International Technical Seminar on REDD+, 16-17 February, 2011, Tokyo, JapanSession 5: R&D Trend about MRV Methods for REDD+A Case Study on a MRV System for REDD+ in Lao P.D.R.

Mitsuru NASU, Ph.D. *Khamma HOMSYSAVATH**,Tooru FURUYA*, Yoshitaka GOMI*, Takahiro HOSOKAWA*,Takao ISOBE, Akitaka IWATA*, Courage KAMUSOKO, Ph.D.*, Hiromichi MORIIKE*,Ryuji NAKADA*, Akihiro NAKAZAWA*, Katsumasa OONO*, Takashi SOMEYA, Ph.D. *,ShunsukeTOMIMURA*,Takeshi YAMASE*,Masayuki YOSHITOMI*, Yukio WADA*, Takio SANO*(*) Asia Air Survey Co., Ltd. (AAS), Tokyo, Japan(**) FIPD, Department of Forestry, Ministry of Agriculture and Forestry, Lao P.D.R.
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1. Outline of the Study(1) Study Project●TITLE: “The Study on the Strengthening of Methodologicaland Technological Approaches for Reducing
Deforestation and Forest Degradation within the REDD
Implementation Framework: Application in Lao P.D.R.”● Support: Forestry Agency, Ministry of Agriculture, Forestryand Fishery (MAFF), Japan● C/P Organization: Forest Inventory and Planning Division(FIPD), Department of Forestry, Ministry of Agricultureand Forestry, Loa P.D.R.
2(2) Objectives of the Study● To implement technical development for monitoring system ofdeforestation and forest degradation including themeasurement methods of forest conditions and changes, theestimation method of forest carbon stock and the method of
future simulation for forest changes using remote sensing and
GIS technologies;● To assist counterparts in the forest sector in a various ways
toward the realization of REDD+;● To provide capacity development assistances for improving
information sharing, knowledge and technical capacity throughtechnical training programs as well as workshops in both Lao
PRG and Japan; and● To contribute the strengthening of regional level's REDD+
approach through implementation of the above activities.
3(3) Driving Factors of Deforestation andForest Degradation*[Deforestation]● (Continuous) Farmland Development● Dam construction● Road construction● Mining● Construction of public facilities● Illegal logging at a large scale[Forest degradation]● Slash-and-burn shifting cultivation● Illegal logging at a small scale(selective logging)(*): Based on the result of the present study

4● Population increase(2%/yr.)● Economical development(8%/yr.)● Forest cover:70%(1940) →41.5%(2002)(FAO)

(4) Contents of the Study (2009 and 2010)
A Practical Approach towards REDD+ Implementation Mechanismand for Establishing an Integrated MRV System

Activities

1. Monitoring
System ofDeforestation
and Forest
Degradation
using RSTechnology

2. Analyses ofDriving Factorsof Deforestation,
and Baseline,
and Simulationof Future Forest
Changes

3. The Creationof a Forest GIS
Database

4. Calculationof the Amountof Carbon
Stocks inForest Area

5. Capacity
Development
Activities- Estimation
Models ofForest Carbon
Stocks- Forest Plot
Survey- Workshops ,- Trainings (Officeand Field),- Trainings in Japan

Results
Land Use /Land
Cover Maps (3＋2time periods)
Deforestation /Forest Degradation
Maps
Geospatial Data for
Forest GIS
5National & Provincial
Level Socio-economic
Data Analyses
District and Village
levels Socio-economic
SurveysGIS Databases
for Reporting at
Various Levels

Technical Manuals

Analyses of Baselines
Simulation Analysis ofFuture Forest
Changes

Integration

GIS database forforest management(Central and local)

(5) MRV System (Result of the Study)
Measurement (Initial and Monitoring)

Reporting

Verification

National Level- Land Use/Cover Maps (Wall-to-wall) basedon Medium Resolution Satellite Images(Landsat, Spot Images, etc.)- Management Unit: Systematic Sample Points
Data (ex. 0.25 ºGrid)

Provincial Level

Grid-based
ManagementSystem(MS)- Land Use/Cover Maps(Wall-to-wall) basedon Medium Resolution Satellite Images(Landsat, Spot Images, etc.)- Management Unit: Unit Watershed

Local/Project Level- Forest Compartment map basedon Medium High Resolution SatelliteImages (ALOS/PRISM, AVNIR2, etc.)

Watershedbased MS- Management Unit: Forest Compartment

Forest Permanent Plot System
Prediction System for Future Forest Change Compartment
6-based MS
Monitoring
System-Publication-Organizational
Auditing-Verification bya third party

2. Study Activities and Results in 2009 -10
2.1 Pilot Study Areas
Two areas having different geographic
environments were selected as pilot study
areas for the Study.
Louangphabang
Province● Area:20,000 km2● Slash-and-burnshifting cultivation

Pakxeng
district
1,600 km2

● Area: 4,400 km2● Slash-and-burnshifting cultivation● Illegal logging● Natural forest
Vientiane Capital
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Khamkeut district

Bolikhamxay province2.2 Monitoring System of Deforestation and Forest
Degradation Using RS Technology
Basic Satellite RS Data: Medium Resolution Data
1992/93
LANDSAT
1996 LANDSAT2000
LANDSAT

2004 LANDSATImage Processing/
Analyses/Interpretation-Preprocessing-Multi-spectral-Multi-temporal-Multi-stage-Multi-station
etc.

2007
SPOT/LANDSATSRTM3GDEM
8ALOS/PRISM, AVNIR2
Aerial Photos

Field Surveys andGround Truth Data

Land Use/coverMaps
Vegetation Index
Forest Degradation/
Analyses
DSM/DEM
Ortho Image
Forest Base Maps
etc.

Data for:- Forest GIS
Database- Simulation
Analyses ofFuture Forest
Cover Change- Forest
CarbonStock
Estimation

Accuracy Check of Land Use/Cover Classifications

Classificationanalysis(Class Code &Landuse)

UsersInterpretation(Class Code)
Louangphabang Province 12345678 Total Accuracy
1 Current forest
2066 311
121111 2381
87%
2 Unstocked forest 332 1814
5631 69 2161
84%
3 Ray
1 13 166
37 18391%
4 Crop Land
13 30
3488%
5 Grass Land
111011283%
6 Other
281080%2323100%
7 Water
8 Cloud0Total Grid Points 2400 2142 175 38 10 15 24 188 4804
Producer Accuracy
86% 85% 95% 79% 100% 53% 96%
Over All Accuracy
86%Classification
analysis(Class Code &Landuse)

UsersInterpretation(Class Code)Bolikhamxay province12345678 Total Accuracy
516 18483 53896%
1 Current forest
2 Unstocked forest 74 271
2212 30 352
77%
226122990%
3 Ray
4 Crop Land21 2012483%
1125956%
5 Grass Land1131493%
6 Other
7 Water
18989%
08 Cloud
Total Grid Points
593 294 29 24
5 20 10 115 975
Producer Accuracy
87% 92% 90% 83% 100% 65% 80%
Over All Accuracy
88%
9 ※The9 number of "Cloud" isn't included in the number of "Total".
Grid Points”.

- Image Interpretation of Pansharpen ALOS/AVNIR2 withField Surveys vs.
Digital Image Analyses- Accuracy Check Points:
2 km Grid Points

Forest Degradation Analyses from Landsat Images

Results of FCD-H analyses(Bolikhamxay province)
May possible to map forest degradation zone.

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Field Checking Surveys of Image Analysis Results● Several field surveys were carried out for checking the results of image
analyses in 2009 and 2011.
● Based on the results of these field surveys, the methodologies andmodels for the study were revised.

112.3 Development of Three Dimensional Forest MappingTechnologies Using ALOS/PRISM ImagesForest Compartment MapTopography

StereoPhotogrammetric●Colored ALOS/PRISM Measurements
Stereo images●GPS points●Field survey data
●Existing topographic maps
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Tree Height Classification Map( 1:25,000 )Forest GIS Database for Regional
or Project-based REDD+Orthoimage

Accuracy Analysis of Tree Height Measurement
Data from 17 Forest Plots (2010)
PRISM

Field

Tree Height(m)Average Tree Height

Measurement PlotPRISM Measurement

20.21

Field Measurement

20.07

Discrepancy

0.14

RMSE

3.8

RMSE: About 4m
Average Discrepancy: 1~2 m

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Data from 41 Accuracy Checking Points (2009)2.4 Forest Plot Survey

DBH Measurement14- 20 x 20 m Plot
- Number of Standing Trees- DBH- Average Tree Height- X,Y,Z Coordinates- etc.

Tree Height Measurement2.5 Estimation of Forest Carbon Stock● Forest compartment/tree height maps, Land use/cover maps were prepared.
● Forest sample plot survey was conducted.
● Forest biomass carbon stocks were estimated utilizing several models such as
Dr. Kiyono’s allometry model and a model in IPCC Guideline using these basic data.

Forest Compartment/Land use/coverTree Height Maps

Forest Carbon
Stock Estimation
ModelsMaps(100km2 test site)

DBH classification
3533

Number of Trees

3025222015105324120< 10< 20< 30< 40< 50< 60< 70

Tier1 (Provincial level)

DBH (cm)

Dr. Kiyono’s allometry model,
IPCC Guideline
Forest Sample Plot Survey(DBH, tree height, species, etc.)
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Forest Biomass Carbon
Estimation Data

Correlation Analysis of Carbon Stock andTree Height16

2.6 Analyses of Deforestation Trends andSimulation of Future Forest Cover Changes
2.6.1 Analyses of Deforestation Trends● Analyses of national forest cover changes based on the available forest coverstatistics (National Forest Inventory Data(1982,1992,2002), FAO(1990,2000,2005))● Analyses of forest cover changes in the pilot study areas based on remotesensing analyses data (1993, (1996), 2000, (2004), 2007)● Setting the baselines or reference levels is critical for implementing REDD+ projects.
● Baselines provide a benchmark against which emissions reduction can be calculated.

Historical Baseline

Realized Path
Crediting Baseline
17Business as usual Baseline

2.6.2 Simulation Analyses of Future Forest Cover Changes using
the Markov-cellular Automata Model and GIS Data
- Village surveys (4 and 20 villages in 2009 and 2010, respectively)- The household survey used a semi-structured questionnaire for 2000 and 2007.
- The sample was drawn using a two-stage stratified random sampling
procedure.
- Sample frame is drawn from the 2008 Lao PDR Department of Statistics.
- A sample of 460 households from 20 villages at 95% confidence level wasused.
- Approximately 23 households were selected per village.

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(2) Preparation of Biophysical Data and Integrated GIS Data
● Land use/cover maps (1993, (1996), 2000, (2004), 2007), slope map, road
networks, distance measures● Integration of socioeconomic and GIS data based on village surveys(3) Implementation of Future Simulation for Land Use/cover Changes
for the Provincial and District Levels with 3 Scenarios
GIS Data
Multi-temporal
Land use/cover data

Simulation Analyses
Using the MarkovCellular Automata Model

Socioeconomic Survey Data

● Simulation was also carried out for a district level.
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Future Forest Change Maps
And Projected Forest Coverunder Three Different Scenarios

Results of Simulated Future Forest CoverChanges (Provincial Level)(1) BAU Scenario1993, 00, 07 ........

2014

1993, 00, 07 ........

2014

1993, 00, 07 ........

2014(2) Pessimistic Scenario(3) Good Governance
Scenario
Forest Cover of BAU
Scenario
20Comparison of Simulation Scenarios (Current Forest)21

2.7 Capacity Development Activities● On-site and off-site capacity building activities have been carried out
in various technological disciplines on REDD+ as follows:
1) Workshops (4 times)
2) On-the-Job Trainings (8 field surveys)
3) Short-term Trainings (Satellite image analyses (4), Forest GIS DB
development (2), Simulation Analyses (3) )4) Training in Japan ( two weeks)
Two officers were also invited from Vietnam for workshops and training in Japan
in 201022

3. Lessons Learned● Analyses of various kinds of satellite images from different sources are needed
to obtain good coverage of the wide area. And, reasonably high quality of data
should be prepared for establishing a reliable MRV system.
● The MRV system needs an integrated approach of various technologies asshown in the study.
● Three dimensional information of forest stand (i.e. tree height) seems to beone of the important information for forest carbon estimation with highcorrelation.
● A multi-stage approach from national level to sub-national and district/projectlevel may be one solution for realizing a MRV system for REDD+.

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