EOS Data Analytics provides innovation-driven tech solutions to boost sustainable agriculture
(Photo : EOS Data Analytics provides innovation-driven tech solutions to boost sustainable agriculture)

Agriculture has undergone significant changes during the last decades. Advanced machinery, fertilizers, and irrigation help growers achieve higher than ever before yields. Yet real game-changing transformations are happening today. The emergence of remote sensing, artificial intelligence, machine learning, and smart sensors gives farming unprecedented opportunities to improve productivity and increase yields. 

However, the expectations for agriculture are also high. In the light of the augmenting food demand induced by the growth in population that is projected to reach 9.7 billion people in thirty years, agriculture must figure out how to feed the world. One more tall order concerns water resources. Scientists say that the water supply will decrease by 40% in the next 5-7 years, posing a serious threat to farming in arid regions where droughts are getting more frequent and severe. And finally, agriculture-engaged businesses should revise their methods, shifting toward sustainable agriculture practices to preserve the environment. Growers are challenged to produce more output with limited water consumption and fewer chemicals and carbon dioxide emissions. And this is where technologies can help!

"Agriculture is one of the last industries adopting digital technologies, mainly due to the long-standing traditional practices rooted in the past. But, at the same time, it has the huge potential to bring the world the most impressive changes impacting the lives of millions," says Brijesh Thoppil, Director of Strategic Partnerships at EOS Data Analytics.

Among the other precision agriculture tools, satellite monitoring plays the first fiddle. Powered by AI and machine learning, satellite imagery provides valuable insights into weather patterns, field productivity, and vegetation state, allowing agrarians to make informed decisions. In a broad sense, satellite-based technologies help agriculture combat climate change and food shortage through a rational approach to fertilization, irrigation, and sowing. Agritech does its bit to ensure food security while reducing environmental impact by giving necessary data to adjust crop growing strategy and predict yields.

EOS Data Analytics, a global provider of AI-powered satellite imagery analytics, has developed the EOS Crop Monitoring platform to streamline farm operations on the one hand and contribute to sustainable development and the mitigation of climate change on the other.

(EOSDA helps businesses boost profitability while being sustainable Video: EOS Data Analytics)

EOS Crop Monitoring platform encompasses miscellaneous data derived from high-quality satellite imagery and processed with mathematical algorithms. 

To deliver customers insightful analytics, the EOSDA R&D team combines agronomic data from verified open sources and information on the weather, field productivity, and soil condition extracted from satellite imagery. The collected data is processed with AI and machine learning models turning them into easy-to-use analytics covering crop growth, weather history and forecasts, soil and root moisture, and vegetation and productivity maps for rational fertilizers application.

(Benefits of using satellite-powered crop monitoring platforms Image: EOS Data Analytics)

With the help of out-of-the-box EOS Crop Monitoring, customers can:

  • Control crop development at different growth stages using vegetation indices;

  • Plan field activities, referring to a 14-day weather forecast and historical data;

  • Optimize fertilizer application using VRA (Variable Rate Application) maps;

  • Arrange scouting tasks to inspect certain field areas;

  • Customize the field leaderboard to catch critical information at a glance.

Besides the predetermined EOS Crop Monitoring solution, EOSDA carries out custom projects - crop classification, yield prediction, and harvest monitoring.

Along with combining satellite images and ground information, the EOSDA team trains neural networks to identify field boundaries and classify crop types. Also, applying this approach helps recognize land cover, detect arable lands, and estimate the area a particular crop takes. The project can be realized for a specified region or a whole country.

Moreover, EOSDA data scientists and engineers developed effective techniques for crop yield prediction utilizing remote sensing technologies and machine learning models. The algorithms analyze crop growth, soil type, temperature, precipitation, and moisture and process the data to project field, region, and country yields. Depending on statistics quality, forecast accuracy can vary from 85% to 95%. 

What's more, EOSDA delivers a range of harvest monitoring and measurement services that assist in streamlining harvesting operations and yield planning. Based on the statistics - harvest dates, area, and the number of fields - farmers can adjust fertilizer applications and sowing dynamics and schedule future crop production.   

"We have proven over the years experience in developing analytics products for the agricultural industry. Leveraging satellite imagery, AI, and machine learning, our R&D team creates solutions to meet even the most complex customer needs," adds Brijesh Thoppil, Director of Strategic Partnerships at EOS Data Analytics.

In 2022, EOSDA will launch the first satellite into low Earth orbit under the EOS SAT project, the world's first agri-focused satellite constellation among companies utilizing remote sensing technologies. The company aims to use received data to refine its tech solutions that can be applied in many agriculture-engaged businesses.

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