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About EAVs

What are Essential Agricultural Variables for GEOGLAM? EAV Data 2 Decisions Cycle-stboyf


Essential Agricultural Variables for GEOGLAM are Earth observation-based “building blocks” that in combination with one another or with other non-EO information provide insight into the “GEOGLAM Agricultural Indicators” – which themselves provide actionable information on the state, change, and forecast of agricultural land use and productivity (Figure 1). GEOGLAM covers land devoted to agriculture, which is defined as the systematic and controlled use of land and livestock to produce food, fiber, and fuel. This includes croplands, rangelands, and short-term fallow lands.

The EAVs can be measured or inferred from satellite data, and are supported through field data for calibration and validation. They support the core work of GEOGLAM and its constituent communities, including supporting national and global policy frameworks (e.g. G20 Action Plan and UN Sustainable Development Goals).


What Value do EAVs for GEOGLAM Add? 


Due to their situation between observations and information for our core usership, EAVs aid in identifying both key observational requirements (and therefore gaps in both in situ and satellite observations) as well as priorities for operational research & development to improve these variables and their eventual policy relevance. They help drive the research agenda (for our operational R&D activity JECAM as well as for funding agencies seeking to support GEOGLAM) as well as plans for future missions. They also help identify which variables require a “Compendium of Best Practices” documentation, an effort under JECAM to document methods and practices which produce high-quality variables, which in turn feed directly into GEOGLAM’s Capacity Development Team. And, of course, EAVs themselves feed the GEOGLAM and its community’s activities – be it the GEOGLAM Crop Monitor Bulletins or the work of the global, regional, and national monitoring activities which comprise GEOGLAM.


Audience for Products which Meet EAV Definitions


The Core EAVs are useful to EO and non-EO communities alike. The Supporting EAVs are useful principally to EO-communities.


The EAVs are divided into two categories, the latter of which has two subcategories:

  1. Top Priority User Facing EAVs: These are higher-order variables which in-and-of-themselves provide meaningful information about agricultural land use and productivity. These may have more direct applicability or interest to non-EO usership.
  2. Supporting EAVs: These are variables which generally require combination with other variables or additional context in order for their impact on or relevance to agricultural land use and productivity to be immediately understood.
    1. Those we articulate ourselves
    2. Those which explicitly leverage the GCOS Essential Climate Variables. 


Audiences for the EAV Framework


The definitions of EAVs are themselves useful and valuable for a variety of audiences:

  1. Space Agencies & the Committee on Earth Observation Satellites (CEOS): EAVs taken together with the GEOGLAM’s EO Data Requirements Table clearly show the purpose of and need for satellite observations of agricultural land. It articulates not just what is currently available or currently feasible, but what we know as a community to be clear priorities of our usership.
  2. Funding Agencies: Funding agencies can utilize the gap assessment (which will be an ancillary product of the EAV specification process, to be undertaken in 2022-2023) to develop solicitations.
  3. Policy Audiences: To quickly understand the ways in which existing EO-methods or EO-products themselves can be integrated into policy frameworks for monitoring, verifying, or reporting with respect to agricultural land use and productivity.
  4. Public and private sector organizations seeking to understand where EO fits in a decision support system, EAVs will help them understand what is feasible with EO with respect to agricultural monitoring.


GEOGLAM  Essential Agriculture Variables (EAV)  Mapping Hierarchy