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16

Given that you have the LIDAR DEM, you should use the streams derived from it. That guarantees perfect registration. The crux of the idea is to estimate mean slopes in terms of the elevations at the ends of the segments. One of the easiest procedures is to "explode" the stream network into its component unbranched arcs. Convert the collection into a ...


16

Commercial: FME Desktop " ability to take a point cloud that has no color information on it, and overlay it into an orthophoto to produce a colorized point cloud" http://blog.safe.com/2012/01/beating-lidar-into-submission-with-fme-2012/ LP360 Add-on to ArcGIS http://www.qcoherent.com/products/index.html LP360 for ArcGIS™ (Basic, Standard and Advanced) ...


11

FUSION/LDV is a powerful and solid open source option developed by the USDA Forest Service to analyze and visualize LiDAR data. General information about FUSION can be found here: Overview of FUSION features: Generates DEMs from point data Produces bare earth surfaces from unfiltered points Displays image data for background reference Subsamples large ...


11

Your PointsXYZIC is now a numpy array. Which means you can use numpy indexing to filter the data you're interested in. For example you can use an index of booleans to determine which points to grab. #the values we're classifying against unclassified = 1 ground = 2 #create an array of booleans filter_array = np.any( [ PointsXYZIC[:, 4] == ...


11

ESRI has a pretty good help section on LiDAR (below). For more formal details on LiDAR, I would recommend the following books: Topographic Laser Ranging and Scanning: Principles and Processing Airborne and Terrestrial Laser Scanning Remote Sensing and Image Interpretation LiDAR Laser Returns Laser pulses emitted from a lidar system reflect from ...


10

This sounds like Tom Patterson's work on Resolution Bumping GTOPO 30 in Photoshop. The theory is described well enough to be adaptable to other software, though work needs to be done coming up with the specifics. The basic idea is to generalize (blur) one data set, a lot, to emphasize the general shape and hide specific detail and then blend the hi-res and ...


10

I'm a little late to the party but here is another suggestion: http://potree.org/ It's an open souce, WebGL based point cloud viewer I've been working on for quite a while. == UPDATE == It can render large amounts of colored point clouds. LIDAR data without colors will be supported soon. Showcase: http://potree.org/wp/demo/ Source code: ...


10

ArcGis has a new LiDAR dataset at 10.1 which will allow you to view your LiDAR data directly and also see more information than what's in a raster... for example you can add to ArcMap and then filter down the display to just tree classes, or just first returns! LiDAR data contains much more than just elevation, there's intensity that is stored by default ...


10

It sounds like you want either a voxel-based thinning or maybe a Poisson-based one. PDAL can do either. See PDAL's tutorial on the topic at http://www.pdal.io/tutorial/dart-throwing.html . As far as the size of the file, please define "large". Just about any technique except simple rank decimation (remove n-th points) is going to want to have access to ...


9

What about the liblas Python API (not sure how lightweight this is though)? >>> from liblas import file >>> f = file.File('file.las',mode='r') >>> for p in f: ... print 'X,Y,Z: ', p.x, p.y, p.z


9

Constructing lidar DEMs from unclassified point clouds with: MCC-LiDAR using the Multiscale Curvature Classification (MCC) algorithm. MCC-LIDAR is a command-line tool for processing discrete-return LIDAR data in forested environments" (Evans & Hudak, 2007). Workflow illustration (gross cloud --> ground returns classified --> bare-earth DEM): ...


9

For converting to las 1.2 from las 1.4, PDAL's translate command is an option: pdal translate --writers.las.minor_version=2 input-las14.las output-las12.las LAStools can also do the job: las2las -i input-las14.las -set_version 1.2 -o output-las12.las In general, las 1.4 support is patchy among free and open-source las-aware software, e.g. liblas ...


8

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. ...


8

Sounds like you're wanting to do this in batch (don't blame you) As STH said, looks like Global Mapper will indeed do batch conversions. Nice price as well. FME Desktop can do using the RasterDEMGenerator transformer and a bit of linking with reader/writer, but you'll need the Pro version, not available in the ArcGIS Data Interop extension. If free is ...


8

I read about variety of algorithms for the job (ie. as per @Hornbydds link). I tried couple appoches, and the best results in my case yield Standard Terrain Analysis from SAGA. Here is what I did and why: Dikes are usually highest feature in the vicinity of river channel, so I turned them into channels by flipping DEM (MapAlgebra DEM * -1 or for ...


8

It all depends on where you draw the line. Regardless, this problem looks like it can be readily addressed using the morphological functions available in Spatial Analyst, especially thresholding (performed with "<" and ">" local operations) and "RegionGroup" to identify and extract components. Although I do not have access to the DEM to illustrate, the ...


8

A common mistake (that I've made too) is to down-sample a raster using the resample tool with bilinear interpolation. See this answer for an explanation why this is not good. A raster can be down-sampled in three steps. The first step might not be required. Reproject the raster to the target extents. Use bilinear interpolation, and keep the output cell ...


8

libLAS can indeed be used commercially. So can Martin Isenburg's LASlib, which is LGPL, and speaking as the author of libLAS, faster and more completely supported than libLAS. Both are indeed C++ libraries, however, and there isn't too much in the ASPRS LAS space for native .NET. I'm also the primary author of PDAL, and PDAL can also read ASPRS LAS data, ...


8

Inside a Geodatabase, there are certain ways you can't name a table or Feature Class. Beginning with a number is one of those ways. Validating Table and Field Names in Python: http://resources.arcgis.com/en/help/main/10.1/index.html#//002z00000020000000 Try renaming your table to las_1 or something and see if it works


8

laspy is another good LAS read/write software. It supports working with the data directly in numpy arrays and a number of other nice Pythonic features. It isn't processing software per se, however. PDAL has the ability to use Python as an in-pipeline filtering language, but this isn't a processing engine either. There isn't too much in the Python quiver ...


8

I develop a free and open-source GIS called Whitebox Geospatial Analysis Tools (can be downloaded here) that has extensive analysis functionality for processing LiDAR data. Whitebox contains a tool specifically for calculating the point-density of LiDAR LAS files called Point Density LiDAR. The tool is highly specific to LiDAR, taking one or more LAS ...


8

You already have a DEM; there is no need for you to create one. The DEM is contained within your files, i.e. you have two copies of the DEM, one contained within an ArcGIS ASCII raster and the other within a GeoTIFF. These are simply file formats that contain the raster data that is your DEM. One of the most common formats for a terrain model is as a regular ...


8

It depends on what version of the LAS specification you are using. If it is 1.3 or less, then the specs define georeferencing information using pre-defined (see specs) variable length records (VLRs) using the same format as the GeoTIFF: Georeferencing for the LAS format will use the same robust mechanism that was developed for the GeoTIFF standard. ...


8

Thank you for clarifying your question as it was previously quite unclear. You can read a multiband raster using the stack or brick function in the raster package and assign the associated RGB values to an sp SpatialPointsDataFrame object using extract, also from raster. Coercion of the data.frame object (which results from read.csv) to an sp point ...


8

I decided to merge other answers with mine to organize them into a tabular format. I think it is easier to read and manage for the future visitors: The table can be accessed from the following link in csv format: View: Free LiDar DataSources Download: Free LiDar DataSources


8

In terms of something akin to a spectral signature, the only way would be through the return intensity values, which are rarely calibrated. Unfortunately, there is really nothing expected in the characteristics of the return intensity that would separate rock and soil, the answer really is that this is not a likely outcome. Now, if you used surface texture ...


8

You should check what the scale and offset are for your file. This can be done as follows: van_taken.header.scale van_taken.header.offset This almost looks like an overflow error to me. The lower case x, y, and z properties need to re-scale and re-offset the coordinates to store it as an integer (which is how LAS files store them). To be honest, setting ...


7

How to compare two Digital Elevation Models (DEMs) Solution using the software R. #------------------------------------------------------------------------- #Creating a reproducible example library(raster) #simulating raster_1 f = system.file("external/test.grd", package="raster") DEM_1 = raster(f) #simulating raster_2 DEM_2 = DEM_1 # ...


7

Try running the sp_help_spatial_geography_index stored procedure to get details on how your spatial index is being used. You should be able to use something like: declare @ms_at geography = 'POINT (-95.66 30.04)' set @ms_at = @ms_at.STBuffer(1000).STAsText() exec sp_help_spatial_geography_index 'lidar', 'SPATIAL_lidar', 0, @ms_at; Post the results in ...


7

I've used SAGA-GIS for identifying tree canopy and creating DSM's from Lidar data. I was very impressed. SAGA seems to be an all around Vector/Rastor/Point Cloud processing tool. It is free and open source. It comes as 32-bit or 64-bit. It does have some scripting capabilities if you build the source code yourself with Python Bindings, but all the tools ...



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