boosting farming potential with satellite technologies
  • Agribusiness solutions

Harnessing The Power Of Space: Satellite Tech For Farming

On March 31, EOS Data Analytics participated in the Malaysian Agriculture virtual conference dedicated to emerging technologies and innovations in farming. The conference organized and hosted by REDtone Digital Berhad, an EOSDA strategic partner in the Southeast Asian region, received support from the Ministry of Agriculture and Food Industries, the Department of Agriculture, and the Malaysian Digital Economy Corporation.

Brijesh Thoppil, the Director of Strategic Partnerships at EOS Data Analytics, talked about the employment of remote sensing in agriculture and the benefits agriculture-engaged businesses can get using satellite-based technologies.

This article will share key takeaways from the conference covering the values of satellite-driven analytics combined with AI and Big Data for agricultural stakeholders. You can also watch an entire presentation via the link.

Digital Revolution In Agriculture

Agriculture, being perhaps one of the last industries undergoing a digital revolution, is expected to bring the world the most significant changes we’ve ever seen. The transformation’s goal is straightforward yet planetary-important — producing more food with less. This statement implies that modern farming aspires to reduce agricultural inputs and minimize harmful environmental impacts while increasing smallholding farmers’ productivity and profitability.

Precision agriculture techniques — such as weather modeling, variable rate seeding, and smart irrigation — strengthened by AI-powered satellite imagery analytics significantly facilitate farming operations and decision-making. Additionally, the development of cloud storage and mobile phone applications makes data easily accessible to farmers and agricultural stakeholders.

Satellite-driven farming technologies enable agriculture to withstand climate change and food insecurity induced by the ever-growing world population. Besides, agtech helps food supply chain companies get maximum output from their fields, predict yields, and plan production to meet the demand and ensure food security.

EOSDA has developed the EOSDA Crop Monitoring platform to ensure our partners and users can contribute to the mitigation of climate change and achieve food security goals while keeping up to sustainability principles.

Farming Challenges In The Developing And Developed Countries

Smallholding farmers are generally prudent when it comes to the adoption of modern technologies. Such a cautious approach is caused by little or no experience using agtech and a poor understanding of what precision agriculture tools may bring them. And the value is huge! The information retrieved from satellite imagery provides farmers with insights they can utilize for soil preparation, planting, crop growing, and harvesting. In the context of global warming reflected in unpredicted weather changes, it’s next to impossible for farmers to foresee, for example, heavy rainfall or cold spell and get prepared for these anomalies without accurate analytics.

Another challenge that agriculturalists often face is the nutrients deficiency impacting soil fertility. The amount of nitrogen, phosphorus, and potassium must be regularly monitored to ensure crops have enough nutrition. And here, we should also mind weeds that need to be controlled since they can absorb nutrients, overgrow, and smother crops.

In addition, there is an Internet connectivity issue in rural areas, which hampers or slows down the adoption of digital agriculture.

EOSDA Crop Monitoring

Performing fields analytics based on relevant satellite data to ensure effective decision-making!

Satellite Data Benefits: How EOSDA Monitors Farms From Space

In essence, our EOSDA Crop Monitoring platform is a combination of various data processed with AI algorithms and packed in an intuitive user interface. We leverage the imagery by Sentinel and Landsat satellites, collect agronomic parameters — soil moisture data, for example — from reliable public sources, and complement them with historical yield data, weather statistics, and information on soil types. Then, it’s the job of AI and machine learning models to transform the inputs into comprehensible analytics stored in the cloud. As a result, users can access a massive dataset and get insights into vegetation growth, field productivity, nitrogen concentration, water stress, and many more factors influencing crop development.

how EOSDA Crop Monitoring proceeds data
EOSDA Crop Monitoring data transformation flow.

EOSDA Crop Monitoring enables to:

  • Track crop state referring to vegetation indices;
  • Build field rating filtered fields by sowing date, crop type, or NDVI (Normalized Difference Vegetation Index) value;
  • Assess the weather risks by checking a 14-day weather forecast and historical analysis;
  • Plan seeds planting and fertilizing using VRA (Variable Rate Application) maps;
  • Organize scouting tasks indicating the GPS coordinates of the field;
  • Manage teams of employees, partners, and third parties, assigning roles for all participants.

Along with the out-of-the-box EOSDA Crop Monitoring platform, we offer custom solutions — crop classification, yield prediction, and harvest monitoring — to satisfy specific customer needs.

Crop classification provides crucial data on land use and crop rotation. We combine Sentinel-2 or any other high-resolution images and ground data, apply our neural networks to detect field boundaries, and classify different types of crops. This method allows us to identify land cover at the global or country level, recognize arable and non-arable land, and estimate actual acreage for each crop type at the country or region scale.

Yield prediction helps farmers and stakeholders estimate the projected crop amount within a growing season. We gather field information, including crop growth stage, temperature, precipitation, and soil type, and process these data with a special algorithm to forecast yields on a field, region, or country level. By employing AI and machine learning models, we achieved over 90% accuracy in our estimates.

Harvest monitoring and analyzing harvest dynamics during several seasons deliver quantitative information for future planning. We process radar and optical Sentinel-2 imagery and compile a technical report that contains essential statistics such as harvest dates, the acreage harvested on a specific date, and the total number of fields.

Using satellite data and multi-level algorithms, strengthened with the expertise of our R&D and Science unit, EOSDA is capable of delivering complex custom solutions. I would say that crop classification and yield prediction functionalities are the most frequently requested by our clients.

Given the feature-rich EOSDA Crop Monitoring functionality, the platform is helpful to customers from different industries.

Smallholding farmers and commercial growers will receive valuable insights to manage crop health, including the data on vegetation indices, field productivity, weather forecast and historical patterns, soil condition, and many more.

Supporting smallholding farmers and growers is the key to digital agriculture success. In the light of climate change and increasing food demand, agrarians need access to comprehensive data to make proper crop growing and field management decisions.

Government agencies can monitor large agricultural areas to gauge the effectiveness of sowing campaigns, control crop development, and quickly eliminate possible threats — pest infestations, water scarcity, weed spread, etc.

And finally, agri-oriented banks and other financial institutions will get an opportunity to evaluate a farm’s productivity based on historical data, predict potential yields, and grant a farmer a loan with the confidence they will pay it off.

Seeking to deliver high standards of products and services, EOSDA is currently working on EOS SAT, the first agriculture-oriented satellite constellation developed by the company employing remote sensing technologies. The constellation will consist of seven optical satellites to be delivered into low Earth orbit by 2024; the launch of the initial one is scheduled for 2022.

EOS SAT is the most anticipated project allowing us to become an independent satellite data provider. With the launch of our satellite constellation, we will cover the whole vertical from imagery acquisition to delivering our customers a ready-to-use solution packed in an intuitive user interface.

The EOSDA team genuinely believes that satellite imagery analytics holds the future of agriculture and is looking forward to introducing enhanced EOSDA Crop Monitoring solutions to millions of farmers.

About the author:

Natalia Borotkanych Project coordinator

Natalia Borotkanych has been working in the space sector for more than 15 years now. Her experience includes working in business, science, education, and government projects.

Natalia has a PhD in space history, Master’s Degree in Foreign Policy from the Diplomatic Academy of Ukraine, as well as Master’s Degree in Public Management and Administration from National Academy for Public Administration under the President of Ukraine.

Building upon her experience of working in the State Space Agency of Ukraine, Natalia now specializes in helping the state bodies and NGOs to implement the satellite monitoring technologies for solving real-world problems and for smart decision-making.

Natalia is an active science communicator. She is a scientific editor at The Universe. Space. Tech magazine. She also teaches a “Space diplomacy” course at the National Aviation University.

Natalia's experience in project coordination and scientific expertise in the space sector are much appreciated at EOS Data Analytics.

Recent articles

EOSDA Custom Neural Net: Deforestation Detection
  • EOSDA Forest Monitoring

EOSDA Custom Neural Net: Deforestation Detection

The Science team at EOS Data Analytics has developed a custom algorithm for intelligent detection and tracking of deforestation in tropical regions using LEO satellite images as a data source.

Slope Erosion: Underlying Factors And Control Methods
  • Soil

Slope Erosion: Underlying Factors And Control Methods

Slope erosion is a particularly difficult problem for farmers to deal with in hilly areas. Fortunately, there are now lots of options for preserving fertile hillside soil.

The Morning Star’s Gradient Implements Remote Sensing
  • Case study

The Morning Star’s Gradient Implements Remote Sensing

The Morning Star combines in-ground sensor data with satellite imagery analytics to ensure proper irrigation and increase tomato yields in California.