Objective A: Quantify the influence of timing imagery collection on soybean limiting factors and management problems.
• The practical outcome of this work will be clear guidance to producers on the best timing of imagery to capture machine compaction impacts, water management impacts, and yield prediction impacts relative to the soybean plant vegetative stage.

• Based on previous research by the investigators it is expected that machine and water impact results will be produced during the initial year of this project.

• Additional site years will be required to quantify best practices for yield prediction factors and for the remote diagnostics of crop diseases.

Objective B: Quantify the repeatability and calibration requirements of commercial imagery sources for use imagery comparisons over time.

• A significant result of this work will be the development of an ISA Remote Sensing Calibration Site for the testing of various sensors (UAV, fixed wing aircraft, and satellite) with regard to the:
o Spatial resolution (impact of pixel size on the identification of important field measurements).
o Spectral resolution (what wavebands give us the best information about the crop response to various field conditions)
o Potential for spectral calibration (conversion to percent reflectance) to enable temporal comparisons of imagery within a given field and the accurate and repeatable computation of various indices (NDVI, SAVI, MSAVI, etc.).
o Understanding the impact of image mosaicking when comparing imagery digital values across a field.
o Understanding the impact of error of image to image registration at various pixel sizes.
o Identification of any inappropriate vendor manipulation of the digital remotely sensed data (nonlinear stretching or compression) that could potentially invalidate the results of any scientific research.
o Impact of using various resampling methods used by vendors as they provide a requested pixel size (resampling to a larger pixel size or resampling to a smaller pixel size).

Objective C: Determine the spatial precision of commercial aerial imagery solutions and develop recommendations best management practices for imagery driven variable rate maps.

• The results of this objective will serve as a best practices guide for producers related to buffer size and GPS technology requirements to accurately develop variable rate management decision maps.

Objective D: Develop a research driven education initiative to promote best management practices for using aerial imagery sources for in-season soybean decisions.

• Multiple web videos on the use and application of aerial imagery for ag decision making will be developed. These videos will help guide the grower’s selection and use of imagery for commercial on-farm management.

• A series of farmer friendly publications and guides related to aerial imagery applications will be developed and released through both ISA and ISU pathways.

• Conduct in-person training for the ISA On-Farm Network staff, CCA as well as through traditional ISU pathways including the Integrated Crop Management Conference.

• Contribute to the ISA Research Advanced Newsletters and present at the ISA Annual Research Conferences.