
Drones Vs. Satellites For The Agri-Sector Use
Satellites and drones allow monitoring fields remotely and each data source has its specifics of use. By knowing the difference between them, it is possible to find the most cost-effective solution.
Satellites and drones allow monitoring fields remotely and each data source has its specifics of use. By knowing the difference between them, it is possible to find the most cost-effective solution.
EOS Data Analytics will host a free webinar to explain how it uses neural networks to transform satellite data into actionable insights for crop production and forestry. The event will take place on March 29, 4 pm GMT.
The improvement of satellite imagery quality and multipurpose usage of satellite data stimulated the Earth Observation market in 2021. EOSDA shared 2021 highlights and future plans.
Integration of vegetation indices into digital solutions for agriculture unlocks multiple opportunities for software providers, especially when satellite analytics custom solutions can be tailored to specific customer needs.
In 2021, there have been many natural disasters, most of them due to climate change. In the future, the situation will worsen unless we change production methods and improve the global environmental management system.
EOS Data Analytics, a global provider of AI-powered satellite imagery analytics, has signed an agreement with Dragonfly Aerospace that the latter will deliver the first satellite for the EOS SAT constellation in 2022.
EOS Data Analytics launches a platform for satellite monitoring of forest stands to provide stakeholders with sustainable forest management tools. Software will help track deforestation and detect fire hazards, save resources and preserve the environment.
Forest fires cause whopping losses globally every year and often start due to human-related ignition. Therefore, caution and wildfire prevention measures are important. Satellite monitoring helps notice and address the problem on time.
Clouds are often obstacles for optical NDVI, which negatively affect image quality and data analytics. Cloud-free NDVI helps resolve the problem as it uses radar-based imagery. This way it is possible to get accurate data even with cloud cover.
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