Santiago A. Utsumi, PhD
Innovations for Sustainable
Farming & Ranching
Inspired by Nature, Driven by Science
Drone- and Satellite- multispectral Imagery
Profitable pasture farming (including pasture dairy robotics!) is heavily reliant on the efficient measurement, allocation, and utilization of grass. Grass monitoring is the task of measuring grass cover across the farm, usually done through weekly pasture walks and by means of different methods. Visual estimation, pasture stick or ruler, and the use of rising plate meters are among most common methods to assess grass cover on farm. Modern laser-based meters are being used increasingly to measure grass heights rapidly and to output grass wedges and geocoded prescription maps. Pasture maps and grass wedges are a great visual aide for dairy farmers to either decide on forage budgets, evaluate past management, or even to define where cows should graze next.
Grass would be the cheapest sustainable feed resource, only if it is grown, utilized and converted efficiently. In order to plan grass-based diets accordingly, consider the following key rules::
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Set goals for stocking rates and feeding system (i.e. systems 1-5)
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Set a suitable average grass cover for your platform
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Set suitable wedge targets for pregrazing and postgrazing cover
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Plan ahead the spring rotation with %s platform for forage and grazing
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Plan ahead actions for the summer slump and heat stress.
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Set a suitable fall cover prior to the first frost
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Integrate feeding systems with environment controls or transient housing systems to give cows better comfort, including roofed ventilated sheds to cool down or for lying down safely, which are much needed to avoid unnecessary poaching and loss of soil structure, damage of soggy fields, reduced intakes, impacted growth rates, muddy feed pads and cow tracks, and impacted animal distress and production during times of unfavorable weather (storms, ice, snow, heat waves, etc.)



With the advent of smart-farming, GIS and precision grazing technologies, there is renewed interest on alternative ways to assess grass cover more rapidly and precisely, As our Fulbright fellow Dr. Juan Insua tested in 2016, drones including large scale quadcopter UAVs equipped with Ag-cams can provide rich multispectral information of pasture cover, at very high resolution (less than 5 cm GSD), precise scale of reference (field or paddock scale) and desired frequency (i.e. daily), Currently, free Sentinel mission's satellite imagery is another alternative method for large scale (farm to regional scales), yet less frequent (5-10 day frequency) remote sensing of pasture, but has limited pixel resolution (usually over 10 m GSDl) and accuracy to assess cover changes and grazing management at field, patch, or even plant scales. Alternatively, privately owned high resolution (<1 m GSD) microsatellite imagery services are presently available for purchase, yet servicing costs are still quite expensive making the use for frequent pasture cover and growth monitoring a difficult endeavor.
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In the figure above, I share examples for multi-spectral grass cover imagery collected with on different spatial resolution (pixel) and spatial extent (mosaic extent) by the use of the Sentinel 2A satellite mission imagery (10 x 10 m pixel) or by an Ag scan and camera (1.5 x 1.5 cm pixel) mounted on a commercial quadcoper drone (top panel). The use of precise drone imagery to monitor, assess and manage ground cover certainly provides robust grass cover information (spatially and temporally), making precision cow traffic and grazing management, possible (bottom panel). The pasture cover maps and prescriptions shown above were collected, analyzed and reported for the experimental dairy herd of the 'Unidad Integrada Balcarce' - INTA, Argentina.
Depending on the task and objectives, including spatial resolution, temporal sampling frequency and degree of precision needed, dairy farmers could either adopt drone-imagery, satellite-imagery, or a combination of both techniques for integrated monitoring and assessment of both grass spectral wedges and grass growth rates, on-farm. Through research at the Robotic Dairy of MSU and computing work conducted in collaboration with my colleagues Dr. Basso and Dr. Insua, and fellow students and farm staff, we have developed a quick Web-based platform called OptiGraze. This tool is intended to extract and map rich multiscale (field, paddock, farm) information of grass cover and growth for precision grazing (left).
