SEPAL Forest and Land Monitoring for Climate Action

FAO has developed a global, standard, large-scale methodology to assess forest dynamics using cloud-computing solutions and open-source tools to map disturbances and quantify direct drivers of deforestation and forest degradation. The methodology has been tested in six Central Africa countries and is supporting national organizations to monitor and assess their forest resources.

Deforestation and forest degradation are complex transboundary processes with many direct as well as underlying causes. A good understanding of why and where forest disturbances occur is instrumental for the development of targeted policies and actions aiming to reduce the loss of forests and the associated carbon emissions. ​

The Central African Forest Initiative (CAFI) and FAO are collaborating on the development of a standardized approach to assess direct drivers of deforestation and forest degradation, piloted in six countries in Central Africa: Cameroon, Central African Republic, Equatorial Guinea, Republic of Congo, Democratic Republic of Congo, Gabon.

Central Africa is home to the second largest tropical rainforest in the world Covering 240 million ha of land, these forests play a crucial role in combatting climate change at a global level, as they represent a significant carbon sink, in addition to supporting thousands of species and millions of people. ​

Central African forests are however under increasing pressure from various drivers of deforestation. Among them are small and large-scale agricultural expansion, mineral extraction, infrastructure development, commercial logging as well as charcoal and biofuel production. A better understanding of these direct drivers at the regional level can help countries consolidate their efforts towards reducing and reversing forest loss. ​

The CAFI initiative is a partnership between Central African countries which serves to highlight and preserve the value of forests in the region, mitigate climate change, reduce poverty, and support sustainable development. Implemented by FAO, the deforestation and degradation drivers project is using a data-driven approach in SEPAL to assess deforestation, degradation and the associated direct drivers inform CAFI priorities and develop investment frameworks to support the sustainable use and conservation of forest resources. ​

  • Uses FAO’s SEPAL platform for cloud –based processing of Earth Observation Data and other tools from the Open Foris suite ​

  • Uses freely available public datasets from  USGSEU Copernicus and Planet Programme​

  • Enables countries to perform their own forest monitoring via capacity building enabled by in-country workshops and regular online webinars.​

  • Supports SDGs 15 Life on Land and 13 Climate Action,​

  • Contributes to the implementation of the Paris Agreement.​


The project uses state-of-the-art approaches for robust assessments of forest disturbance, sample-based area assessments and visual interpretation of direct drivers. Four major components of the methodology are shown here. The SEPAL workflow, steps and parameters are described in more detail in the SEPAL documentation.


A new statistical approach to estimating areas of change integrating multiple change detection algorithms is being developed for the second phase of the project. This will enable the combination of multiple sensors and approaches, coupled with a semi-automated validation methodology to increase the efficiency of post analysis interpretation.  ​


All derived data are validated through visual interpretation of high-resolution satellite imagery using Collect Earth Online. A customized online interface allows the team of more than 40 users from the region and abroad to identify forest types, change, date of change and the associated direct drivers. ​

Time Series Analysis

The project uses a number of different time series analysis, which detect changes in forest cover from multiple satellite observations. Different magnitudes of change are used to discern deforestation from degradation​

Regional Land Cover Classification System

Detecting changes in forest ecosystems and associated direct drivers, requires a baseline map indicating land cover, which depending on the country’s national forest definition will be classified as forest/non-forest. Official definitions of forest are not the same in the 6 CAFI countries. We developed a regional classification scheme that integrates national systems and definitions. ​

Satellite Image Mosaics

The project leverages the power of SEPAL to integrate multiple satellite observations into multi-temporal composites. Cloud-free optical mosaics combing Landsat and Sentinel-2 imagery have been produced for the entire region. These are complemented by active radar observations from Sentinel-1, ALOS PALSAR which enrich the available information for baseline forest and land cover mapping.​


Project results are presented through interactive maps and dashboards built with various visualization and analysis tools inlcuding arcGIS online, Tableau, and Power Bi. Geo-spatial data are compiled in this online database including Google Earth Engine assets which can be used and visualized in SEPAL. Data are also available in FAO’s Hand-in-Hand geo-spatial platform.

Global Forest Watch App

You can visualize the project data with Global Forest Watch information which can be analysed in this Map Builder Application from WRI

Validation Data Explorer

You can view all the validation data and evaluate various drivers and high-resolution satellite imagery with this dashboard. 

Drivers Dashboard

​Explore the direct drivers and the type and date of disturbance and impact on various forest types

Interactive map

All the data produced and associated with the project are visible in this Google Earth Engine App

Story map: Drivers of Forest Cover Change in the Congo Basin

A summary of the methods and results of the CAFI/FAO pilot study on deforestation and forest degradation and direct drivers in six Central African countries.

CAFI DDD project library

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