Sorted pulse data (SPD) library - Part II: A processing framework for LiDAR data from pulsed laser systems in terrestrial environments

The management and spatial-temporal integration of LiDAR data from different sensors and platforms has been impeded by lack of generic open source tools and standards. This paper presents a new open source software system, the sorted pulse data software library (SPDLib), that provides a processing framework based on an implementation of a new file format for the storage of discrete-return and waveform LiDAR data from terrestrial, airborne and space borne platforms. A python binding and a visualisation tool (SPD Points Viewer), which build on top of the SPDLib and SPD file format have also been provided. The software and source code have recently been made freely available and can be accessed online through an open source code repository. Future developments will focus on the development of advanced waveform processing functionality and optimising IO performance. The software and documentation can be obtained from http://www.spdlib.org.

[1]  Andrew Thomas Hudak,et al.  A Multiscale Curvature Algorithm for Classifying Discrete Return LiDAR in Forested Environments , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[2]  William Puech,et al.  FullAnalyze: A Research tool for handling, processing and analyzing full-waveform lidar data , 2009, 2009 IEEE International Geoscience and Remote Sensing Symposium.

[3]  Norbert Pfeifer,et al.  ORIENTATION AND PROCESSING OF AIRBORNE LASER SCANNING DATA (OPALS) - CONCEPT AND FIRST RESULTS OF A COMPREHENSIVE ALS SOFTWARE , 2009 .

[4]  A. Suratno,et al.  Tree species identification in mixed coniferous forest using airborne laser scanning , 2009 .

[5]  S. Durrieu,et al.  Advanced full-waveform lidar data echo detection: Assessing quality of derived terrain and tree height models in an alpine coniferous forest , 2009 .

[6]  Richard M. Lucas,et al.  Sorted pulse data (SPD) library. Part I: A generic file format for LiDAR data from pulsed laser systems in terrestrial environments , 2013, Comput. Geosci..

[7]  K. Kraus,et al.  FROM SINGLE-PULSE TO FULL-WAVEFORM AIRBORNE LASER SCANNERS: POTENTIAL AND PRACTICAL CHALLENGES , 2004 .

[8]  R. Sibson,et al.  A brief description of natural neighbor interpolation , 1981 .

[9]  Gottfried Mandlburger,et al.  THE OPALS DATA MANAGER - EFFICIENT DATA MANAGEMENT FOR PROCESSING LARGE AIRBORNE LASER SCANNING PROJECTS , 2012 .

[10]  Dimitri Lague,et al.  3D Terrestrial LiDAR data classification of complex natural scenes using a multi-scale dimensionality criterion: applications in geomorphology , 2011, ArXiv.

[11]  Chaitanya K. Baru,et al.  OpenTopography: a services oriented architecture for community access to LIDAR topography , 2011, COM.Geo.

[12]  M. Pfennigbauer,et al.  Laser scanning by echo signal digitization and waveform processing , 2011 .

[13]  M. Pfennigbauer,et al.  Echo Digitization and Waveform Analysis in Airborne and Terrestrial Laser Scanning , 2011 .

[14]  P. Argouris,et al.  Photogrammetric Week 1993: 20–25 September 1993, Stuttgart, Germany , 1994 .

[15]  Alex C. Lee,et al.  A LiDAR-derived canopy density model for tree stem and crown mapping in Australian forests , 2007 .

[16]  Alistair M. S. Smith,et al.  Discrete Return Lidar in Natural Resources: Recommendations for Project Planning, Data Processing, and Deliverables , 2009, Remote. Sens..

[17]  I. Burke,et al.  Estimating stand structure using discrete-return lidar: an example from low density, fire prone ponderosa pine forests , 2005 .

[18]  Keqi Zhang,et al.  Identification of gaps in mangrove forests with airborne LIDAR , 2008 .

[19]  N. Coops,et al.  Estimating canopy structure of Douglas-fir forest stands from discrete-return LiDAR , 2007, Trees.

[20]  Hans-Gerd Maas,et al.  Automatic forest inventory parameter determination from terrestrial laser scanner data , 2008 .

[21]  Nicholas C. Coops,et al.  Evaluating error associated with lidar-derived DEM interpolation , 2009, Comput. Geosci..

[22]  Ralph Johnson,et al.  design patterns elements of reusable object oriented software , 2019 .

[23]  W. Wagner,et al.  Gaussian decomposition and calibration of a novel small-footprint full-waveform digitising airborne laser scanner , 2006 .

[24]  Peter Scarth,et al.  Prediction and validation of foliage projective cover from Landsat-5 TM and Landsat-7 ETM+ imagery , 2009 .

[25]  A. Neuenschwander,et al.  Evaluation of waveform deconvolution and decomposition retrieval algorithms for ICESat/GLAS data , 2008 .

[26]  Chengcui Zhang,et al.  A progressive morphological filter for removing nonground measurements from airborne LIDAR data , 2003, IEEE Trans. Geosci. Remote. Sens..