Synergizing global tools to monitor progress towards land degradation neutrality: Trends.Earth and the World Overview of Conservation Approaches and Technologies sustainable land management database. Issue 93 (March 2019) - Gonzalez-Roglich, Mariano; Zvoleff, Alex; Noon, Monica; Liniger, Hanspeter; Fleiner, Renate; Harari, Nicole; Garcia, Cesar
Highlights: Remote sensing productivity indicators identified improvements in areas with sustainable land management. At least 10 years from the intervention establishment were needed for the impact to be detected. The impacts of some sustainable land management practices were not detected, highlighting the need for further research. Integration of remotely sensed data with expert knowledge is recommended for assessing and monitoring progress towards land degradation neutrality. Abstract: As part of the Sustainable Development Goals, countries are striving to achieve by 2030 a land degradation neutral world. Land degradation neutrality (LDN) is the state whereby the amount and quality of land resources remains stable or increases within specified temporal and spatial scales. Achieving this will require the uptake of sustainable land management (SLM) practices to increase the sustainable provision of ecosystem goods and services the human population will require. It will also require the development of systematic, robust, and validated methods for tracking progress at project, subnational and national scales. However, to date, no systematic comparison between the SLM practices and the indicators proposed for monitoring LDN has been performed. In this article, we used the United Nations Convention to Combat Desertification primary recommended global sustainable land management database of World Overview of Conservation Approaches and Technologies (WOCAT), and an innovative tool designed to assess and monitor land condition via changes in land productivity, Trends.Earth, to evaluate the agreement between self-reported sustainable land management technologies and indicators derived from satellite-based earth observations. We found that a combination of two primary productivity indicators derived from annual integrals of normalized difference vegetation indices (NDVI), trajectory and state, were able to identify increases in primary productivity in the locations where the SLM practices are implemented in comparison to control sites where SLM practices are not known to have occurred. Moreover, different SLM practices showed unique responses in terms of proportional area which experienced increase, decrease, or remained stable terms of primary productivity. We also found that the time since establishment of the SLM technology was critical for identifying improvements in the SLM sites, as only technologies with more than 10 years since implementation show statistically significant improvements. Our results show that satellite-derived land productivity indicators are successful at detecting the impacts of SLM practices on primary productivity, positioning them as essential elements of the monitoring and assessment tools needed to track land condition to assure the achievement of a land degradation neutral world.