarta, 2014
• Regional-level “REDD+ Academy” ToT events:– Argentina in 2015
– Modules refined by UN-REDD regional team andadapted to national contexts– http://www.unredd.net E-course launchedWhat we’ve learned• A few dedicated individuals can make all the difference– Use of international advisors hand-in-hand with national technicians• Need to see capacity building in broader terms– Training of resilient national institutions and consultants– Mandate of institutions should be clear• Integration NFI and RS, as well as integration of global data and national(local) knowledge• On-the-job training is key– Trainings are geared towards producing results– Essential to get faster delivery• Sharing data and data access is crucial and key: data sharing agreements
for national products• Near-real time monitoring for early warning (e.g. Global Forest Watch),
not for reporting of AD purposes in se• Resilience is often at risk
– Easy to develop quickly elements of NFMS, but resilience will be lacking– Long-term commitment is required by government and partners in order to securesustainability

Benefits of collaboration
FAO/UN-REDD+GEO-GFOI?
• Share expertise and skills (recognise respectivestrengths)• Coordination on country activities/regional events• Avoid overload of limited capacity• Collaborate on methods (improve efficiency)• Share data (sovereignty, institutional / licensing issues)• Negotiate data sharing agreements jointly (+bulk buy?)• Share field and RS validation data (improve accuracy, overcome
institutional inconsistencies)• Strive for Consistent results – reduce policy confusion

Way forward• Integration of existing data pre-processing and change
detection algorithms as well as integration of global datsets
into SEPAL preprocessing chains• Approach of ‘modules’ which allows the countries to pick andchose dependent on the country needs (data bulk
downloading ,preprocessing (geometric/radiometric), cloudmasking, change detection, statistics, mapping)• In-country support using best available data
• Practical hands-on guidance documents• Ongoing and new collaborations with institutions, NGOs andacademia

Thank You!
Inge Jonckheere
FAO-UNREDD & colleagues of FAO Forestry
Inge.jonckheere@fao.org
Erik.lindquist@fao.org
Remi.dannunzio@fao.org
Websites:
http://www.un-redd.org
www.slms4redd.org