‘Data’ and agriculture
By Dale Steele P.Ag. Precision Agronomist
Everyone is talking about it, but what does data mean to agriculture? It all starts with digital field borders.
Every farmer knows his fields and where the field boundaries are located. Indeed, urban folks are sometimes in awe of how farmers keep track of every field when there are no trees and few landmarks in the wide-open Prairies.
The first step in any process is to identify and define the field. Driving the field boundaries to create digital field borders is an option if you don’t have access to precise GIS tools and good imagery. On large farms or complicated fields with coulees and ponds across the fields, it is cost prohibitive and time consuming to drive every non-crop boundary.
Precise field borders are the beginning of everything in precision agriculture. Some smartphone apps allow you to quickly draw your field borders on background imagery with your finger. This method is not accurate enough because your fingers sometimes won’t place the field boundary precisely. Your field boundary could be out 100 feet or eight feet depending on your skill, and the acreage measurement will be incorrect. The inaccurate field border will cause later issues with equipment guidance, VR prescriptions and sectional control applications.
Good technicians can define accurate digital field boundaries with a click of the mouse using GIS tools and high-resolution ortho-rectified imagery. Creating digital field borders only needs to be completed once, unless the field boundaries change when you remove fence lines or enlarge fields. Google Earth provides a nice imagery viewer but I have found errors where a collection of images weren’t stitched together accurately or the dated imagery doesn’t reflect the current field area.
For large farms, I suggest a field naming structure that makes sense to your farm staff and can be utilized in equipment controller formats, and shared with companies that provide services on your farm. I suggest a short field name, a legal land description and year the digital field border was created. This will accommodate adding, deleting and merging fields as rotation dictates or as your farm grows. Adding a file tree with multiple farms or sub-farms can aid the equipment operators to quickly select or identify fields in the equipment controller displays.
Field boundaries guide the trucks and can provide equipment guidance for your farm employees and service providers. Think of the digital field border as a “cookie cutter” for data. As with cookie dough, we take big batches of data and roll out the layers of data to make the final product. Data could be anything related to the field such as satellite imagery collected over the past 30 years or UAV/drone imagery collected earlier in the day. Additional layers of data can be soils information, sensor data or yield data files collected from multiple combines across hundreds of fields. The field borders cut through the data and grab only the data associated with the specific fields. This enables the analysis of a single field or batch processing by variety, crop type for the farm or county, or soil zone.
As a farmer, consider the information you have when you rent or buy a new field. Have you ever visited a snow-covered field to consider a new field decision? What data did you have for that field? Years of farming experience has always been a criteria to assess knowledge because that individual’s knowledge is a collection of experiences and information gathered over numerous years. One common trait is recalling past experiences for a field while monitoring current situations and determining the timing for future actions that are adaptive to each growing season. Farmers and agronomists know nature has a multitude of factors that affect crop growth and final yields.
Precision agriculture offers the data to look back in time instead of farming blind with limited field history. Sometimes the field history may have died with the farmer, but now a convergence of technology is enabling farmers and others to retrieve past information about agriculture. The technology pieces are ready and different companies possess different components of data. Equipment companies have built the hardware. Different levels of government have the EC maps for every irrigation field and soil maps for the country. Each satellite network has historic and in-season remote sensing for the entire Earth. Numerous weather station networks collect and archive weather data. Seed, fertilizer and chemical companies have years of research plot data. Crop insurance has detailed field information. Farmers have details on crop rotation, soil lab results, planting dates, fertilizer rates and final yields.
A lot of software programmers are focused on creating another app or game for smartphones. Imagine if more efforts were directed to feeding the world. The individual skills and data sets have been underutilized because they don’t offer a direct benefit or an easy way to see patterns in the data because agriculture is complex.
Growing food is the most valuable job on the planet, and technology wants to help you do it better. It all starts with digital field borders.