Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/14307
Title: Open source software DASOS: efficient accumulation, analysis, and visualisation of full-waveform lidar
Authors: Miltiadou, Milto 
Grant, Michael G. 
Campbell, Neill D.F. 
Warren, Mark 
Crewley, Daniel 
Hadjimitsis, Diofantos G. 
Major Field of Science: Engineering and Technology
Field Category: Agriculture Forestry and Fisheries
Keywords: Software Engineering;Remote Sensing;Data analysis;Full-waveform LiDAR;Forestry
Issue Date: Jun-2019
Project: Advancement of Tree Structure Observation Algorithms for FOREST Monitoring 
Conference: Seventh International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2019) 
Abstract: Full-waveform (FW) LiDAR have been available for 20 years, but compared to discrete LiDAR, there are very few researchers exploiting these data due to the increased complexity. DASOS is an open source command-line software developed for improving the adoption of FW LiDAR in Earth Observation related applications. It uses voxelisation for interpreting the data, which is fundamentally different from the state-of-art tools interpreting FW LiDAR. There are four key features of DASOS: (1) Generation of polygonal meshes by extracting an iso-surface from the voxelised data. (2) the 2D FW LiDAR metrics exported in standard GIS format; each pixel corresponds to a column from the voxelised space and contains information about the spread of the non-open voxels, (3) efficient alignment with hyperspectral imagery using a hashed table with buckets of geolocated hyperspectral pixels. The outputs of the alignment are coloured polygonal meshes, and aligned metrics. (4) The extraction of 3D raw or composite features into vectors using 3D-windows; these feature vectors can be used in machine learning for describing objects, such as trees. Machine learning approaches (e.g. random forest) could be used for classifying trees in the 3D-voxelised space.
URI: https://hdl.handle.net/20.500.14279/14307
DOI: 10.1117/12.2537915
Type: Conference Papers
Affiliation : Cyprus University of Technology 
University of Bath 
Plymouth Marine Laboratory 
Funding: This research was funded by EPSRC Engineering and Physical Sciences grant number EP/G037736/1 (Centre for Digital Entertainment) and the NERC Airborne Research Facility Data Analysis Node, which is based at Plymouth Marine Laboratory. The continuation of this research and the preparation of the paper is co-funded by the European Regional Development Fund and the Republic of Cyprus through the Research Promotion Foundation (project ”FOREST”: OPPORTUNITY/0916/MSCA/0005).
Publication Type: Peer Reviewed
Appears in Collections:Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation

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