An Eye in the Sky – Finding the Real Arable Area and Field Sizes

About the project

It is highly beneficial for a farmer to obtain some key pieces of information before planting a crop, especially on a new area of land. This can include answering questions like what is the exact size of each field, are there any key features such as trees, rocks, and archeological features which would impact on-field operations, and more.

This project looked at how Agremo Eagle Eye Report can help provide all the information a farmer needs to get the most out of his field.

The main project participant was Phil, a corn grower who wanted to rent new fields for a new season. According to the Castradal map from the Bureau of Land Management (BLM), the total area was  was 439.5ha, broken down into three fields as follows:

Field 1: 112.5ha

Field 2: 146.9ha

Field 3: 180.1ha

However, as he was unfamiliar with the land, the farmer wanted to get more precise information about these three fields. Given their size and location, he could not simply walk across the full extent of the land, which is why he turned to drones and Agremo to get the answers he needed.

Drones can survey large areas of land without the inherent safety risks and high costs involved with the use of much larger manned aircraft. Furthermore, UAV Systems can provide real-time imagery and sensor data from farm field areas which cannot be quickly accessed on foot or by vehicle [3]. In this case, Phil was able to use a drone to generate an eagle eye report on the land he was about to rent, which allowed him to save $26,625.00 on inputs before the season had even started.

Customer requirements and challenges

Farmers and agricultural contractors need to know the exact size of their fields to efficiently plan operations, work out yields, and decide on inputs. Still, traditional survey methods can be costly and time-consuming. Besides, ground-based methods may also miss certain key features when it comes to growing crops.

Client needs

  • Assess the land quickly and get accurate information on the extent and exact position of features which would impact on-field operations.
  • Target inputs and manage his crop efficiently
  • Boosting profitability and reducing the environmental impact of his farming operations.

Field conditions / Existing processes

Phil had previously used traditional methods when assessing new land, which included walking across the field with traditional surveying techniques. These, however, were time-consuming and he often missed objects such as rocks or points of interest hidden by thick vegetation or a growing crop. Ground-based surveys can also be affected by the topography of the land, which can be especially difficult in mountainous and hilly areas.

It was because of these shortcomings that Phil decided to look at using drones. Drone surveys are also cheaper and more flexible than aerial surveying methods that utilize manned aircraft and are less weather dependent.

How Agremo approached the project

After consulting with Agremo, Phil decided to carry out Eagle Eye Reporting Analysis of the land to provide a real overview before he starts to plan cropping for the coming season and operations. Eagleview reports offer farmers the possibility to visually depict points and areas of interest in a field throughout the year. The reports also allow a farmer to create a list view of all points of interest on specific blocks of land. After mapping all three fields with a drone, Phil uploaded the map to the Agremo app, and with the help of Agremo measurement tools, he eliminated all the areas in the field that are non-arable. The results were as follows:

Field 1: 12% non-arable (there was a forest on the bottom 13.2ha)

Field 2: 6% non-arable (trees on the field 8.8ha)

Field 3: 7.5% non-arable (dredge 13.5ha)

The extent of these features could only be properly assessed and identified from the air.

Design and Plan

Collect data

Analyze data

Deliver and Apply

The Process and the solution

What had happened in the field

Phil’s fields contained significant areas of wooded land, as well as dredges (7.96% of the total area) which impacted the actual area available for cultivation.

What went as planned

The drone was able to identify areas of woodland and wet areas within the block of land and provide an accurate size in hectares for each.

What was unplanned

The extent of the Non Arable area such as the trees and woodland within the fields.

Where there any issues

A significant area of the land was down to trees or dredge and was not suitable for corn production.

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What were the decisions informed by Eagle Eye Report

Phil used the eagle eye reports to:

  • Point out and mark points of interest on the map such as trees, rocks, irrigation systems, etc. with their exact georeferenced location (longitude, latitude).
  • Calculate the exact distance between specific points on the map, such as roads, plant, and row distance, the distance between fields, etc.
  • Determine the size of areas on the field, such as ponds, problematic areas, arable areas, and many more.

This data helped him plan for a wide range of operations and to make decisions regarding everything from spraying and applying fertilizer to yield management and boundaries maintenance. Accurate data on the position of key features, such as rocks and other obstacles, can help plan field operations and aid in producing variable rate prescriptions.

Return on investment

Eagle eye reports show that from the total size he rented, 35.5ha (7.96%) cannot be cultivated. Knowing this information, he can plan his production more precisely and only order the seeds and chemicals that are actually needed. This means less waste and lower farm costs.  In this case, the grower will only plant corn in those fields where input cost per acre is around $750. Agremo eagle eye analysis had thus saved him $26,625.00 on inputs before the season had even started.

Aerial images taken by drones greatly accelerate and simplify topographic surveys for land management and planning, including that for farmland. Better data is the key to precision farming and allows for better planning and decisions.

Drones can be equipped to carry various agricultural sensors, ranging from RGB and active NDVI crop sensors to full-spectrum and near-infrared cameras. Agremo analysis can provide more than just an NDVI of a growing crop – our software delivers other georeferenced data for planning purposes. Eagle eye reports can survey farmland more efficiently than walking, and in that way take out much of the guesswork that goes into planning and managing a field of any size. Insights from an eagle eye report can thus help to lower production costs and increase yield for growers looking to turn their drone-collected images into actionable and accurate data.

Just as importantly, drone operators can get into areas that would otherwise be difficult to access.  An agricultural drone can survey terrain that would be challenging for people on foot or in ground vehicles, such as densely forested locations, hilly or mountainous land, and swamps. They can check the content and condition of land and wooded areas much quicker by pinpointing issues that can then be inspected by walking.

Eagle eye analysis can also help with more effective boundary management by providing accurate data on the location and length of boundaries, which can help with maintenance and budgeting for the upkeep of fences and ditches.

The data provided by the Eagle Eye Report can make the use of inputs more efficient in the long run, enhancing sustainability and profitability. Accurate data on field sizes can help with calculating the number of crop nutrients and crop protection products applied to a field, and more accurate and sustainable use of these inputs.

References

  • FAO and ITU, E-agriculture in action: drones for agriculture. 2018.
  • G. Grenzdörffer et al., “UAVs in Agriculture : Perceptions, Prospects, and ” Probably Not ”,” Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci., 2008.
  • C. Malveaux, S. Hall, and R. R. Price, “Using drones in agriculture: Unmanned aerial systems for agricultural remote sensing applications,” in American Society of Agricultural and Biological Engineers Annual International Meeting 2014, ASABE 2014, 2014, doi: 10.13031/aim.20141911016.
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