Generating LiDAR DEMs from unclassified point clouds with:
MCC-LIDAR - Multiscale Curvature Classification (MCC) algorithm.
(supports LAS versions 1.1 to 1.3)
MCC-LIDAR is a command-line tool for processing discrete-return LIDAR data in forested environments (Evans & Hudak, 2007).
a) unclassified point cloud.
b) ground returns ...
To solve the problem one needs to transform 2D images of 3D structures from different angles/perspectives into a solid model. This was earlier a manual job, but software allows for automated processes.
Remember that processing software could provide both digital surface models (DSM) or digital elevation models (DEM)
Products from such processes can include ...
Yes you need to Georeference the images. The Exif data explains where the photo was taken, so it describes where your drone/camera was at that time and often many other values (heigth, bearing etc). QGIS and mapping packages work off a different method of locating the image and usually require a location of the center of the upper left pixel, knowledge of ...
I've done this before with success using the Photosynth Toolkit (http://www.visual-experiments.com/demos/photosynthtoolkit/), except instead of a drone I was hanging my head out of a small plane taking pictures of the downtown area of a small town. You could also check out Visual SFM (http://ccwu.me/vsfm/); I haven't used it but it seems to be another tool ...
I think that LasTools might suit your needs, see LASGround. The license is a bit funny depending on what tools. The tools can be downloaded and evaluated prior to purchase; also the product is relatively inexpensive.
If you want an absolute positioning of your images, you'll need control points.
If your drone is equipped with onbord GPS (which is now most of the time the case), then it is possible to estimate the absolute coordinate using a large number of overlapping images. However, I recommend that you collect at least a few ground control points to validate your ...
All of the specific answers I can come up with would have likely already occurred to you as a photographer. A low distortion lens with a shorter focal length (based on your prospective altitude). High shutter speed to minimize motion/vibration impacts. Interval and speed are something of a function of your flight plan and altitude - I don't know if there ...
For ground control, you're going to want something easily visible from your UAV. Temporary GCPs may be good enough for your purposes. Personally, I've used weighted plywood painted with an arrow in bright colors like yellow and red. The tip of the arrow gives you a precise location to both set your RTK unit over and visually identify when georeferencing ...
I have been using three different programs for that: AirPhotoSE, VSfm and OpenDroneMap. All of them are easy to work, specially if default values give good results for your pictures.
AirPhotoSE is the slowest one (it is an old project that it is not active yet), but it works well and gives good results, both for orthophotos and point-clouds (and even DSMs)...
I can confidently say yes. Add in some surveyed ground control points and you can easily get 10 cm positional accuracy.
So far there are two big players that I have been using pix4d is by far the best but it is the most expensive it is really good for editing mosaics. Actually pix4d now has apps to directly work with your phantom and even has a free ...
Give RAPID for DJI a try. It will geo-reference and process up to 100 images from any DJI sensor or drone for free. The results are WGS84 Lat/Lon GeoTIFF format digital elevation models, point clouds and orthomosaic maps.
Disclaimer: I wrote the software and dronemapper.com SaaS service. Thanks!
You can use GRASS GIS 6 for orthorectification of aerial photos (UAV should work the same). See for related instructions:
Orthorectification chapter from the GRASS GIS book
Here a "work in progress" answer...
We are currently developing bundle block adjustment support in the orthorectification chain of GRASS GIS 7. It will be usable for aerial photos and UAV imagery. A prototype will hopefully be available in early 2014. If you are interested and willing to test, please contact me directly. It is an enormous amount of work, so ...
I highly recommend Agisoft PhotoScan Pro. It costs about $3500, but they have an academic version for about $500. If you contact them they can set you up with a 30 day trial. It has a lot of options and export formats and is quite easy to pick up and get good results. They also have options for python scripting.
Another opensource ...
If you want any kind of accuracy you will need carefully surveyed points on the ground.
Even if the UAV has the best GPS available it is buffeted by air currents, thermals and so on, which will skew the camera. An unmeasurable tilt in the air can produce a large position error on the ground, rapidly increasing with altitude.
The city I lived in in the ...
The common definitions for these coefficients when using MODIS are: L=1, C1 = 6, C2 = 7.5. The C1 and C2 coefficients are aerosol resistance terms that rely on the blue band to partial out atmospheric influence in the red band. The gain is commonly defined as 2.5
So, here is the thing. One would not expect the same atmospheric influences in UAV imagery as ...
You can't unless you know the distance from the ground, and the pitch, roll, and yawl of the camera (in addition to the CCD size and camera lens info you have). Plus, the onboard drone GNSS may not give you sufficient precision and accuracy to determine those coordinates without some ground control anyway. Better would be to georeference your image to some ...
This can be done with a pdal filter using either Simple Morphological Filter (SMRF) or Progressive Morphological Filter (PMF) algorithms.
pdal ground --cell_size=5 --extract input.laz out-bare-earth.laz
Creates a bare earth compressed LAS file with a 5 ground unit cell size using PMF. (docs)
For more explanation see the Identifying ground returns ...
Delft University is doing a lot of research into CityGML, one of the upcoming standard formats for visualising 3D building information. They have a viewer and also this tool, to turn LIDAR info into CityGML.
So, opensource, and supports a standard. Double win: https://github.com/tudelft3d/3dfier
It is possible and actually in practice. For example, Owyhee Air Research conducts wildlife surveys using aircraft mounted Forward Looking Infrared (FLIR) Sensors. The following is a video link highlighting the capabilities of using FLIR for grouse surveys:
The screenshot shows a Sagegrouse lek filmed in 1080p from a fixed wing ...
TileMill from MapBox is designed to be code free as possible.
There are some impressive tiles in the gallery
There are 4 steps:
Style your data (time consuming)
Export Map (MBtiles, PNG, SVG)
If your question is how to stitch UAV jpgs together, here are some software options for mosaicing drone imagery
Open Drone Map (free, open source)
Pix4D (commercial, but there is a limited free version)
Agisoft Photoscan (commercial)
I would do it the following way:
create a new point feature (Layer -> New Shapefile Feature) with an attribute for the elevation (Type: Decimal number). Make sure your create the point feature in the same coordinate system as your DEM.
set the points where you want them (Toggle Editing)
install the plugin Point sampling tool (Plugins -> Manage and ...
I had a look at Sentinel imagery. The S2 images are too cloudy, as you can check here.
And with S1 there is an image on 27/8 (the day after the lightning) and another one with similar characteristics on 22/8 so I made the difference between both images but I could see nothing but speckle noise in the area.