Announcing support for MicaSense Altum and Thermal Imagery

With the release of the new 3-in-1 sensor Altum from MicaSense, we are excited to announce the latest updates in Solvi that add support for its high-resolution imagery and additional new layer for visualization of thermal data.

With the variety of RGB and multispectral sensors available on the market, our goal has always been to support imagery from as many sensors as possible, so that our customers can have the flexibility to analyze imagery that suits best their need

MicaSense is one of the leading providers of high-quality multispectral sensors used by farmers, agronomists, and researchers all over the world. Their latest addition Altum features high spatial resolution across 5 multispectral narrow bands as well as the new thermal sensor, all in a single compact device.

New thermal layer visualisation

The new Altum features a thermal layer which can help reveal differences in crop temperature. To make full use of this new source of data we have added a new Thermal-layer to our Analytics toolbox with the color scheme that makes it easier to see variations. Similar to our tools for vegetation indices, histogram acts as a legend for the thermal map and allows to adjust threshold values to help bring out the differences in temperature in various parts of the field.

Plant counts with high-resolution multispectral imagery

Another new feature in Altum is high spatial resolution across all 5 bands — 4 cm/px GSD at 120m altitude. This makes it possible to use imagery even for applications like plant counts that require very high level of detail. With imagery collected at lower altitude, even smaller plants like vegetables or corn can be clearly visible and our plant counting algorithms will be able to identify and count them. We have done several tests with plant counts on imagery from Altum and have seen great results with it. Below is an example of a pumpkin field flown at 100m altitude. Red dots show where our algorithms found the plants — even the smallest ones have been identified and counted!

Automated processing with calibration

One of the features that our users came to appreciate is the ease of processing of multispectral data in Solvi. Be it from the popular sensors like MicaSense RedEdge or Parrot Sequoia, all you need to do is to upload imagery from all bands along with shots of calibration target. Once uploaded, the imagery will be aligned and processed together, reflectance panels will be automatically identified and used for calibration so that the final orthomosaics reflect accurate measurements and can be compared over time.

With MicaSense Altum, we’ve made sure that this whole process still remains as easy. Now imagery from all 6 sensors can be uploaded together and will be aligned and calibrated during the processing resulting in a single orthomosaic with 6 different bands — Blue, Green, Red, Red edge, Near-infrared and the new thermal band. For the visualisation purposes we will automatically generate a composite RGB-orthomosaic. This rich set of data makes it possible to use a wide range of different vegetation indices and help extract even more useful insights about the crops — all from a single flight.

We are really excited to add support for this new high-quality multispectral data and the new visualization for thermal imagery! To showcase various use cases, we have set up datasets with crops like corn, alfalfa, and pumpkins that you can view at https://solvi.ag/showcase/micasense

Feel free to explore them in detail or process your own data and let us know what you think!