Satellite images for Paraguay in 2010

(ALOS/AVNIR-2 data)

Identification of carbon stock changes at a national level using a combination of remote

sensing and ground-based inventory for REDD+ in Paraguay

Presenter: Vega Isuhuaylas, Luis AlbertoResearcher at Climate Change Laboratory

Forestry and Forest Products Research Institute (FFPRI) - Japan

Background

• REDD+ is identified as one of the most effective means to reduce GHG emission in the post-Kyoto climate change negotiation.

• A reliable and credible system of measurement, reporting and verification (MRV) of forest carbon changes is a cornerstone of any national REDD+.

• An MRV system should follow the international requirements and also be adapted to the country’s specific conditions, e.g. vegetation, economy, culture, institution and/or the deforestation/degradation drivers.

Objective

• The objective of this study is to develop potential methodologies for a forest carbon change MRV system that could be implemented in REDD+ in Paraguay.

• The research aims the following outputs;• Land-use and land-use change MRV by satellite remote sensing• Forest carbon change MRV by combination of remote sensing and

ground measurements• Monitoring for Forest carbon change on main forest types• Allometric equations for estimation forest biomass in Paraguay.

Forest carbon stock estimation by combination of remote sensing and ground

measurements

= (Forest areai x Averaged carbon stocki)

• The method to calculate the carbon stock involves monitoring forest land and summing up the carbon stock of the forest area for important forest types.

Forest areai : forest area of forest type i

Averaged carbon stocki : averaged carbon stock in forest type i

remote sensing ground measurements

Total carbon stock

Two types of data from field survey:

• Data for area estimation

– Training data for image classification

– Verification data for the result of classification

• Data for estimation of averaged carbon stock per area unit as emission factor

– Tree census data

– Destructive sampling data

(Allometric equations)

Field survey for estimating carbon stock

Land-use and land-use change MRV by satellite remote sensing

Discussion on the definition of forest and forest types from satellite data

Field Survey: Collection of ground truth data/ validation data

Production of forest type map 2010 by object-oriented classification from satellite data

Validation of the result using field data

Change detection of land-use between 1990-1995, 1995-2000, 2000-2005, and 2005-2010

Monitoring Land Cover Change using remote sensing

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Total Forest Area: 1 411 (1000Ha) (16.4%)

Forest – Non Forest Prediction accuracy: 95.6% , CI (95.4% , 95.7%)

Total Forest Area: 3 364 (1000Ha) (26.2%)

Forest – Non Forest Prediction accuracy: 90.0% , CI (88.9% , 91.0%)

Land Cover - Forest Area from satellite data (2010)

Ecoregion: Humid Chaco

Ecoregion: Atlantic Forest

Ecoregions of Paraguay

DC- Dry Chaco

HC - Humid Chaco

AF - Atlantic Forest of Upper Paraná

AF HC

DC

9999999999999999999999999999999999999999999999999999999999999999999999999999999999

10

1995

Forest area: 2 755 * 103 ha

1990

Forest area: 3 150 * 103 ha

2000

Forest area: 2 459 * 103 ha > >

2010

Forest area: 1 411* 103 ha >

Forest area 1990 – 2010 (Atlantic Forest)

1111111111111111111110

0 500

1000 1500 2000 2500 3000 3500 4000

1985 1990 1995 2000 2005 2010 2015

Forest Area (1000 Ha)

Forest Area (1000 Ha)

Average deforestation rate: 81 *103 ha/year

Forest carbon stock change MRV by combination of remote sensing and ground measurements

Forest carbon stock monitoring in sample plots

Destructive sampling for allometric equation development and forest biomass estimation

Forest carbon stock estimation by combination of remote sensing and ground measurements

Change detection of carbon stock between 1990-1995, 1995-2000, 2000-2005, and 2005-2010

Forest carbon stock monitoring in sample plots

Forest type (Ecoregion)

Mature Forest (1ha)

Slightly Degraded Forest (0.2ha)

Degraded Forest (0.2ha)

Atlantic forest 9+1 10 10

Humid Chaco 1+9 10 10

Dry Chaco 7+3 10 10

Red : already surveyed plots, Black : new plots

• It is necessary to discuss on classification of degradation types• Tree census data was obtained.

Design of Plot distribution Ecoregion and Degradation level

Establishment of sample plots

Yhu

Lima

Yguazu

Cerro Leon

IPTA410

IPTA312

San Rafael 1,2

Escola Agricola

Golondrina

Pirapo

Salazar

Agroganadera JO

Lagna-Pora

CFAP

Golondrina y Morombi

Privada Tapyta

Reserva Ecol. Itavo

PSP reported 2011 PSP reported 2012 Temporary plot

Asuncion Emboscada Est. San Cayetano

Est. Santa Maria Doce

Victoria S.A.

Est. la Patria

Parque defensores de Chaco

Tree census data

Total biomass

R2 = 0.9845

Measuring trunk weight

Tree felling by heavy machine

Root of sample#5

Preparation for weight measurement

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Destructive sampling

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Allometric equations

Forest Carbon Stock Estimation (2010): Atlantic Forest

Class1 Class2 Class3 Biomass 92.88 138.75 181.74 (ton/ha)

Area 558.6 622.4 230.3 (1000 ha)

Total B 51.9 86.4 41.9 (106 ton)

Total: Forest Area 1411.5 (1000 ha) Total biomass 180.1 ( 106 ton) Total Forest 90.1 ( 106 ton) Carbon Stock

Field survey Remote sensing

Estimation of mean carbon stock by forest type and disturbance

degree

Estimation of forest area by forest type and disturbance degree

Classification decision Plotless sampling in each class

Image classification

Verification

Plot survey in each class

Allometry

Calculation of carbon stock

i x mean carbon stocki)

Calculation of carbon stock at a national level

Eco-region Degradation

No/light Medium Heavy

Atlantic

Chaco Humid

Chaco Seco

Conclusions

• Potential methodologies for a forest carbon stock change MRV system were developed for REDD+ in Paraguay.

• In REDD monitoring, not forest area change but forest carbon stock change is asked for.

• Combination with ground-based inventory is essential.

• Monitoring of forest degradation differs in the possibility of detection by cause and degree.

• Monitoring methodology changes with the situation of the forest of each country, and the data & information that can be used.

Thank you for your attention!