NAD 1983 CSRS and transformations...

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06-07-2021 11:30 AM
N_W_S_E
New Contributor III

Hello my fellow Canadians!

Lately I have been researching more and more about transformations from NAD 1983 GCS to NAD 1983 CSRS GCS, and then NAD 1983 CSRS into WGS 1984 Web Mercator (auxiliary sphere), and the more I read, the more confusing it gets.

There are a few articles I have found, but they seem to be dated. This article is absolutely fantastic (shoutout to all of the ESRI Blog Creators, your information is invaluable, and has helped me immensely), but I don't think it has been updated to fit 2021 and all the changes that has happened to NAD 1983 CSRS.

 This article states:

Please note that different Geographic systems need specific transformations. As of 2018, CSRS v6 and v7 are becoming very popular - however there is no specific transformations available at this time. If using ArcGIS 10.6x, the newer v6 and v7 Geographic systems are available

With that being said I am using both ArcGIS Desktop 10.8.1 and ArcGIS Pro 2.8.

From the first article I linked, I downloaded the ON83CSv1.gsb from LIO / Geohub and created a custom transformation that transforms data from NAD 1983 ORIGINAL to NAD 1983 CSRS. This works perfectly to align data that has been projected in NAD 1983 to transform on-the-fly into NAD 1983 CSRS:

N_W_S_E_0-1623089596774.png

My confusion comes from the latter part of the article where Ms. Sibbet talks about doing a transformation to WGS 1984 Web Mercator (auxiliary sphere) in order to upload to ArcGIS Online (which I do a lot, hence I want to get this right).

Generally. she states that if transforming from NAD 1983 CSRS to WGS 1984 Web Mercator (auxiliary sphere), one should use the transformation: NAD_1983_CSRS_To_WGS_1984_2.

In her example, she uses her custom transformation followed by NAD_1983_To_WGS_1984_2:

N_W_S_E_1-1623089915400.png

After all this background info, I am finally getting to my question. Currently ArcGIS Pro is defaulting to the following:

N_W_S_E_2-1623089993808.png

And it aligns perfectly.

For curiosity sake, I tried this:

N_W_S_E_4-1623090461119.png

And it resulted in slight misalignment.

I am wondering why 'we' are now using WGS 1984 (ITRF00) to NAD 1983. The following transformations in the photo BELOW work perfectly to align everything precisely, but I am confused about the deviation from NAD_1983_To_WGS_1984_2 and the implementation of WGS 1984 (IRF00) TO NAD 1983

N_W_S_E_3-1623090307103.png

I understand the common practice is to avoid projecting on the fly, but this doesn't just apply to that, it also applies to transformations when reprojecting data, so I'm trying to understand it all!

Thanks in advance! I look forward to hearing your thoughts.

4 Replies
MatthewCriel
New Contributor III

Hello N_W_S_E

Great question , I hope we see some answers.

We have the same issues with the custom transformation vs built ins, there is always a incorrect shift.

My problem is with GPS data points collected in Collector and survey123 . These points only align with web mercator basemaps. I cant find a transformation that will project the web mercator layers on a NAD 1983 CSRS Zone 17N Dataframe correctly, so points are shifted when overlayed on the 2020 SWOOP aerial.

It is frustrating.

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MelitaKennedy
Esri Notable Contributor

Hello! 

I'm sorry for the delay in answering.

NOTE: This answer also generally applies to the US for WGS 84 versus later NAD83 realizations.

Part of the answer depends on what the WGS 1984 Web Mercator base map is really using. Truly accurate WGS 84 coordinates are reserved for military and military-adjacent users. Everyone else, if you're performing RTK or otherwise improving the civilian GPS signals are really getting data on NAD83 (CSRS) or ITRFxx. So data that's turned into a base map, depends on what transformation may have been used to convert to WGS 84. 

In general, NAD83 (CSRS) is about 1 m / 3 ft (either one) away from WGS 84 / ITRFxx. So if someone says they have data and it's about that much offset, my first thought is that it's a transformation issue, and specifically WGS 84/ITRFxx vs. NAD83. Several transformations are really NAD83 and ITRFxx but have a 'duplicate' or 'equivalent' transformation that's to WGS 84 instead because we know that's what customers need for base maps and ArcGIS Online. 

The ArcGIS Pro default is two steps: your custom transformation between NAD83 CSRS and NAD83, and WGS84 (ITRF00) and NAD83. Basically, this ends up almost a null transformation. You convert from CSRS to to NAD83 then to WGS84 (ITRF00), so the data's almost back where it was. Not exactly of course, because the custom transformation is using an NTv2 grid file and can be more precise with its offsets. 

The second workflow using NAD83 CSRS to WGS 84 2 is very similar to but not exactly the WGS84 (ITRF00) to NAD83 transformation so you see some offset, but not the same. 

Sometimes the software requires a transformation because it knows the input and output CRS are different and won't let a process go farther unless they're reconciled. 

You can look at the transformation parameter values in our public GitHub repo or in the transformation PDF file.

Melita

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N_W_S_E
New Contributor III

Hi @MelitaKennedy,

Coming back to this, I have a couple more questions!

Here is some background:

The spatial reference of my data is:

N_W_S_E_0-1659707002696.png

The spatial reference of my basemap is:

N_W_S_E_1-1659707062903.png

I am wondering what the difference between these two transformations are, and what you suggest would be the appropriate one to use?

N_W_S_E_2-1659707245484.png

If I am in Ontario, Canada, should all of my data be re-projected into NAD_1983_CSRS_UTM_Zone_17N? If so, what transformation do you suggest I use?

Thank you in advance!

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BojanŠavrič
Esri Contributor

@N_W_S_E 

To see the difference between the two transformations you mentioned, you can select one and then click details (green link below selected transformation path):

Bojanavri_0-1659717780277.png

This will open you a transformation details window with all the transformation info including the areas of use and accuracy.

Bojanavri_1-1659717839973.png

Bojanavri_3-1659717961986.png

As you can see in the details above, both transformations should be used to transform USA data. 

For suggestions and advice, I will let @MelitaKennedy to reply.

 

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