Essential earth observation variables for high-level multi-scale indicators and policies

Description

Several holistic approaches are based on the description of socio-ecological systems to address the sustainability challenge. Essential Variables (EVs) have the potential to support these approaches by describing the status of the Earth system through monitoring and modeling. The different classes of EVs can be organized along the environmental policy framework of Drivers, Pressures, States, Impacts and Responses. The EV concept represents an opportunity to strengthen monitoring systems by providing observations to seize the fundamental dimensions of the Earth system.

The Group on Earth Observation (GEO) is a partnership of 113 nations and 134 participating organizations in 2021 that are dedicated to making Earth Observation (EO) data available globally to inform about the state of the environment and enable data-driven decision processes. GEO is building the Global Earth Observation System of Systems, a set of coordinated and independent EO, information and processing systems that interoperate to provide access to EO for users in the public and private sectors. The progresses made in the development of various classes of EVs are described with their main policy targets, Internet links and key references.

The paper reviews the literature on EVs and describes the main contributions of the EU GEOEssential project to integrate EVs within the work plan of GEO in order to better address selected environmental policies and the SDGs. A new GEO-EVs community has been set to discuss about the current status of the EVs, exchange knowledge, experiences and assess the gaps to be solved in their communities of providers and users. A set of four traits characterizing an EV was put forward to describe the entire socio-ecological system of planet Earth: Essentiality, Evolvability, Unambiguity, and Feasibility. A workflow from the identification of EO data sources to the final visualization of SDG 15.3.1 indicators on land degradation is demonstrated, spanning through the use of different EVs, the definition of the knowledge base on this indicator, the implementation of the workflow in the VLab (a cloud-based processing infrastructure), the presentation of the outputs on a dedicated dashboard and the corresponding narrative through a story map.