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I am hoping to get some insight from others who are familiar with comparing multiple LiDAR surveys to one another. I have two LiDAR surveys with similar extents that I would like compare for elevation change. I have the point cloud .las files for each of them, so I am able to manipulate the original data in any way that is necessary.

So far, I have created 3 ft. resolution (1/2 the sampling density) rasters for each of the surveys using the same (IDW) interpolation method. I was hoping that by creating a grid of the same size for each of the surveys that I would get rid of any artifacts in the subtraction product. This has not been the case thus far as there is grid-like striping in the subtraction product. These artifacts result in about a +/- 3 feet error in the product. Maybe with a 3 feet grid spacing this is the best that I can hope for??

Does anyone have a comparison method that works well for them?

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  • Is it mandatory that the gridding happens to a finer resolution than the (ground) point spacing? Usually, to avoid artifacts, using 1 to 3 times the average ground point spacing is better. For example, see: gis.stackexchange.com/questions/101970/….
    – Andre Silva
    Nov 22, 2019 at 22:41

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I have a few thoughts that hopefully will assist you:

First, the fine print... I don't have any experience converting LAS to DEM, but I do have a fair amount of elevation change detection with LAS-derived DEMs.

Specific to the striping that you mentioned... as a US President once said, "I feel your pain!". In my experience striping (sometimes seen in DEM-derived hillshades, even resembling a hounds-tooth fabric pattern) has ALWAYS been due to improper resampling somewhere along the data handling chronology. With elevation data, NEVER use the Nearest Neighbor option (which is, unfortunately, often displayed as the default option - and thereby easily bypassed). I have found that the Bilinear Interpolation option generates great output without any striping. So I would recommend that you repeat every command and tool used in your process to get the LAS data to its current state and wherever there's a resampling technique option in the tool dialog (for example, it's right there in the Project Raster tool dialog) use Bilinear. For those tools that don't display a resampling technique, click the Environments... button at the bottom and replace any Nearest Neighbor options with Bilinear in the Raster Storage section. It only takes one Nearest Neighbor somewhere in your chronology for stripes to make their unwelcome appearance!

Other thoughts:

You mention that you have data sets from two different LIDAR projects. You'll need to assure that the two resulting DEMs are a) in the same CRS, both horizontally and vertically and b) exactly aligned to each other in the X-Y dimensions. The latter commonly involves adjusting the DEMs to fit several ground control points (think road intersections) located across the study area. There's lots of how-to articles on the internet if you are unfamiliar. I would also recommend becoming familiar (query GIS Stackexchange) with the snap raster concept found in Environment Settings > Processing Extent.

Even after taking pains to assure that both DEMs are aligned, I've still had to solve weird patterns following subtraction. Happy processing!

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  • Stu, thanks for the great feedback regarding the matter. I was not aware of raster snapping, though the thought of a misalignment has always run through my mind. I think that I generally have to much faith in the consultant/agency acquiring/processing the raw data.
    – JamesS
    Oct 22, 2019 at 17:07

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