Change language
Sidebar content Main content

Mapping Together: A Guide to Monitoring Forest and Landscape Restoration Using Collect Earth Mapathons


Mapping Together helps people use Collect Earth mapathons to monitor tree-based restoration. Collect Earth enables users to create precise data that can show where trees are growing outside the forest across farms, pasture, and urban areas and how the landscape has changed over time.

Building on WRI and FAO’s Road to Restoration, a guide that helps people make tough choices and set realistic goals for restoring landscapes, Mapping Together takes this process one step further. It helps them to track progress on their biophysical restoration goals using Collect Earth, an open-source data collection tool that pairs freely available, very high-resolution satellite imagery with local knowledge of the landscape.

Collect Earth mapathons can help stakeholders answer key monitoring questions by providing the framework for tracking changes in land use/land cover, tree cover and count, tree spatial pattern, and related indicators. Mapathons involve local stakeholders and people familiar with the landscape as data collectors and interpreters, increasing the data’s accuracy. The resulting data and products are then owned by local experts.

Four case studies – from El Salvador, Ethiopia, India, and Rwanda – presented in Mapping Together show how various stakeholders have used and adapted Collect Earth mapathons to answer their own questions about restoration progress.
Four case studies presented in Mapping Together show how governments have used and adapted Collect Earth to suit their individual context.

Cerron Grande watershed, El Salvador: The government of El Salvador used a Collect Earth mapathon to collect data on recent changes in land use and tree cover. Their goal was to identify restoration opportunities within this critically important watershed that supplies water to the capital city, San Salvador. The data collected show average percent tree cover across forest, cropland and grassland areas to determine whether there was opportunity to increase tree cover on various land uses. The majority of croplands had 0% tree cover, while grasslands had 10% tree cover, and forests had 90% tree cover.

Sodo Guragie Woreda, Ethiopia The Ethiopian Environment, Forest and Climate Change Commission (EFCCC) used Collect Earth to track where trees are growing within a local distict. The objective of their survey was to report on local progress toward the national Climate Resilient Green Economy strategy and the woreda’s target of reaching 19% forest cover. Data was collected for 2010 and 2015 to show progress toward the target of 19% forest cover. Results showed that forest cover increased from 7.5% in 2010 to 8.1% in 2015, a positive trend but still short of the target.

Sidhi District, India: The Collect Earth mapathon for Sidhi assessed where land could benefit from restoration. The objective was three-fold: show where tree cover already exists outside of the forest; show where restoration was already occurring on and around farms; and identify where more trees could be grown. To highlight the opportunity to increase on-farm tree cover in Sidhi district, data showed where existing tree cover was less than 40% and could be increased through growing trees on farms and other techniques.

Gatsibo District, Rwanda: National and district experts conducted a Collect Earth mapathon to show how many trees are growing in this rural district and to assess progress toward meeting the district’s target of 30% forest cover. Results showed that percent tree cover across the sectors of Gatsibo ranged from 12 to 22%, showing that all sectors needed to increase tree cover to meet the 30% target. The majority of land cover change that occurred between 2006 and 2014 involved net loss of forest, wetland, grasslands, and shrublands and net gain of cropland and settlements.

(by Katie Reytar, Dow Martin, Florence Landsberg, Sabin Ray, Carolina Gallo Granizo, René Zamora Cristales, Marie Duraisami, Kanchana CB, Tesfay Woldemariam, Fred Stolle, Bernadette Arakwiye, Anne-Maud Courtois, Rémi d’Annunzio and Yelena Finegold)

Copy numberShelfmarkLoan categorySiteLoan status
LAN/GEN/874 ELAN/GEN/874 EBookmainavailable
AIS uses strictly necessary cookies to improve the user experience.
This AIS also uses analytical cookies.