User:MiltoMiltiadou/sandbox/Open source software DASOS

Open source software DASOS

LiDAR technologies are particularly useful in Remote Sensing since they are able to acquire height related information by measuring the round trip time of the emitted laser beam. Traditional LiDAR system were able to acquire a few peak returns, while full-waveform (FW) LiDAR are able to record and digitise the entire reflected signal into equally spaced time intervals. According to the LAS file specifications, the result is a a set of waveform samples. For each waveform sample, we can calculate its geolocation and associate it with an intensity value. The intensity values combined form a waveform.

The open source software DASOS has been developed for interpreting full-waveform LiDAR data into a voxelised representation. Let's explain. During voxelisation, the 3D space of the area of interest is divided into 3D cells, named voxels. Each waveform sample has a geolocation. We find the voxel that each voxel lies inside and associate that value with the voxel that it lies inside. Then normalisation is applied by taking the average value of each voxel.

DASOS has three main functionalities:


 * 1) It can export 2D metrics e.g. "height" that related to the Digital Elevation Model, "average height difference", which is an edge detection algorithm
 * 2) It can create 3D polygonal meshes from the scanned area  and recently a study was published that compares different data structures for testing the efficiency of the approach implemented on DASOS for generating those polygonal meshes
 * 3) The third functionality is the exportation of 3D structural information from local areas using 3D windows (e.g. standard deviation of height difference). This has being used for the detection of dead standing trees, which are important for biodiversity

Overall full-waveform LiDAR data have many prospects but the large amount of data makes handling difficult. DASOS is open source, available on Github, and aims to improve the usage of these datasets.