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1 | Timestamp | Name | Organization | 1. What are your major sources for surface scan point clouds? | 2. What formats do you use to store point clouds? | 3. What formats do you use to transfer point clouds (both internally and to external entities)? | 4. What are your most common use cases for point clouds? | 5. What are your main application areas for point clouds? | 6. How do you store point clouds? | 7. What attributes do your point clouds contain besides XYZ coordinates? | 8. What conversion do you apply to the point clouds in order to use them? | 9. Which temporal aspect of point clouds are relevant for you? | 10. During what phase do you encounter interoperability challenges? | 11. What do you consider the most important area of point cloud standardization? | 12. What volume of point clouds have you managed/processed/stored/etc. in the last 12 month? | 13. What tools do you use? | Comments: | |||||||||||||||||||||||||
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6 | 2/3/2016 11:29:38 | Peter van Oosterom | P.J.M.vanOosterom@tudelft.nl | TU Delft | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping), Indoor Laser Scanning, SONAR (single and multi-beam echo’s) | LAS (ASPRS), LAZ, ASCII, Oracle SDO_PC, PostgreSQL-PostGIS PCPATCH, PDAL-generated blocks, Flat table | LAS (ASPRS), LAZ, ASCII | Visualization | Water Management, Smart City | In a database | None | None, direct use of point clouds | Temporal granularity at data set (a ‘point cloud’) level, Temporal resolution / update frequency years | Storage / Management, Dissemination, Visualization / Interaction | Data Model, File Format / Encoding, DBMS / SQL, Web Service (WxxS) protocol | More than 1 billion (109) points | PDAL, Potree, LAStools, Esri ArcGIS, Oracle SDO_PC, PosgreSQL/PostGIS, MonetDB, FME | looking forward to results! | ||||||||||||||||||||||||
7 | 2/4/2016 13:21:40 | Jay Hermann | jhermann@harris.com | Harris | Airborne LiDAR, Photogrammetry | LAS (ASPRS), LAZ, bpf | LAS (ASPRS) | Visualization, Digital Terrain Modelling, Feature Extraction, GIS | Civil Engineering, Asset Management | In a database, In the cloud | Timestamp, Intensity, Classification | To features (vector object rafter detection/recognition), None, direct use of point clouds | Temporal granularity at data set (a ‘point cloud’) level, Temporal resolution / update frequency months, Temporal resolution / update frequency days, Monitoring applications, change detection | Change Reference System, Analysis / Simluation, Dissemination, Visualization / Interaction | File Format / Encoding, Web Service (WxxS) protocol | More than 1 trillion (10^12) points | Potree, PosgreSQL/PostGIS, environment lidar, qt modeler | |||||||||||||||||||||||||
8 | 2/8/2016 10:31:00 | MORREALE | morreale.jean.roc@pasdecalais.fr | Conseil Dép. du Pas de Calais | Airborne LiDAR, Photogrammetry | LAS (ASPRS), LAZ, PostgreSQL-PostGIS PCPATCH | LAS (ASPRS), LAZ | Digital Terrain Modelling, GIS | archeology | In a file on a network drive, In a database | Timestamp, Colour, Classification | To regular grid (raster), Level of Detail (LoD) representation | Temporal resolution / update frequency years | Combining Data from multiple source, Analysis / Simluation | Data Model, File Format / Encoding | More than 100 million (10^6) points | PDAL, Potree, LAStools, GRASS, PosgreSQL/PostGIS, cloudcompare | |||||||||||||||||||||||||
9 | 2/8/2016 10:47:05 | Matthias | matthias_mueller@tu-dresden.de | TUD | Airborne LiDAR, Photogrammetry | LAS (ASPRS), ASCII | LAS (ASPRS), ASCII | Digital Terrain Modelling, Feature Extraction, GIS | Smart City, Civil Engineering | In a file on a computer, In a file on a network drive | Timestamp, Colour | To regular grid (raster), Level of Detail (LoD) representation | Temporal granularity at data set (a ‘point cloud’) level, Temporal resolution / update frequency years, Temporal resolution / update frequency months, Monitoring applications, change detection | Storage / Management, Combining Data from multiple source, Change Reference System | Data Model, File Format / Encoding | More than 1 billion (10^9) points | LAStools, Esri ArcGIS, PCL | |||||||||||||||||||||||||
10 | 2/8/2016 10:51:34 | DAVID MALTBY | david@surveymbs.com | MBS SURVEY SOFTWARE | Terrestrial Lidar (including Mobile Mapping) | E57 | E57 | 3D BUILDING MODELS | DAYLIGHT PLANNING | In a file on a network drive, REMOVABLE DRIVE | Intensity | None, direct use of point clouds | Temporal granularity at data set (a ‘point cloud’) level | Storage / Management, DISSEMINATION | NO OPINION | More than 1 trillion (10^12) points | Leica CloudWorx, UNDET | |||||||||||||||||||||||||
11 | 2/8/2016 10:51:57 | Sam Meek | s.meek@helyx.co.uk | Helyx SIS | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping), Indoor Laser Scanning | LAS (ASPRS), LAZ, ASCII, PLY, Flat table | LAS (ASPRS), E57, ASCII, PLY | Visualization, Digital Terrain Modelling | Civil Engineering | In a file on a computer | Timestamp, Intensity, Colour | To TIN, None, direct use of point clouds | Monitoring applications, change detection | Storage / Management, Combining Data from multiple source, Dissemination, Visualization / Interaction | Data Model, Web Service (WxxS) protocol | More than 100 million (10^6) points | Esri ArcGIS, CloudCompare | Used a lot in previous work, mainly for internal and external building mapping using a lidar scanner. Are web services suitable for this because of the large data volumes? Perhaps engineering products or sections on the fly could be interesting. | ||||||||||||||||||||||||
12 | 2/8/2016 11:10:47 | Gene Roe | gene.roe@lidarnews.com | Lidar News | Terrestrial Lidar (including Mobile Mapping) | LAS (ASPRS), E57, ASCII | LAS (ASPRS), E57 | Visualization, Digital Terrain Modelling, Feature Extraction | Civil Engineering, Asset Management | In a file on a network drive | Intensity, Colour, Classification | To features (vector object rafter detection/recognition) | Monitoring applications, change detection | Storage / Management, Combining Data from multiple source | Data Model, File Format / Encoding | More than 1 billion (10^9) points | Esri ArcGIS, Bentley Pointools, Leica CloudWorx | |||||||||||||||||||||||||
13 | 2/8/2016 11:37:35 | Sjoerd Brandsma | sbrandsma@cyclomedia.com | CycloMedia | Terrestrial Lidar (including Mobile Mapping), Photogrammetry | LAZ, PLY, Own format | LAZ, Own format | Visualization, Feature Extraction, Intermediate product for 3D textured mesh reconstruction | Smart City, Asset Management | In a file on a network drive | Timestamp, Colour, Accuracy (stddev) | To features (vector object rafter detection/recognition), None, direct use of point clouds, simplification, 3d delaunay triangulation | Temporal granularity at data set (a ‘point cloud’) level, Temporal resolution / update frequency months | Storage / Management, Combining Data from multiple source, Analysis / Simluation, Visualization / Interaction | Data Model, File Format / Encoding, DBMS / SQL, Web Service (WxxS) protocol | More than 100 million (10^6) points | Potree, LAStools, Esri ArcGIS, PosgreSQL/PostGIS, PCL, FME, Own software | |||||||||||||||||||||||||
14 | 2/8/2016 11:38:46 | Peter Baumann | baumann@rasdaman.com | Jacobs University | Photogrammetry, Subsurface Point Cloud from Seismic | database | ASCII | Visualization, Digital Terrain Modelling | research | In a database | None | To regular grid (raster) | Temporal granularity at point level, Monitoring applications, change detection | Data Acquisition, Change Reference System | Data Model, DBMS / SQL, Web Service (WxxS) protocol | More than 100 million (10^6) points | Fledermaus | |||||||||||||||||||||||||
15 | 2/8/2016 11:43:42 | Howard Butler | howard@hobu.co | Hobu, Inc. | Airborne LiDAR | LAS (ASPRS), LAZ, PCD, ASCII, PLY, Oracle SDO_PC, PostgreSQL-PostGIS PCPATCH, PDAL-generated blocks | LAZ, PDAL-generated blocks | Visualization, Digital Terrain Modelling | Hydrology, Civil Engineering | In a database, In the cloud | Timestamp, Intensity, Colour, Classification, Pulse Form, Pulse Count, Direction and Length of Scanline | To regular grid (raster), Level of Detail (LoD) representation | Temporal granularity at data set (a ‘point cloud’) level, Temporal resolution / update frequency years | Storage / Management, Dissemination, Visualization / Interaction | File Format / Encoding, Web Service (WxxS) protocol | More than 1 trillion (10^12) points | PDAL, Potree, LAStools, Oracle SDO_PC, PosgreSQL/PostGIS, PCL | |||||||||||||||||||||||||
16 | 2/8/2016 11:48:06 | Hans Heidemann | kheidemann@usgs.gov | USGS/EROS | Airborne LiDAR | LAS (ASPRS), LAZ | LAS (ASPRS), LAZ | Visualization, Digital Terrain Modelling, Feature Extraction | Forestry, Hydrology | In a file on a computer, In a file on a network drive | Timestamp, Intensity, Colour, Classification, Pulse Form, Pulse Count, Direction and Length of Scanline, We keep everything we receive | To regular grid (raster), To TIN, Level of Detail (LoD) representation, To features (vector object rafter detection/recognition) | Temporal granularity at point level, Temporal granularity at data set (a ‘point cloud’) level | Combining Data from multiple source, Change Reference System, Analysis / Simluation, Dissemination, Visualization / Interaction | Data Model, File Format / Encoding, Web Service (WxxS) protocol | More than 1 trillion (10^12) points | PDAL, LAStools, GRASS, Esri ArcGIS, TerraSolid, LP360, VG4D, ENVI/IDL, C++ | Our role at the USGS is a bit different from other users, as we are tasked with handling, managing, and exploiting data from ALL vendors, systems and other end users. And doing so in a project-agnostic, somewhat seamless manner. | ||||||||||||||||||||||||
17 | 2/8/2016 11:53:56 | Kirk Waters | Kirk.Waters@noaa.gov | NOAA | Airborne LiDAR | LAZ | LAS (ASPRS), LAZ, ASCII | Visualization, Digital Terrain Modelling, GIS | Hydrology, Water Management, Civil Engineering | In a file on a network drive | Timestamp, Intensity, Classification, Pulse Count | To regular grid (raster), To TIN | Temporal granularity at point level, Temporal granularity at data set (a ‘point cloud’) level, Temporal resolution / update frequency years, Temporal resolution / update frequency months, Monitoring applications, change detection | Combining Data from multiple source | Web Service (WxxS) protocol | More than 1 trillion (10^12) points | LAStools, homegrown tools for datum transformation. | We use a combination of things to manage data for distribution. While the data are left as LAZ files on network disks, the information about the data is stored in a database and we use that to find the data needed for a given request. | ||||||||||||||||||||||||
18 | 2/8/2016 11:56:21 | Carl Reed | carl.n.reed@gmail.com | Self | Don't use. Just interested. | Don't use. Just interested in what others do. | Don't use. Just interested in what others do. | Don't use. Just interested in what others do. | Don't use. Just interested in what others do. | Don't use. Just interested in what others do. | Don't use. Just interested in what others do. | Don't use. Just interested in what others do. | Don't use. Just interested in what others do. | Don't use. Just interested in what others do. | File Format / Encoding, Web Service (WxxS) protocol | Less than 100 million (10^6) points | Don't use. Just interested in what others do. | I am interested in the results of the survey WRT standards requirements. | ||||||||||||||||||||||||
19 | 2/8/2016 12:00:45 | Mike McCann | mccann@mbari.org | MBARI | Subsurface Point Cloud from Seismic | PLY, x3d | x3d | Visualization, Digital Terrain Modelling | Oceanography | In a file on a computer, In a file on a network drive | None | To TIN, SRC/gltf | Monitoring applications, change detection | Storage / Management, Visualization / Interaction | File Format / Encoding, Web Service (WxxS) protocol | Less than 100 million (10^6) points | PosgreSQL/PostGIS, GMT, Meshlab, InstantReality, X3DOM | I've eavesdropped on the issue where vendor lock-in is being attempted for this important type of data. Our community is big enough to have a real community standard that avoids vendor lock-in. | ||||||||||||||||||||||||
20 | 2/8/2016 12:30:58 | Jason Stoker | jstoker@usgs.gov | USGS | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping), Photogrammetry, SONAR (single and multi-beam echo’s) | LAS (ASPRS), LAZ | LAS (ASPRS), LAZ | Visualization, Digital Terrain Modelling, Feature Extraction, GIS | Forestry, Hydrology, Water Management, Asset Management | In a file on a computer, In a file on a network drive, In a database, In the cloud | Timestamp, Intensity, Colour, Classification, Pulse Form, Pulse Count, Direction and Length of Scanline | To regular grid (raster), To TIN, Level of Detail (LoD) representation, To features (vector object rafter detection/recognition), None, direct use of point clouds | Temporal granularity at point level, Temporal granularity at data set (a ‘point cloud’) level, Temporal resolution / update frequency years, Temporal resolution / update frequency months, Monitoring applications, change detection | Storage / Management, Combining Data from multiple source, Change Reference System, Analysis / Simluation, Dissemination, Visualization / Interaction | Data Model | More than 1 trillion (10^12) points | PDAL, Potree, LAStools, GRASS, Esri ArcGIS, TerraSolid | |||||||||||||||||||||||||
21 | 2/8/2016 13:06:37 | michael s rosen | michael.rosen@gmail.com | Lizardtech | Airborne LiDAR, Photogrammetry | LAS (ASPRS), LAZ, PLY | LAS (ASPRS), LAZ | Visualization, Digital Terrain Modelling, GIS | Forestry | In a file on a computer | Intensity, Colour, Classification | To regular grid (raster), To TIN | Analysis / Simluation, Visualization / Interaction | Web Service (WxxS) protocol | More than 1 billion (10^9) points | LAStools, GRASS, Esri ArcGIS | ||||||||||||||||||||||||||
22 | 2/8/2016 13:09:10 | David Caress | caress@mbari.org | Monterey Bay Aquarium Research Institute | Photogrammetry, SONAR (single and multi-beam echo’s), subsea lidar | MB-System supported sonar formats | MB-System supported sonar formats | Visualization, Digital Terrain Modelling, Feature Extraction, GIS | Marine geology and geophysics, seafloor habitat mapping | In a file on a computer, In a file on a network drive | Timestamp, Intensity, Colour, Pulse Form, Pulse Count, Direction and Length of Scanline, sonar attributes | To regular grid (raster), To TIN | Temporal granularity at point level, Monitoring applications, change detection | Data Acquisition, Storage / Management, Combining Data from multiple source, Change Reference System, Analysis / Simluation, Dissemination, Visualization / Interaction | Data Model, File Format / Encoding | More than 1 billion (10^9) points | MB-System, GMT | My responses are from a seafloor mapping context. In the past most topography data derived from multibeam sonars, for which soundings have overlapping footprints rather than representing points, and were used to represent topography in 2D grids. We are now working with subsea lidar based mapping, plus mapping fully 3D features. Therefore the methods developed for working with point cloud data from subaerial lidars are increasingly relevant to seafloor mapping. | ||||||||||||||||||||||||
23 | 2/8/2016 13:20:41 | Jed Frechette | jed@lidarguys.com | Lidar Guys | Terrestrial Lidar (including Mobile Mapping), Indoor Laser Scanning | E57, ASCII, PLY, PTX and various vendor specific formats | LAS (ASPRS), E57, ASCII, ptx | Digital Terrain Modelling, GIS, Fully 3D object modeling | Civil Engineering, VFX, terrain analysis | In a file on a computer, In a file on a network drive | Intensity, Colour, Classification, estimated surface normals, various arbitrary attributes | To regular grid (raster), None, direct use of point clouds, Fully 3D mesh, i.e. not a 2.5D TIN | Temporal granularity at data set (a ‘point cloud’) level, Monitoring applications, change detection | Storage / Management, Combining Data from multiple source, Analysis / Simluation, Dissemination | File Format / Encoding | More than 1 billion (10^9) points | PDAL, Potree, GRASS, Esri ArcGIS, PCL, FARO Scene, PolyWorks, Sequoia | |||||||||||||||||||||||||
24 | 2/8/2016 13:39:32 | Val Schmidt | vschmidt@ccom.unh.edu | University of New Hampshire | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping), Photogrammetry, SONAR (single and multi-beam echo’s) | ASCII, CSAR, Any of various vendor formats, MATLAB .mat | ASCII | Visualization, Feature Extraction | Seafloor Mapping | In a file on a computer, In a file on a network drive | Timestamp, Intensity, Measurement angle, vehicle location/attitude, | To regular grid (raster), To features (vector object rafter detection/recognition) | Temporal granularity at data set (a ‘point cloud’) level | Data Acquisition, Storage / Management, Combining Data from multiple source | File Format / Encoding | More than 1 billion (10^9) points | CARIS, Fledermaus, MATLAB | |||||||||||||||||||||||||
25 | 2/8/2016 14:15:32 | C. Crosby | crosby@unavco.org | UNAVCO / OpenTopography | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping), Photogrammetry | LAS (ASPRS), LAZ, ASCII | LAS (ASPRS), LAZ, ASCII | Visualization, Digital Terrain Modelling, Feature Extraction, GIS | Forestry, Hydrology, Geology, Geophysics, Geodesy, natural hazards, mapping, cryosphere and climate change, education/teaching | In a file on a computer, In a database, In the cloud, as files on high performance computers (HPC) | Timestamp, Intensity, Colour, Classification, full suite of ASPRS LAS attributes, scan position | To regular grid (raster), To TIN, Level of Detail (LoD) representation, To features (vector object rafter detection/recognition), None, direct use of point clouds, to voxel | Temporal granularity at point level, Temporal granularity at data set (a ‘point cloud’) level, Temporal resolution / update frequency years, Temporal resolution / update frequency months, Temporal resolution / update frequency days, Temporal resolution / update frequency seconds, Monitoring applications, change detection | Data Acquisition, Storage / Management, Combining Data from multiple source, Change Reference System, Analysis / Simluation, Dissemination, Visualization / Interaction | Data Model, File Format / Encoding, Web Service (WxxS) protocol | More than 1 trillion (10^12) points | PDAL, LAStools, Esri ArcGIS, PosgreSQL/PostGIS, PCL, RiScan Pro, libLAS, GDAL, Global Mapper, various academic/open source tools | |||||||||||||||||||||||||
26 | 2/8/2016 14:42:07 | Derek Shockley | derek.j.shockley@nga.mil | National Geospatial-Intelligence Agency | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping), Photogrammetry, RADAR (PS-InSAR) | .bpf | .bpf | Visualization, Digital Terrain Modelling, Feature Extraction, GIS | Defense | In a database | Timestamp, Intensity, Colour, Classification, Pulse Form, Pulse Count, Direction and Length of Scanline | None, direct use of point clouds | Temporal granularity at data set (a ‘point cloud’) level, Monitoring applications, change detection | Storage / Management, Combining Data from multiple source, Change Reference System, Visualization / Interaction | File Format / Encoding | More than 1 billion (10^9) points | PDAL, PosgreSQL/PostGIS | |||||||||||||||||||||||||
27 | 2/8/2016 15:52:14 | Chris Volpe | cvolpe@ara.com | Applied Research Assoc., Inc | Airborne LiDAR, Photogrammetry | LAS (ASPRS), BPF | LAS (ASPRS), BPF | Digital Terrain Modelling, Feature Extraction | Intelligence Community (IC) operations | In a file on a computer, In a file on a network drive | Intensity, Colour, Classification | To regular grid (raster), To features (vector object rafter detection/recognition) | N/A | Combining Data from multiple source, Change Reference System | Data Model | Less than 100 million (10^6) points | LAStools, GRASS, PCL, FugroViewer, QT Reader | |||||||||||||||||||||||||
28 | 2/8/2016 15:58:56 | Markus Schuetz | mschuetz@potree.org | potree | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping), Photogrammetry | LAS (ASPRS), LAZ, PLY | LAS (ASPRS), LAZ | Visualization | anything | In a file on a computer, servers | Intensity, Colour, Classification, normals | Level of Detail (LoD) representation | none | Combining Data from multiple source, Visualization / Interaction | File Format / Encoding, Web Service (WxxS) protocol | More than 1 billion (10^9) points | Potree, LAStools, CloudCompare | las/laz is nice and simple but I'd realy appreciated a format where you can selectively choose the attributes. * Don't store more attributes than necessary * Additionally to a set of standard attributs (position, classification, ...), let users define custom attributes. | ||||||||||||||||||||||||
29 | 2/8/2016 17:01:27 | David Simon | david.simon@ga.gov.au | Geoscience Australia | Airborne LiDAR | LAS (ASPRS), LAZ, ASCII | LAS (ASPRS), LAZ | Digital Terrain Modelling, Feature Extraction | Hydrology | In a file on a network drive, In the cloud | Timestamp, Intensity, Classification, Pulse Form, Pulse Count | To regular grid (raster), None, direct use of point clouds | Temporal granularity at data set (a ‘point cloud’) level, Temporal resolution / update frequency years, Monitoring applications, change detection | Storage / Management, Analysis / Simluation, Dissemination | File Format / Encoding, Indexing | More than 1 trillion (10^12) points | LAStools, Esri ArcGIS | |||||||||||||||||||||||||
30 | 2/8/2016 17:49:17 | Ross Winans | ross.winans@noaa.gov | NOAA | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping), Photogrammetry, SONAR (single and multi-beam echo’s), RADAR (PS-InSAR) | LAS (ASPRS), LAZ | LAZ | Visualization, Digital Terrain Modelling, Feature Extraction, GIS | Hydrology, Water Management, Smart City, Civil Engineering | In a file on a computer, In a file on a network drive | Timestamp, Intensity, Classification, Pulse Count, Direction and Length of Scanline | To regular grid (raster), To TIN, To features (vector object rafter detection/recognition) | Temporal granularity at point level, Temporal resolution / update frequency years, Temporal resolution / update frequency months, Temporal resolution / update frequency days, Temporal resolution / update frequency seconds, Monitoring applications, change detection | Combining Data from multiple source, Change Reference System, Dissemination | Data Model, File Format / Encoding, Web Service (WxxS) protocol | More than 1 billion (10^9) points | PDAL, LAStools, GRASS, Blue Marble and MARS7 | |||||||||||||||||||||||||
31 | 2/8/2016 18:12:40 | Michael Sutherland | mike.sutherland@noaa.gov | NOAA NCEI | Airborne LiDAR, SONAR (single and multi-beam echo’s) | LAS (ASPRS), LAZ, ASCII | LAS (ASPRS), LAZ, ASCII | Digital Terrain Modelling | Water Management | In a file on a computer, In a file on a network drive | Timestamp, Intensity, Colour, Classification, Pulse Count, Direction and Length of Scanline | To regular grid (raster), To TIN | Temporal granularity at point level, Temporal granularity at data set (a ‘point cloud’) level, Monitoring applications, change detection | Storage / Management, Combining Data from multiple source, Analysis / Simluation | File Format / Encoding | More than 1 trillion (10^12) points | LAStools, Esri ArcGIS, CARIS, Fledermaus | |||||||||||||||||||||||||
32 | 2/8/2016 19:14:01 | Peter Sforza | sforza@vt.edu | virginia tech cgit | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping), Indoor Laser Scanning, Photogrammetry | LAS (ASPRS), LAZ, ZLAS, ASCII, PLY | LAS (ASPRS), LAZ | Visualization, Digital Terrain Modelling, Feature Extraction, GIS | Forestry, Hydrology, Smart City, Civil Engineering, Asset Management | In a file on a computer, In a file on a network drive, In a database, In the cloud | Timestamp, Intensity, Colour, Classification, Pulse Form, Pulse Count, Direction and Length of Scanline | To regular grid (raster), To TIN, Level of Detail (LoD) representation, To features (vector object rafter detection/recognition) | Temporal granularity at data set (a ‘point cloud’) level, Temporal resolution / update frequency years, Temporal resolution / update frequency seconds, Monitoring applications, change detection | Data Acquisition, Storage / Management, Combining Data from multiple source, Change Reference System, Analysis / Simluation, Dissemination, Visualization / Interaction | Data Model | More than 1 trillion (10^12) points | PDAL, LAStools, Esri ArcGIS, PosgreSQL/PostGIS | |||||||||||||||||||||||||
33 | 2/8/2016 20:09:05 | Philip Lorenzo | philip@rithm.io | Rithm | Indoor Laser Scanning | E57, FLS | E57, FLS | Visualization, Feature Extraction, Coordination, Construction Quality Control | Asset Management, Construction | In a file on a computer, In a file on a network drive, In the cloud | Colour | None, direct use of point clouds | Temporal granularity at point level, Monitoring applications, change detection | Combining Data from multiple source, Analysis / Simluation, Visualization / Interaction | File Format / Encoding, Web Service (WxxS) protocol | More than 1 billion (10^9) points | PCL, Faro Scene, AutoDesk ReCap | |||||||||||||||||||||||||
34 | 2/9/2016 2:52:15 | Vasanth Reddy | vasanthmarvel@gmail.com | GRMC Inc | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping), Indoor Laser Scanning | LAS (ASPRS), LAZ, E57, POD, PLY, PostgreSQL-PostGIS PCPATCH, PDAL-generated blocks | LAS (ASPRS), E57, PLY, PostgreSQL-PostGIS PCPATCH | Visualization, Digital Terrain Modelling, Feature Extraction, GIS, BIM | Hydrology, Civil Engineering, Asset Management, BIM | In a file on a computer, In a file on a network drive, In a database | Timestamp, Intensity, Colour, Classification, Direction and Length of Scanline | To regular grid (raster), To TIN, Level of Detail (LoD) representation | Temporal resolution / update frequency years | Combining Data from multiple source, Dissemination | File Format / Encoding | More than 1 billion (10^9) points | PDAL, Potree, LAStools, Esri ArcGIS, Bentley Pointools, PosgreSQL/PostGIS, TerraSolid, PCL, Revit | * There is an unnecessary brawl between Corporates and Openness regarding LAS1.4 * Point cloud streaming (Stored in PostGIS as pcpatch)/ Integration through Geoserver as standard option for Cesiumjs * New LAS standard to reflect doppler capabilities of FMCW ladar | ||||||||||||||||||||||||
35 | 2/9/2016 3:11:01 | Antonio Ruiz | antonio.ruiz@icgc.cat | Institut Cartografic i Geologic de Catalunya | Airborne LiDAR, Photogrammetry | LAS (ASPRS), LAZ | LAS (ASPRS), LAZ | Digital Terrain Modelling, Feature Extraction | Forestry, Hydrology, Smart City | In a file on a computer, In a file on a network drive | Timestamp, Intensity, Classification | To regular grid (raster), To TIN, To features (vector object rafter detection/recognition) | Temporal resolution / update frequency years, Monitoring applications, change detection | Storage / Management, Analysis / Simluation | File Format / Encoding | More than 1 billion (10^9) points | LAStools, GRASS, Esri ArcGIS, Bentley Pointools, Leica CloudWorx, PosgreSQL/PostGIS, TerraSolid | |||||||||||||||||||||||||
36 | 2/9/2016 3:37:26 | Oscar Martinez Rubi | o.rubi@esciencecenter.nl | Netherlands eScience Center | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping), Photogrammetry | LAS (ASPRS), LAZ, Oracle SDO_PC, PostgreSQL-PostGIS PCPATCH, PDAL-generated blocks, Flat table | LAS (ASPRS), LAZ | Visualization, GIS | Archaeology | In a file on a computer, In a database, In the cloud | Colour, Classification | Level of Detail (LoD) representation, None, direct use of point clouds | Temporal granularity at data set (a ‘point cloud’) level, Temporal resolution / update frequency years | Storage / Management, Combining Data from multiple source, Visualization / Interaction | Web Service (WxxS) protocol | More than 1 billion (10^9) points | PDAL, Potree, LAStools, Oracle SDO_PC, PosgreSQL/PostGIS, MonetDB | |||||||||||||||||||||||||
37 | 2/9/2016 3:40:00 | Douglas Daniel | douglas.daniel@subsea7.com | Subsea 7 | Indoor Laser Scanning, Photogrammetry, SONAR (single and multi-beam echo’s) | LAS (ASPRS), ASCII | LAS (ASPRS), ASCII | Visualization, Digital Terrain Modelling | Asset Management, Oil and Gas | In a file on a network drive | Intensity, Colour | To regular grid (raster), None, direct use of point clouds | Temporal granularity at point level, Temporal granularity at data set (a ‘point cloud’) level | Data Acquisition | File Format / Encoding | More than 100 million (10^6) points | Potree, LAStools, Esri ArcGIS, EIVA NaviModel | |||||||||||||||||||||||||
38 | 2/9/2016 5:52:06 | Charles Thomson | charliethomson@gmail.com | UCL | Terrestrial Lidar (including Mobile Mapping), Indoor Laser Scanning | LAS (ASPRS), E57 | LAS (ASPRS), E57, Rcs | Visualization, Feature Extraction | Civil Engineering, Asset Management | In a file on a computer, In a file on a network drive | Intensity, Colour | To features (vector object rafter detection/recognition), None, direct use of point clouds | Temporal granularity at point level, Temporal resolution / update frequency seconds, Monitoring applications, change detection | Analysis / Simluation, Dissemination, Visualization / Interaction | DBMS / SQL | More than 1 billion (10^9) points | PCL, Cloudcompare | |||||||||||||||||||||||||
39 | 2/9/2016 9:08:59 | JC nelson | jcnelson@usgs.gov | USGS | Airborne LiDAR | LAS (ASPRS), LAZ, Flat table | LAS (ASPRS) | Visualization, Digital Terrain Modelling, Feature Extraction, GIS | Forestry, Hydrology, Water Management | In a file on a computer, In a file on a network drive | Timestamp, Intensity, Classification | To regular grid (raster), To TIN, To features (vector object rafter detection/recognition), None, direct use of point clouds | Monitoring applications, change detection | Data Acquisition, Storage / Management, Combining Data from multiple source, Change Reference System | Data Model | More than 100 million (10^6) points | LAStools, Esri ArcGIS, LP360 | |||||||||||||||||||||||||
40 | 2/9/2016 9:09:05 | Richard Vincent | richard@polarisgeomatics.com | Polarisgeomatics | Indoor Laser Scanning | LAS (ASPRS), LAZ | LAS (ASPRS), LAZ | Visualization, Feature Extraction | Civil Engineering, Asset Management | In a file on a network drive | Timestamp, Intensity, Colour, Classification | Level of Detail (LoD) representation, To features (vector object rafter detection/recognition) | Temporal granularity at point level, Temporal resolution / update frequency years | Data Acquisition, Combining Data from multiple source, Visualization / Interaction | Data Model, File Format / Encoding | More than 1 trillion (10^12) points | LAStools, TerraSolid | |||||||||||||||||||||||||
41 | 2/9/2016 9:51:22 | Ben Houston | benjamin.h.houston@gmail.com | Spatial Analytix | Airborne LiDAR, UAV based Photogrammetry | LAS (ASPRS), LAZ, ESRI LASD | LAS (ASPRS), LAZ | Digital Terrain Modelling, Feature Extraction, GIS | Hydrology, Civil Engineering, Asset Management, Site Characterization | In a file on a computer, In the cloud, Cloud = Dropbox | Intensity, Colour, Classification, Pulse Count | To regular grid (raster), To TIN, Extract vectors, not direct conversion | Temporal granularity at data set (a ‘point cloud’) level, Temporal resolution / update frequency years, Temporal resolution / update frequency months, Temporal resolution / update frequency days, Monitoring applications, change detection, UAV vs airborne have different temporal resolution relevancies | Analysis / Simluation, Dissemination | Web Service (WxxS) protocol | More than 100 million (10^6) points | LAStools, Esri ArcGIS, LP360, Pix4D | |||||||||||||||||||||||||
42 | 2/9/2016 10:11:45 | Peter Bonne | peter.bonne@orbitgt.com | Orbit GT | Terrestrial Lidar (including Mobile Mapping), Indoor Laser Scanning | LAS (ASPRS), LAZ, E57, ASCII, PLY, Flat table | LAS (ASPRS), LAZ, E57 | Visualization, Feature Extraction, Profiling, Clash detection, Volumetric Analysis, ... | Asset Management, Road Admin, Rail, Tunneling, Utilities, ... | In a file on a computer, In a file on a network drive, In the cloud | Timestamp, Intensity, Colour, Classification, Pulse Form, Pulse Count, Direction and Length of Scanline, Scanner # | To features (vector object rafter detection/recognition), None, direct use of point clouds, Textured Meshes, Orthophoto, ... | Temporal granularity at data set (a ‘point cloud’) level, Monitoring applications, change detection | Our software solves these problems ;-) | Data Model, File Format / Encoding, Web Service (WxxS) protocol | More than 1 trillion (10^12) points | Orbit | |||||||||||||||||||||||||
43 | 2/9/2016 10:46:19 | Jonathan Bouffard | jonathan@topo3d.ca | T3D | Terrestrial Lidar (including Mobile Mapping), Indoor Laser Scanning, Photogrammetry | LAS (ASPRS), LAZ, E57, PCD, POD, ASCII, PLY, Pts, ptx | LAS (ASPRS), LAZ, E57, POD, PLY | Visualization, Digital Terrain Modelling, Feature Extraction | Civil Engineering, Industrial, plants | In a file on a network drive | Intensity, Colour | None, direct use of point clouds | Temporal granularity at point level, Monitoring applications, change detection | Combining Data from multiple source | File Format / Encoding | More than 1 billion (10^9) points | Potree, LAStools, Bentley Pointools, Leica CloudWorx, FME | |||||||||||||||||||||||||
44 | 2/9/2016 11:01:06 | Daniel Buscombe | dbuscombe@usgs.gov | U.S. Geological Survey | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping), Photogrammetry, SONAR (single and multi-beam echo’s) | ASCII, GSF, H5, netCDF | ASCII, GSF, H5, netCDF | Visualization, Digital Terrain Modelling, Feature Extraction, GIS, geological/sedimentary description/quantification | sedimentology, geomorphology | In a file on a computer, In a file on a network drive | Timestamp, Intensity, acoustic backscatter, acoustic variables such as pulse length, beam direction, etc. VVV imp for sonar processing that all these things are kept together | To regular grid (raster), None, direct use of point clouds | Temporal resolution / update frequency years, Temporal resolution / update frequency months, Temporal resolution / update frequency days, Temporal resolution / update frequency seconds, Monitoring applications, change detection | Dissemination, Visualization / Interaction | Data Model, File Format / Encoding | More than 1 billion (10^9) points | Hypack. Plus I developed my own tools: http://dbuscombe-usgs.github.io/pysesa/ | There is a pressing need for standardizing point cloud formats from terrestrial (lidar / laser scanning / sfm, etc) and from sonar systems (multibeam, sidescan, singlebeam). Increasingly, the two are being used together in single survey systems, simultaneously acquiring terrestrial and bathymetric data. Current data formats cannot contain all required attributes from lidar and sonar. Sonar analysis needs fields for backscatter, launch angles, beam numbers, and time-varying acoustic variables such as pulse length, frequency, etc. | ||||||||||||||||||||||||
45 | 2/9/2016 11:15:28 | Johannes Schumacher | josc@ign.ku.dk | University of Copenhagen | Airborne LiDAR | LAS (ASPRS), LAZ | LAS (ASPRS), LAZ | Feature Extraction, calculation of descriptive statistics of return heights for modeling vegetation characteristics | Forestry | In a file on a computer, In a file on a network drive, external HDD | Intensity, Classification, Pulse Form, Pulse Count | None, direct use of point clouds | Monitoring applications, change detection | Change Reference System | File Format / Encoding | More than 100 million (10^6) points | LAStools, Esri ArcGIS, Fusion LDV | |||||||||||||||||||||||||
46 | 2/9/2016 13:08:48 | Luiz C E Rodriguez | lcer@usp.br | USP | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping) | LAS (ASPRS), LAZ | LAZ | Forest biomass assessments | Forestry | In a file on a computer, In the cloud | Timestamp, Intensity, Classification, Pulse Form, Pulse Count, Direction and Length of Scanline | None, direct use of point clouds | Temporal granularity at point level, Temporal resolution / update frequency days, Monitoring applications, change detection | Storage / Management, Combining Data from multiple source | File Format / Encoding, DBMS / SQL | More than 100 million (10^6) points | LAStools, FUSION, QGIS | |||||||||||||||||||||||||
47 | 2/9/2016 13:31:47 | Lewis Graham | lgraham@geocue.com | GeoCue Group | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping), Photogrammetry | LAS (ASPRS), ZLAS, ASCII | LAS (ASPRS), ZLAS, ASCII | Visualization, Digital Terrain Modelling, Feature Extraction, GIS, Volumetric Analysis | Hydrology, Smart City, Civil Engineering, Mining | In a file on a computer, In a file on a network drive, In the cloud, LIDARServer (www.lidarserver.com) | Timestamp, Intensity, Colour, Classification, Pulse Count, Direction and Length of Scanline, Normal Vector | To regular grid (raster), To TIN, To features (vector object rafter detection/recognition) | Temporal resolution / update frequency years, Temporal resolution / update frequency months, Temporal resolution / update frequency days, Monitoring applications, change detection, Granulatiry at the block and polygon level | Never. Everyone seems to uderstand LAS | File Format / Encoding, Web Service (WxxS) protocol | More than 1 trillion (10^12) points | Esri ArcGIS, TerraSolid, LP360, LIDARServer | LP360 is a standard tool used by USGS, USDA, many state, local governments. Should probably be on your survey. | ||||||||||||||||||||||||
48 | 2/9/2016 16:35:27 | Ken VanBree | ken@ebuilts.com | e-Builts | Indoor Laser Scanning, Photogrammetry | E57, .fls, .zfs | E57, .fls, .zfs | Feature Extraction, Measurement | Asset Management, as-built documentation | In a file on a computer, In a file on a network drive, In the cloud | Timestamp, Intensity, Colour, Images | To features (vector object rafter detection/recognition), point to point measurement | Temporal granularity at data set (a ‘point cloud’) level | Storage / Management, Combining Data from multiple source, Dissemination, Visualization / Interaction | File Format / Encoding, Auxillary data | More than 100 million (10^6) points | LAStools, Faro Scene, Leica Cyclone | I am working with the E57 committee to extend the current standard for use as an archive of point cloud and image data generated during construction. | ||||||||||||||||||||||||
49 | 2/9/2016 18:33:33 | Sean William Morrish | seanwilliammorrish@gmail.com | UCD | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping), Indoor Laser Scanning, Photogrammetry | LAS (ASPRS), LAZ, ZLAS, E57, ASCII, PDAL-generated blocks | LAZ, ZLAS, ASCII | Visualization, Digital Terrain Modelling, Feature Extraction, GIS | Hydrology, Smart City, Civil Engineering, Asset Management | In a file on a network drive, In a database, In the cloud | Timestamp, Intensity, Colour, Classification, Direction and Length of Scanline | To regular grid (raster), To TIN, Level of Detail (LoD) representation, To features (vector object rafter detection/recognition) | Temporal resolution / update frequency years, Monitoring applications, change detection | Data Acquisition, Storage / Management, Combining Data from multiple source, Change Reference System, Analysis / Simluation, Dissemination | Data Model, File Format / Encoding, Web Service (WxxS) protocol | More than 1 billion (10^9) points | PDAL, Potree, LAStools, Esri ArcGIS, Oracle SDO_PC, FME | |||||||||||||||||||||||||
50 | 2/9/2016 20:54:23 | Francisco Goncalves | fgoncalves@mcelhanney.com | PTMI | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping), Photogrammetry | LAS (ASPRS), LAZ, ASCII | LAS (ASPRS), LAZ, ASCII | Digital Terrain Modelling, Feature Extraction, GIS, Slope analysis, Vol Calculations, watershed, Feature Detection | Forestry, Hydrology, Water Management, Civil Engineering, Asset Management, Archaeology, Agribusiness, Environment | In a file on a network drive | Intensity, Colour, Classification, Feature extraction, profiling, X-Sections, Volume Calculations, Time Change | Level of Detail (LoD) representation | Temporal granularity at point level, Monitoring applications, change detection | Combining Data from multiple source, Dissemination | Data Model, File Format / Encoding | More than 1 trillion (10^12) points | Esri ArcGIS, Bentley Pointools, TerraSolid | |||||||||||||||||||||||||
51 | 2/10/2016 9:03:35 | Mike Meiser | mike.meiser@woolpert.com | Woolpert | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping) | LAS (ASPRS), LAZ, ASCII | LAS (ASPRS), LAZ, ASCII | Digital Terrain Modelling, Feature Extraction, GIS | Forestry, Hydrology, Water Management, Smart City, Civil Engineering, Asset Management | In a file on a computer, In a file on a network drive, In a database | Timestamp, Intensity, Colour, Classification, Pulse Form, Pulse Count, Direction and Length of Scanline | To regular grid (raster), To TIN | Temporal resolution / update frequency years, Monitoring applications, change detection | Combining Data from multiple source | File Format / Encoding | More than 1 trillion (10^12) points | LAStools, Esri ArcGIS, TerraSolid, TopoDOT, FME, QT modeler, global mapper, LP360, Geocue | |||||||||||||||||||||||||
52 | 2/10/2016 9:22:21 | Martin Isenburg | martin@rapidlasso.com | rapidlasso GmbH | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping), Photogrammetry | LAS (ASPRS), LAZ | LAZ | Visualization, Digital Terrain Modelling, Feature Extraction, GIS | Forestry, Hydrology, Water Management, Civil Engineering, Asset Management | In a file on a computer, In a file on a network drive | Timestamp, Intensity, Colour, Classification, pulse source ID (flightline ID), scan angle, withheld flag, overlap flag, number of returns, return count, user data | To regular grid (raster), To TIN, To features (vector object rafter detection/recognition), None, direct use of point clouds | question is not clear | as long as we use LAS/LAZ there are no interoperability challenges | widely existing support in all major software packages | More than 1 billion (10^9) points | Potree, LAStools, GRASS, TopoDOT, QGIS, FUSION, FugroViewer, QT Reader, CloudCompare, RiProcess, CloudPro, Optech LMS 3.0, Trimble RealWorks, Envi LiDAR, Leica LIDAR Survey Studio LSS, ZEB1, Voyager, Scop++, DTMaster | The list of LiDAR software is rather incomplete. | ||||||||||||||||||||||||
53 | 2/10/2016 9:32:58 | Julià Talaya | julia.talaya@icgc.cat | ICGC | Airborne LiDAR, Photogrammetry | LAS (ASPRS) | LAS (ASPRS), LODTree | Visualization, Digital Terrain Modelling | Hydrology, Smart City | In a file on a network drive | Timestamp, Intensity, Classification, Pulse Count | Level of Detail (LoD) representation, None, direct use of point clouds | Temporal granularity at data set (a ‘point cloud’) level | Dissemination, Visualization / Interaction | Data Model, Web Service (WxxS) protocol | More than 1 billion (10^9) points | Bentley Pointools, TerraSolid | |||||||||||||||||||||||||
54 | 2/10/2016 9:59:55 | Amelia Astley | a.astley@noc.soton.ac.uk | National Oceanography Centre | SONAR (single and multi-beam echo’s) | ASCII | ASCII | Visualization, GIS | Hydrology | In a file on a computer | None | To regular grid (raster), To TIN, To features (vector object rafter detection/recognition) | Temporal resolution / update frequency years, Temporal resolution / update frequency months | Analysis / Simluation | Data Model | More than 100 million (10^6) points | Esri ArcGIS, CloudCompare | |||||||||||||||||||||||||
55 | 2/10/2016 10:40:07 | Eric Morris | eric.morris@noaa.gov | NOAA | Airborne LiDAR, RADAR (PS-InSAR) | LAS (ASPRS), LAZ, ASCII | LAZ | Visualization, Digital Terrain Modelling, GIS | Hydrology, Asset Management | In a file on a network drive, In the cloud | Timestamp, Intensity, Colour, Classification, Direction and Length of Scanline | To regular grid (raster), To TIN | Temporal resolution / update frequency years, Monitoring applications, change detection | Analysis / Simluation | Web Service (WxxS) protocol | More than 1 trillion (10^12) points | LAStools, homemade scripts/tools | Thanks for doing this! | ||||||||||||||||||||||||
56 | 2/10/2016 14:30:54 | Marcus Glass | mglass@geoterra.us | GeoTerra | Airborne LiDAR, Photogrammetry | LAS (ASPRS) | LAS (ASPRS) | Visualization, Digital Terrain Modelling, Feature Extraction, GIS | Forestry, Civil Engineering, Asset Management | In a file on a network drive, In a database, In the cloud | Timestamp, Intensity, Colour, Classification, Pulse Form, Pulse Count, Direction and Length of Scanline | To regular grid (raster), To TIN, To features (vector object rafter detection/recognition) | Temporal granularity at point level, Temporal granularity at data set (a ‘point cloud’) level, Temporal resolution / update frequency years, Temporal resolution / update frequency months, Temporal resolution / update frequency days, Temporal resolution / update frequency seconds, Monitoring applications, change detection | Data Acquisition, Combining Data from multiple source | Data Model, File Format / Encoding, DBMS / SQL | More than 100 million (10^6) points | LAStools, Esri ArcGIS, TerraSolid, Inpho | |||||||||||||||||||||||||
57 | 2/10/2016 18:05:09 | Christian Ferreira | Cferreira@marum.de | MARUM | SONAR (single and multi-beam echo’s) | Kongsberg ALL | MB-System | Visualization, Digital Terrain Modelling | Bathymetry | In a file on a network drive | Many attributes | To regular grid (raster) | Temporal resolution / update frequency years | Storage / Management, Combining Data from multiple source | File Format / Encoding | More than 1 billion (10^9) points | MB-System | |||||||||||||||||||||||||
58 | 2/10/2016 20:15:17 | Peter Srajer | psrajer@shaw.ca | WSP Global | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping), Indoor Laser Scanning, Photogrammetry | LAS (ASPRS), LAZ, ZLAS, POD | LAS (ASPRS) | Digital Terrain Modelling, Feature Extraction | Civil Engineering, Asset Management | In a database | Timestamp, Intensity, Colour, Classification | To regular grid (raster), To TIN, To features (vector object rafter detection/recognition) | Temporal granularity at data set (a ‘point cloud’) level, Temporal resolution / update frequency months, Monitoring applications, change detection | Storage / Management, Combining Data from multiple source | File Format / Encoding | More than 1 billion (10^9) points | Potree, LAStools, GRASS, Esri ArcGIS, Bentley Pointools, Leica CloudWorx | |||||||||||||||||||||||||
59 | 2/11/2016 2:04:01 | Antonio San José | sanjosealbacete@yahoo.es | GIS Consultant | Airborne LiDAR, RADAR (PS-InSAR) | LAS (ASPRS), LAZ, ASCII | LAS (ASPRS), LAZ, ASCII | Visualization, Digital Terrain Modelling, Feature Extraction, GIS | Forestry, Hydrology, Archaeology | In a file on a computer, In a database | Intensity, Classification, Direction and Length of Scanline | To features (vector object rafter detection/recognition), None, direct use of point clouds | Monitoring applications, change detection | Storage / Management, Combining Data from multiple source | Data Model, File Format / Encoding | Less than 100 million (10^6) points | LAStools, GRASS, Esri ArcGIS, PosgreSQL/PostGIS, TerraSolid, FME | |||||||||||||||||||||||||
60 | 2/11/2016 3:59:53 | antoine cottin | a.cottin@carbomap.com | carbomap ltd | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping), RADAR (PS-InSAR) | LAS (ASPRS), LAZ, PulseWaves | LAS (ASPRS), LAZ, PulseWaves | Visualization, Digital Terrain Modelling, Feature Extraction, tree extraction | Forestry | In a file on a computer, In a file on a network drive | Intensity, Pulse Form, full-waveform analysis | None, direct use of point clouds | Temporal resolution / update frequency years, Monitoring applications, change detection | Visualization / Interaction | File Format / Encoding, industry needs to move towards Full-Waveform rather than just point cloud | More than 1 trillion (10^12) points | Potree, LAStools, GRASS, PCL, this list misses CloudCompare - we also use our in-house tools for full-waveform processing | |||||||||||||||||||||||||
61 | 2/11/2016 4:04:52 | Jorge Delgado | jdelgado@ujaen.es | Universidad de Jaén | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping), Indoor Laser Scanning, Photogrammetry | LAS (ASPRS), LAZ, POD, ASCII | LAS (ASPRS), LAZ | Visualization, Digital Terrain Modelling, Feature Extraction | Smart City, Heritage Documentation | In a file on a computer, In a file on a network drive | Intensity, Colour, Classification | To regular grid (raster), To TIN, Level of Detail (LoD) representation, To features (vector object rafter detection/recognition) | Temporal granularity at data set (a ‘point cloud’) level, Monitoring applications, change detection | Combining Data from multiple source, Analysis / Simluation | Data Model, Web Service (WxxS) protocol | More than 1 trillion (10^12) points | LAStools, Bentley Pointools, Leica CloudWorx, SOCET SET / DTM Master | |||||||||||||||||||||||||
62 | 2/11/2016 7:36:45 | Jon Horgan | jon.horgan@os.uk | Ordnance Survey | Photogrammetry | LAS (ASPRS), LAZ, ASCII | LAS (ASPRS), LAZ, ASCII | Visualization, Digital Terrain Modelling, Feature Extraction, GIS | Smart City | In a file on a computer, In a file on a network drive | Timestamp, Colour, Classification | To regular grid (raster), To TIN, To features (vector object rafter detection/recognition), 3D mesh | Temporal granularity at point level | Storage / Management, Analysis / Simluation | File Format / Encoding | More than 1 billion (10^9) points | Esri ArcGIS, TerraSolid, VR Mesh | |||||||||||||||||||||||||
63 | 2/11/2016 7:44:43 | James Holmes | james.holmes@renishaw.com | Renishaw plc | Terrestrial Lidar (including Mobile Mapping), SONAR (single and multi-beam echo’s) | LAS (ASPRS), LAZ, POD, ASCII, La20 (Trimble format) | LAS (ASPRS), LAZ, ASCII | Visualization, Digital Terrain Modelling, Feature Extraction | Hydrology, Civil Engineering, Asset Management | In a file on a computer, In a file on a network drive | Timestamp, Intensity, Classification | To TIN, None, direct use of point clouds | Monitoring applications, change detection | Combining Data from multiple source, Change Reference System, Analysis / Simluation | File Format / Encoding | More than 1 billion (10^9) points | Bentley Pointools, TerraSolid, Hydrographic software (e.g. QINSy, HYPACK, PDS), Trimble's Trident software, Maptek's I-Site Studio | |||||||||||||||||||||||||
64 | 2/11/2016 7:54:09 | Karol Krajewski | karol.krajewski@nmgroup.com | NMGroup | Airborne LiDAR | LAS (ASPRS), LAZ | LAS (ASPRS), LAZ | Digital Terrain Modelling, Feature Extraction, GIS | Asset Management, Utilities | In a database | Timestamp, Intensity, Colour, Classification, Pulse Count, Direction and Length of Scanline | To regular grid (raster), To TIN, None, direct use of point clouds | Temporal resolution / update frequency years, Monitoring applications, change detection | Combining Data from multiple source, Visualization / Interaction | DBMS / SQL, Web Service (WxxS) protocol | More than 1 trillion (10^12) points | Potree, LAStools, Bentley Pointools, TerraSolid, FME | |||||||||||||||||||||||||
65 | 2/11/2016 13:01:26 | Ian Davies | Ian@indeep-consulting.uk | Consultant | Airborne LiDAR, SONAR (single and multi-beam echo’s) | LAS (ASPRS), LAZ, ASCII | LAS (ASPRS), ASCII | Digital Terrain Modelling | Civil Engineering, Coastal zone management | In a file on a network drive | Timestamp, Intensity, Classification, Pulse Form, Pulse Count, Direction and Length of Scanline | To regular grid (raster), To TIN, Level of Detail (LoD) representation, To features (vector object rafter detection/recognition) | Temporal resolution / update frequency years | Storage / Management, Combining Data from multiple source, Visualization / Interaction | File Format / Encoding | More than 1 billion (10^9) points | LAStools, GRASS, CARIS, Fledermaus, TerraSolid | |||||||||||||||||||||||||
66 | 2/12/2016 4:13:59 | Lee McDougall | lee.mcdougall@ahr-global.com | AHR | Terrestrial Lidar (including Mobile Mapping), Indoor Laser Scanning | E57, POD, PTS, PTX, PCG, RCS | E57, POD, PCG, RCS | Visualization, Digital Terrain Modelling, Feature Extraction, Building Modelling | Civil Engineering, Design | In a file on a network drive, data centre, tape | Intensity, Colour | None, direct use of point clouds | Temporal granularity at data set (a ‘point cloud’) level | Dissemination | File Format / Encoding | More than 1 trillion (10^12) points | Leica CloudWorx, Recap, Point tools, Scene | |||||||||||||||||||||||||
67 | 2/12/2016 8:29:29 | Brédif | mathieu.bredif@ign.fr | IGN | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping), Indoor Laser Scanning, Photogrammetry | LAS (ASPRS), PLY, PostgreSQL-PostGIS PCPATCH | PLY | Visualization, Feature Extraction, City modelling, surface reconstruction, forestry | Forestry, Smart City, Civil Engineering, Asset Management | In a file on a computer, In a file on a network drive, In a database, In the cloud | Timestamp, Intensity, Colour, Classification, Pulse Form, Pulse Count, Direction and Length of Scanline, sensor position !!! | Level of Detail (LoD) representation, To features (vector object rafter detection/recognition), None, direct use of point clouds | Temporal granularity at point level, Temporal granularity at data set (a ‘point cloud’) level, Temporal resolution / update frequency years, Temporal resolution / update frequency months, Temporal resolution / update frequency days, Monitoring applications, change detection | Change Reference System, Analysis / Simluation, Dissemination | Data Model, Web Service (WxxS) protocol | More than 1 trillion (10^12) points | PDAL, Potree, LAStools, PosgreSQL/PostGIS, PCL | |||||||||||||||||||||||||
68 | 2/12/2016 18:23:48 | Adam Steer | adam.d.steer@gmail.com | National Computational infrastructure (Australia), ACE-CRC | Airborne LiDAR, Photogrammetry | LAS (ASPRS), ASCII, netCDF | ASCII | Visualization, as a start point for estimating characteristics of sea ice | marine cryosphere characterisation | In a file on a computer, In a file on a network drive | Timestamp, Intensity, scan angle, position uncertainty (x,y,z,3d), sometimes trajectory information | None, direct use of point clouds | Temporal granularity at point level, Temporal granularity at data set (a ‘point cloud’) level | Data Acquisition, Storage / Management | Data Model | More than 100 million (10^6) points | GRASS, Bentley Pointools, TerraSolid, PCL, CloudCompare, Python, MATLAB, QGIS | My work with point clouds has been really research-focussed. I've used 'standard' tools for some of my work (eg. terrasolid), but mainly work with customised coordinate systems and therefore customised software from raw laser data /aircraft trajectories -> point clouds. A big issue for me has been keeping all the data managed, since I have to track all the data and processing prior to spitting out a point cloud (from either lasers or cameras). So provenance, or lack thereof, is something I need to solve. I haven't used .las much purely because it is harder to work with than just messing around with text files (also awkward). I see a future in HDF formats (eg HDF or it's subset netCDF), because on that path I can quickly grab data in subsets, I can also track provenance, and versions, and .... In terrasolid, for example, the concept of flight lines is key to making things happen. In my mind it would be possible to index a netcdf file by line, and have some pretty simple wrappers to pull out data in whatever format desired (eg; pointcloud.tolas(data), or pointcloud.ingest(lasfile, line, ...) For 3D photogrammetry, for example, the point cloud is not really 4D but the aircraft trajectory is. If one wants to keep provenance, storing these things gets tricky unless a HDF style scheme is used. Anyway - it gets complicated. and I see only one small speck of the point cloud world. However - ina world moving toward semantic web style operations, I see no reason to commit all point clouds to a specific and rigid format, as much as some vendors would like. In a way, if there exists a metadata specification that is used everywhere, and can refer to a long list of formats, and the tools exist to translate, then a good and accepted metadata standard is possibly the best approach I can see. After all, data are just bits on a disk - the trick is making those bits meaningful! Cheers Adam | ||||||||||||||||||||||||
69 | 2/15/2016 4:51:32 | Bruce Napier | brn@bgs.ac.uk | British Geological Survey | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping), Photogrammetry | LAS (ASPRS), ASCII | LAS (ASPRS), ASCII | Visualization, Digital Terrain Modelling, geological interpretation | Geology | In a file on a computer, In a file on a network drive | Intensity, Colour | Level of Detail (LoD) representation, octree | Monitoring applications, change detection | Visualization / Interaction | Data Model, File Format / Encoding, Web Service (WxxS) protocol | More than 1 billion (10^9) points | LAStools, Esri ArcGIS, FME, GeoVisionary | |||||||||||||||||||||||||
70 | 2/16/2016 1:34:58 | gülch | eberhard.guelch@hft-stuttgart.de | HFT Stuttgart | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping), Indoor Laser Scanning, Photogrammetry | LAS (ASPRS), PLY | LAS (ASPRS), PLY | Visualization, Digital Terrain Modelling, Feature Extraction | Smart City | In a file on a computer | Timestamp, Intensity, Colour, Classification | To regular grid (raster), To features (vector object rafter detection/recognition) | Temporal granularity at point level | Combining Data from multiple source | Data Model | Less than 100 million (10^6) points | LAStools | |||||||||||||||||||||||||
71 | 2/16/2016 10:53:52 | Sherri Barnes | slbrne@mwdh2o.com | MWD | Terrestrial Lidar (including Mobile Mapping) | LAS (ASPRS), POD | LAS (ASPRS) | Digital Terrain Modelling, Feature Extraction | Civil Engineering, Land Surveying Topo | In a file on a network drive | Classification | None, direct use of point clouds | Temporal resolution / update frequency years, Temporal resolution / update frequency months, Monitoring applications, change detection | Data Acquisition, Visualization / Interaction | Data Model, File Format / Encoding | More than 100 million (10^6) points | Bentley Pointools | |||||||||||||||||||||||||
72 | 2/17/2016 15:16:04 | Peter Guth | pguth@usna.edu | US Naval Academy | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping), Photogrammetry | LAS (ASPRS), LAZ, 3D shapefile | LAS (ASPRS), LAZ | Visualization, Digital Terrain Modelling, GIS | Geology and general Terrain Analysis | In a file on a computer | Timestamp, Intensity, Colour, Classification, Direction and Length of Scanline | To regular grid (raster), None, direct use of point clouds | Monitoring applications, change detection | Combining Data from multiple source | File Format / Encoding | More than 1 billion (10^9) points | LAStools, MICRODEM, Cloud Compare | Any formats should be open with the specifications published. No format should lock users into a particular proprietary software package. Software should be free to optimize data formats for internal use, but the distribution formats should be open and documented | ||||||||||||||||||||||||
73 | 2/17/2016 15:18:38 | Tobias | tobias.kohoutek@digimapas.cl | digimapas chile | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping), Photogrammetry | LAS (ASPRS), LAZ, ASCII, SPD | LAS (ASPRS), LAZ, ASCII | Digital Terrain Modelling, Feature Extraction | Forestry, Civil Engineering | In a file on a network drive, In a database | Timestamp, Intensity, Classification, Pulse Count, Direction and Length of Scanline | To regular grid (raster), To TIN | Temporal granularity at point level, Monitoring applications, change detection | Storage / Management, Analysis / Simluation | Web Service (WxxS) protocol | More than 100 million (10^6) points | LAStools, Inpho, TopPit | |||||||||||||||||||||||||
74 | 2/17/2016 15:19:36 | Mateusz Loskot | mateusz@loskot.net | OSGeo | Airborne LiDAR | LAS (ASPRS), LAZ, PDAL-generated blocks | LAS (ASPRS), LAZ | Visualization, GIS | Forestry, Civil Engineering | In a file on a computer, In a file on a network drive | Timestamp, Intensity, Classification | To regular grid (raster), To TIN | Temporal granularity at data set (a ‘point cloud’) level | Data Acquisition, Combining Data from multiple source | Data Model, File Format / Encoding | More than 100 million (10^6) points | PDAL, LAStools, PosgreSQL/PostGIS | |||||||||||||||||||||||||
75 | 2/17/2016 15:24:41 | Kyle Shannon | kyle@pobox.com | Boise State Univerisity | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping) | LAS (ASPRS), ASCII, SQLite | LAS (ASPRS), ASCII, SQLite | Digital Terrain Modelling, Feature Extraction, GIS | Forestry, Hydrology, Water Management | In a file on a computer | Timestamp, Intensity, Colour, Classification, Pulse Form, Pulse Count | To regular grid (raster), None, direct use of point clouds | Temporal granularity at point level, Monitoring applications, change detection | Data Acquisition, Storage / Management, Combining Data from multiple source, Change Reference System, Analysis / Simluation, Dissemination, Visualization / Interaction | File Format / Encoding, DBMS / SQL | More than 100 million (10^6) points | LAStools, Custom written LASF access | I would strongly suggest investigating SQLite as a storage container. LASF is okay, but SQLite gives access to many programming and scripting languages with out extra work. APIs are easily written without 3rd party libraries, and can be written in native programming languages. Also, recent releases of SQLite have built in R*Tree based spatial indexing. GeoPackage uses SQLite for a good reason. | ||||||||||||||||||||||||
76 | 2/17/2016 15:25:27 | Mike Lackner | mlackner@uwaterloo.ca | University of Waterloo | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping), Photogrammetry | LAS (ASPRS), LAZ | LAZ | Visualization, Digital Terrain Modelling, Feature Extraction | variety (education) | In a file on a computer | Timestamp, Intensity, Colour, Pulse Count | To regular grid (raster), To features (vector object rafter detection/recognition) | Monitoring applications, change detection | Data Acquisition, Combining Data from multiple source, Change Reference System, Analysis / Simluation, Visualization / Interaction | File Format / Encoding, ideally open format and widely used (las/laz) | More than 100 million (10^6) points | LAStools, Esri ArcGIS, FME, eCognition, ENVI | I've been following that whole laz vs zlas conundrum, and don't understand why ESRI had to come up with their own closed proprietary format. Seemed to me that laz was doing all that zlas is doing and Martin from lastools was cooperative into adding further functionality if needed. So why duplicate the effort and create more work converting back and forth unnecessarily??? I like the ArcMap Lidar functionality and use it quite a bit but it annoys me a lot that I cannot use laz files directly and so far I haven't seen any advantage (or actual use) for zlas. I'm sure there's lots of politics involved there, but I'm hoping that whole zlas thing doesn't take off and companies that have embraced the laz approach stick with it and make it the de facto standard. | ||||||||||||||||||||||||
77 | 2/17/2016 15:25:37 | Jarlath O'Neil-Dunne | joneildu@uvm.edu | University of Vermont | Airborne LiDAR | LAS (ASPRS), LAZ | LAS (ASPRS), LAZ | Feature Extraction | Forestry, Hydrology, Smart City | In a file on a network drive | Intensity, Colour, Classification | To regular grid (raster), To features (vector object rafter detection/recognition) | Temporal granularity at data set (a ‘point cloud’) level | Data Acquisition | File Format / Encoding | More than 1 trillion (10^12) points | LAStools, Esri ArcGIS, FME, Quick Terrain Modeler | The biggest threat to LiDAR is proprietary formats. Keep LiDAR open! | ||||||||||||||||||||||||
78 | 2/17/2016 15:30:15 | Ramesh Sridharan | Ramesh.Sridharan@Autodesk.com | AUTODESK, INC. | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping), Indoor Laser Scanning, Photogrammetry | LAS (ASPRS), E57, ASCII, RCS | LAS (ASPRS), RCS | Visualization, Digital Terrain Modelling, Feature Extraction, GIS, 3D Modeling | Forestry, Hydrology, Water Management, Smart City, Civil Engineering, Asset Management | In a file on a computer, In a file on a network drive, In the cloud | Timestamp, Intensity, Colour, Classification | To regular grid (raster), To TIN, Level of Detail (LoD) representation, To features (vector object rafter detection/recognition), None, direct use of point clouds | Temporal granularity at point level, Temporal granularity at data set (a ‘point cloud’) level, Monitoring applications, change detection | Analysis / Simluation, Visualization / Interaction | Data Model, File Format / Encoding | More than 1 trillion (10^12) points | Autodesk products like ReCap and Infraworks | |||||||||||||||||||||||||
79 | 2/17/2016 15:31:27 | Thomas Knudsen | thokn@sdfe.dk | SDFE - the Danish National Mapping Authority | Airborne LiDAR | LAS (ASPRS), LAZ | LAZ | Digital Terrain Modelling | NMA | In a file on a network drive, In a database | Timestamp, Intensity, Colour, Classification, Pulse Count, Full LAS1.3 gamut | To regular grid (raster), To TIN, None, direct use of point clouds | Temporal granularity at point level, Monitoring applications, change detection, Granularity at Data subset (tile) level | None. LAS ensures interoperability | File Format / Encoding, Web Service (WxxS) protocol | More than 1 billion (10^9) points | PDAL, Potree, LAStools, PosgreSQL/PostGIS, TerraSolid, QGIS | I find Esri's pushing for a closed file format (zlas) absolutely detrimental to interoperability, and countering a National Mapping Authority mission of ensuring long term access and interoperability of elevation data. Please have this in mind in OGC's further work om point cloud data | ||||||||||||||||||||||||
80 | 2/17/2016 15:33:22 | Arjan van houwelingen | Houwe191@yahoo.ca | Vansteenis geodesie | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping) | LAS (ASPRS), LAZ, ASCII | LAS (ASPRS), LAZ, ASCII | Visualization, Feature Extraction | Water Management, Civil Engineering, Asset Management | In a file on a computer | Timestamp, Intensity, Colour, Classification, Direction and Length of Scanline | To regular grid (raster), To TIN, To features (vector object rafter detection/recognition), None, direct use of point clouds | Temporal granularity at point level, Temporal granularity at data set (a ‘point cloud’) level | Data Acquisition, Storage / Management, Combining Data from multiple source, Analysis / Simluation, Visualization / Interaction | Data Model, File Format / Encoding | More than 1 billion (10^9) points | PDAL, LAStools, GRASS, Esri ArcGIS, Leica CloudWorx, TerraSolid, FME, Leica cyclone and map factory | |||||||||||||||||||||||||
81 | 2/17/2016 15:39:50 | Doug Newcomb | doug_newcomb@fws.gov | USFWS | Airborne LiDAR | LAS (ASPRS), LAZ, ASCII | LAS (ASPRS), LAZ | Digital Terrain Modelling, Feature Extraction | Forestry, Hydrology | In a file on a computer | Timestamp, Intensity, Colour, Classification, Pulse Count, Direction and Length of Scanline | To regular grid (raster) | Temporal granularity at point level, Temporal resolution / update frequency years, Monitoring applications, change detection | Data Acquisition, Combining Data from multiple source, Change Reference System | File Format / Encoding | More than 1 billion (10^9) points | PDAL, LAStools, GRASS | |||||||||||||||||||||||||
82 | 2/17/2016 15:49:20 | Jacob Edwards | jacob.edwards@dogami.state.or.us | Oregon Dpeartment of Geology and Mineral Industries | Airborne LiDAR | LAS (ASPRS), LAZ | LAZ | Visualization, Digital Terrain Modelling, Feature Extraction, GIS | Forestry, Hydrology, Water Management, Civil Engineering | In a file on a network drive | Timestamp, Intensity, Colour, Classification, Pulse Form, Pulse Count, Direction and Length of Scanline | To regular grid (raster) | Temporal resolution / update frequency years | Storage / Management, Change Reference System, Dissemination | File Format / Encoding | More than 1 trillion (10^12) points | LAStools, Esri ArcGIS, Bentley Pointools, TerraSolid, Quick Terrain Modeler | I prefer open LiDAR formats over proprietary clones | ||||||||||||||||||||||||
83 | 2/17/2016 15:49:24 | David Webb | david.webb@transgrid.com.au | TransGrid | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping) | LAS (ASPRS), LAZ, POD, IMP | LAS (ASPRS), POD | Visualization, Digital Terrain Modelling, Feature Extraction | Forestry, Civil Engineering, Asset Management | In a file on a network drive | Intensity, Colour, Classification | To regular grid (raster), To TIN, To features (vector object rafter detection/recognition), None, direct use of point clouds | Temporal resolution / update frequency years, Monitoring applications, change detection | Storage / Management, Combining Data from multiple source | File Format / Encoding | More than 1 trillion (10^12) points | Potree, LAStools, Bentley Pointools, Leica CloudWorx, TerraSolid, FME, Leica Cyclone | |||||||||||||||||||||||||
84 | 2/17/2016 15:58:31 | Kari Salovaara | kari.salovaara@pp1.inet.fi | OSGeo Finland | Airborne LiDAR | LAZ, PostgreSQL-PostGIS PCPATCH, PDAL-generated blocks | LAZ, PostgreSQL-PostGIS PCPATCH, PDAL-generated blocks | Digital Terrain Modelling, GIS | nature cons., ecology | In a file on a computer, In a database | Timestamp, Intensity, Colour, Classification, Pulse Form, Pulse Count, Direction and Length of Scanline | To regular grid (raster), To TIN, Level of Detail (LoD) representation, To features (vector object rafter detection/recognition) | Temporal granularity at data set (a ‘point cloud’) level | Data Acquisition, Combining Data from multiple source, Analysis / Simluation, Dissemination | Data Model, File Format / Encoding, DBMS / SQL | More than 100 million (10^6) points | PDAL, LAStools, GRASS, PosgreSQL/PostGIS | |||||||||||||||||||||||||
85 | 2/17/2016 16:35:57 | Floris Groesz | floris.groesz@blomasa.com | Blom | Airborne LiDAR, Photogrammetry | LAS (ASPRS), LAZ, Terrasolid Fast Binary | LAS (ASPRS), LAZ, ASCII | Visualization, Digital Terrain Modelling, Feature Extraction, Modelling of forest variables | Forestry, terrain analysis | In a file on a network drive | Timestamp, Intensity, Colour, Classification, Pulse Count, Direction and Length of Scanline | To regular grid (raster), To features (vector object rafter detection/recognition), None, direct use of point clouds | Temporal granularity at point level, Temporal granularity at data set (a ‘point cloud’) level, Monitoring applications, change detection | Analysis / Simluation | Data Model, File Format / Encoding | More than 1 billion (10^9) points | LAStools, Esri ArcGIS, TerraSolid, eCognition, Global Mapper, R | The name "zlas" by ESRI and the term "optimized LAS" is confusing. There should be a clear distinction between open/standard formats and proprietary formats, also for compressed versions. The success of the LAS format has been of great benefit to all producers and users of point cloud data. This success should not be nullified during shift to compressed formats. | ||||||||||||||||||||||||
86 | 2/17/2016 16:40:10 | Ben Discoe | bdiscoe@gmail.com | Leica Geosystems | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping), Indoor Laser Scanning | LAS (ASPRS), E57 | LAS (ASPRS), E57, ASCII | Visualization, Digital Terrain Modelling, Feature Extraction, GIS | Hydrology, Civil Engineering, Asset Management | In a file on a computer, In a file on a network drive, In a database, In the cloud | Intensity, Colour, Classification, Normals | To TIN, Level of Detail (LoD) representation | Temporal granularity at data set (a ‘point cloud’) level | Storage / Management, Combining Data from multiple source, Change Reference System, Dissemination, Visualization / Interaction | File Format / Encoding, Web Service (WxxS) protocol | More than 1 billion (10^9) points | LAStools, Leica CloudWorx | |||||||||||||||||||||||||
87 | 2/17/2016 17:02:45 | Dr. Uwe Bacher | uwe.bacher@geo4you.de | Geo4You.de | Photogrammetry | LAS (ASPRS), PLY | LAS (ASPRS), PLY | Digital Terrain Modelling, GIS | Forestry, Civil Engineering | In a file on a computer | Timestamp, Intensity, Colour | To regular grid (raster), None, direct use of point clouds | Monitoring applications, change detection | Analysis / Simluation, Visualization / Interaction | Data Model, File Format / Encoding | More than 100 million (10^6) points | GRASS | |||||||||||||||||||||||||
88 | 2/17/2016 17:19:14 | yuichi hayakawa | hayakawa@csis.u-tokyo.ac.jp | Univ Tokyo | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping), Indoor Laser Scanning, Photogrammetry | LAS (ASPRS), LAZ | LAS (ASPRS), LAZ, ASCII | Digital Terrain Modelling, Feature Extraction, GIS | geomorphology | In a file on a computer | Intensity, Colour | To regular grid (raster), To TIN | Temporal resolution / update frequency years, Temporal resolution / update frequency months, Monitoring applications, change detection | Data Acquisition, Storage / Management, Analysis / Simluation, Visualization / Interaction | File Format / Encoding | More than 1 billion (10^9) points | Potree, LAStools, Esri ArcGIS | |||||||||||||||||||||||||
89 | 2/17/2016 17:51:05 | ariel c. blanco | ariel.blanco@coe.upd.edu.ph | university of the philippines | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping), Indoor Laser Scanning, Photogrammetry, SONAR (single and multi-beam echo’s) | LAS (ASPRS), LAZ | LAS (ASPRS), LAZ | Visualization, Digital Terrain Modelling, Feature Extraction, GIS | Forestry, Hydrology, Water Management | In a file on a computer, In a file on a network drive, In a database | Timestamp, Intensity, Colour, Classification, Pulse Form, Pulse Count, Direction and Length of Scanline | To regular grid (raster), To TIN, To features (vector object rafter detection/recognition), None, direct use of point clouds | Temporal granularity at data set (a ‘point cloud’) level, Temporal resolution / update frequency years, Temporal resolution / update frequency months, Monitoring applications, change detection | Storage / Management, Combining Data from multiple source | Data Model, File Format / Encoding | More than 1 billion (10^9) points | LAStools | |||||||||||||||||||||||||
90 | 2/17/2016 18:33:23 | Bill Kruse | bkruse@kruseimaging.com | Kruse Imaging | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping), Photogrammetry, SONAR (single and multi-beam echo’s) | LAS (ASPRS), LAZ | LAS (ASPRS), LAZ, Flat table | Visualization, Digital Terrain Modelling, Feature Extraction, GIS | Forestry, Hydrology | In a file on a computer, In a file on a network drive | Timestamp, Intensity, Colour, Classification, Pulse Count, Direction and Length of Scanline | To regular grid (raster), To features (vector object rafter detection/recognition) | Temporal granularity at point level, Temporal granularity at data set (a ‘point cloud’) level, Temporal resolution / update frequency years, Monitoring applications, change detection | Storage / Management, Combining Data from multiple source | Data Model, File Format / Encoding | More than 1 billion (10^9) points | PDAL, LAStools, GRASS, Esri ArcGIS, PCL | |||||||||||||||||||||||||
91 | 2/17/2016 18:50:42 | Cameron Wallace | cameron.wallace@snclavalin.com | SNC Lavalin Inc. | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping), Photogrammetry | LAS (ASPRS), ASCII, CSAR, PostgreSQL-PostGIS PCPATCH, Flat table | LAS (ASPRS), ASCII, CSAR, PostgreSQL-PostGIS PCPATCH, Flat table | Visualization, Digital Terrain Modelling, Feature Extraction, GIS | Forestry, Hydrology, Water Management | In a file on a computer, In a file on a network drive, In a database | Timestamp, Intensity, Classification | To regular grid (raster), To TIN, To features (vector object rafter detection/recognition), None, direct use of point clouds | Temporal granularity at data set (a ‘point cloud’) level, Temporal resolution / update frequency days | Storage / Management, Combining Data from multiple source, Dissemination, Visualization / Interaction | File Format / Encoding | More than 100 million (10^6) points | Esri ArcGIS, PosgreSQL/PostGIS, CARIS | open compressed standards would be great. I'm primarily a consumer of data at this point, although we may start producing some in the future. | ||||||||||||||||||||||||
92 | 2/17/2016 19:42:54 | Mark Seibel | Mseibel@ectinc.com | Environmental consulting and technology Inc. | Airborne LiDAR | LAZ | LAS (ASPRS) | Visualization, Digital Terrain Modelling, Feature Extraction, GIS | Hydrology | In a file on a network drive, Moving towards PostgreSQL with lidar extension | Timestamp, Intensity, Classification | To regular grid (raster), Level of Detail (LoD) representation | Temporal granularity at data set (a ‘point cloud’) level, Temporal resolution / update frequency years | None, we use laz or las | File Format / Encoding | More than 1 billion (10^9) points | PDAL, LAStools, GRASS, Esri ArcGIS, MCC lidar | Please help keep lidar formats open. I've been a geospatial analytical professional for almost 20 years. I also administer Linux systems and heavily use I also use FOSS. I am on the analytical use and data distribution side. Few things are as frustrating as dealing with proprietary data formats. They are an obstacle to the progress of research and knowledge. They prevent sharing of data. Lidar, like other geospatial data, best serves the global community by openly accessible formats. | ||||||||||||||||||||||||
93 | 2/17/2016 20:22:00 | Ben Edmond | Ben@connected2fiber.com | Connected2Fiber | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping) | PostgreSQL-PostGIS PCPATCH | PostgreSQL-PostGIS PCPATCH | Visualization, GIS | Asset Management | In the cloud | Timestamp, Classification | To features (vector object rafter detection/recognition) | Temporal granularity at point level | Data Acquisition, Dissemination | Data Model | More than 100 million (10^6) points | PosgreSQL/PostGIS | |||||||||||||||||||||||||
94 | 2/17/2016 21:37:01 | Shanmugam Ganeshkumar | Ganesh@geicon.com | GeoICON | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping) | LAS (ASPRS), ASCII, PostgreSQL-PostGIS PCPATCH, PDAL-generated blocks | LAS (ASPRS) | Visualization, Digital Terrain Modelling, GIS | Smart City, Asset Management | In a file on a network drive, In a database | Timestamp, Intensity, Colour, Direction and Length of Scanline | Level of Detail (LoD) representation | Temporal granularity at point level, Temporal resolution / update frequency months, Temporal resolution / update frequency days | Storage / Management, Combining Data from multiple source, Analysis / Simluation, Visualization / Interaction | Data Model, File Format / Encoding, DBMS / SQL, Web Service (WxxS) protocol | Less than 100 million (10^6) points | PDAL, LAStools, PosgreSQL/PostGIS | Please keep the format open. Don't like esri approach. | ||||||||||||||||||||||||
95 | 2/17/2016 21:37:06 | Shanmugam Ganeshkumar | Ganesh@geicon.com | GeoICON | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping) | LAS (ASPRS), ASCII, PostgreSQL-PostGIS PCPATCH, PDAL-generated blocks | LAS (ASPRS) | Visualization, Digital Terrain Modelling, GIS | Smart City, Asset Management | In a file on a network drive, In a database | Timestamp, Intensity, Colour, Direction and Length of Scanline | Level of Detail (LoD) representation | Temporal granularity at point level, Temporal resolution / update frequency months, Temporal resolution / update frequency days | Storage / Management, Combining Data from multiple source, Analysis / Simluation, Visualization / Interaction | Data Model, File Format / Encoding, DBMS / SQL, Web Service (WxxS) protocol | Less than 100 million (10^6) points | PDAL, LAStools, PosgreSQL/PostGIS | Please keep the format open. Don't like esri approach. | ||||||||||||||||||||||||
96 | 2/17/2016 22:43:21 | John Armston | john.armston@dsiti.qld.gov.au | Queensland Government | Airborne LiDAR, Terrestrial Lidar (including Mobile Mapping) | LAS (ASPRS), LAZ, SPD | LAS (ASPRS), LAZ, SPD | Digital Terrain Modelling, Feature Extraction | Forestry, Hydrology | In a file on a computer, Tape mass storage connected to a HPC | Timestamp, Intensity, Colour, Classification, Pulse Form, Pulse Count, Direction and Length of Scanline, Waveform derived return metrics | To regular grid (raster), None, direct use of point clouds | Temporal granularity at data set (a ‘point cloud’) level, Temporal resolution / update frequency years, Temporal resolution / update frequency months, Monitoring applications, change detection | Data Acquisition, Combining Data from multiple source | Data Model | More than 1 billion (10^9) points | PDAL, Potree, LAStools, PosgreSQL/PostGIS, spdlib; pylidar | |||||||||||||||||||||||||
97 | 2/18/2016 1:35:13 | Claudia Knoor | claudia.knoor@bezreg-koeln.de | Bezirksregierung Köln | Airborne LiDAR | ASCII | LAS (ASPRS), ASCII | Digital Terrain Modelling, Feature Extraction | Civil Engineering | In a file on a network drive | Classification | To regular grid (raster), None, direct use of point clouds | x | Data Acquisition | File Format / Encoding | More than 1 billion (10^9) points | Trimble-Inpho | |||||||||||||||||||||||||
98 | 2/18/2016 2:03:15 | Antonio San José | sanjosealbacete@yahoo.es | GIS Consultant | Airborne LiDAR, RADAR (PS-InSAR) | LAS (ASPRS), LAZ, ASCII | LAS (ASPRS), LAZ, ASCII | Visualization, Digital Terrain Modelling, Feature Extraction, GIS | Forestry, Hydrology | In a file on a computer, In a file on a network drive | Intensity, Classification, Direction and Length of Scanline | To features (vector object rafter detection/recognition), None, direct use of point clouds | Monitoring applications, change detection | Combining Data from multiple source | Data Model, File Format / Encoding | Less than 100 million (10^6) points | LAStools, GRASS, Esri ArcGIS, TerraSolid, FME | |||||||||||||||||||||||||
99 | 2/18/2016 2:06:21 | Andreas Røstad | andreas.rostad@kartverket.no | Norwegian Mapping Authority | Airborne LiDAR | LAS (ASPRS), LAZ | LAS (ASPRS), LAZ | Visualization, Digital Terrain Modelling, GIS, Distribution to users. | Distribution to users. | In a file on a network drive, In the cloud | Timestamp, Intensity, Classification | None, direct use of point clouds | Temporal granularity at point level, Temporal granularity at data set (a ‘point cloud’) level, Temporal resolution / update frequency years, Temporal resolution / update frequency months, Temporal resolution / update frequency days, Temporal resolution / update frequency seconds | Storage / Management, Combining Data from multiple source, Change Reference System | Data Model, File Format / Encoding | More than 1 billion (10^9) points | LAStools | |||||||||||||||||||||||||
100 | 2/18/2016 2:13:58 | Marcin Sołoguba | marcin.sologuba@bialystok.lasy.gov.pl | Regional Directorate of The State Forests in Bialystok | Airborne LiDAR | LAZ | LAZ | Digital Terrain Modelling, GIS | Forestry | In a file on a computer | Intensity, Colour | To regular grid (raster), To features (vector object rafter detection/recognition) | Temporal resolution / update frequency years | Combining Data from multiple source, Visualization / Interaction | Data Model, File Format / Encoding | More than 100 million (10^6) points | PDAL, LAStools |