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How Agricultural Holdings and Farmers Can Use Drones for Precision Agriculture by@inteticsinc
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How Agricultural Holdings and Farmers Can Use Drones for Precision Agriculture

by Intetics Inc.July 22nd, 2022
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The success of breeding and chemical industries has made it easier to engage in agriculture. But on the other hand, there are serious challenges coming from climate change and black swan events like the COVID-19 pandemic and the US-China trade war. This changes the rules of the game and calls out to you, “Hey, farmer! You have to have a large margin of safety. And you have to continuously improve your work efficiency.”
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Can you recall Bill Gates’s comment saying that “if your business is not on the Internet, then your business will be out of business”? The same will soon be said about agriculture and the use of technologies in that industry. If you have never taken aerial photographs of your farm and water you crop by eye, you don’t have a farm. Of course, it does exist, but you don’t use even a third of its potential.

Why So Adamant?

On the one hand, the success of breeding and chemical industries has made it easier to engage in agriculture. But on the other hand, there are serious challenges coming from climate change and black swan events like the COVID-19 pandemic and the US-China trade war. This changes the rules of the game and calls out to you, “Hey, farmer! You have to have a large margin of safety. And you have to continuously improve your work efficiency.”


Not everyone can afford to increase their earnings by expanding their fields or gardens. So, it’s not about how much land you have but how you use it. And it’s not about planting twice as much wheat on 10 square feet of land; it’s about making your farm smart.

Innovative solutions allow you to automate some tasks, increase yields, cut costs, and boost profits. This is as important for a small family farm as it is for large farm groups or massive agro-industrial complexes.


Sure, you can’t be prepared for certain events. In 2019, Midwest flooding devasted many crops. According to officials, damage exceeded $1.2 billion in Iowa alone, one of the three most affected states. But technology comes to the rescue even in cases like this and makes it possible to quickly assess the damage and receive proper insurance payments.


The climate becomes less predictable in other parts of the United States and worldwide. Droughts, floods, and hurricanes severely affect yields and market prices of crops, sometimes leaving farmers without income. Now they need to preserve and increase the harvest even in less-than-favorable weather conditions to be able to sell profitably amid market shortage and rising prices. And excess allows farmers to grow other crops that will be more profitable to cultivate in the coming season.


The price of corn futures in the United States has doubled – from $330 to almost $700 – since June 2020. But has it become easier to grow? And how can a farmer increase yields on a set piece of land without resorting to harmful chemicals or disrupting soil composition? Or how can they start growing new crops that are difficult to cultivate in the region but bring good profit?

Farm owners and managers that are looking for improved yields, work efficiency, and earnings are starting to take advantage of UAVs more often. And these are not just beautiful aerial photos – there is a lot more to it.

What You Can Monitor on a Farm with a Drone?

Drone photography allows you to get information that no farmer could collect, no matter how attentive or experienced they are, if they simply walked around the fields.

The Quantity and Quality of Green Mass

Aerial photos or colored orthophoto maps help to control farming at all stages – from germination to harvesting. Essentially, it’s a single shot of your fields stitched together from thousands of drone shots. It has a great amount of detail, so it can be zoomed in to clearly show the seedling density, unseeded areas, plant color, etc.


Orthophoto maps obtained with drones eliminate the need for extensive manual fieldwork or expensive shoots from a manned aircraft. This is important background information, the field model in a smartphone. A series of plans makes it possible to track real changes in crops within a certain timeframe both for the entire field and individual plants.

Terrain Relief of the Fields

By using conventional cameras or laser rangefinders, drones can create 3D maps of the terrain, even if the soil on the field is densely covered by plants. The resulting terrain models clearly show all the hills and lowlands and the general land slopes of the field fragments. Such maps help to plan sowing and irrigation more efficiently as well as carry out anti-erosion measures in time.

Characteristics of Soil and Water Bodies

While focusing on how the plants look, farmers sometimes fail to track changes in their field. But orthophoto maps made up of images in different spectral bands can provide information that is invisible on regular images.


In contrast to a conventional camera or the human eye, a multispectral camera takes images in different spectra of light – particularly in the visible spectrum (RGB), infrared (NIR), near infra-red radiation edge, and each of the RGB channels (alternating). The latter is suitable for shooting objects made of different materials.


Thus, shooting in the green channel makes it possible to visualize vegetative plant activity and its growth dynamics. The red channel, above all, provides information about the soil condition. A blue channel provides valuable information about conditions at the bottom of reservoirs, artificial and natural ponds, and lakes.


Multispectral RGB data can also be visualized as combinations of strips of these three colors. Thus, you can see things that aren’t obvious: swampy soil, drainage problems, erosion, an outbreak of weeds, etc. These problems aren’t always visible during a pedestrian survey but often require a prompt solution.

State of the Livestock

Drones are excellent at observing living and moving objects. While searching for food, animals can go very far and even get lost in large, open pastures. Drones help control their movement, search for missing animals, assess green mass quality in the grazing area, and react to unforeseeable circumstances, such as injury or attempted theft, in time.

Plant Health and Maturity

Vegetation index maps tell us about plant health and maturity much more than simple photographs. Those are compiled based on data in various spectral bands. Each index has a color value corresponding to a certain norm. Anything that differs from the norm signifies a disease, drought, element deficiency, or poor plant growth – depending on which index is analyzed.


The main indices that can be used for UAV-based mapping are:

  • Normalized difference vegetation index (NDVI). It allows to measure plant photosynthetic activity and the relative volume of green biomass;
  • Normalized difference red edge index (NDRE). It is used to analyze high-density perennial crops;
  • Soil-adjusted vegetation index (SAVI). It allows to assess soil fertility;
  • Optimized soil adjusted vegetation index (OSAVI).


Let’s see how it works in a bit more detail.

How to Assess Plant Health by Its Color, and Why Satellite Data Is Not Enough?

The type of information a drone obtains can sometimes surprise even experienced farmers, who call it farming with a cheat sheet. That is because vegetation indices not only show if something is wrong with the plant but also accurately describe the problem: what exactly it’s lacking, what is in excess, and how serious the situation is.


Vegetation indices are based on the spectral reflectance of plants and soil. In simple terms, if we take pictures in different regions of the light spectrum and alternate and combine the data, we can have a fairly accurate assessment of the content of water, nitrogen, carbon, pigments, etc., in plants.


Healthy and unhealthy, mature and growing plants reflect light differently. The benefit of having vegetation index maps is that characteristics of development are noticeable in the early stages, unlike in ordinary images.

Let’s take chlorophyll as an example

Chlorophyll, the main compound in green plants, reflects green light well, so most plants look green to us. On the other hand, red light is absorbed by chlorophylls and used for photosynthesis. When the plant gets sick, it becomes worse at reflecting green light and absorbing red light. These changes are clearly visible when analyzing vegetation indices.


Index maps can be used throughout the season – they provide specific, relevant information at different times. For instance, in the beginning, you can see how the plants survived the winter and how they manage the shift to warmer conditions. In the middle of the season, index maps show how the crops are developing and whether there are enough moisture and essential elements for growth. At the end of the season, you can see which parts of the field are already ready for harvesting and where the crop is not ripe yet. Plant diseases and soil problems can be identified at all times.

Satellite Data Is Not Enough

A combination of data from drones and satellites gives the optimal effect for monitoring fields. There are projects that offer monitoring through satellite imagery alone. This approach is valid, but it has multiple restrictions and neglects important opportunities.


Satellite imagery is useful for working with very large fields as well as remote-controlled farms. But there are serious limitations: you are tied to the satellite schedule and may not be able to see the fields for months in cloudy weather. Plus, it is expensive and not always justifiably so.

UAV can be effective for surveying farms, vineyards, and orchards of any size. Drones operate at low altitudes, so the clouds won’t be a problem. You can determine the schedule and flight duration. If necessary, you can fly the UAV daily.


At the same time, data from satellites can provide a solid foundation for the following detailed survey of the field using drones. The quality of the survey varies dramatically, but satellite data is collected at regular intervals.


Combining data and trend extrapolation based on regular satellite data is a good all-around approach for smart farming.