New Technologies in Agriculture and How They Help Farmers

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Agriculture is gradually becoming technologically advanced. Machinery is automated, seed and fertilizer rates can be calculated automatically, and satellite images are used to determine plant conditions. Here's how new technologies work in agriculture.
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Satellite images and agriculture

Background: The first satellite was launched into space back in 1957. In the 1970s, satellites started being used for agricultural needs. That's when scientists calculated the NDVI index that helps farmers understand what's happening with plants in their fields. But 50 years ago, the NDVI index couldn't be used to its full potential. Image accuracy was about 50 meters, and NDVI couldn't be calculated in cloudy weather.

The next breakthrough in satellite use for farmers came in 2015, when a satellite with a spatial resolution of 10 meters became available. Firstly, this new resolution provides a clear picture of what's really happening in different areas of a field. Secondly, with the invention of smartphones and apps for farmers, technology became more affordable, allowing any farmer in the world to monitor the NDVI index in their fields. However, image quality still suffers during cloudy weather, and there's no solution for this yet that works everywhere on earth.

Benefits: Satellite monitoring makes it possible to remotely monitor plant development using NDVI, CCCI, NDRE, MSAVI, and other vegetation indices, find problem areas in the field, identify crops, and predict yield.

What we do: We collect open data from the Sentinel-2 satellite, process it, calculate various indicators, and display them in the OneSoil app. This helps farmers outline field boundaries, view the NDVI index, identify productivity zones, and create maps for variable-rate seeding and fertilizer application. In addition, we're developing Cloud-Free NDVI technology to display NDVI even in cloudy weather. This feature is already available in Argentina.
NDVI map of a field calculated using a satellite image

Aerial photography and drones

Background: Small drones appeared in the 1980s and were first used for military purposes. When these devices became more affordable, they started to be used in agriculture, as well. In the late 1990s, Japan and South Korea began to use drones to survey fields and spray fertilizers and plant protection products (PPP).

Benefits: Drones take high-resolution images that need to be merged into a single orthophoto, or photographic map of the area that has been geometrically corrected to make the scale uniform. Drone photography helps detect weeds, pests, and soil changes, determine plant height, and generally assess plant health.

What we do: We used to use drone images to determine relief, identify field boundaries, and analyze plant conditions after wintering and during the season. The disadvantage of drone images is that they can't be scaled to the entire world. That's why we don't use this method anymore and prefer satellite images instead.
Команда OneSoil в поле_Блог OneSoil
The OneSoil team. Photo from our Instagram:

Weather sensors and IoT

Background: The first agricultural weather sensors were developed in the 1970s. Today, modern sensors are installed directly in fields and controlled via mobile apps. Weather sensor networks sometimes function on the Internet of Things (IoT), which means other devices can perform certain automated actions by receiving data from the sensors.

Benefits: Measuring everything that can be measured in the soil and air. Location sensors can determine the latitude, longitude, and altitude of any object in a field using GPS. Optical sensors measure soil properties by light. They're mounted on satellites or drones and calculate the soil's clay, organic matter, and moisture content. Electrochemical sensors detect certain ions in the soil and provide farmers with pH and nutrient levels. And the list goes on.

What we do: To monitor soil moisture and temperature, we make weather sensors. They help monitor soil conditions in different field areas, optimize irrigation schedules, and determine the best time to plant and apply fertilizers.
Беспроводной метеодатчик OneSoil в поле_Блог OneSoil
A OneSoil weather sensor in the field


Background: Geographical information systems can be traced back to 1854, when Dr. John Snow identified the source of a cholera outbreak in London. He took a city map and marked the home of each patient and the nearest sources of water, which turned out to be the cause of the cholera outbreak. The first real GIS was developed in Canada and used for rural areas to map data on soils, farms, wildlife, and recreational areas.

GPS is a global navigation satellite system that can do three basic things: determine absolute location, calculate relative motion, and transmit time data to a GPS receiver. Originally a military project, GPS is now constantly in use in all walks of life.

Benefits: GIS programs can be used to create field maps. For example, they're used in soil analysis to select the right points for taking samples. GPS is used in agricultural machinery. You can choose the best route for several tractors and combines, or correctly configure autopilot. Onboard computers and GPS navigators help avoid overlapping and skipping areas when applying seeds, fertilizers, and PPP.

What we do: GIS and GPS are often used together in precision farming. We use GIS analytics to identify productivity zones in fields and allocate areas for variable-rate seed, fertilizer, and PPP applications. Then we create a prescription map and upload it to the onboard computer of the vehicle that will apply seeds or fertilizers to certain areas of the field using GPS. What's more, when a farmer leaves a note in the OneSoil app during field scouting, the GPS positioning data is automatically saved for the note. The same GPS data can then be used to easily find the same spot in the field.
A satellite image in GIS software
An image processed with OneSoil's algorithms. Fields with standard NDVI values
The same image with Contrasted NDVI values

Illustrations by Dasha Sazanovich
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