the gmes forest monitoring redd services preparation of...

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Sentinel-2 for Science Workshop 21 May 2014, Frasacti

The GMES Forest Monitoring REDD Services Preparation of Sentinel 2 Applications T. Haeusler, S.Gomez, G.Ramminger, R. Siwe

GSE FM REDD Consortium Partners

Page 3 Sentinel-2 for Science Workshop, May 2014

Poland: ME

Austria: UBA-A

Sweden: NBF

Latvia: SFS

Pan-European: EEAGermany:

BMVEL,TLWJF,UBA-G,

Global Woods,LANU,LFG

The Netherlands: LNV

France: AFOCEL,CAFSA,CFBL

Greece: NOA

Italy: MATT

Switzerland: SAEFL

Spain: MMA,

SBO-ME

French Guiana: CITEPA,MAAPAR

South Africa: CSIR

Indonesia: BPPT

Russia: FS-I

GSE Forest Monitoring – active since 2003 Services are driven by policy and user demands:

Service Users

Service Sectors

PAN European Forest Monitoring

Support to UNFCCC and Kyoto Protocol Reporting

Forest Information Up-date

Support to Clean Development Mechanism Projects

Support to Environmental Monitoring

Monitoring of Forest Operations and Disturbances

Climate Change Mitigation

Forest and Environment

Sustainable Forest Management

GMES Service Element Forest Monitoring

Became involved in REDD in 2006

Sentinel-2 for Science Workshop, May 2014

REDD - Reducing Emissions from Deforestation & Degradation in Developing Countries

REDD has emerged within the UNFCCC process as a post-Kyoto mechanism

Developing countries can claim financial compensation from redeucing emmission from deforestation and degradation

© Sentinel-2 for Science Workshop, May 2014

• REDD requires National Forest Monitoring Systems • Remote Sensing is a key contributor for Activity Data (AD)

assessment

Presenter

Presentation Notes

Reduction of greenhouse gasses is central to the climate change initiatives in the United Nations Framework Convention on Climate Change (UNFCCC). A new UNFCCC mechanism in which developing countries can receive financial credits for reducing emissions from deforestation and degradation (REDD) is being negotiated as part of a future post-Kyoto Protocol scenario. In this context GAF AG and a consortium of experts have initiated the design and implementation of REDD Pilot cases using Earth Observation and terrestrial surveys for carbon monitoring with strong counterpart support in African Countries: Cameroon, Republic of Congo and Gabon Central Republic of Africa A main objective is to establish baseline projections of emissions caused by deforestation using a wall-to-wall approach

REDD Experiences Africa

1. REDD Pilot Cameroon 2008 -2009

2. GSE REDD Extension in Rep. of Congo and Gabon 2009 - 2014

3. R&D REDD for Africa Cameroon and CAR 2010-2013

4. REDD+ MRV for SADC 2011-2014

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5. GSE REDD – Dry Forest Mapping – Zambia, Malawi, Zimbabwe 2014-2015


Project Components

• User and Stakeholder Analysis – To identiy capacities and gaps for national

MRV

• Activity Data Assessment based on EO methods − Development of EO based methods for

historical and current forest cover mapping (1990-2000; 2000-2010), MMU 0.5 -1 ha, Acc. >90%

− Classification of deforested areas into IPCC compliant Land cover/use categories:

Cropland, Wetland, Settlement, Grassland, Other land

− Development of methods for degradation mapping

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• Capacity Building − Training on EO and GIS − Technolgy transfer of

developed methods

• User Engagement − Utility assessments − Validation of services


Service in Republic of Congo

Page 8

Forest cover and forest cover change maps for Republic of Congo


Expansion of the class settlement into forest land between 1990 and 2010 (Refugee camp near the border to the Democratic Republic of Congo)


Service in Gabon

Page 10

Forest cover change map between 2000 and 2010 for Gabon


Developments for Degradation Monitoring

Workflow based on analysis of dense time series:

Page 11

Requirements: •High frequency of cloud free, multi-temporal data coverages •Radiometric calibration of critical importance


Monitoring Degradation


Challenges for Monitoring Degradation


EO Data for 2010 National coverage: temporal variabilty of +/- 3 years

EO Data for 2010 National coverage: spectral and spatial variability due to multi-sensor coverages

Challenge: Heterogeneity of National EO Data Coverages

Acquisition Coverage [%]

2010 31,95%

+/- 1 year 54,60%

+/- 2 years 9,12%

+/- 3 years 4,33%

Sensor Coverage [%]

SPOT 4 26,84 % SPOT 5 29,78% Landsat 7 8,86% Landsat 8 1,90% RapidEye 22,62% DMC 10,00%

Temporal Variations Sensor Variations


Impacts of Challenges on Tropical FM

• Higher processing effort and higher costs

• Multi-sensor adjustments • Radiometric calibrations • Number of residual spectral strata to be

treated separately • Thematic quality • Potential for having a robust and

repeatable monitoring system (REDD requirement)

These challenges lead to the following impacts:


Roll-out of GSE FM: Regional REDD+ MRV for SADC

• SADC - Southern African Development Community, 15 Member States, 5,5 mio km²

• Dry Forest Ecosystems cover 2.7 million sq.km in Africa and these countries have some of the highest deforestation rates

• SADC is interested in a regional, ecosystem based REDD+ MRV system

• Thus there is a GSE FM service roll-out to support SADC

• However: Current GSE FM processing chains are optimized for humid tropical forest and not for dry tropical forest


Forest Change in Malawi

• Landsat images on Zambia Malawi border

• Changes in Forest Cover due to agricultural expansion

Area enlarged in Miombo study area


Challenges of Accurate Forest Mapping in Dry Forests

Forest, i.e. areas ranging from 10% to 100% tree cover

Phenology of the tree species and stand sites: • low tree height of mature trees (7-15m), • low canopy closure on large areas • bare soils, shrubs and thickets interspersed in varying intensity

causing spectral confusion leading to higher uncertainty of the area assessments.

Non-Forest

Challenges of Accurate Forest Mapping in Dry Forests

Seasonality: • Deciduous tree species with leaf fall in dry season • Only small time windows between the seasons provide optimal

forest detectability

End of Rainy Season: Landsat-5 1991-03-11 Dry Season: Landsat-5 1991-10-28

Landsat-5 TM courtesy of the U.S. Geological Survey. Landsat-5 TM courtesy of the U.S. Geological Survey.

Example of Phenolgy difference between seasons: Test site in North Botswana

Seasonality effects lead to higher area uncertainties. Dense time series needed!

Baikieae Forest Woodland

Baikieae Forest Woodland


The Potential of S2 for REDD

Page 20

Sentinel 2 addresses the various challenges in tropical and dry forest mapping by offering: •high repetition rates to acquire large data coverage in short time periods, 5 day repetition cycle (with 2 satellites), 290 km swath width! •high spatial resolution to assess also forest stands with low canopy closure, 10, 20 and 60 m •high spectral resolution to discriminate between forest and spectrally similar vegetation types, 13 spectral bands (VIS, NIR & SWIR)


Landsat

Landsat & Sentinel 2A

Landsat & Sentinel 2A & Sentinel 2B

Landsat / Sentinel 2 Coverages in Cameroon (10 days Simulation)

Courtesy ESA

Presenter

Presentation Notes

Revisiting time in tropical areas, meaning we can get the data everywhere

Conclusions and Outlook

• National Forest Monitoring Systems are obligatory requirements in the REDD policy process.

• Countries moving towards results-based payments need to document data and methods used to achieve repeatable, accurate, consistent, and complete FM systems (required for international review process)

• GSEFM REDD has set the foundations to meet these requirements in an operational manner.

• However, the Sentinel-2 data will have an enhanced and possitive impact to address the rigorous requirements of regular and near real time monitoning


SADC-GIZ REDD Project

Thank you very much!

Contact: [email protected]

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