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Background:

ArcGIS Desktop 10.5.1, Spatial analyst

We have acquired two bare-earth DEMs derived from lidar. YEAR2007 was produced in 2007, and YEAR2015 eight years later. Both are 32-bit, floating-point tifs, with the same horizontal and vertical CRS/projection/datum and same pixel size (3 feet). YEAR2015 was snapped to YEAR2007.

We compared elevation values for both years at known control points on roads with open sky views. Both years matched the known values closely, within a mean difference of about 0.1 feet and standard deviation of about 0.3 feet.

Here's a hillshade of the project watershed (northwest Washington state, USA) created from YEAR2007, with a few streams superimposed. Note that the ridges trend northerly. All appears normal. YEAR2015 looks similar:

enter image description here

The Problem:

We need to determine where stream channel deposition and erosion occurred between the two years by looking for increases or decreases in channel elevation, respectively. To accomplish this, we used the SA Minus tool, subtracting YEAR2007 from YEAR2015 (that is, YEAR2015 - YEAR2007).

For the output "minus" tif, we assigned a blue color ramp to cells where elevation values increased between the two years, and a pink-red color ramp for decreased elevation values.

The output is displayed below. This is where the weirdness appears.

Although no hillshade is used in the following image, it has that impression because the blue and pink areas tend to follow the slope aspect(!) That is, easterly-facing slopes tend to contain increased elevation cells between the two years, and westerly-facing slopes tend to contain decreased elevation cells.

Using the Identify button, typical blue increases are around +2 feet, and pink decreases trend closer to -3 feet.

How is this possible? When compared at known control points, the two DEM elevation values match closely, as described above. But the difference output is, well, really different, with the odd pattern related to aspect.

Everyone here is scratching their head, and an internet search turns up nothing.

Certainly the earth has not heaved around according to aspect in the intervening eight years. Yet there certainly appears to be a relationship between aspect and DEM elevation differences!

enter image description here

Here is a satellite image dated August, 2016:

enter image description here


After a great deal of testing, I did find the solution, which turned out to be quite simple.

The solution: shift one of the rasters (I chose YEAR2007) EXACTLY one cell to the EXACT northeast. Voila!, after subtracting the two rasters, the aspect effect disappeared completely - problem solved!

Although the two years' rasters were previously snapped and visually registered, this simple one-cell shift instantly and completely removed the aspect appearance. Based on the various helpful comments, I tested a lot of shifting in varying direction/distance combinations. Using the SA Shift tool, I shifted the YEAR2007 raster (recall, 3-foot cell size) each of the eight cardinal directions (north, northeast, east...) by the following distances (in feet):

0.01, 1.00, 3.00, 4.00, 6.00, 7.00, 7.50, 7.75, 8.00, 9.00

That's 80 different direction/distance combinations. After subtraction, the ONLY one that solved the problem was, as previously mentioned, to shift one of the two rasters exactly 3.00 feet - one cell - to the northeast (that is, 3.00 feet to the north and 3.00 feet to the east).

All 79 other combinations, following subtraction, resulted in some type of aspect effect.

(FWIW, given the 3-foot cell size, shifting at the 3.00, 6.00 and 9.00 distances retained the original snapping; all other values "undid" the snap)

With the problem solved, I was able to complete the project.

However, the original question remains unanswered: How does the elevation difference between the two (now known to be misaligned) years result in an ASPECT effect?

Perhaps re-framing the question would be of interest: Imagine that these two rasters had been correctly registered from the beginning, showing no aspect effect upon subtraction. Would we then expect to create an output aspect raster by 1) purposely mis-aligning them and then 2) subtracting them? Is that how the SA Aspect tool works?

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    The first step is to align the values properly, not just snapping the cell boundaries together, find immutable locations between the rasters and perform a very fine (subpixel) adjustment... then resample to a larger cell size to spread the difference. The problem isn't so much Z as XY. Between 2007 and 2015 there has been some advancement in LiDAR technology which can also show false differences if the scanners used are different. Commented May 16, 2018 at 5:25
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    More vegetation on east facing slopes? Are seasons the same? Wetter year? Perhaps add aerial image.
    – FelixIP
    Commented May 16, 2018 at 5:43
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    I'd use a script to find x shift that result in minimum standard deviation for difference raster or simply try minus 1, plus 1 cell shift s.
    – FelixIP
    Commented May 16, 2018 at 21:12
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    When it comes to change detection lines up pretty well isn't good enough, the alignment needs to be less than half your cell size in the XY; any difference less than the sum of your vertical accuracy can be considered superfluous, the values in this range must be omitted from the results. Do you have the LiDAR that made these DEMs? If the DEMs were created using different methods which will also lead to noise, it might be better to coalign the multipoints and generate the DEMs again to take control of the process. If it's still stubborn you will need to perform a Z adjustment (last resort) Commented May 16, 2018 at 22:27
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    Maybe one of the surfaces was reprojected using a transformation that introduced a slight shift in the data. The control point were placed on roads and the shift was not evident when you compared control point z values because the width of the road is greater than the pixel size? 2007 LiDAR for Mount Baker? What is the data source. It does not appear on the PSLC or DNR Portal.
    – GBG
    Commented May 17, 2018 at 15:38

1 Answer 1

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The two scans are not properly aligned in east-west direction.

alignment error

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