Webinar: March 9th 2021 at 4pm CET

The Future of Farming: Drive crop and business growth with satellite imagery, weather data, and deep learning

Learn about intelligent industrial agriculture

Industrial agricultural methods coupled with geospatial insights are enabling huge strides forward in terms of crop productivity and yield consistency, the optimization of scarce and expensive resources, and the effects of large-scale farming on the natural landscape.

This webinar will provide a technical overview of the most cutting-edge geospatial technologies centered around agricultural efficiency and tap into the latest trends in optical and radar imagery, weather data, and deep learning algorithms.

March 9th 2021 at 4pm CET

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Get a blueprint

Get a blueprint

Learn how to build your own geospatial agriculture products directly from industry-leading developers.

Gain a competitive advantage

Gain a competitive advantage

Enhance traditional agricultural indices analysis with weather data, machine learning, and more.

Receive deep, technical insights

Receive deep, technical insights

Learn about the entire geospatial solution development process, from data access to algorithm development and deployment.


Building powerful agricultural analysis workflows using Earth imagery

Shawn Melamed, Product Marketing Manager at CATALYST

In this webinar, we will present an approach to quantify historical crop performance by using reliable vegetation indices created from a stack of harmonized SPOT-1 to SPOT-7 imagery, dating back to the early 1990s. There are many vegetation indices used today to measure the performance of crops (e.g. health and density) at a given point in time. However, by analyzing these performance metrics in a timeseries, and comparing them to historical outcome information, such as actual yield, we can unlock valuable predictive modeling capabilities.

An important prerequisite for timeseries analysis and predictive modeling is using accurate and normalized measurements. We will leverage CATALYST’s automated Analysis Ready Data (ARD) workflow to create vegetation indices from surface nbar measurements allowing us to compare the data from the different SPOT sensors across time.


Learn how Meteomatics' weather forecasts and satellite data provide detailed weather insights to AgriTech businesses

Larissa Ott, Meteorologist at Meteomatics

Many agriculture businesses recognize the impact of weather on their activities, although the information they currently use can include limited detail on the local topography and the grounds hydrological behaviour, impacting the accuracy of the forecast.

Our presentation will give attendees an overview of how to request detailed and accurate forecasts, and how they can be used alongside satellite data to give insight into agricultural needs. After the presentation users will have a clear understanding of how to make similar queries and they understand the value it can bring to the AgriTech industry.


Why detecting the world’s most accurate field boundaries using satellite data and deep learning is important to the future of agriculture

Nils Helset, Co-founder & CEO at DigiFarm

All precision agriculture services start with accurate field boundaries and seeded acres. Unfortunately, we’re making critical decisions based on inaccurate data which is affecting the entire agricultural value chain from pre-production to retailers. Large scale boundary data is managed through cadastral maps and national agencies: LIPS in CAP (EU) and CLU’s in the US, however, as boundaries and seeded acres change continuously, this existing map data becomes unreliable and inaccurate.

Understanding how deep neural network models are able automatically detect field boundaries and seeded acres better than the human eye, worldwide, is the key for creating a solid foundation on which we can help farmers optimize their production.