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Open source software DASOS: efficient accumulation, analysis, and visualisation of full-waveform lidar
Author(s): M. Miltiadou; Michael G. Grant; N. D. F. Campbell; M. Warren; D. Clewley; Diofantos G. Hadjimitsis
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Paper 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.

Paper Details

Date Published: 27 June 2019
PDF: 17 pages
Proc. SPIE 11174, Seventh International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2019), 111741M (27 June 2019); doi: 10.1117/12.2537915
Show Author Affiliations
M. Miltiadou, Plymouth Marine Lab. (United Kingdom)
Univ. of Bath (United Kingdom)
Cyprus Univ. of Technology (Cyprus)
Michael G. Grant, Plymouth Marine Lab. (United Kingdom)
N. D. F. Campbell, Univ. of Bath (United Kingdom)
M. Warren, Plymouth Marine Lab. (United Kingdom)
D. Clewley, Plymouth Marine Lab. (United Kingdom)
Diofantos G. Hadjimitsis, Cyprus Univ. of Technology (Cyprus)


Published in SPIE Proceedings Vol. 11174:
Seventh International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2019)
Kyriacos Themistocleous; Giorgos Papadavid; Silas Michaelides; Vincent Ambrosia; Diofantos G. Hadjimitsis, Editor(s)

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