Land degradation is a critical issue globally requiring immediate actions for protecting biodiversity and asso-ciated services provided by ecosystems that are supporting human quality of life. The latest IntergovernmentalScience-Policy Platform on Biodiversity and Ecosystem Services Landmark Assessment Report highlighted thathuman activities are considerably degrading land and threating the well-being of approximately 3.2 billionpeople.In order to reduce and ideally reverse this prevailing situation, national capacities should be strengthened toenable effective assessments and mapping of their degraded lands as recommended by the United NationsSustainable Development Goals (SDGs). The indicator 15.3.1 (“proportion of land that is degraded over totalland area”) requires regular data production by countries to inform and assess it through space and time. EarthObservations (EO) can play an important role both for generating the indicator in countries where it is missing,as well complementing or enhancing national official data sources.In response to this issue, this paper presents an innovative, scalable andflexible approach to monitor landdegradation at various scales (e.g., national, regional, global) using various components of the Global EarthObservation System of Systems (GEOSS) platform to leverage EO resources for informing SDG 15.3.1. Theproposed approach follows the Data-Information-Knowledge pattern using the Trends.Earth model (http://trends.earth) and various data sources to generate the indicator. It also implements additional components formodel execution and orchestration, knowledge management, and visualization.The proposed approach has been successfully applied at global, regional and national scales and advances thevision of (1) establishing data analytics platforms that can potentially support countries to discover, access anduse the necessary datasets to assess land degradation; and (2) developing new capacities to effectively andefficiently use EO-based resource
Knowledge generation using satellite earth observations to Support Sustainable Development Goals (SDG): A use case on land degradation
Year: 2020