Service Development and Integration

REDDAF - Reducing Emissions from Deforestation and Degradation in AfricaRequirements Analysis and Research are Fundamental Inputs

The REDDAF Service Portfolio is based on the requirements analysis and the research activities. Research is conducted on the improvement of the EO-based forest cover change mapping, the development of EO methods for degradation mapping and the improvement of EO-based methodologies to directly assess above-ground-biomass.

Thematic Maps for Cameroon and CAR

The Products in the REDDAF Service Portfolio encompasses a set of Thematic Maps. A Thematic Map is a classified image with varying thematic content depending on the service:

  • Forest Cover Map for 1990, 2000 and 2010
  • Forest Cover Change Map for the periods 1990-2000 and 2000-2010
  • Forest Degradation Map for a single time period
  • Biomass Map of Low Carbon Forest

REDDAF - Reducing Emissions from Deforestation and Degradation in Africa

Left Image: Service Coverage Area Cameroon - The service demonstration area covers about 70 000 km² and comprises the Centre Province.
Right Image: Service Coverage Area in CAR - The service demonstration area covers about 70 000 km² and comprises the 4 regions Bangui, Ombella-M’Poko, Lobaye and Sangha-Mbaéré.

Forest Cover Maps for 3 Points in Time

The production of Forest Cover Maps showing forest vs. non-forest lands will be conducted for 3 points in time (1990, 2000 and 2010) based on EO data (Landsat, RapidEye and DEIMOS). Forest definitions adhere to National or International standards (e.g., FAO, IPCC 2006), or specific national and regional forest definitions. Non forest class can be subdivided into several broad land use classes.

REDDAF - Reducing Emissions from Deforestation and Degradation in Africa

Landsat and RapidEye Data Coverage for Centre Province of Cameroon for 1990, 2000 and 2010

REDDAF - Reducing Emissions from Deforestation and Degradation in Africa

Detail of Centre Province, Cameroon: RapidEye data for 2011 with NIR, RedEdge and Red channel compared to Landsat 5 TM for 1990 and Landsat 7 ETM+ for 2000 with NIR, SWIR and Red channel

Forest Cover Change Maps for 2 periods

Forest Cover Change Maps will be delivered for the periods 1990-2000 and 2000-2010, based on Forest Cover Maps and additional EO data. The changes will be classified into the IPCC compliant land use categories of forest land, cropland, settlement, grassland, wetland and other land. Forest Cover Maps as well as deforestation rates derived from Forest Cover Change Maps can be used to support reporting obligations to national/international conventions (e.g. REDD), decision making within sustainable environmental monitoring practices, and/or as input to forest management tools and GIS.

REDDAF - Reducing Emissions from Deforestation and Degradation in Africa

Extract of Forest Cover Change Map for Centre Province, Cameroon (2000-2010) based on Landsat 7 ETM+ (left) and RapidEye (right)

Forest Degradation Map for a single time period

The Forest Degradation Map product is conducted for a single time period. Nevertheless, an interpretation of images in the months/years preceding the main image is important to understand the forest degradation phenomenon, since the signals are rapidly lost. Degraded forest areas are derived from remotely sensed data using the direct or indirect approach described in GOFC-GOLD, 2009. Both methods allow to distinguish intact forest and non-intact forest which include logged forest (recent and older logged forest in the field); degraded forest (heavily burned, heavily logged and burned forests in the field); and regeneration (old heavily logged and old heavily burned forest in the field). Forest degradation maps who distinguish different degree of degradation will support monitoring and reporting in the REDD framework.

REDDAF

Example of Degradation Map for Eastern Province, Cameroon (2009-2011) based on RapidEye data

Biomass Maps of Low Carbon Forests

The Direct Biomass Assessment (DBA) is represented as Biomass Maps of Low Carbon Forests which give indication of biomass variation in tons per pixel in a region. The direct biomass assessment is currently limited to forests with less than 150-200t carbon per hectare due to the wavelengths of available EO sensors (savanna and woodland forests). Biomass maps allow estimating emissions and changes in forest carbon stocks from deforestation and forest degradation.

REDDAF

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.

Useful Optical and Radar Data for Mapping Products

The mapping products are generally based on Landsat-type (30m resolution) optical data (for example, Landsat series, SPOT4/5, RapidEye, DMC, IRS LISS etc.), except the DBA using ALOS-PALSAR data. In areas characterised by persistent cloud coverage, Synthetic Aperture Radar (SAR) data are also used for deforestation and degradation mapping. Optical HR data are the preferred EO data source since they offer a higher thematic content and a greater accuracy for comparable thematic mapping classes.

REDDAFAccuracy Requirements for Mapping Products

The mapping results are expected to fulfill the following accuracy requirements:

  • Geometric accuracy <30m
  • Minimum Mapping Unit (MMU) of 1ha
  • Thematic accuracy from 90% +/- 5%

Accuracy Assessment for Forest Cover Maps via Area Frame Sampling Approach

Capacity Building to Ensure Sustainability of the Project

Additionally to the mapping services, the REDDAF Service Portfolio comprises different Capacity Building measures: 

  • REDD awareness seminars
  • Remote sensing and GIS training on activity data assessment
  • Emission factor estimation
  • Provision of support for REDD negotiations

Sustainability is Strengthened by Local Project Partnership

The development of GMES services for REDD and the institutional support including capacity building proposed by REDDAF for the user communities in the Congo region will expand their knowledge base, which will further enhance their participation in the REDD process. As the REDDAF project partnership includes the University of Bangui, CAR and the Geospatial Technology Group SARL, Cameroon the uptake of REDDAF methods and products will be ensured by developing a local capacity.