thanks! and new forest ecology paper using Map Pilot for iOS

Hi Zane, the Map Pilot team, and fellow Map Pilot users,

I want to share some new forest ecology work of ours that was just published that relied heavily on drone methodology. We used structure from motion photogrammetry from over 400,000 photos to map, measure, and classify trees in California after a mass tree die-off to investigate some of the most likely factors explaining the spatial patterns of tree mortality rates.

We conducted these flights back in 2018, and the *only* way we were able to do so safely and confidently in the hilly, forested terrain was by relying on your flight software. After several false starts with other flight software, I still remember being overjoyed at watching my aircraft successfully climb and navigate the terrain the first time I used Map Pilot!

Here's the paper: https://www.nature.com/articles/s41467-020-20455-y

We also released all of our data (including original images) from the RGB camera (DJI Zenmuse X3) and the Multispectral camera (Micasense Rededge3) in case that's useful: https://osf.io/3cwf9/files/ (see the data organization scheme as Figure 4 in the paper linked above, or as the ASCII tree on the GitHub repository readme (https://github.com/mikoontz/local-structure-wpb-severity).

I wanted to thank you all in particular for your willingness to adopt several feature requests/bug fixes that we corresponded about as I was doing this project. From our Acknowledgements section: "We gratefully acknowledge the Map Pilot for iOS team (who implemented several feature requests that helped us conduct our drone flights), Pix4D (which provided free cloud infrastructure for much of the Structure from Motion photogrammetry processing), and the Open Science Framework (who facilitated the public access to our complete dataset)."

Thank you!