Our team at Agrolytic spent the 2014 growing season in the fields, working with growers, and flying UAVs with different sensors. Our single goal was to create a practical, online service that empowers growers to benefit from the latest in sensor and big data processing technologies, but without the technical complexity of data processing and infrastructure.

We are pleased to offer free 2015 beta accounts on our data processing platform for UAV operators and growers in order to perform extended trials, work closely with the UAV and agriculture community to create new and useful insights, and expand our features.  Our system is uniquely designed as a platform for scientists to easily develop new environmental analyses on top of a variety of input data types, so if you're flying a sensor we don't support or need an analysis our system doesn't yet offer, simply let us know, and we'll work quickly to support it.

See more at http://www.agrolytic.com or contact kyle@agrolytic.com

About Us:

Our team at Agrolytic combines expertise in scientific environmental modeling and remote sensing with expertise developing large-scale, commercial-grade cloud data processing solutions.


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  • Yes, thank's

  • Hey Cala!  Since most commonly we see people out flying infrared cameras, we currently support a biomass/leaf area view and a vegetation health view.  The examples you see in our video are from our vineyard flights last summer. We did five flights over the entire summer, so the five results for each analysis type are shown side by side. You can see us switching between views of veg health and biomass.  We also ran thermal flights last year but are looking to see how much of the community is flying thermal and what sensors they're using before building that support into the system.  Our system doesn't just calculate NDVI and display it.  Rather, we want each analysis to say something specific about the field conditions that a grower can quickly incorporate into his/her decision making.  For example, our system is aware of the common NDVI ranges for different plant types, and this enables us to present a view of relative health for that crop type.  It can also assist in weed quantification by segmenting the known crop signature from non-crop signatures and quantifying the two clusters.  Does this help?

  • Interest proyect Kyle, can you share some examples you can do?

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