For download, use the Download Request form below, but perhaps you may first consier to make a donation that will enable us to continue our work into the future.
Fill in your Email Address and Name and give us a short description of why you would like to download the data.
Make sure you have ticked the box(es) for the desired area(s) and then submit.
It should be obvious, but needs to be said:
All data is ARA Copyright.
If you use the data for any purpose, there has to be a reference
to ARA - Airborne Research Australia.
These data cannot be offered for sale in any form or manner.
The data are made available "as is" - without any warranty of any type.
By downloading this data, you confirm that you will only use this data under the Creative Commons BY-NC-SA 4.0 License.
For legal details, see
For file formats, further descriptions, comments and (free) software recommendations to view the data, click here.
Currently available products and data sets
RGB-mosaics - mosaics from Aerial Photos
Lidar - 3D pointclouds from airborne Lidar
DSM/DTM - Digital Elevation Models with and without vegetation/trees (bare ground) from Lidar
CIR - Colour Infrared Images from hyperspectral data (shows health of vegetation/trees)
CAUTION - Some of these datasets are huge
If you have problems with the size, contact us and we will see how we can help
Google Earth kmz-files - to be loaded into Google Earth for viewing.
Google Earth is free and can be downloaded from
jpg-files - can be loaded/viewed in image viewing programs; zip-file contains geo-referencing info.
Some jpgs are available as zipped files - unzip before viewing
Lidar laz-files - require a pointcloud viewer
Unless you have your own preferences, you may want to try DispLAZ ()
Description of and comments to available products
The greyscale images for the Lidar DSM and DTM are **not** elevation files, but only geo-referenced images for viewing. If you need the actual elevation (TIF) files, please contact us via - or use Martin Isenburg's LAStools utilities or other suitable software.
The grey scale images were rendered using RVT - Relief Visualization Toolbox Version 2.0
Kokalj, Žiga, Klemen Zakšek and Krištof Oštir. 2011. Application of Sky-View Factor for the Visualization of Historic
Landscape Features in Lidar-Derived Relief Models. Antiquity 85 (327): 263–273.
Zakšek, Klemen, Krištof Oštir and Žiga Kokalj. 2011. Sky-View Factor as a Relief Visualization Technique. Remote Sensing 3: 398–415.
On the hyperspectral CIR-images (Colour InfraRed), one can often see "striping" between the flightlines. This "striping" can be eliminated, but that's a time-consuming process and at this stage we decided to leave it as is, because the information contained in these images would not change - the images would just look "nicer".
CIR-images show the health of vegetation in red colours - the brighter the red, the healthier it is. Browns tend to show dried foliage, blacks and greys are burnt. Our CIR-images were generated from our VNIR hyperspectral pushbroom line scanner, a SPECIM EAGLE II, configured to deliver the best SNR by binning down from 495 down to 128 bands between 400nm to 1000nm. The raw EAGLE data was processed with ARA in-house software and instrument calibrations through to calibrated at-sensor radiances and has not yet been corrected for atmospheric, topographic or other illumination effects.
The EAGLE is paired with an OXTS RT4003 L1/L2 dual antenna MEMS-based attitude and heading system. The data from the OXTS RT4003 system was post-processed using OXTS software.
Georeferencing of the hyperspectral data at this stage has only been done by projection onto SRTM elevations and is not at a final level of precision.
On the flight of 13 April 2020, the GPS/IMU unit developed a fault and therefore the hyperspectral data from that day are imperfectly geo-referenced. We decided to still offer the somewhat imperfectly georeferenced CIR-imagery for download, because some of them are truly spectacular and are showing the first phase of re-growth. Some flightlines from that day were manually post-processed to improve the imperfect georeferencing, but this is a very labour-intense task. The unit has been fixed and by now perfectly again.
If you would like to dive further into the hyperspectral data, please contact us and we'd be pleased to discuss and share it - the full hyperspectral data has been processed to individual gridded flightlines in .BSQ-format but these are large files requiring suitable software for further analysis and processing (such as ENVI and ATCOR or similar) and so we are not distributing these files in the same way as other data.
All Lidar data was collected using a Riegl Q680i-S small-footprint laser scanner coupled to a NOVATEL SPAN tactical grade IMU/GPS system that includes a LITEF ISA fibre-based gyro. The LIdar data was initally processed into sdc-files by the RiAnalyze software. LAZ-files were then generated by bringing together the sdc-data with the navigation data from the NOVATEL SPAN system. The LAZ-files were then further processed using a combination of Martin Isenburg's LAStools utilities and the GlobalMapper software. Visualisations were generated using POTREE; animations were generated using the VEESUS ARENA4 software.
If you would like to work with the raw or intermediate Lidar data, or even with the full-waveform data, please contact us.
All RGB images were taken by a CANON EOS Mk4 DSLR fitted with a CANON EF24mm f/1.4L II USM lens and initially processed by the DxO-Software using standard settings. The RGB-mosaics were generated using the Agisoft MetaShape software.
If you would like to get the raw images from the RGB-camera, please contact us.