In recent years, the adoption of digital technologies in precision agriculture has been adjusting the ways that farmers treat crops and manage fields. One doesn’t have to be an expert to see how the technology has changed the concept of smart farming making it more profitable, efficient, safer, and simple. Among other technologies, farmers have picked five they deem to be the best:
- GIS software and GPS agriculture
- Satellite imagery
- Drone and other aerial imagery
- Farming software and online data
- Merging datasets
As a result, modern farms get significant benefits from the ever-evolving digital agriculture. These benefits include reduced consumption of water, nutrients, and fertilizer, reduced negative impact on the surrounding ecosystem, reduced chemical runoff into local groundwater and rivers, better efficiency, reduced prices, and many more. Thereby, business becomes cost-effective, smart, and sustainable. Let’s discuss some of these agricultural technologies.
Since fields are location-based, GIS software becomes an incredibly useful tool in terms of precision farming. While using GIS software, farmers are able to map current and future changes in precipitation, temperature, crop yields, plant health, and so on. It also enables the use of GPS-based applications in-line with smart machinery to optimize fertilizer and pesticide application; given that farmers don’t have to treat the entire field, but only deal with certain areas, they are able to achieve conservation of money, effort, and time.
Another great benefit of GIS-based agriculture is the application of satellites and drones to collect valuable data on vegetation, soil conditions, weather, and terrain from a bird’s-eye view. Such data significantly improves the accuracy of decision-making.
Predicting yields, as well as conducting almost real-time field monitoring, with a view to detect a variety of threats with satellite data in service has never been so easy.
The sensors are able to give imagery in various spectra, allowing for the application of numerous spectral indices, such as the Normalized Difference Vegetation Index (NDVI). NDVI allows for the detection of vegetation content, the amount of wilting plants, and overall plant health. Next is the Canopy Chlorophyll Content Index (CCCI) that helps with nutrient application. Then, the Normalized Difference RedEdge (NDRE) detects Nitrogen content. And lastly, the Modified Soil-Adjusted Vegetation Index (MSAVI) is designed to minimize soil background impact at the earliest developmental stages of plants; the list goes on.
Data From The Sky – Drones
With the assistance of drones farmers have an opportunity to define crop biomass, plant height, the presence of weeds, and water saturation on certain field areas with high precision. They deliver better and more accurate data with higher resolution in comparison to satellites. When they are locally operated, they provide valuable information even faster than scouts. Drones are also considered to be unrivaled aides in the battle against insects; the invasion is prevented by applying the insecticide on the hazard areas using drones, all while reducing the likelihood of direct exposure leading to chemical poisoning.
Despite the fact that drones are easy to use and are capable of collecting large amounts of data within short time frames, there are still challenges when using them on a constant basis as they don’t come cheap. Drones are almost helpless where mapping or monitoring of large areas is required, and it is better to complement the technology with satellite monitoring among already mapped areas, where specific zones need to be cross-checked.
Online Data – The Key To Precision Farming
To assist farmers and other agronomists in crop production, EOSDA designed EOSDA Crop Monitoring – a digital satellite-based platform for monitoring crops and speeding up a farmer’s decision-making process.
Among the most useful features available on the platform, are:
- Normalized Difference Vegetation Index (NDVI) for tracking crop health. This index measures the density of vegetation in the field which strongly correlates with healthy crops at certain growth stages. Higher NDVI values mean healthier vegetation, but other indices and growth stages should be taken into account as well.
- Scouting. It is available as a mobile app synced with the platform that relies on digital field maps and GPS to guide scouts to problem areas in the field. Maps can be used even when the app is in the offline mode. While using this app, a farmer is able to assign multiple tasks to scouts in just a few clicks. Add a field, drop a pin, set a task. That’s all that it takes. Once the task is assigned, a scout moves directly to the selected location and checks the issue on the site, inspects pest activity, performs weed management activities etc., putting all the information obtained in the report generated in the app. This allows for the inspection of the problem areas only when needed, thereby saving ample time to take necessary preventative actions.
- Weather analytics. By analyzing weather data along with the data on crop health derived from satellite imagery analytics, farmers can more precisely apply irrigation and prevent frost or heat damage. For example, one of the best methods to avoid drought issues is drip irrigation with automatic or manual valve control, allowing the farmer to apply the required amount of water to the dry areas.
- Productivity and Vegetation maps. This feature helps farmers save money on fertilizers and reduce the negative impact of Nitrogen on the environment. By calculating the differences in productivity and vegetation state across the field, it is possible to apply seeds and fertilizers in a “differential” way. This variable-rate application is more efficient compared to the flate-rate one, taking into account the needs of different areas of the field. Maps are calculated and visualized as zones (hence, zoning) and can be used as instructions for the agricultural machinery. Precision agriculture in action!
Diverse Types of Data in One Place
The EOSDA Crop Monitoring platform integrates data obtained from multiple sources, including satellite-derived incides, weather data, information on field activities, and more. By having all this data neatly in one place, you can obtain more in-depth insights into the state of crops and how to take the best care of them.
For example, you can compare different vegetation indices of the same field with one another to get a more objective picture of the crop health at a given moment. The indices can be further compared to the history of temperatures and precipitation going back years, obtaining a better understanding of the field’s productivity variations over a long period of time.
The Findings On Precise Agriculture
Promising agricultural technologies are moving into the future by leaps and bounds. They offer substantial help for farmers in their endeavour for optimizing inputs, simplifying farm management, and increasing productivity. Increased yields, as well as reduced maintenance costs, help boost profit margins. In the context of smart solutions, precision agriculture offers a Swiss army knife of farming techniques for today’s, and tomorrow’s farmers.
Kateryna Sergieieva joined EOS Data Analytics in 2016. She has a Ph.D. in information technologies and a 15-year experience in remote sensing.
Kateryna is a Senior Scientist at EOSDA. Her specialty is the development of technologies for satellite monitoring of natural and artificial landscapes and surface feature change detection. Kateryna is an expert in the analysis of the state of mining areas, agricultural lands, water objects, and other features based on multi-layer spatial data.
Kateryna is an Associate Professor conducting research at the Dnipro University of Technology. She is the author of over 60 scientific papers.