Tools4LDN Project Roadmap for Trends.Earth Data Enhancements - A Review of Publicly Available Geospatial Datasets and Indicators in Support of Land Degradation Monitoring

Land degradation affects the livelihoods of millions of people worldwide. Diminished overall productivity and reduced resilience in the face of climate and environmental change, have made addressing land degradation a global priority formalized by the United Nations Convention to Combat Desertification (UNCCD) and the Sustainable Development Goals (SDGs), in particular Target SDG 15.3 on Land Degradation Neutrality (LDN). The LDN scientific framework provides the conceptual underpinning for how to achieve LDN, while the SDG 15.3.1 Good Practice Guidance (GPG) outlines a set of methodological options countries can follow to perform the land degradation assessments based on their local capacities. However, for many countries, limited resources and human capacity have hindered their ability to implement such recommendations. To address this need, Trends.Earth was developed as a free and open source platform which provides standardized methods, following SDG 15.3.1 GPG, and curated global datasets for the development of land degradation assessments. Over 130 countries were trained to use Trends.Earth for the 2018 SDG 15.3 reporting cycle, significantly lowering the technical barriers for providing robust assessments of land degradation. Country representatives, the UNCCD, scientists, and the Group on Earth Observations (GEO) acknowledged the significant contribution of Trends. Earth to supporting the achievement of land degradation neutrality, while at the same time identifying numerous areas for improvement which would allow for more robust monitoring. The objective of this report is to review currently available geospatial datasets which could be used in support of monitoring the three SDG 15.3.1 sub-indicators: trends in land cover, trends in land productivity, and trends in carbon stocks, in order to enhance Trends.Earth functionalities before the 2022 SDG 15.3 reporting cycle. Remote sensing offers the most cost-effective approach to monitor and evaluate large scale Earth surface change. Several spatially-explicit datasets at relatively fine spatial resolution (i.e. 10 – 30 m) have become available in recent decades at no cost to end users; these data, combined with cloud-based computing power processing, have enabled the assessment of natural and anthropogenic forces that modify land structures and process over long time-series. Based on the review of currently available global geospatial datasets, we have identified datasets at fine spatial resolution (i.e. 10 – 30 m) with significant potential for contributing to the assessment of land degradation complementing products at moderate to coarse spatial resolution that have already been successfully used so far. The Harmonized Landsat-Sentinel collection is the most promising of those datasets, given its high spatial resolution (10 – 30 m) combined with high revisiting frequency (3 to 4 days). For the assessment of changes in land productivity, the Normalized Difference Vegetation Index (NDVI) is the most studied and accepted vegetation index making it the preferred option, although limitations on some conditions would indicate that other better suited vegetation indices could provide better insights on the productivity trends. We have identified two other vegetation indices which can enhance assessments in particular conditions: for areas with high biomass, the two-band Enhanced Vegetation Index (EVI2), and for areas with low biomass, the Modified Soil-Adjusted Vegetation Index (MSAVI). Based on the review, we suggest developing processing capabilities in Trends.Earth to compute productivity indicators using the Harmonized Landsat-Sentinel collection with NDVI, EVI2, and MSAVI for improving monitoring of changes in land condition to complement the current assessment produced with MODIS NDVI long term series data. Detailed user guidance on conditions in which each indicator should be used should also be added. For land cover and soil organic carbon, no new finer spatial resolution global resolution datasets were identified as currently available. Trends.Earth will continue then supporting current global datasets and will regularly check with data providers to incorporate any new relevant dataset which could be added into the tool if they meet the recommendations and quality requirements determined by the SDG 15.3.1 GPG and the GEO LDN Initiative.This report was produced as an output of the Global Environment Facility (GEF)-funded project "Strengthening Land Degradation Neutrality data and decision-making through free and open access platforms". For additional information on the project see https://www.tools4ldn.org/. This project is a collaboration of Conservation International, Bern University, University of Colorado, and the University of California Santa Barbara