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I want to load approximately 10 large LIDAR tiles for analysis. I have tried using ArcScene but it appears there is a limit on how much data ArcScene can handle at one time. Each tile is 65-90MB in size. The only returns that I am using (and that are available) are ground returns.

My computer has 8GB ram, an amd 6 core processor, and a really good video card. I am fairly certain that it is more than sufficient to handle large amounts of data.

I am not against using something other than an ESRI product to complete this task.

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6 Answers 6

up vote 8 down vote accepted

Tips: Note: Your computer has plenty of spec:

Develop a full or partial disk cache whenever possible. Disk caches allow data to be pre-rendered for optimum ArcGlobe/ArcScene display performance. Store ArcSDE/ArcScene data sets using the Cube projection This will avoid pyramid resampling and data reprojection for ArcGlobe.

http://webhelp.esri.com/arcgisdesktop/9.3/index.cfm?id=3482&pid=3453&topicname=Optimizing_ArcScene

http://webhelp.esri.com/arcgisdesktop/9.3/index.cfm?TopicName=Disk_cache_formats_in_ArcGlobe

Other helpful ArcGIS tips... (includes AMD Processors) http://mapperz.blogspot.com/2007/02/esri-arcgis-92-tips-and-tricks.html ArcGIS/Utilities/ArcMap Advanced Settings Use with Administrator Privileges.

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You may want to look into LAStools, which can do a number of data conversions and basic visualizations of input LAS files, and conversions to both TIN and DEM. The same author also wrote a tool to visualize LIDAR data with Google Earth that may be of use.

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In LAStools there is a small viewer called lasview.exe (README) that down-samples on the fly. When run via the GUI you can easily select a region of interest and re-run the viewer in full resolution for that area. –  Martin Isenburg Feb 13 '12 at 12:50
    
We appreciate replies from vendors and other commercially interested parties, Martin, but in such cases to retain credibility it's crucial that you identify your connection with the solution you are recommending. –  whuber Feb 13 '12 at 15:47
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You may try specific free softwares for lidar visualization:

  1. FugroViewer is a software specialized in geospatial data visualization (including LiDAR data).
  2. Quick Terrain Reader
  3. MARS® FreeView™
  4. Las Reader for ArcGis 9
  5. Las Reader for ArcGis 10
  6. PointVue LE
  7. M Lidar
  8. Bentley Pointools View
  9. ccViewer
  10. 3D Reshape Viewer
  11. Trimble RealWorks Viewer

This* is a research accomplished by Tobias Wittwer, which compared many of the lidar viewers listed above taking note of the file formats supported, display options and other functionalities. On page 11, the author lists the main advantages and disadvantages of these softwares.

*Wittwer, T. A short comparison of freely available point cloud viewers for Windows. v.1.3. www.geonext.nl. 2014.

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If you have access to the original .las files, you might want to try something like LP360. It is designed to speedily render LiDAR data... much faster than raster (and worlds faster than a point return shapefile or feature class.)

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I have access but its a matter of "what can I do with the data I already have?" –  Ryan Mendieta Aug 23 '10 at 11:47
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ArcGIS is a 32bit application and not a multi-threaded one so there are limits.

Did you try terrain datasets? You could also try generalizing your data.

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I thought about terrain, but wanted to find out if it was feasible to use the TINS that were already created. I found out GRASS has a 64 bit version but haven't found anything on memory/cpu limitations. –  Ryan Mendieta Aug 23 '10 at 11:49
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In lidar world, those aren't even large tiles! Rather than reiterate a snazzy presentation from the latest ESRI 2010 user conference, I'll point you to the pdf of the presentation.

It basically walks you through how to quickly pull point cloud data into a 2.5d rasterized dataset, instead of interpolating the mass points (important if using the ground dataset, since it's already interpolated from the rest of the cloud and usually fairly dense anyway).

This is especially useful if you don't want to spend the time waiting for data to load into a Terrain dataset.

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