7, Jul 2025

The Use of Satellite Imagery in Agriculture: A New Era of Precision and Productivity

Satellite imagery gives farmers accurate, up-to-date information on crop health and field conditions. With this data, agriculture professionals can spot issues early, improve resource use, and achieve more consistent harvests.

Satellite Imagery in Agriculture

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ABOUT THE AUTHOR

Serhii Stavichenko, CTO

Serhii knows everything about project architecture, data science, and machine learning. His superpower is translating clients' business needs into top-notch technical solutions.

Traditional agriculture faces numerous challenges, including climate change and soil degradation. The increasing demand for food and inefficient resource use make human survival more difficult. That's why industry experts are seeking to raise productivity and improve decision-making. Digital transformation and the use of satellite imagery in agriculture help farmers monitor crop health and soil conditions. It enhances control over huge areas without the need for field visits. According to the forecast, the modern remote sensing technology market will reach 42.64 billion USD by 2030.

This article will review how satellite imagery changes traditional agriculture approaches and improves farmers' work. Here, you can find more information about satellite imagery types and their benefits. We will also examine modern use cases and real examples of companies actively applying remote sensing technology.

What Is Satellite Imagery for Agriculture?

Satellite imagery is a remote sensing technology used to gather information about the atmosphere, surface, and oceans. Sensors and cameras on satellites capture images from space. The received data is widely used for weather monitoring and tracking environmental changes. It enables the evaluation of natural disasters on the planet. The technology is quite handy for mapping and military purposes. But did you know how much it brings to the agriculture industry?

No matter how often the field visits are, farmers can still miss many things when checking the area with the naked eye, including the progression of disease or damage from pests. With spectral analysis, farmers will know about potential problems like chlorophyll degradation before the disease becomes visible.

What Is Satellite Imagery for Agriculture?

High-resolution images from the satellite enable more effective crop monitoring. Empowered with valuable information, farmers can analyze soil moisture and canopy density. It improves the identification of problems such as nutrient deficiency and water stress. Modern farmers can increase their yield and allocate available resources smartly with a technologically powered approach. For instance, agriculturists will be able to calculate the exact amount of water and fertilizers that are required, avoiding unnecessary spending.

What Are The Benefits of Satellite Imagery Agriculture Approach?

In our experience, there are three main benefits to consider when using satellite imagery: efficiency, sustainability, and enhanced decision-making.

Operational efficiency

Satellite imagery can significantly improve operational efficiency by tracking plant growth and soil health. For instance, farmers can apply the right amount of water and use pesticides only when necessary, minimizing guessing. By identifying problems early, agriculturists can avoid escalation and save costs.

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Environmental sustainability

Satellite data enables precision agriculture and helps ensure that fields receive the right input of all necessary elements, including water and nitrogen. It reduces negative environmental impact. With efficient operations and optimized machinery planning, farmers can lower gas emissions.

Data-driven decision-making

With advanced monitoring, agriculturists will always be informed about the state of the crop at every stage of the cycle. Artificial intelligence and predictive analytics can utilize historical data from satellites for better risk monitoring and accurate predictions of potential income. It enables smarter strategic planning and helps align production with current demand.

Benefits of Satellite Imagery for Agriculture

What Are the Different Types of Agriculture Satellite Imagery?

To clarify how exactly satellite imagery can help farmers, we will review its types and explain what information they collect. Knowing each one's main focus, you will be able to choose the most suitable combination for your business.

Multispectral

For multispectral imagery, satellites capture images within specific wavelength ranges of the electromagnetic spectrum and break light into 4 to 36 bands. Typically, it utilizes near-infrared and visible types (red, green, and blue). Landsat, Sentinel-2, PlanetScope, and many other satellites supply multispectral data vital for farmers.

For instance, vegetation monitoring (NDVI) enables plant health and biomass identification. Multispectral data helps to detect early signs of stress and pest infestation. This technology improves crop growth monitoring and allows agriculturists to identify problematic areas.

Multispectral

Hyperspectral

Like multispectral imaging, hyperspectral imaging also works with the light spectrum, breaking the light into hundreds of narrow bands. Hyperion and Prism collect data for hyperspectral imagery in visible and short-wave infrared ranges. It enables precise disease diagnosis based on changes in plant chemistry. Accurate spectral signatures can help identify nutrient levels and evaluate mineral composition. As a result, farmers have systems for early warning about soil issues and can fix the problem before it's too late.

Hyperspectral

Thermal

While multispectral and hyperspectral types capture light, the thermal imagery sensors detect infrared radiation. In simple words, it captures heat emitted from the surface. For instance, the Landsat 8 satellite can collect data with thermal infrared sensors. The objects on the ground emit heat and help evaluate temperature variations showing unhealthy crop states. With accurate calibration and removal of all unnecessary elements, the thermal imagery can provide advanced reports without data corruption.

Thermal

Each color demonstrates the specific range of temperatures; for example, yellow areas mean hotter regions, while purple areas mark cooler spaces.

Thermal imagery is an accurate tool for drought detection, as higher surface temperatures may signal water stress. With precise irrigation monitoring, farmers can identify uneven irrigation and detect broken systems as the water cools vegetation, and thermal sensors capture it.

Satellite Technology's Impact on Agriculture: Modern Use Cases

Now that we know what to expect from satellite technology, we can explore the real use cases and examples of companies that use satellite imagery. For now, we want to focus on four major applications impacting modern agriculture: precision farming, soil health mapping, CAP, and climate risk assessment.

Precision farming (satellite agriculture)

Precision farming is the concept of agricultural management based on measuring and reacting to satellite data. It heavily relies on specific equipment, IT, and software. While the traditional farming approach means the same level of treatment for the entire field, the precision one enables more accurate and efficient soil and crop management. For instance, with satellite crop monitoring, farmers can make decisions about each area and optimize water use, fertilizers, and other elements vital for the field's existence. It enables more attention to problematic areas and raises the quality of the entire yield.

For instance, AGRAIN utilizes remote sensing for Ukrainian field monitoring. It enables early warning about potential issues related to plant growth and soil conditions. With accurate data, the agricultural consulting company helps farmers detect insect risks and recommend efficient solutions before the situation escalates uncontrollably. Enhanced with mobile and browser versions, the platform boosts efficiency by 20-50%.

Midwest Wheat utilizes satellite analytics to detect poorly performing areas and adjust the irrigation strategy to be more efficient. Targeted adjustment enables a significant yield increase and helps to optimize harvest schedules.

Soil health mapping

Soil health mapping utilizes satellite imagery in combination with artificial intelligence and on-ground data to analyze soil. For instance, experts can access details about texture, moisture, nutrients, pH, and many other factors. It reduces the need for physical field visits and increases efficiency.

Perennial is an MRV company that provides crop measurements and has created a digital soil mapping solution for emission and carbon removal control. It enables accurate crop and geography measurements without physical soil sampling and farmer data. The company utilizes mapping to provide insights into soil state and productivity, considering the risk of degradation.

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CAP

CAP, or Common Agricultural Policy, was created to support farmers and improve productivity in the agricultural industry. Its main goal is to provide a stable food supply and economy by promoting farming and related sectors. With satellite monitoring, verifying what farmers do on their land is easier, such as whether the plants match those declared.

As an example of real-world use, you can refer to the European countries where the Area Monitoring System has become mandatory for policy performance assurance. With accurate satellite data, EU farms can undergo automated compliance checks for receiving subsidies. The AMS analyzes the data received from the Sentinel satellite and provides insights into agricultural activities in the specific area automatically via set algorithms.

Climate risk assessment

Climate changes like drought and floods can seriously impact the agricultural industry, reducing farmers' productivity and causing damage to soil and water systems. Satellites provide accurate real-time data for climate risk evaluation. It can help anticipate problems and adapt faster to potential impacts. Climate risk monitoring enhanced with satellite information will be a valuable data source for farmers, governmental organizations, and insurers.

Fancampo Mexico applies remote sensing monitoring for crop insurance. The company utilizes innovative technologies and satellite data to create risk management strategies considering variable factors, including climate change. The company started with NDVI and expanded crop analytics with more tools. If an accident may impact crop health and cause damage to the field, the company's agronomists utilize data from the satellite to analyze the impacted property.

What Are the Limitations of Satellite Imagery in Agriculture?

As you can see, satellite imagery can be a game-changer for farmers' work. Still, it is better to know your challenges and limitations before implementing the new technology. In our experience, there are two main reasons for issues: technical and human factors.

Challenges of Satellite Imagery in Agriculture

Technical issues

Clouds

Cloud cover seems harmless from the solid ground, but satellite capture can be problematic, as sensors do not see through clouds. Clouds can affect the collected data and reduce the report's accuracy. To handle this problem, cloud masking technology is applied, as it detects and filters cloud-covered zones to reduce the loss of accuracy.

Resolution

Resolution is everything for monitoring results, but reaching high-resolution imagery on small farms is difficult. Analyzing narrow irrigation channels and specific diseases on small or fragmented fields would be challenging. High-resolution imagery is also quite expensive, and the pricing can be unaffordable for small organizations.

Satellite revisits also play a key role in monitoring, as even the highest resolution may not help if the satellite has a view of the field every several days (Landsat and Sentinel-2), while the disease can affect the crops within shorter terms.

To exclude the issue of temporal resolution, agricultural companies can also work with several satellites with different revisit times to cover the gaps or choose the satellite with a daily repetition of the cycle (PlanetScope, Planet SkySat). Pleiades Neo, for instance, repeats the cycle 40 minutes after the request. Artificial intelligence can also predict changes in crop conditions between image captures based on historical patterns and weather data.

Integration issues

Agriculturists may struggle to connect satellite insights with farm technologies and decision-making applications. For instance, it can be challenging to integrate NDVI into old-fashioned machine software. Small farms may use different formats and data models, raising the difficulty of integrating technology into daily farm workflows.

Human factor

Lack of expertise and knowledge

Satellite imagery integration into existing workflows is a complex process, and to make it right, you need the help of an expert team. Working with an experienced service provider raises the chances that the farm will get the right software and equipment for specific purposes. For instance, Requestum works with various industries to find the perfect solutions for customers' needs, and our experience enables professional recommendations for tool selection and app function choice.

Not all farmers and agronomists are trained to interpret satellite data and utilize the required tools. Misinterpretation can cause more trouble than help, worsening situations in the field. Additional training or extra staff may fix the problem and make the use of new tools more productive.

Limited adoption

Farmers heavily rely on personal experience and time-proven solutions. Although this is a good tendency, it can also limit the adoption of new technology and raise resistance to change, slowing down innovation acceptance. Also, real-time data technology would be difficult for farms with limited internet access, and a stable connection is needed for prompt reports.

What Is The Future of Satellite-Driven Farming?

At Requestum, we believe further development of satellite technologies will encourage agriculturists to adopt them more actively. Farmers will always be aware of potential risks with a data-driven approach and can adapt strategies to minimize issues and raise productivity and outcomes.

Future of Satellite-Driven Farming

Expansion of artificial intelligence and machine learning

Artificial intelligence and machine learning have become integral parts of workflows in various industries thanks to their ability to reduce human effort and maximize results. Automated algorithms can detect early signs of plant stress and potential diseases, informing farmers immediately. They can control pest movements and react to irrigation issues automatically, changing schedules or sending notifications to the responsible staff.

Growth of small satellite networks and access to near-real-time imagery

While traditional satellites are huge constructions, small ones can become more cost-effective and scalable solutions with high-frequency monitoring capabilities. Combined with AI and ML, they will improve automated anomaly detection and enable real-time warnings for critical situations. We suppose they will launch much faster and can increase the amount of sensor data received. Farmers can react to potential threats faster thanks to more frequent field revisiting.

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Wider adoption among small and mid-sized farms

For now, it is more difficult for smaller farms to adopt satellite imagery due to the resolution issue. However, we believe technology will continuously develop and become more accessible to mid-sized and small areas. Once the possibility of monitoring the field is enhanced with better resolution, the developing regions can utilize the advantages of satellite imagery. With more affordable and localized tools with mobile and browser access, satellite imagery will become more available for smallholders.

Conclusion

Using satellite imagery in agriculture widens the possibilities for farmers and improves their control over situations in the fields. With accurate data from multispectral and thermal sensors, agriculturists know potential risks related to soil health and crop state and can mitigate issues before they escalate. Farmers can analyze satellite data more effectively with an AI-powered approach and adjust their strategy to improve potential outcomes. It enables a stable food supply and reduces the cost related to water and fertilizer use. Healthy soil with the right amount of irrigation increases the yield.

If you need a solution for satellite imagery monitoring, contact us. Requestum will be glad to develop a high-tech agricultural application for your business to give you full control over field safety and crop growth.

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