Cover Crop Information System: Using remote sensing and modeling to map detailed information about cover crops across wide regions

Decisions regarding the implementation of conservation and soil health practices in agriculturalareas can have a significant effect on productivity and environmental outcomes including soilerosion water quality and carbon sequestration. In addition the effects of management can varydue to soil type and topographic conditions. While Dagan's OpTIS system produces wide areamaps of the presence of cover crops there is currently no systematic and cost-effective methodfor documenting winter cover crop quality or the resulting effects of these cover crops over alarge region. During Phase I activities we demonstrated the feasibility of using multi-sensorsatellite observations and biogeochemical modeling for operational cover crop monitoring thatwill systematically provide detailed information about the spatial and temporal dynamics ofcover crop adoption and vigor. In Phase II we propose to operationalize these algorithms tofacilitate deployment of the system over wide areas back through time. This monitoringsystem will be tied to our existing Operational Tillage Information System (OpTIS) toprovide the enhanced detailed information that our data service clients require forsustainability reporting ecosystem service market participation and scenario planning.Under Phase II activities our goal is to bring the research demonstrated under Phase I activitiesinto a fully functional and largely automated prototype system and evaluate the products in fourdemonstration regions. This goal will be accomplished through five technical objectives:• Technical Objective1: Refine and implement the automated data acquisition pre- processing and sensor integration framework outlined during Phase I activities.• Technical Objective 2: Refine and implement the automated optimization of the fAPARCSDM model that provides the foundation for estimating biomass fractional cover andcrop calendar as outlined during Phase I activities for the four implementation sites.• Technical Objective 3: Refine and implement the automated integration of remotesensing-based estimates of biomass to constrain and improve the modeling of soil healthand greenhouse gas emissions in the DNDC biogeochemical model.• Technical Objective 4: Refine and implement the API delivery system outlined duringPhase I activities.• Technical Objective 5: Work hand-in-hand with end-users at the Ecosystem ServiceMarket Consortium The Nature Conservancy and General Mills to tailor our productsand assist in integrating these products into their existing systems.This project targets five primary decision-makers as users of a cover crop information system: agnon-profit organizations (e.g. The Nature Conservancy) the developing ecosystem servicemarkets (e.g. ESMC) watershed- and state-level water quality programs the US Dept. ofAgriculture NRCS and National Agriculture Statistics Service [NASS] and private corporations(e.g. General Mills and Bayer). Each of these organizations need accurate timely and spatiallycomprehensive information about the dynamic state of cover crops across large regions andseveral representative organizations have provided Letters of Support.