Experience of France for reporting under the Kyoto Protocol Etienne MATHIAS (CITEPA) Nicolas STACH (IFN) – Michel-Paul MOREL (SSP) Technical workshop on

Experience of France for reporting under the Kyoto Protocol

Etienne MATHIAS (CITEPA)Nicolas STACH (IFN) – Michel-Paul MOREL (SSP)

Technical workshop on LULUCF reporting issues under the Kyoto Protocol

13-14 November 2008

13-14 November 2008 1JRC - LULUCF

Plan

1. Global scheme of French LULUCF inventory

2. French reporting under the Kyoto protocol

3. Specific issues related to the Kyoto protocol

3.1. Land use monitoring

3.1.1. Annual survey – Mainland

3.1.2. Data treatment

3.1.3. Remote sensing analysis – French Guiana

3.2. Reporting by region - improvements/difficulties

4. Conclusion


1. Global scheme of the LULUCF inventory

• France applies the 2003 Guidelines for LULUCF since the submission of April 2006 for the UNFCCC. The discussions on the implementation of the reporting under the Kyoto protocol have begun in the same time.

• The inventory is based on land use change matrixes which represent all the possible land use changes.

• For each of this land the net carbon balance is estimated for each carbon pool.

Aboveground biomass

Underground biomass

Litter

Dead wood

Soil


1. Global scheme of the LULUCF inventory

• On forestland the carbon balance for living biomass is estimated thanks to the method of fluxes. The net balance is estimated by difference between the growth and the harvests.

Net carbon balance = carbon growth – carbon harvests

• For the dead organic matter and the soils, a tier 1 default method is used; emissions and removals are reported when there are land use changes.

∆Carbon = Carbon before conversion - Carbon after conversion

A BA=>B B=>A

Dead organic matter 1year 20years

Soil 20years 20years


2. French reporting under the Kyoto Protocol

• France chose to submit annually the estimate of the figures for the articles 3.3 and 3.4 under the Kyoto Protocol.

• France elected the only Forest management option under the article 3.4.

• The cap for France for this option is 0.88tC/year (3.2 tCO2/year) for the commitment period 2008-2012.

• A trial on the year 2006 within the Kyoto format was submitted to the UNFCCC for the 15th of April 2008.


3. Specific issue related to the Kyoto Protocol

• The reporting under the UNFCCC doesn’t perfectly correspond to what is demanded for the Kyoto Protocol especially on two points according to France:

– Areas have to be monitored from 1990 to the end of the commitment period

– The reporting must be done for smaller regions than the entire territory.


3.1. Land use change survey

• Many ways have been imagined to be able to report under the Kyoto Protocol with :

– accuracy (0.5 ha of deforested forestland must be detected),

– completeness (all the different land uses, forestlands, croplands, grasslands… must be considered)

– representativeness (the entire territory must be covered).

• France decided to use a national survey based on fixed and systematic sample plots which is named TERUTI. Since 2005, it is named TERUTI-LUCAS because of the harmonization with the other European countries within the framework of LUCAS.

• In French Guiana, this survey was not available a remote sensing based study has then been implemented.


3.1.1. TERUTI concept

•An annual area frame sampling survey

•A two-stage systematic sampling design PSUs (Primary Sample Unit) of 324 ha SSUs (Secondary Sample Unit) of 9 m2 •A double observation : for each SSU, the surveyor has to determine, on the spot, land cover and land use (2 nomenclatures).

land cover : wetland, broadleaved forest, wheat, roads …land use : agriculture, forestry, residential, leisure …

•A location based on aerial photographsfield documents used since 1962


3.1.1. TERUTI sample

A grid of 4,700 elementscovers the whole territory

4 to 8 PSUs of 324 hain each grid element

36 SSUs observedin each PSU

Altogether, more than 15,500 PSUs et 555,000 SSUsvisited every year


3.1.1 TERUTI sample

La maille Le segment

Les huit positions de tirage Disposition des points pour une photographieau 1/5 000e tirée sur format 50x50

12 km

2 km 6 km 4 km

1 3

6 km

12 km 5 6

4 2

4 km7 8

150 m 1500m 150 m

300 m

x x x x x x

1 2 3 4 5 6

x x x x x x

7 8 9 10 11 12

x x x x x x

13 14 15 16 17 18

x x x x x x

19 20 21 22 23 24

x x x x x x

25 26 27 28 29 30

x x x x x x

31 32 33 34 35 36

The SSU represents a surface of 100 ha


3.1.1. LULUCF nomenclature for France

Level 1 Level 2 Level 31 Woodland 11 Managed 111 Managed Broadleaved Woodland

112 Managed Coniferous Woodland113 Managed Mixed Woodland114 Poplar stand

12 Unmanaged 121 Unmanaged Broadleaved Woodland122 Unmanaged Coniferous Woodland123 Unmanaged Mixed Woodland

2 Grassland 21 Managed 211 Managed Grassland without tree cover212 Managed Grassland with sparse tree cover

22 Natural 221 Unmanaged Grassland without tree cover222 Unmanaged Grassland with sparse tree cover

3 Cropland 31 Managed 310 Cropland4 Wetland 41 Managed 410 Managed wetland

42 Unmanaged 420 Unmanaged wetland5 Settlements 51 Managed 510 Settlements6 Other land 61 Managed 610 Managed Other land

62 Unmanaged 620 Unmanaged Other land


3.1.1 From TERUTI to LULUCFCat. Sous-catégorie Ipcc par NFONC

NPHYS IPCC 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 99

11 4 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 2 2

12 4 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 2 2

13 4 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 2 2

14 4 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 2 2

11 1 1 113

12 1 1 113

13 1 1 113

14 1 1 113

15 6 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 2 2

16 6 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 2 2

17 6 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 2 2

18 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 1 2 1 1 2 2 2 1

19 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 1 2 1 1 2 2 2 2

20 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 1 2 1 1 2 2 2

20*1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 1 2 1 1 2 2 2 1

20*2 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 1 2 1 1 2 2 2 2

20*3 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 1 2 1 1 2 2 2 3

21 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 1 2 1 1 2 2 2 3

22 2 1 1 1

22 5 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

22 6 2 2 2

23 2 1 1 1

23 5 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

23 6 2 2 2

24 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 4

25 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 4

26 2 1 1 1

26 5 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

26 6 2 2 2

Spéciation IPCC pour les forêts


3.1.1. LUCF matrix from 2003 to 2004Matrice d'évolution 2004=moyenne 1999-2004

forêt gérée feuillue

forêt gérée conifères

forêt gérée mixte

forêt gérée peuplier

forêt naturelle feuillue

forêt naturelle conifères

forêt naturelle

mixte

Prairies non boisées gérées

Prairies boisées gérées

Prairies non

boisées non

gérées

Prairies boisées

non gérées

CulturesZones

humides gérées

Zones humides naturelles

Zones urbanisées

Autres terres gérées

Autres terres

naturelles

111 112 113 114 121 122 123 211 212 221 222 310 410 420 510 610 620 Total 2004

forêt gérée feuillue 111 9 155 721 10 484 10 113 1 079 6 878 211 218 8 120 9 961 0 0 3 658 144 364 1 578 0 16 126 9 224 655

forêt gérée conifères 112 5 785 3 791 041 5 990 72 71 4 916 284 3 737 2 383 0 0 1 009 0 288 870 0 4 717 3 821 163

forêt gérée mixte 113 12 265 13 363 1 302 688 286 723 284 1 558 1 293 1 033 0 0 73 0 72 1 296 0 3 214 1 338 147

forêt gérée peuplier 114 437 216 73 243 905 0 0 0 721 180 0 0 1 187 0 73 71 0 643 247 505

forêt naturelle feuillue

121 6 422 0 143 0 419 370 1 089 3 711 635 857 0 71 0 0 72 577 0 7 856 440 802

forêt naturelle conifères

122 359 2 905 358 0 1 971 245 564 3 766 140 70 0 0 140 0 0 146 0 2 894 258 312

forêt naturelle mixte 123 432 356 1 278 0 5 463 6 040 210 871 71 0 0 72 0 0 0 219 0 3 778 228 579

Prairies non boisées gérées 211 2 791 1 077 359 217 217 139 71 10 354 022 12 111 0 145 190 182 288 572 5 675 0 20 241 10 588 108

Prairies boisées gérées 212 779 218 141 73 146 0 0 9 245 1 517 848 0 0 4 797 71 289 3 791 0 13 390 1 550 789

Prairies non boisées non

gérées 221 0 0 0 0 0 0 0 70 0 632 0 0 0 0 0 0 0 702

Prairies boisées non

gérées 222 0 0 0 0 0 0 0 359 145 0 21 395 359 0 0 327 0 145 22 730Cultures 310 3 241 1 298 358 287 508 73 143 146 835 6 685 0 142 18 447 260 719 145 7 329 72 18 766 18 633 861

Zones humides gérées 410 217 0 73 73 0 0 0 935 361 0 0 789 598 437 2 101 793 0 577 604 357Zones

humides naturelles 420 216 0 0 289 0 0 0 428 216 0 0 436 2 226 352 158 611 0 499 357 080

Zones urbanisées 510 2 846 1 874 1 296 217 651 364 213 22 451 8 302 0 432 33 180 433 142 4 636 432 145 12 688 4 721 667

Autres terres gérées

610 0 0 0 0 73 363 0 71 0 0 144 73 0 0 292 137 203 143 138 362

Autres terres naturelles 620 143 72 0 0 356 143 73 21 957 10 925 74 73 20 008 145 216 4 268 0 2 683 914 2 742 368

Total 2003 9 191 654 3 822 903 1 322 871 246 499 436 426 259 186 220 909 10 571 089 1 571 076 707 22 474 18 703 151 602 462 356 494 4 664 274 137 420 2 789 592 54 919 187


3.1.1. Teruti-Lucas PSUs


3.1.2. Creation of matrixes to implement the inventory

• For the UNFCCC inventory different matrixes are needed for each year of inventory to separate the land keeping the same land use and the land changing of land use:

– 1 Land use change matrix for a period of 20 years

– 1 Land use change matrix for a period of 1 year

• With the Kyoto reporting another matrix is needed to separate the areas under the articles 3.3 and the 3.4:

– 1 Land use change matrix for the period between 1990 and the inventory submission.


3.1.2. Creation of matrixes to implement the inventory

• All those matrixes are very difficult to implement for two main reasons:– The 1 year matrixes are used especially to detect deforested areas

but according to the survey it is difficult to estimate if a change is temporary or permanent.

For example when a forested area is cut for wood production it is not possible to know if there will be a land use change or if the forest will come back. The choice made by France is to consider that if the area remains more than five years without forest it is counted as deforested. A special treatment has then been applied to estimate this deforestation but it means that you can estimate the deforested areas only after five years.

– There are different time series of the TERUTI database (1982-1990; 1992-2004; 2005-…)

the differences are some definitions of categories, a different number of sample plots and different places of plots. Consequently, it is not possible to have the monitoring of one plot from 1970 to today. Treatments are then needed to build the 20 year matrixes

» To make consistent the different time series of TERUTI.» To estimates all the changes during the period.


3.1.3. Case of the French Guiana

• TERUTI doesn’t cover the entire territory, and especially not the department of French Guiana which is essentially covered by rainforest. Moreover there is currently no forest inventory in this area.

• 2 specific studies have then been implemented within the framework of the Kyoto Protocol

– 1 study to estimate the area deforested

– 1 study to estimate the biomass released with this deforestation.


13-14 November 2008 JRC - LULUCF 18

3.1.3 Context : French Guiana

Limited deforestation concerning small parcels : a challenge for monitoring

French overseas “Department” ~84 000 km²

Cayenne

Brazil

Surin

am

Oyap

ock

Mar

oni

Managed Managed forestforest

NationalPark

Petit Saut• French Guiana forest– ~80 000 km² of tropical forest. ~ 95% of the total territory ~ 1/3 of total French forest (including mainland)

• Deforestation causes in French Guiana– Traditional shifting cultivation: Small individual areas (0.3 to 1 ha)– Extension of modern agriculture– Gold mining: Small individual areas - Legal or illegal – About 12 000 ha since 1990 - Along streams and rivers – Petit Saut dam: Hydroelectricity – reservoir about 30 000 ha, Dam filling in 1994

• Human activity concentrated in a narrow coastal strip and along main rivers


3.1.3. French Guiana and Kyoto protocol

Specific constraints in French Guianao France is the only Annex 1 country with tropical forestso No preexisting systematic and exhaustive land use survey

• Very recent and partial Land use inventory from the Ministry of agriculture (TERUTI LUCAS)

• French NFI permanent inventory of forest resources is limited to mainland France

o Impossibility to carry out a systematic ground based survey o No exhaustive Aerial photography missiono Important cloud cover


3.1.3. Satellite Data : LANDSAT 1990

7 Images from Global Landcover Facility (GLCF – Uni. Maryland)

+ 1 image USGS

All Images around 1990o From 1986 to 1992o 62% of the territory covered by

1990 imageso Mean acquisition date October 1989

• Landsat images georeferenced again using SPOT orthos as references

– 24 to 49 tie points between each Landsat scene and the corresponding SPOT images

– Bilinear model between Landsat Coordinates and SPOT Coordinates

Geometric accuracy from 19 to 27 meters


3.1.3. SEAS-Guyane

Multiple partner Project leaded by IRD

Technologic platform for acquisition and processing of High resolution satellite data (SPOT et ENVISAT)

o 2005: Installation of a new SPOT/ ENVISAT Ground Receiving Station in Cayenne

The AntennaThe receiving area

Dramatic Increase of SPOT image acquisition capacities over the region


3.1.3. Annex

SPOT Receiving station Network


3.1.3. Partenaires

Inventaire Forestier Nationalo Porteur du projet / Photo-interprétation / Articulation avec

inventaire Kyoto / Appui méthodologique et technique au traitement d’image

IGN Espaceo Spatiotriangulation, géoréférencement

IRD Unité Espace o Acquisition et Traitement des imageso Transfert local (résultats et applications)

Cemagref UMR TETIS o Appui scientifique (traitement d’images et protocole de Kyoto)

ONF Direction régionale Guyaneo Expertise forestière locale / Aide à la stratification

11/03/08

Assessment of forest cover changes in French Guiana using satellite imagery

24/18

3.1.3. Satellite Data : SPOT 2006

Several thousands SPOT scenes acquired at the Cayenne Ground station during 2006

SPOT 5 SPOT 4 SPOT 2

Cloud cover < 10 %Cloud cover < 25 %Cloud cover < 75 %

• Selection of 2 to 7 images per frame(depending on the cloud coverage)

–65 SPOT 2 20m multispectral–63 SPOT 4 20m multispectral–47 SPOT 5 10m multispectral–Mean acquisition date : September 2006


3.1.3. Definition of the strata

2km Buffer

Source: ONFSource: DAF 2005Source: ONFSource: ONFSource : Agence Régionale d’Urbanisme et d’Aménagement de la Guyane (ARUAG) 2003

Sources : ONF levés terrain lors de missions aéroportées exploitation légale et clandestine Source: ARUAG

Sources : ONF

DIREN

• ONF GIS analysis on existing information– Roads – Agriculture – Human settlements– Cities– Urban areas– Gold mining– Maroni villages– Camopi & 3 Sauts Villages

→ Strata R definition

11/03/08

Assessment of forest cover changes in French Guiana using satellite imagery 26/18

3.1.3. Sampling design

Strata Total Area Sampling type

Sample size

Sample points distance

N 7 021 597 Normal 973 8388

P 212 641 Reinforced 2453 932

R 1 162 273 Reinforced 13360 932

• Systematic/random grid– Square grid - 932 m between points– Random origin and inclination

• Permanent sampling : same sample in 1990 and 2006Good estimation of Land Use areas AND Land Use Changes

Localization of the 3 strata

• Sample definition

– Strata R : All Grid points

– Strata P : All Grid points

– Strata N : sub-sample 1 point out of 9


3.1.3. Photo interpretation

Gold mining

Agricultureextension

ShiftingCultivation

Petit Saut Reservoir

Landsat 5 TM 1990 - GLCF



SPOT 5 2006 – © CNES Landsat 5 TM 1990 - GLCF

SPOT 5 2006 – © CNES

SPOT 4 2006 – © CNES SPOT 4 2006 – © CNES


3.1.3. Results: Land uses 1990 & 2006

Land use 1990 / 2006


3.1.3. Results

Analysis forest changes in French Guyana 1990-2006 Total forest / non forest conversion: 94 061 ha – standard error 12 %

3 181 ha

16 947 ha

35 064 ha

17 403 ha

10 379 ha

11 087 ha

5 000 ha

10 000 ha

15 000 ha

20 000 ha

25 000 ha

30 000 ha

35 000 ha

40 000 ha

Usual deforestation

Punctual event 1994 std. err. 4%

Natural changesSt. err. 67%

42 050 ha (standard error 4%)2 486 ha/year

Forest 1990 / Gold mining 2006

Forest 1990 /Other settlements 2006

Forest 1990 / Croplands 2006

Forest 1990 / Other Land uses 2006

Forest 1990 /P. Saut Reservoir 2006

Mangrove 1990 / sea 2006

0 ha


3.1.3. Emission factors

ONF / CIRAD/ CNRS Dendrometric expertiseo Dispositifs

• Autres compartiments - étude bibliographique : > Biomasse épigée vivante autre que les arbres > 10 cm : 15 à 30 T/ha ;> Biomasse épigée morte (litière et bois mort) : 20 à 40 T/ha ;> Matière organique du sol : 75 à 100 TC/ha

• Biomasse épigée totale des arbres de plus de 10cm> Volume sur écorce, densité, facteurs d’expansion> Terre ferme 350 T/ha ± 25> Marécages 290 T/ha ± 30

3.2. Reporting by regions

• In the framework of the Kyoto protocol, France has to report by smaller geographical units than the entire country. The administrative level of the regions has been chosen for this reporting which means that 26 results are reported for the LULUCF sector for the 26 different regions (with oversea territories).

– It has been an opportunity to take more specific parameters

– Many parameters and data don’t exist with this accuracy and must be estimated

– It represents a lot of work.


3.2. An opportunity for improvements• One of the base of the LULUCF inventory is the cross between the land use

data (TERUTI) and the Forest inventory data (IFN), the results of land use survey can perfectly be given by region the result for

=> France is the sum of the regional data, of course the accuracy is lower when we just look at the regional level, but it doesn’t change anything for the total.


• The IFN was able to provide data of growth and carbon stocks by super regions (5 super regions in France).

=> This changes a lot the results compared to the previous submission to the UNFCCC and should improve the relevancy of the result.

• The data for soils were also improved with updated data by region for each type of land use.

=> This changes the results too.

3.2. Estimation of unknown regional parameters

• The harvests are well known by department (smaller geographical units than regions) except for fuel wood, the national consumption of wood fuel is estimated thanks to the energy data to not forget non commercial consumption. But this data is not available by region each year. Moreover it is very difficult to estimate the transport of fuel wood between regions.

=> For the last test submission we considered that there is no transport of fuel wood between regions but inconsistencies can appear and corrections could be necessary.


4. Conclusion on the submission within the Kyoto format

• This regional reporting demands a lot of work but has been an opportunity to look for more accurate data. It is difficult to estimate the relevancy at the level of the region but French local actors feel really more concerned with this level of result.

• The monitoring of the surfaces remains a very difficult issue especially to have time and geographical consistency (especially because the Kyoto Protocol put the stress on afforested and deforested areas which are very small areas compared to the lands without change)

• No big trouble was met with the filling of the new reporting tables.


4. Conclusion on the submission within the Kyoto format

• France was very involved to estimate the balance of the article 3.3, and the first estimate for the year 2006 gave a net sink of 23.000 tons of carbon which means clearly nothing according to the level of uncertainty (impossible to know whether the future balance will be positive or negative).

• If the trends and the methodology were completely stable we could assume that the balance would be positive for the commitment period but it is currently not the case.

• It is very difficult to communicate with these different estimates under the Convention and the Kyoto Protocol, for example because the afforested areas in the Kyoto Protocol (since 1990) are not the same than in the Convention reporting (for 20 years).

• The future French submissions for the UNFCCC and the Kyoto Protocol should be completely harmonized and consistent but there is no way to check this consistency.


Documents

Experience of France for reporting under the Kyoto Protocol Etienne MATHIAS (CITEPA) Nicolas STACH (IFN) – Michel-Paul MOREL (SSP) Technical workshop on