LiDAR to DEM – How to Determine Average Points Spacing and Cell Size in ArcGIS

arcgis-10.1arcgis-desktopdemlidarraster

I am using ArcGIS 10.1 to generate a DEM (bare earth) from LAS dataset. To accomplish this, I use Las Dataset to Raster tool as described in Esri website.

I have read here and there in the web that the the cell size of the output raster should be set at a value corresponding to the average LAS points spacing; somewhere else, they suggest to use a value that is three times the average point spacing.

Now, since I wish to produce a bare earth DEM (i.e., with only ground returns), I am wondering if the cell size has to be set at the average point spacing of the whole LAS dataset (i.e., comprising non-ground, ground, etc), or exclusively of the ground points?

On the basis of the ArcGIS's point file information tool (example), I managed to get statistics for each LiDAR class. The average spacing (whole dataset) is 1.5 m, while for ground points only is 0.67.

Any insight into the issue?

Best Answer

It really depends on what you're going for here. If your goal is to make accurate measurements, you will want the grid spacing to be smaller, around the average point spacing of the dataset. If this is part of a process of creating orthophotos or analyzing watersheds, or any other task which requires a more generalized terrain model, you will want the spacing to be larger.

Also, if you've filtered the data to the ground points, USE THOSE! You can ignore the other classifications.

Three times the size of the point spacing is generally considered a good idea for generalization because it allows the grid cell three points to average out to a theoretically consistent value. In my profession, sometimes when I produce orthophotos I allow a huge grid size, often 8-12 times the size of the point spacing.

My point (heh) is: there is no right or wrong way to produce a bare earth model. Sure, there are specifications sometimes (and if this is one of those cases, I suggest you disregard whatever I'm saying and follow the specifications), but producing what you need to suit your problem can be totally heuristic.

Do you want a more rigid, presumably more accurate model with harder edges on which you can model terrain more precisely? Use a smaller spacing. Do you want a more general terrain model that is smoother, less precise, but shows the overall terrain characteristics of a large area? Use a large spacing.

A lot of this is trial and error. That's the beauty of this kind of thing: it's about 30% science and 70% art.

Related Solutions

[GIS] Determining bare earth DEM from unclassified LAS file

Generating LiDAR DEMs from unclassified point clouds with:

MCC-LIDAR - Multiscale Curvature Classification (MCC) algorithm.
_{(supports LAS versions 1.1 to 1.3)}

MCC-LIDAR is a command-line tool for processing discrete-return LIDAR data in forested environments (Evans & Hudak, 2007).

Workflow:

a) unclassified point cloud.
b) ground returns classified.
c) bare-earth DEM (raster).

enter image description here

Let's create a hypothetical situation to further provide an example with code.

MCC-LIDAR is installed in:

C:\MCC

The unclassified LiDAR point cloud (.las file) is in:

C:\lidar\project\unclassified.las

The output which are going to be the bare-earth DEM is in:

C:\lidar\project\dem.asc

The example below classifies ground returns with the MCC algorithm and create a bare-earth DEM with 1 meter resolution.

#MCC syntax: 
#command
#-s (spacing for scale domain)
#-t (curvature threshold)
#input_file (unclassified point cloud) 
#output_file (classified point cloud - ground -> class 2 and not ground -> class 1)
#-c (cell size of ground surface)
#output_DEM (raster surface interpolated from ground points)

C:\MCC\bin\mcc-lidar.exe -s 0.5 -t 0.07 C:\lidar\project\unclassified.las C:\lidar\project\classified.las -c 1 C:\lidar\project\dem.asc

To understand better how the scale (s) and the curvature threshold (t) parameters work, read: How to Run MCC-LiDAR and; Evans and Hudak (2007).

The parameters need to be calibrated to avoid commission/labeling errors (when a point is classified as belonging to the ground but actually it belongs to vegetation or buildings). For example:

enter image description here

The MCC-LIDAR uses Thin Plate Spline (TPS) interpolation method to classify ground points and generate the bare-earth DEM.

_References:

_{Evans, Jeffrey S.; Hudak, Andrew T. 2007. A multiscale curvature algorithm for classifying discrete return LiDAR in forested environments. IEEE Transactions on Geoscience and Remote Sensing. 45(4): 1029-1038.}

_{For more options about ground point classification algorithms, see Meng et al. (2010):}

_{Meng, X.; Currit, N.; Zhao, K. (2010). Ground Filtering Algorithms for Airborne LiDAR Data: A Review of Critical Issues. Remote Sensing, 2(3), 833–860. doi:10.3390/rs2030833}

Best Answer

Related Solutions

[GIS] Determining bare earth DEM from unclassified LAS file

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