Drones, aerial imagery, 3D models and VR.

I've been working a lot with drones and aerial imagery recently, and have been really enjoying myself. I'll be writing about a specific project I'm currently undertaking in another blog post, which will include pictures and 3D models. In this post, however, I wanted to jot down a few of the things that are possible with a cheap source of high-quality aerial imagery.

Satellite imagery is amazing; I have made use of it extensively in the past, and continue to do so today. For most applications, the only technical requirements needed to access and use satellite imagery are a good internet connection and a decent computing device.* Satellite imagery has its limitations though; between cheap, timely and high quality, you'll be lucky to get two out of three. This isn't necessarily a problem if you want to understand the movement of glaciers or look at how wetlands have vanished in a region. However, if you want high-quality data depicting a post-disaster site today to help plan humanitarian interventions tomorrow, you may have access to all the satellite imagery in the world but it isn't of much use if there are clouds covering the site.**

There are  applications that satellite imagery isn't suitable for; mapping small areas at a very high resolution, at a chosen time, is a task that drones are far better suited to.*** When I first started using drones, this was what I first thought of drones as: another source of aerial imagery with both advantages and disadvantages. However, prolonged use, lots of reading and lots of tinkering with various photogrammetry software packages has also made me aware of how much more than that they can be.

Drones aren't just flying toys; they're robots. They can be programmed to fly specific patterns while collecting data at specific points. In the case of imagery, which is the application I'm limiting this post to, mobile-based software tools such as DroneDeploy and Pix4Dcapture can make a drone collect imagery automatically over a large area. With a large number of images covering the same area, it's possible to create a very accurate 3D model with 1cm/pixel resolution or better.

For me, this is truly where it gets interesting. With this 3D model, it's possible to undertake formerly-laborious tasks, such as quantifying the biomass in a stand of trees, very easily; 3D models are great for volumetric analysis. It's also possible to use a 3D printer or CNC router to create a physical model, which would make a great art piece or communication tool. Finally, it's possible to use the 3D model as a basemap for a virtual reality experience set within the landscape. In combination with data on the local biodiversity, this could result in amazing products for conservation outreach and research.

*One of the reasons that led me into spatial analysis was that Landsat data became free to use in 2007, right when I was first learning how to use GIS.

** Another issue with satellite imagery used to be overpass times; no matter how large your budget for satellite imagery was, it was still possible that no satellite was in the right position to collect the imagery you wanted. That's rapidly changing; satellite imagery providers such as Planet state that their goal is to have enough satellites in orbit to image the Earth's entire surface once a day.

*** There's a lot of discussion about appropriate nomenclature; do we call them UAVs or drones? My take is that if it's a technical piece where the distinction between robots of various kinds (UAVs, UCAVs, AUVs, ROVs, UGVs) etc is important, then I use the acronyms; if it's just a placeholder for 'flying-robot-without-a-person-inside', I'm going to call it a drone.