Reducing Emissions from Deforestation and Degradation in Africa (REDDAF)

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1 Reducing Emissions from Deforestation and Degradation in Africa (REDDAF) Thomas Haeusler/GAF AG, Sharon Gomez/GAF AG, René Siwe/GAF AG, Thuy Le Toan/CESBIO, Stephane Mermoz/CESBIO, Mathias Schardt/JR, Ursula Schmitt/JR, Christophe Sannier/SIRS GAF AG (Co-odinator), Germany; CESBIO, Universite Paul Sabatier Toulouse, France; JOANNEUM Research Forschungsgesellschaft (JR), Austria; Système d'information à Référence Spatiale (SIRS), France; MESAconsult, Germany; Geospatial Technical Group (GTG), Cameroon; Universite de Bangui, Laboratory of Climatology, Cartography and Geography Studies (LaCCEG-UB), Central African Republic ABSTRACT The REDDAF Project aims to develop operational forest monitoring services in two Congo Basin countries that are engaged in the Reducing Emissions from Deforestation and Degradation (REDD) policy process. The project which is being implemented from will test and provide improved methodologies using both optical and radar Earth Observation (EO) data for deforestation/degradation assessment in Cameroon and the Central African Republic (CAR). The Project started with initial assessments of country specific user requirements to identify the needs of stakeholders in terms of implementing REDD Projects. Based on these national frame conditions research and development of methods for improved EO/ in-situ data applications to estimate the areal extent of deforestation and forest degradation as well as above ground biomass per unit area are being undertaken. Improved pre-processing methods for atmospheric and radiometric adjustments for multi-sensor EO data have been developed. Existing methods for deforestation mapping have been optimized by the application of radar data. Advanced methods for forest degradation mapping are developed, comprising a multi-temporal spectral mixture analysis as well as 3D-mapping options. These methods will be further developed and tested in Existing methods for direct biomass assessment using radar data have been improved to fully exploit the potential of the available EO data. The preliminary biomass mapping results will be calibrated and verified by using in situ biomass measurements. Specific Technology Transfer/Capacity Building activities to the country are ensuring that Project results, methodologies and lessons learned are provided in a manner to best support the work of national and regional counterparts. KEYWORDS: REDD, EO, Deforestation, Degradation, Biomass Assessment, Capacity Building BACKGROUND AND OBJECTIVES A key requirement in the United Nations Framework Convention on Climate Change (UNFCCC) REDD process is the need for countries to develop national forest monitoring systems in order to ascertain deforestation/degradation rates and their spatial extent. The role of EO in combination with in-situ data has been underscored as an important tool for forest cover and land use monitoring in the REDD methodological developments. The main objective in the REDDAF project which is being implemented from , is to test and provide improved methodologies using both optical and radar EO data for deforestation/degradation assessment in Cameroon and the Central African Republic (CAR).

2 An additional research objective is the investigation of radar data for direct biomass assessment. The improved methodologies will support the development of operational service chains which can be scaled up to national level and therefore contribute to the current national REDD+ Monitoring, Reporting and Verification (MRV) activities in these countries. The REDDAF project was prepared drawing on the experience of the GMES Service Element on Forest Monitoring (GSE FM) REDD activities in Cameroon which was implemented and formulated several research and development needs. The project also emphasizes the importance of involving the user community; the UNFCCC Focal Points in both Cameroon and CAR have supported and endorsed the REDDAF concepts and objectives in specific Service Level Agreements (SLA). The main Ministries involved are the Ministry of Environment and Ecology (MoEE) in CAR and the Ministry of Environment and Nature Protection (MINEP) in Cameroon. WORK PROGRAMME AND METHODOLOGY The work programme is organised on the understanding that there is on the one side a strong user requirement for the REDD forest monitoring embedded in the UNFCCC policy process, and on the other side the industries intention to offer cost efficient services based on innovative scientific and technological developments. Additionally, the work programme addresses the strong demand of the user community for technology transfer and capacity building. Therefore, the Project is being implemented and coordinated along five main Tasks: Requirements - The Project started with collecting the functional requirements for the REDDAF service developments, building an optimal trade-off between the REDD policy requirements, operational user needs and technology constraints. Research/Methods Development Several research topics such as improving the land use and forest change mapping in cloudy areas by utilising multi-sensor and multi-resolution techniques, improving degradation mapping and investigating direct biomass assessments with SAR data are being addressed. Additionally, methods are being developed to factor out anthropogenic degradation, which is required for the policy reporting process. Service Development and Integration The results from the research activities provide inputs to improve existing end-to-end REDD processing chains. In order to integrate the service into the user environment a REDD User geo-database is being developed by the local counterparts in CAR. Validation and Proof of Concept A validation system is being implemented which comprises of an end-to-end verification of all items and processes of a technical processing and service chain to demonstrate and provide evidence to the end user that the service meets the pre-defined user specifications and also is fit for purpose. It defines the procedures for reviewing, inspecting, testing, checking, auditing and documenting. The user community in both CAR and Cameroon will perform a comprehensive utility assessment of the REDD services and additionally an independent third party validation will be performed. Dissemination and Training The technology transfer to the user community as well as disseminating the Project results to a wider external audience, is being undertaken via training workshops, on-the-job training as well as presentations at various fora. As a result of this work programme, the services and products that will be delivered to the user community are as follows:

3 Forest Cover Maps for 1990; 2000; and 2010: forest and non-forest classes; Forest Cover Change Maps for and : forest land, cropland, settlement, grassland, wetland, settlement, other land (compliant with Intergovernmental Panel on Climate Change (IPCC) land use categories); Degradation Maps; Above Ground Biomass Maps for 2007, 2008, 2009, In the absence of national definitions for forest and/or mapping standards the REDDAF products and services will comply with international standards for forest cover mapping in REDD as explained in the IPCC Good Practice Guidelines (2006) and the GOFC GOLD REDD Source book (2011). Thus, the Food and Agriculture Organisation (FAO) definition of forest will be adopted as well as the definition of deforestation and forest degradation stipulated by the Central African Forestry Commission (COMIFAC) in its submissions to the Subsidiary Body on Scientific and Technological Advice (SBSTA). ACHIEVED RESULTS The implementation of the work programme in the first 12 months achieved the stakeholder analysis and the assessment of the user and policy requirements in both Cameroon and CAR. Furthermore, the advances in the R&D thus far give adequate inputs for the mapping in the countries which is planned for This section focuses on summarising the main scientific and technical results for deforestation, degradation and direct EO biomass assessment. Deforestation Assessment The production of the Forest Cover Maps is based on high resolution satellite data which are suited for mapping at minimum mapping units (mmu) from 0.5 to 1 ha. Available historical Landsat data (1990, 2000) as well as current SPOT or RapidEye data (2010) are being used for the mapping. The Forest Cover Maps are then used to produce Forest Cover Change maps and assess the forest area change. In order to improve the usability of multi-sensoral data, robust radiometric calibration techniques are being developed. Additionally, atmospheric correction models and de-hazing approaches as well as the optimisation of a combined spectral-geometric approach for cloud and cloud shadow detection have been developed and tested. To optimize the use of optical satellite data a method was developed which radiometrically enhances areas covered by cloud shadows and, thus, make these areas usable for further processing. The method is based on morphological techniques in order to take into consideration the diffuse intersection area between a cloud shadow and its surrounding. The radiometric correction is performed by histogram matching to the surrounding area. These technical steps facilitate the overall pre-processing of optical data in the production process. In addition to optical data it is also important to assess the utility of radar data in cloudy areas as a means to optimize the forest cover and change mapping. Forest cover change maps were derived from L-band SAR data (ALOS PALSAR) using different polarizations. A processing chain was developed and implemented considering both pre-processing and thematic classification. The first land cover classification (based on IPCC classes) led to validation accuracies between 76% (mean class accuracy) and 95% (overall accuracy). In

4 order to give a final recommendation on using SAR as alternative input data, the results will be further compared to the accuracies derived from optical satellite data. Degradation Assessment The complex issue of degradation mapping in tropical forest areas has been addressed by developing a concept based on selective logging. For this purpose an improved spectral mixture analysis (SMA) method (Asner et al., 2002) was developed which integrates multitemporal regeneration signals. This method will be tested in a concession area in South- Eastern Cameroon where recent degradation activities have occurred. The approach for developing further EO methods for degradation mapping started with an investigation on the options for 3-D mapping of forest canopy disturbances. The work comprised InSAR processing, radargrammetric processing, and the extraction of degradation areas from digital surface models. Figure 1 illustrates the possible detection of features such as logging roads from a COSMO SkyMed image. The methods developed for the detection of forest gaps from 3-D imagery have yet to be tested and validated. Figure 1: Degradation mapping using 3D information (COSMO Skymed coherence image) Direct EO Biomass Assessment The activities related to direct biomass assessment with SAR data aim to provide a transferrable methodology to deliver a mapping product that contains gridded and geocoded values of Above Ground Biomass (AGB). The approach focuses on improving existing image processing and biomass inversion methods to fully exploit the potential of the currently available data (ALOS PALSAR-L-band). The work is based on testing existing methods using in situ biomass data from Cameroon. The study site has been selected in the Adamawa region, which is one of the demonstration sites of the Group on Earth Observation- Forest Carbon

5 Tracking (GEO FCT). Over this site, 38 ALOS PALSAR datasets (28 FBD scenes and 10 PLR) have been made available by JAXA. In situ reference plots of 1 ha have been identified and biomass field measurements for each plot will be made during the field mission from January to March The improvement of the methods beyond the state of the art in biomass mapping (in particular in Cameroon, as reported by Mitchard et al., 2011) include several aspects: improvements of the spatial resolution of the biomass map, based on an optimized use of multitemporal and polarimetric data, reduction of the uncertainties in biomass for biomass values beyond ton/ha by taking into account the perturbing effects which mask the sensitivity of the backscatter to biomass (e.g. topographic and temporal variation effects). A Bayesian inversion method is also used to improve the retrieval performance. Changes in biomass will be observed in more details with ALOS PALSAR data in 4 years, Figure 2 presents the preliminary biomass map of the study area. The map is derived from ALOS PALSAR 2007 data using an inversion model developed for L-band SAR data (Le Toan et al., 2004) and recently tested in Vietnam and in French Guiana. In situ data from the Cameroon test area will be used for calibration of the model and verifying the results. In particular, in situ data will also be used for relative radiometric calibration between tracks and between data acquired at different dates. The validated processing chain will be further tested in CAR Figure 2: Preliminary biomass map of the region of Adamawa (about 120 km x 130 km), central Cameroon. The biomass value for each 25 m pixel is in ton/ha and has a resolution of 25 m. It is derived from 4 FBD ALOS-PALSAR data, acquired on July 26, 2007 (East track) and August 12, 2007 (West track).

6 The map in Figure 2 highlights the dense humid forests (Mbam and Djerem National Park) with biomass > 150 ton/ha, and the gallery forests in the savanna, with biomass lower than 100 ton/ha. It should be noted that large areas of gallery forests and transitional forests (with biomass reaching ton/ha) contain a large amount of carbon stocks, which is often neglected in carbon estimates. The preliminary results will be updated and assessed based on the in situ data. The transition between forest and savanna and the changes in biomass from 2007 to 2010 will be analysed. CONCLUSIONS The REDDAF Project has achieved technical results in the use of optical and SAR EO data which will now facilitate product development for the demonstration sites in Cameroon and CAR. For the SAR data, most of the processing steps are achieved using free software so that the method can be easily transferred to users. Extensive field based surveys for calibration of the research results in these tropical forests, have proven to be challenging to implement due to logistical and budgetary reasons. However, a confined field mission in Cameroon is being undertaken in the first quarter of 2012 to collect specific ground truth data for calibration of the direct biomass maps. Over all, the experience gained in this study will be used for future SAR missions dedicated to measuring above ground biomass such as e.g. the P-band SAR BIOMASS mission (Le Toan et al., 2011). Important achievements in the REDDAF Project have been the formalization of the partnerships with national institutions such as University of Bangui and GTG of Cameroon which ensures the uptake of REDDAF methods and products in the relevant countries. Additionally, capacity building modules were prepared based on the stakeholder analysis and some training has already been implemented. These activities will raise national awareness on the REDD+ process as well as address the technology transfer that is required. The overall impact on the beneficiaries is therefore to expand the knowledge base of the users, which will further enhance their participation in the REDD process. The REDDAF Project is contributing to the scientific and conceptual understanding of the technical challenges, whilst taking note of the most recent developments in the scientific and policy communities. REFERENCES Asner, G. P.; Keller, M.; Pereira, R.; Zweede, J.C.; (2002): Remote Sensing of Selective Logging in Amazonia Assessing Limitations Based on Detailed Field Observations, Landsat ETM+, and Textural Analysis: Remote Sensing of Environment, 80(3): GOFC-GOLD, (2011): Reducing Greenhouse Gas Emissions from Deforestation and Degradation in Developing Countries: a Sourcebook of Methods and Procedures for Monitoring, Measuring and Reporting, GOFC-GOLD Report Version COP16, (GOFC-GOLD Project Office, Natural Resources Canada, Alberta, Canada). Haeusler, T.; Gomez, S.; Seifert-Granzin, J.; Amougou, J. A.; (2009): REDD Pilot Projects in Cameroon and Bolivia: Contribution to the UNFCCC Post-Kyoto Protocol Process, 33rd ISRSE Symposium, Proceedings of 33rd ISRSE Symposium, Stressa, Italy.

7 Hirschmugl, M.; Maier, A.; Haas, S.; Siwe, R.; Schardt, M. & Amougou, J. (2008): REDD Pilot Project in Cameroon - Monitoring Forest Cover Change with EO Data: Proceedings of AARSE 2008 International Remote Sensing Conference IPCC (2006): 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Prepared by the National Greenhouse Gas Inventories Programme, Eggleston H.S., Buendia L., Miwa K., Ngara T. and Tanabe K. (eds). Published: IGES, Japan. Le Toan, T.; Quegan, S.; Davidson, M.; Balzter, H.; Paillou, P.; Papathanassiou, K., S.; Plummer, S.; Saatchi S.; Shugart, H.; Ulander, L.; (2011): The BIOMASS Mission: Mapping Global Forest Biomass to Better Understand the Terrestrial Carbon Cycle, Remote Sensing of Environment, Volume 15, Issue 11, 15 November Le Toan T., Quegan, S.; Woodward, I.; Lomas, M.; Delbart, N.; Picard, G.; (2004): Relating Radar Remote Sensing of Biomass to Modelling of Forest Carbon Budgets: J. of Climatic Change, Vol 67, Number 2-3, , December Mitchard, E.T.A; Saatchi, S. S.; Woodhouse, I. H.; Feldpausch, T.R.; Lewis, S.L.; Sonke, B.; Rowland, C.; Meir, P.; (2011) : Measuring Biomass Changes Due to Woody Encroachment and Deforestation/Degradation in a Forest-Savanna Boundary Region of Central Africa using Multi-temporal L-band Radar Backscatter. Remote Sensing of Environment. Volume 15, Issue 11. Mermoz, S.; Le Toan, T.; Villard, L.; Lasne, Y.; (2012): Biomass Assessment in an African Forest-Savanna Region using ALOS-PALSAR Data. Submitted to Int. Geoscience and Remote Sensing Symposium (IGARSS 2012).