portuguese foreseen methodology for arts. 3.3 and 3.4 quantification under the kyoto protocol...

Portuguese foreseen methodology for Arts. 3.3 and 3.4 quantification under the Kyoto Protocol

“Technical workshop on LULUCF reporting issues under the Kyoto Protocol”

13-14 November, Ispra

Inês Mourão & Teresa Pereira, “Technical workshop on LULUCF reporting issues under the KP, November the 14th 2008, ISPRA

List of Authors

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Teresa Costa Pereira, APA

Inês Mourão, APA/Ecoprogresso

Mário Caetano, IGP

Maria Conceição Ferreira, AFN

José Paulino, GPP/MADRP

Maria Conceição Pereira, IGP

Helena Ramos, IFAP

Paula Soares, AFN/ISA

Ricardo Teixeira, IST

Rui Teixeira, MADRP/LQARS

Margarida Tomé, AFN/ISA


List of Entities

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APAmbiente (ex-IA) – Portuguese Agency for the Environment http://www.apambiente.pt

MADRP - Ministry of Agriculture/ Ministério da Agricultura, do Desenvolvimento Rural e das Pescas GPP – Gabinete de Planeamento e Políticas http://www.gpp.pt

AFN - Forestry National Authority/ Autoridade Florestal Nacional estais/MADRP http://www.dgrf.min-agricultura.pt

IFAP (ex-INGA) - Instituto Financiamento Agrícola e Pescas www.ifap.min-agricultura.pt

LQARS - Laboratório Químico Agrícola Rebelo da Silva http://www.iniap.min-agricultura.pt

ISA - Instituto Superior de Agronomia / Technical University of Lisbon http://www.isa.utl.pt

IGP - Geographical Institute/ Instituto Geográfico Português http://www.igeo.pt http://www.igeo.pt/gdr/projectos/prek/

IST – Instituto Superior Técnico/ Technical University of Lisbon UE – Universidade de Évora

Ecoprogresso http://www.ecoprogresso.pt

InventAr http://www.inventar-environment.com


Overview

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SNIERPA: PT National System PT Initial Report

Units of land identification Forest included in 3.4 GM/CM (hierarchy rules) Cartographic products and additional information Land Use Maps (COS) Identification of 3.4 areas Annual monitoring of forest fires and clear cuts Carbon in soil

Pilot study for defining and testing reporting methodology under UNFCCC and KP


No previous Reference to Art. 7.1 of KP

Inclusion of 3.3 and 3.4 activities on SNIERPA through a MoU concerning Design, test and implementation of the methodology and responsibilities’ sharing

in data gathering (including QA/QC to data producers/products)

SNIERPA including Arts. 3.3 and 3.4 Single Responsible Entity: produces the Inventory Focal Points: Co-operate in Methodological Development and Data Gathering Involved Entities: Public or private entities which generate or hold information

Experts

SNIERPA – PT National System

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SNIERPA/Art. 3.3 and 3.4 Working Group

Focal Points

Responsible Entity

Involved Entities

Experts

InventArEstudos e Projectos Unip Lda

INERPAArt. 3.3 & 3.4


PT Initial Report

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Forest Definition

Minimum area: 1 ha, consistent with LU/LUC cartography (FAO 0,5 ha) Minimum width: 20 m Tree crown cover: 10% Minimum tree height: 5 m

Additional Activities under 3.4

FM - Forest Management – all forest is managed CM - Cropland Management GM - Grazing Land Management

Accounting 3.3 & 3.4

At end of 1st Commitment Period


Cartographic products and additional information

Monitoring of clear cuts and new forest plantations

20

10

19

90

COS1990

COS2010

COS2007

20

08

20

09

20

11

20

12

Annual cartography of burnt areas

Base year1st Kyoto Protocol Commitment period

Additional DB: e.g. agro-environmental incentives


Methodology envisaged - COS90 vs COS07 vs COS10/11: LU/LUC Cartography based on aerial images.

Minimum mapping unit: 1 ha; minimum distance between lines: 20 m

COS90 F in 1990

COS07 F areas at the beginning of the commitment period (CP) F and D areas since 1990

COS90 vs COS07 LUC – yearly rates

COS10/11 F and D areas since the beginning of the CP Changes in FM areas: surface and species during the CP

COS07 vs COS10/11 LUC CP – yearly rates

Additional Information Annual detection of fires, clear cuts and new plantations Biomass – deforestation, harvesting and fires

Stocks, age from NFI (Plots) Biomass increment

Growth rates: NFI + Forest simulators (ISA) New forest plantations (FEADER)

agro-environmental incentives DB units of land monitored annually; 5 years)

Units of land identification – 3.3 and 3.4 FM

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Two tier methodology

Level Detail A - for Specific C Management Activities No tillage; Sown biodiverse permanent grasslands

Methodology: georeferenced DB on agro-environmental incentives under

FEADER and other CAP support schemes (obtained from IFAP – Portuguese CAP payment agency)

Annual identification of land units Land units continually tracked Identification of the beginning of the activity

Level Detail B – “Non-Managed” Areas Remaining Agriculture and Grassland areas

Methodology Detection of change in land use according to COS classes types

Soil carbon in equilibrium

Units of land identification – 3.4 CM+GM

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Forest included in 3.4 GM/CM (hierarchy rules)

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Agro-forestry systems (Montado) classified under CM or GM

Carbon stock changes result from changes in agricultural practices in understorey

Tree system is in equilibrium (Dominant Mature trees)


Land Use Map (COS) (IGP)

•Technical specifications

•Nomenclature

•Generalization rules

Production

Land use map 2007Aerial images (50 cm)


COS 2007 (IGP)

Ortho-images characteristics

Owner IGP

Camera Ultracam, Vexcel (North) + DMC, Intergraph (South)

Flight altitude Approx. 5800 m

Image format Tiff

Area covered 4 x 5 Km

Spatial resolution 0,5 m

Radiometric resolution 8 bits

4 Bands Blue, Green, Red and NIR

Reference system ETRS89 / PT-TM06

Image dates July – August 2007 (North)July – November 2007 (South)


COS: Production method (IGP)

Computer assisted visual interpretation


COS2007 Technical specifications (IGP)

Data model and structure Vector (polygon)

Minimum mapping unit (MMU) 1 ha

Minimum distance between lines 20 m

Minimum distance between polygons 20 m

Projection Transverse Mercator

Reference system ETRS89/PT-TM06

Ellipsoid GRS80

Nomenclature COS2007

Thematic accuracy >= 85%

Positional accuracy >= 5.5 m

(http://www.igeo.pt/gdr/projectos/cos/)


COS2007 Nomenclature

Level 1

Level 2

Level 3

Level 4

Level 5

Detail

(5 classes)

(15 classes)

(43 classes)

(92 classes)

(192 classes)+

-

The COS2007 nomenclature classifies both land cover and land use

It is a 5 level hierarchical nomenclature with 192 classes at its most detail

COS 2007 nomenclature was developed to allow compatibility with the six IPCC land-use categories (GPG ch.2, pp. 2.6)

This was done in the framework of an advisory committee that was established to contribute in the definition of COS2007 nomenclature. This committee involved all relevant public and private entities and end-users of the cartography, including SNIERPA representatives


COS2007 Nomenclature vs IPCC categories


Identification of 3.4 areas

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• Annual crops (irrigated, non irrigated, rice)

• Permanent crops (vineyards, orchards, olive groves)

• Annual crops and/or pastures associated to permanent crops

• Complex cultivation patterns (mixed parcels of annual crops and permanent crops)

• Agro-forestry areas (forests with irrigated, non irrigated or permanent crops as understorey)

• Annual crops (irrigated, non irrigated, rice)

• Permanent crops (vineyards, orchards, olive groves)

• Annual crops and/or pastures associated to permanent crops

• Complex cultivation patterns (mixed parcels of annual crops and permanent crops)

• Agro-forestry areas (forests with irrigated, non irrigated or permanent crops as understorey)

CROPLAND MANAGEMENTCROPLAND MANAGEMENT• Pastures

• Agro-forestry areas (forests with pastures as understorey)

• Natural grasslands

• Pastures

• Agro-forestry areas (forests with pastures as understorey)

• Natural grasslands

GRAZING LAND MANAGEMENTGRAZING LAND MANAGEMENT

• Forests (>30% cover broadleaved, needleleaved, mixed forests)

• Transitional woodland/shurb (10-30% cover forests, clear-cuts, new plantations)

• Forests (>30% cover broadleaved, needleleaved, mixed forests)

• Transitional woodland/shurb (10-30% cover forests, clear-cuts, new plantations)

FOREST MANAGEMENTFOREST MANAGEMENT


Annual Monitoring of Forest Fires

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Cartography of Burnt Areas in Portuguese MainlandAFN is the national authority for forestry and is also designated for the elaboration of the official cartography of burnt areas

Cartographic methods

• Identification in the office or in the field in military map or orthophotomap

• Field identification with GPS • Analysis through satellite image (MODIS and LANDSAT)

Besides field surveys, that include only a minor number of annual

occurrences, AFN has a cartographic series of the burnt areas, identified using LANDSAT, that starts in 1984 and covers all the Portuguese Mainland

The detail of the satellite images has allowed to reduce the cartography minimal area to 5 ha (in 1990 the minimal area was 25 ha)


Annual Monitoring of Forest Fires

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The forest fires that have areas superior to 5 ha are responsible for the major part of the burnt area

The fires with minor areas are a common phenomena in urban-forestry interfaces in north and centre littoral

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

Proporção de áreas ardidas com limiar de 5 ha

<=5.00 >5.00


Monitoring of clear-cuts

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AGRO 130 Project remote sensing images to automatically map clear cuts and new forest plantations

Consortium: IGP+AFN Project 2003-2006. Concluded

Objectives Test/demonstrate the use of satellite image (LandSat 7 ETM; IKONOS) for the

detection of clear-cuts areas and new plantations

Status Testing in restricted areas at regional and local level Expansion to full scale monitoring project to be decided

(http://www.igeo.pt/gdr/projectos/agro130/)


AGRO130 – remote sensing to automatically map clear cuts and new forest plantations

Objectives: Demonstrate the usefulness of Landsat-5 TM and IKONOS images to produce clear

cut and new forest plantations maps by automatic means for local and regional scales.

Demonstrate the usefulness of monitoring clear cuts and new forest plantations for data base updates and decision making.

Images used to test the local and regional scale hypotheses

Local scale

IKONOS 2004 IKONOS 2005

Regional scale

Can we visually distinguish the changes,

and automatically?

Can we visually distinguish the changes,

and automatically?

Landsat 2004 Landsat 2005


AGRO130Methodology

NDVIdifference

NDVIdifference

MapGeneralization

MapGeneralization

ClassificationClassification CombineCombine

2005 Image2005 Image

2004 Image2004 Image

Veg. DecreaseVeg. Decrease

Classified ImageClassified Image

Clear cuts and new plantations

Clear cuts and new plantations

Simplified approach to the automatic change detection methodology


AGRO130Results

Users accuracy obtained in the change detection using Landsat e IKONOS images

Vegetation decrease at 5ha MMUVegetation decrease at 5ha MMU

LandsatLandsatIKONOSIKONOS

Vegetation decrease at 0.5ha MMUVegetation decrease at 0.5ha MMU

No change

Change

Water


Forest Parameters and ModelsNFI (AFN)

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Sampling

Grids 500m x 500m – Photointerpretation (360 000 points)

2km x 2km – Forest (22 091 points)

Determination of forestry points (12 258) - remote sensing using Landsat images

4km x 4km – Bush land

Field validation of the plots identified above relating to forestry and bush land


Forest Parameters and ModelsNFI

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Carbon stock Live biomass estimates available in the recent NFI 2005/06 (field work 2006): stem,

branches, leaves estimated with allometric equations

Growth rates (t.ha-1.y-1) Estimated with yield tables developed by Forest Regional Plans (PROFs – 21 regions)

using existing growth models by specie

Data analysis by PROF: Tables of biomass stock by main specie (P. pinaster, Eucalyptus sp., Q. suber) per

age and region/PROF Tables with national averages for other species (Q. rotundifolia, Q. sp., C. sativa, and

others)

Litter and dead wood Data available for two pilot areas

Root biomass data Limited data available (P. pinaster and E. globulus)

AFN + APA + ISA


Expected outcomes Replacement of IPCC defaults

LUC – Climate; crops; soil original material LU constant – Soil carbon in equilibrium

Data set available – LQARS (research Institution since 1886) ICP Forest Project (UNECE)

Plots 16 x 16 km: forest + agriculture Same plots in 1997 and 2004

DB with soil characterization data most representative agricultural crops soil fertility trials and surveys (1986 to 2006)

Studies for specific agriculture activities No-tillage (Carvalho e Basch) Sown biodiverse grasslands (Teixeira et al., 2008)

AFN + LQARS + Portuguese Universities (IST and Évora University)

Carbon in Soil

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Carbon in Soil

1

3

5

6

7 84

2

Teixeira, R., Domingos, T., Costa, A.P.S.V., Oliveira, R., Farropas, L., Calouro, F., Barradas, A.M., Carneiro, J.P.B.G. (2008). The dynamics of soil organic matter accumulation in Portuguese grasslands soils. Options Méditerranéennes – Sustainable Mediterranean Grasslands and Their Multi-Functions, A-79: 41-44.

Soil organic matter series from 2001 to 2008

Farm No. Farm Location Soil original material Texture 1 H. Cabeça Gorda Vaiamonte Gneiss Loam 2 H. Mestre São Vicente Limestone Clay loam 3 H. Claros Montes Pavia Granite Sandy loam 4 H. Refroias Cercal Schist Sandy loam 5 H. Cinzento e Torre Coruche Sandstone Sand 6 Quinta da França Covilhã Granite Sandy loam 7 H. Monte da Achada Castro Verde Schist and Greywacke Sandy loam 8 H. Corte Carrilho Mértola Schist Loamy sand


Carbon in Soil

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Evaluation of C soil content according to cultivated crop and region Average values from 1986 to 2002 (great majority of the crops) 20 cm depth for annual crops (winter cereals, and maize) 20 cm and 20 -50 cm depth for perennial crops (olivegrove, vineyards, and apple and pear

orchards) 10 cm depth for pastures The same sampling methods along the surveys

EDP – Terraprima Contract Yearly monitoring of soil organic matter at 10 cm and 30 cm at >30 plots at Quinta da

França and other Portuguese farms

Research Project “Biopast” (2007-2010) Micro-level study of soil organic matter dynamics at Quinta da França Continuation of the yearly soil organic matter time series from eight points in Portugal Analysis of soil analyses by project Extensity farms (> 50 farms implementing sown

biodiverse pastures and no-tillage)

IST+INIA (LQARS+EZN+ENMP) + ESAB (Escola Superior Agrária de Bragança)

Evaluation of C analytical determination methods Relationships between dry combustion method and wet oxidation method (LQARS)


Pilot study for defining and testing reporting methodology under UNFCCC and KP

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Alentejo region (3.3 + 3.4 FM + 3.4 CM + 3.4 GM) Integrated CO2 emissions/removals quantification Objectives: verify methodology and parameters, using:

LUC areas identification; test sampling and spatially explicit approaches

intersection of different cartographic existing products and NFI data plots

use of agro-environmental incentives georeferenced data base

application of forest simulators for main species per age (P. pinaster, Eucalyptus, Q. suber) – in the pilot area only for Q. Suber

quantification of soil C using the maximum available information from soil surveys

evaluation of potential data gaps, main drawbacks and defining ways to solve eventual problems or further data needs

proposal/choice of a concrete methodology for area identification and quantification of E/R

fill in the KP tables using the results from the application of the methodology (2009 submission)


Pilot study for defining and testing reporting methodology under UNFCCC and KP (IGP)

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Study Area: AMDE – Assoc. Municípios do Distrito de Évora


Pilot study: identification of areas in the 1st year - methodology (IGP)

Areas classified as:

3.3 D3.3 A/R3.4 FM3.4 CM3.4 GM


Pilot studyCOS 2007, COS90 and COS AMDE (IGP)

Main technical specifications of the different cartographies


Pilot Study Land-use change matrix from 1990 to 2004

(generalised) for COS’ major categories (IGP)


Pilot Study Transitions from 1990 to 2004 as percentage of the total area of each

category in 2004 and total area and as percentage of the study area (IGP)


Pilot study – next steps from phase 1 recommendations (IGP)

Improvement of the correction of COS90: Refine the procedure since not all geometric errors were eliminated Conversion of the correction procedure into a fully automated one The correction algorithm will have to be calibrated in view of being extended to

the whole country, namely through the use of other test areas particularly important for the North of the country, where more geometric

problems are expected

Revision of the integration of no-tillage data from 2004 and biodiverse pastures data from 2007, with COS AMDE referring to 2004.

Overlay IFAP’s forestry projects’ database with the transitions to new plantations (class novas plantacões, code 3.2.4.8.2)

In order to know what forest species are present in the new plantations the database doesn’t cover all possible new plantations in Continental Portugal

– dependent on the ability of WG 3.3/3.4 to get sufficient data


Pilot study – next steps from phase 1 recommendations (IGP)

Areas of Continental Portugal which are not covered by COS90 – 8% of the territory

use COS based on Orthophotos from 1995, or use CLC90 (Corine Land Cover based on images from 85/86/87)


Pilot study – next steps phase 1 and 2 and recommendations (IGP)

Unlikely transitions and transitions that may result from different visual interpretations in COS90 and COS AMDE (COS2007 in the reporting)

Determine the error that may be involved in these transitions since real land-use changes that may be included in these transitions, are not

eliminated thematic accuracy of both COS90 and COS2007 will be known at the time

of reporting thematic accuracy of COS2007 will be >= 85 % COS90 is envisaged to be further geometrically corrected, so less errors

are expected in terms of land-use changes Independent validation of the whole methodology Phase 2:

Simulation of land use and land-use change area estimation for reporting in the intermediate years of the KP commitment period in which COS will not be produced

Yearly overlay of information related to disturbances Uncertainty and sensitivity analyses


Pilot study: next steps

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Entities TasksMonth

Oct Nov Dec Jan Feb Mar Apr

GPP (/IST)Definition of the soil retention rate – managed

areas

GPP (/UARN-INIA-INRB)Definition of the soil retention rate – non-managed

areas

AFN Definition of the soil retention rate – forest areas

IGP Overlay of COS90+AMDE+IFAP Concluded

APA Determination of 3.3&3.4 areas Concluded

AFN (/ISA)Biomass models – development of production

tables by specie and class age

IGP/AFN(/ISA)Biomass models – harvest, fires and new

plantations

IGP/AFN(/ISA?)/GPP(/IFAP) Overlay of geographical info with NFI

APA Emissions/removals estimation 3.3&3.4

APA Application of QC/QA procedures

Milestones

APA EC’s Submissions 15 15

APA UNFCCC’s Submission 15


Ove

rvie

wLU

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Thank you!

portuguese foreseen methodology for arts. 3.3 and 3.4 quantification under the kyoto protocol...

Documents

lulucf reporting issues

kp slide

ins mouro teresa pereira

ispra slide

fm lulucf crf

ispra overview lulucf

ispra methodology

teresa costa pereira