The Democratic Republic of Congo National Forest Monitoring System to Provide Initial Information on REDD+ Activities
Satellite Land Monitoring System and the National Forest Inventory are fully functioning and will soon provide key information on REDD+ activities in this country.
The Satellite Land Monitoring System, also known as TerraCongo will soon offer official biannual statistics of national forest change cover. The system was launched by the Directorate of Forest Inventory and Planning (DIAF) of the Ministry of Environment of the Democratic Republic of Congo, in collaboration with the UN-REDD National Programme and the National Spatial Research Institute of Brazil (INPE).
This system is used to compare the national forest cover between two or more time intervals, calculating rates of deforestation, and in locating and tracking deforestation hotspots. It is used as one of the inputs for calculating forest carbon emissions.
During 2012 and 2013 professionals in remote sensing and global information systems (GIS) from the geomatics laboratory of DIAF, supported by experts from the UN-REDD Programme, have developed a methodology based on the spectral response of forest types in the province of Kasai Occidental.
The main advantage of this system is the use of open source software, such as the database manager system Postgres and the two platforms for image processing: TerraAmazon and OpenForis. Likewise, freely available Landsat and satellite images are used as primary inputs, because they have advantages such as multi-temporal coverage of the whole country, spatial resolution of 30 m, and multispectral information. With these tools, users may follow changes in one of the largest forest areas of the world, the forest of the Congo Basin.
DIAF is going to set up a comprehensive protocol for the quantification of deforestation that will provide confidence and transparence information of historical forest emissions and deforestation rates in Democratic Republic of Congo to all donors, civil society and international communities.
In order to collect information on forest carbon stocks and changes for estimating emissions and removals, DRC has been working for the last two years in a pre-National Forest Inventory (pre-NFI).
The aim of this pre-NFI is to collect relevant data and information at a large scale, using the methodology developed within the UN-REDD Programme and several partners of DIAF.
The methodology used in the country’s first assessment in carbon stock and carbon stock changes requires the measurement at the ground level of 470 sample plots in 65 random sites from across the country. This coverage will offer dendrometric, biodiversity, soil and biodiversity information.
Initial activities began with the recovery of information collected during inventories carried out since the 1970s. More than 20,000 field data sheets were entered into a database over eight months. Over 600 maps were recovered and are in the process of classification and digitalization.
Parallel to these archiving activities, capacity building has been established to strengthen the skills of forestry engineers and technicians who are members of the national team.
In early 2013, three teams were in the field in Bandundu province to collect the first 33 sample plots, using the first version of the filed data sheet. The sheet was then amended and validated in a workshop carried out by partners from different NGOs, FAO, the Japan International Cooperation Agency(JICA) and civil society.
Already, a total of nine sites have been measured in two provinces. The next goal is the completion by January of measurements of 20 sites in the provinces of Orientale, Equateur, and Katanga, using five different strata selected within the methodology.
A dedicated database (Open Foris) has already been installed and is ready for staff to insert inventory data.
Both the Satellite Land Monitoring System and the National Forest Inventory are two pillars of the National Forest Monitoring System fulfilling that help fulfill the Measurement, Reporting and Verification (MRV) function for REDD+.