Here are some quick results from the drone camera tests we did two days ago. We flow four different cameras under similar conditions. The data set should ideally be used buy a student to do some project and a deeper evaluation of the cameras. But as we know that many in the forest industri are thinking about the difference between the Dji Phantom 4pro camera with a global shutter and a larger sensor compared to the Dji Mavic pro which is smaller, cheeper and has a, for photogrammetry, poorer camera.
The drones (and cameras) was flown in the evening with low sun behind thin clouds, generating no shadows but also not bright light. This lighting condition should push the cameras a bit and at the same time give less problem with bright sunlit tree crowns against a dark shadowed ground.
A orthophoto was made in Pix4D cloud service using default settings. Here are the results:
The Phantom 4 pro camera (on the left) has a higher dynamic range in the spectral resolution and is also less over exposed on the road compared with the Mavic pro (right image).
For the final test the Sony a5100 and the Parrot sequoia needs to be added and the images needs to be compared in more depth as well as their performance when generating point clouds.
We decided to take our drones to the forest and test some cameras today. We flow two 3DR Solo; one with Parrot Sequoia and one with a new Escadrone SoloMapper (Sony QX1 camera) and two DJI drones; one Phantom 4 pro and one Mavic pro. This was done because we had a great opportunity to acquire data from four forest patches that has just been scanned with a good terrestrial laser scanner. The scans was multi-scans with 16 scans in a 8 x 2 grid. The point cloud from the laser could be used for evaluating the point clouds generated from the drone cameras.
We tried to fly slow (5 m/s) and with lots of overlap (90/90). Sadly we ran in to trouble with the new SoloMapper, it did not acquire more then 15 images and then the system stopped. This was the first time ever we tested the camera system on the drone so it was probably a installation error of ours. We switch camera to a Sony a5100 that we have used before but which doesn’t have a gimbal, so we got good quality images.
This data set, with four different cameras, would be perfect for some student to use for a project or thesis.
The scientists at the Ljungberg Lab at the Swedish University of agricultural Sciences in Umeå went for a two day field excursion to test thermal cameras and new drones. Joining the students at the Fire Management course at the Forest faculty, who were going to make a prescribed burning of a 20 ha clear-cut. We wanted to test our new Solo helicopter drone from 3Drobotics and to capture thermal video and images from our Flir Vue camera. We also wanted to test the thermal camera in our fixed wing Smartplane drone.
We started by capturing RGB images from 200 meters above ground with the Smartplane before the fire was started. From this imagery we created a 7 cm Ground Sampling Distance (GSD) orthorectified image mosaic. Which could be used for describing the pre-fire state of the area.
Under the duration of the controlled burning we flew the thermal camera multiple times, with the purpose of acquiring aerial thermal and visual (RGB) images to describe the burn process and to test the usefulness of having a thermal camera to find hotspots or ground fire hours after the fire front have passed an area.
This will be evaluated later, when all data sets had been processed to orthorectified imagery and also to 3D point clouds.
On Thursday (21st April), Heather Reese, Head of Remote sensing division at SLU in Umeå, will give a seminar about “Removing the topographic effect from satellite data with the new 2m DEM”. It is scheduled to 14:30 in Ljungbergslaboratoriet (1st floor in the SLU building).
Today, the teachers and students of the Ljungberg lab, went to SLU’s new forest estate in Innertavle, close to Umeå. This forest is going to be used for teaching and research purposes. Our aim was to map it with a drone to get a high resolution orthophoto map and 3D data before the winter comes.
Mattias is fixing with the drone to get us in the air (in the background students making fire).
We sprayed red crosses, which are used for ground control points (GCP) to reference the images into the national coordinate system. These where to be positioned after the drone flight using a survey grade RTK-GNSS.
Unfortunately the winter came during the drone flight! Making it a very hard job to find the GCPs both when trying to position them and in the images when doing the image processing.
But we got some result! Here is a low resolution (GSD 29 cm) orthophoto of the eastern half of the estate (click image for full size). The final products will have better geometry and resolution.
Thanks to the students who brought BBQ lunch for us all!