Measuring the impact of restoring degraded forests and landscapes from the local to the global level.
More than 60 countries have committed to bring over 170 million hectares of degraded land into restoration by 2030. Introducing trees and shrubs to landscapes – and protecting existing plants – improves livelihoods and halts the degradation of ecosystem services. Governments around the world recognize that supporting farmers, landowners, and local communities to restore land revitalizes rural landscapes, bringing social and economic benefits and boosting incomes. Restoration provides food and energy, improves water, soil, and biodiversity conservation, and mitigates climate change by storing carbon in trees.
The global recognition of the benefits of restoration has led to significant commitments under the global Bonn Challenge and through AFR100 in Africa and Initiative 20x20 in Latin America and the Caribbean. It is now time to implement those commitments, but to understand where we are now and show success, the global restoration movement needs to establish an effective system for measuring progress.
Many countries have deforestation monitoring systems in place, but deforestation is a sudden event. Restoration is slow and subtle. Most deforestation monitoring systems are therefore not suitable for measuring restoration progress. To detect and quantify restoration we need similar, but distinct, methods and tools.
To understand which techniques and practices most effectively restore and protect the land
To inspire replication by providing independent evidence of success to peer institutions, investors, local and national governments, and international bodies
To understand what worked, and what did not, to better support adaptive management and see how local communities benefit from restoration
What do we need for good monitoring?
WRI works through five guidance principles to ensure accuracy, inclusion and sustainability:
Balanced Landscape: Promoting a landscape perspective and analyzing and balancing trade-offs;
Holistic Thinking: Incorporating measurements of biophysical, social, economic, and governance improvement;
Adaptable Approaches: Being lean and sustainable, results-oriented, simple, realistic, adaptable, and cost efficient;
Data-Based Approaches: Integrating qualitative and quantitative, small and big data into a single system without bias.
Information Management: Reporting information in an open, transparent manner to encourage better management, information sharing, reporting, learning, and research.
How is WRI involved?
Restoration has many different goals, including increasing crop yields, improving water quality and local incomes, and reducing soil erosion. Identifying and reporting on the primary drivers of degradation and how restoration can improve damaged ecosystem services is a critical first step. Many systems exist for reporting on restoration efforts, including country-led and global efforts. Most notably, the Bonn Challenge Barometer, a global effort led by the International Union for Conservation of Nature (IUCN), has created national-level reports on restoration progress in several countries.
To fully understand if restoration activities are making progress toward the intended goals, however, a complex monitoring system that complements these reporting efforts is necessary. With this in mind, WRI has worked to be as inclusive as possible in its approach to measuring restoration progress. So what does WRI do?
Assisting governments and local project leaders to develop restoration monitoring systems: WRI is working with stakeholders to think through their restoration monitoring goals and select the best indicators to measure progress. With the UN Food and Agriculture Organization (FAO), we have developed a guide, The Road to Restoration, that helps users select indicators and develop a restoration monitoring system. The guide helps create a system that can be tailored to each specific landscape using different types of available data, including biophysical and socioeconomic variables.
With this methodology, WRI supports multiple countries with their restoration monitoring systems, including Brazil, El Salvador, Ethiopia, Honduras, India, Indonesia, Kenya, Malawi, Nicaragua and Rwanda.
Malawi: Learn more about how we helped designed a framework for monitoring progress on Malawi’s National Forest Landscape Restoration Strategy.
Rwanda:Learn more about how we looked at restoration progress in Rwanda’s Gatsibo District through measuring biophysical, socioeconomic and governance indicators.
Ethiopia: Learn more about how measuring progress on tree-based landscape restoration meant identifying how trees could contribute to the goals of reversing degradation, increasing food production, and limiting flood and landslide risk.
El Salvador: The Ministry of Environment created an index to measure the impact of restoration on climate change adaptation and mitigation, biodiversity, water quality in rivers, and rural livelihoods.
Read about the AFR100 Working Paper Series on Monitoring Progress here.
Developing and implementing tools to measure tree cover gained from restoration: The scientific community has already developed a robust set of methods and tools to monitor deforestation (e.g., Global Forest Watch). Restoration monitoring is more difficult, since restored tree cover is often widely dispersed over a broad area. In addition, remote sensing imagery can miss tree cover increase in the short term, as trees grow slowly. As a result, WRI is working on new tools to measure tree cover from restoration:
The University of Maryland, Global Forest Watch, and Resource Watch are using Landsat satellite data to identify annual tree height classes at a 30-meter resolution. Currently, a 35-year data set is available for South America, a pilot set is available for Southeast Asia's Mekong region, and other regions will be developed soon. These data sets will give users a better overview of medium-term progress towards restoration goals.
WRI is also involved in two additional efforts to monitor restoration at the landscape scale:
Google Earth Engine is used to classify satellite images of landscapes with differing tree cover density, using Sentinel 10 m and Landsat 30 m data.
Collect Earth is a software program developed by FAO that builds on Google Earth’s ability to generate satellite images of sample plots that can be interpreted visually. WRI and partners organize Collect Earth ‘Mapathon’ workshops where local experts familiar with a certain landscape interpret and classify high-resolution satellite images. This analysis results in tree cover datasets that can be used as baselines for restoration and measure progress. A comprehensive guide to Collect Earth with six restoration case studies, written by WRI and FAO, is forthcoming.
Collect Earth baselines have been developed for landscapes in El Salvador, Ethiopia, India, and Rwanda.
As part of the five-year assessment report of the New York Declaration on Forests, WRI conducted a pioneering study that identified where trees are growing both inside and outside the Mekong region's forests, including on the farms and pastures where people most benefit. By employing both GLAD satellite data on tree cover gain and Collect Earth mapathons, the pilot produced the first-ever independent and comprehensive assessment of tree cover gain and loss. This analysis is the first step toward designing a global restoration monitoring system. Learn more here.
Training the trainers: WRI has organized training sessions in Ethiopia and Nicaragua to equip local Collect Earth specialists with the skills to train others. These trainings allow country specialists to measure restoration progress on their own and to ensure that the restoration work will be sustainable over the long term.
We welcome questions or ideas for collaboration. Please reach out to Katie Reytar for more information.