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

Agricultural row crops occupy over 240 million acres of land in the United States (USDA-NASS2012). Decisions regarding the implementation of management practices in these agricultural areashave a significant effect on other environmental outcomes including soil erosion water quality andcarbon sequestration. There is currently no systematic and cost-effective method for documentingdetailed information on cover crops over a large region. We propose to evaluate the feasibility ofusing fused multi-sensor observations for operational cover crop monitoring that will systematicallyprovide detailed information about the dynamics of cover crop systems. Our initial focus will be onthree agricultural test areas: the Maumee River Watershed within the western basin of Lake Erie theVermilion Headwaters and Mackinaw watersheds in Illinois and sites with the Northeast andSouthern Cover Crop Council with the ultimate goal of providing a continental scale system.Fractional cover and biomass of the winter cover crop are the primary determinants of howeffectively the cover crop protects the soil and immobilizes the nutrients (Prabhakara et al. 2015)and while information regarding the presence or absence of cover crops is rare informationregarding the quality of cover crops is essentially non-existent. Currently some informationregarding cover crops is collected in a drive-by survey method as part of a tillage transect. Thisapproach is time consuming expensive limited in spatial extent and temporal sampling andprovides very limited information about the potential effectiveness of the cover crop. The use ofremote sensing and modeling to extract detailed information on cover crops across large regionsrepresents a cost-efficient solution.This project targets five primary decision-makers as users of a cover crop information system:private corporations and foundations (e.g. The Nature Conservancy Walton Family Foundation)the growing ecosystem services and water quality trading markets (e.g. Noble Research InstituteOhio River Basin WQ Trading program) watershed- and state-level water quality programs (e.g.Chesapeake Bay Program Partners such as Pennsylvania Dept. of Agriculture) the US Dept. ofAgriculture (USDA; with a focus on the National Resource Conservation Service [NRCS] andNational Agriculture Statistics Service [NASS]) and consumer packaged goods companies lookingto track the supply chain. All of these groups need accurate timely and spatially comprehensiveinformation about the dynamic state of cover crops across large regions.Studies have shown that cover crop presence can be mapped with moderate resolution remotesensing data (e.g. SPOT Landsat) on a case-by-case basis (Hively et al. 2009). However thesestudies have not demonstrated that mapping with remote sensing and modeling can beoperationalized to produce detailed information on cover crops. The primary barrier to operationalmapping with Landsat data is its limited temporal coverage in combination with the high temporaldynamics of the cover crop cycle. In this project we will assess the feasibility of mapping cover cropattributes (location fractional cover green-up date kill date and biomass) with high frequency timeseries information from a combination of modeling and multiple satellite sensors including Landsat8 Landsat 7 Sentinel 2 and MODIS.