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March 30th, 2018
Pix4D is Announcing Pix4Dfields

To give you fast and accurate maps while in the field, with a simple yet powerful interface fully dedicated to agriculture. One product for all of your drone-based agricultural workflows.

“Our solution fits the needs of the agriculture industry and we believe Pix4Dfields will become a staple tool, just like a meter is for a construction site worker”, Christoph Strecha, Pix4D CEO

Agriculture is one of—if not the biggest industry in the world. There is no wonder why. Humans heavily depend on food as fuel to keep us going. The progress in this industry has gone beyond what we could have imagined, combining drones, sensors, machine learning, mathematical algorithms, and advanced analytics.

When we decided to create a product for agriculture, we wanted to go beyond the research and development and create a product that understands agriculture. So in July 2017, we opened a new office in Berlin fully dedicated to do exactly that: Understand the agriculture industry, listen to our users, and create a product that caters to all the main agricultural practices.

That’s why we are happy to announce Pix4Dfields today

Equipped with a new fast processing that provides accurate and instant results and an easy-to-use interface with tools tailored to agricultural workflows, our users will be set to cover everything from simple to complex scenarios.

 

 

Essentially, the idea behind Pix4Dfields comes from two observations:
the need to produce accurate, repeatable measurements of crop health and the need to produce results efficiently and rapidly in the field, while performing more detailed analysis in the office. Both of these factors are essential to support decision making of the farmer, agronomist or the breeder.

Pix4Dfields is currently available as a closed beta, which we are opening to select users to test it and give us feedback. The product will evolve in a fast pace with new and updated features being added with every new iteration.

Pix4Dfields is currently available for macOS only, next iterations will include Windows support as well.