The last column, February 2017, focused on addressing the following questions: (1) Is the large GPS on benchmarks residual due to an issue with the NAVD 88 orthometric height or the NAD 83 (2011) ellipsoid height? and (2) Should stations with large GPS on benchmarks residuals be included in the development of NGS’ hybrid geoid models? The column provided suggestions on how users can assist NGS in determining the reason for the large difference between the modeled hybrid geoid value and computed GNSS/leveling geoid computed value. It was mentioned that this information will be useful to NGS when developing hybrid geoid models and the 2022 Vertical Transformation model. My previous columns have focused on the conterminous United States. This column is going to discuss the GPS on benchmarks residuals for the state of Alaska.
The February 2017 column noted that many of these large GPS on BM residuals could be due to an invalid NAVD 88 published height because the benchmark moved since the last time the height of the benchmark was adjusted and published, and/or an undetected error in an ellipsoid height due to a weak GNSS project design. The State of Alaska is very large; it has a sparse leveling network, and benchmarks are subject to movement due to ground conditions, isostatic effects, and seismic activity. The Geophysical Institute at the University of Alaska, Fairbank, has a lot of interesting reports on the movement in Alaska. Many of these stations would be identified as benchmarks with invalid heights when users follow Federal geodetic survey guidelines, procedures, and specifications. Benchmarks with invalid heights would not be used in controlling geodetic surveys and, in my opinion, should not be used in the hybrid geoid model. As I mentioned in my previous columns, this is not meant to be a criticism of NGS process for creating their hybrid geoid model. NGS’ goal is to create a hybrid geoid model that is consistent with published NAVD 88 values. I believe NGS is using all the data and information available to them. A goal of my last column was to emphasize to users the importance to strategically occupy stations to help support the GPS on benchmarks program which will result in the creation of a hybrid geoid model that accurately represents the current NAVD 88.
First, let’s look at the leveling network design of Alaska. Figure 1 depicts the leveling network design used to establish heights in the NAVD 88. The figure indicates that most of the leveling data used in NAVD 88 was between 1965 and 1975. It should be noted that a major releveling project was performed in 1965 after the 1964 Good Friday Alaska Earthquake. There were some short leveling lines performed in the late 1980s and early 1991s. These data are now old and the question about whether the NAVD 88 height of the benchmark is still valid must be addressed.
Alaska is prone to both episodic crustal motion (i.e. earthquakes) and the effects of long-term isostatic adjustment, which makes maintaining accurate vertical control difficult at best. (See figure 2 for a plot of earthquakes in Alaska). The 1964 Good Friday Alaska Earthquake, a magnitude of 9.2, changed heights as much as 8 feet. In addition to the initial damage at the time of the earthquake, there’s a post seismic vertical deformation movement that occurred. Suito and Freymueller (2009) provided a postseismic deformation model predictions for the 1964 earthquake [see box titled “Postseismic Velocity Predictions from Suito and Freymueller (2009)]”. An ArcGIS raster layer was developed using the grid values obtained from the website. Figure 3 is a plot of the vertical deformation model using Suito and Freymueller’s gridded dataset.
This page provides access to postseismic deformation model predictions for the 1964 earthquake. The model includes afterslip and viscoelastic relaxation (including the viscoelastic response to the afterslip), for the best-fit model derived by Suito and Freymueller (2009). That model includes a realistic slab geometry and a uniform asthenospheric relaxation time of 20 years. The full reference for the paper and the model is given below:
1. A text file, Suito_vel.enu.txt with east, north and vertical model predictions evaluated on a 0.25 degree grid covering all of Alaska.
Units for all of these files are mm/yr.
Saying that, Alaska’s system of NAVD88 benchmarks is based on old leveling data and, due to ground ice conditions and crustal movement, are subject to changes in heights. This makes it difficult to evaluate the geoid model in Alaska using published NAVD 88 heights. However, NGS’ GPS on benchmarks program can help to identify outliers and long wavelength trends between NAVD 88 heights and GNSS-derived orthometric heights. GPS on BMs residuals using the published GEOID12B values in the State of Alaska were generated using the data from the NGS’ website. I described these data and the process in my February 2017 column. Figures 4 through 6 depict the GPS on benchmarks residuals using the hybrid geoid model GEOID12B for stations in Alaska. It should be noted that only bench marks that had NAD 83 (2011) published coordinates and NAVD 88 published heights with the attribute of “Adjusted” were used in this analysis. This analysis does not include any OPUS results.Looking at figures 4-6, most of the GPS on BMs residuals using GEOID12B appear to be less than a couple of centimeters. There are several stations that have large outliers but this is seen in every State in the conterminous United States. The small residuals using GEOID12B doesn’t really tell us much because the large threshold level used by the NGS Geoid Team can mask some issues. This was demonstrated in my last column. Notice that figure 6 only shows two GPS on BMs residuals in the Haines and Skagway area of Alaska. This is an area where more GPS on BMs would be helpful to evaluate the geoid model.
As I’ve mentioned in my previous columns, the user should analyze the GPS on BMs stations using the latest experimental gravimetric geoid that includes the new airborne GRAV-D data, e.g. xGeoid16b. NGS has a website that enables users to compute geoid height values using the latest experimental gravimetric geoid model. All benchmarks in Alaska that had NAD 83 (2011) published coordinates were submitted as input to the NGS’ xGeoid16 website and the results were used to create a file of GPS on BMs residuals for the State of Alaska. An example of the output from the xGeoid16 website is provided in the box titled “Output from xGeoid16 Website.” NGS’ experimental geoid website was described in my October 2015 column.
It should be noted that the input to the xGeoid16 website was NAD 83 (2011) coordinates and the output was provided in the IGS08 reference frame; therefore, the xGeoid16b geoid heights are referenced to IGS08. The GPS on BMs residuals was computed using the formula GPS on BMs Residual = [xGEOID16b value – (IGS08 ellipsoid height value – NAVD 88 orthometric height value)]. Figure 7 is a plot of the GPS on BMs residuals computed using xGeoid16b geoid values, IGS08 ellipsoid heights, and NAVD 88 orthometric heights.Figure 7 indicates that there is an obvious bias of about a meter between the GNSS-derived orthometric heights referenced to IGS08 and the NAVD 88. This bias is expected since these GPS on BMs residuals are referenced with respect to IGS08. This has been described in more detail in my December 2016 column, and depicted in a figure on the NGS website. A bias and trend from the GPS on BMs residuals was removed by performing a least squares best fit planar surface of the differences (basically solving for a bias and a North-South and East-West tilt). Figure 8 is a plot of the GPS on BMs residuals using xGeoid16b in Alaska were a bias and trend was removed from the original computed GPS on BMs residuals that are depicted in figure 7. These GPS on BMs residuals will be used to identify outliers and will be referred to as GPS on BMs residuals (with a trend removed) in the reminder of this column. The large absolute difference and tilt are not concerning, it’s the large relative differences between closely-spaced stations that need to be identified and explained. Removing the bias and trend in the GPS on BMs residuals is useful in identifying large relative differences between neighboring stations.
Figure 9 is another plot of the GPS on BMs residuals using xGeoid16b with the trend removed using different symbology. The “up” blue arrows indicated a positive residual and a “down” red arrow indicates a negative residual. It’s not surprising to see both positive and negative residuals because a trend was removed from the residuals.What should be noticed is that there are a lot of large negative and positive residuals. Figure 10 is a plot of the GPS on BMs residuals (with a trend removed) with residuals greater than +/- 20 cm labeled. It may be difficult to see in the plot but there are two residuals in the Hains and Skagway, Alaska, region (see right corner of figure 10). Both stations have large positive GPS on BMs residuals. What is important is that the relative difference between the two stations is also large, i.e., 42 cm (80.4 cm – 38.4 cm). We will address this difference later in this column. As previously mentioned, investigating GPS on BMs with large relative differences between closely-spaced stations helps to identify outliers. Figure 11 is a plot of the GPS on BMs residual (with a trend removed) in the Matanuska-Susitna Borough, Alaska, region. There are several stations that are relatively close to each other (TT2213, TT2332, and TT2299) and have large relative GPS on BMs residuals. That is, the relative difference in GPS on BMs residuals between stations TT2313 and TT2332, 24 km apart, is -9.9 cm (-6.3 cm – 3.6 cm), and between stations TT2332 and TT2299, 19 km apart, the difference in GPS on BMs residual is -26.3 cm [-32.6 cm – (-6.3 cm)]. These stations have published NAVD 88 heights but should stations with large GPS on BM residuals be included in the development of NGS’ hybrid geoid models? At a minimum, other stations near these stations should be occupied with GNSS to help determine if other monuments in the area have moved in the similar manner. Figure 2, a USGS plot of earthquakes in Alaska, highlighted the problems with maintaining reliable, accurate NAVD 88 orthometric heights in Alaska. Figure 12 is a plot of GPS on BMs residuals (with a trend removed) using xGeoid16b in the State of Alaska with an overlay of fault lines. The ArcGIS layer of fault lines was obtained from ArcGIS online layers. Looking at figure 12, it’s obvious that the heights of benchmarks in Alaska are probably being influenced by seismic activity. Figure 13 is a plot of the vertical velocity values at GNSS stations generated by UNAVCO’s GPS Velocity Viewer Program at this website. Looking at figure 13, it is obvious that benchmarks that haven’t been releveled in the past 30 years could have been significantly influenced by crustal movement.
Figure 14 is the same plot as figure 11 with an overlay of the fault lines. Are these stations being influenced by crustal motion? Repeat measurements are needed to address this issue. There is a great opportunity to assist in the development and assessment of hybrid geoid models if researchers and others that are conducting campaign GNSS surveys with long static occupations share their results with NGS. NGS has a Regional Geodetic Advisory in Alaska that could help facilitate getting the appropriate information to NGS’ geoid team. Nicole Kinsman is the NGS Regional Geodetic Advisor for Alaska. Ms. Kinsman is very knowledgeable on National Spatial Reference System (NSRS) issues in Alaska. She was very helpful to me as I was preparing this column.Figure 15 is a plot of GPS on BMs residuals in the Yukon-Koyukuk borough, Alaska, region. Notice that there’s a large difference between relatively closely-spaced stations TT3571 and TT3555, 22.6 cm (31.7 cm – 9.1 cm). Saying that, the plot also depicts all the fault lines around these stations. This is another example of how difficult it is to maintain reliable orthometric heights in Alaska. Figure 16 is a plot of GPS on BMs residuals in the Haines and Skagway, Alaska, region, with an overlay of fault lines. Figure 10 highlighted that the two stations, TT0118 and TT8080, have a large relative difference (42 cm) but figure 16 indicates that the two stations lie between a couple of fault lines. What does this mean to surveyors and mappers in Alaska? In my opinion, the new 2022 Vertical Reference Datum, denoted as the North American-Pacific Geopotential Datum of 2022 (NAPGD 2022) will help Alaskans maintain a vertical reference frame that’s reliable and traceable. Saying that, it is extremely important to know the relative accuracy of the geoid model used to establish GNSS-derived orthometric heights in NAPGD2022. NGS is performing projects to evaluate the relative accuracy of the gravimetric geoid model. The projects are known as Geoid Slope Validation Surveys. I would encourage the Alaska surveying and mapping community to develop plans to transition to the new NAPGD2022. Evaluation of the experimental gravimetric geoid model is critical to the implementation of the new 2022 datum and should be part of a transition plan. Performing a geoid slope validation project similar to NGS may be too expensive to be performed by Alaskans. However, Alaskans may be able to perform low budget geoid slope evaluation surveys. These surveys could include performing combined GNSS and leveling surveys to evaluate the relative accuracy of the gravimetric geoid model in areas that require accurate orthometric heights. Performing several of the gravimetric geoid evaluation surveys in major cities and/or areas that require accurate heights would help to facilitate the implementation of NAPGD2022.
These types of geoid evaluation surveys should also be performed in other areas of the country that are influenced by crustal movement. For example, the published NAVD 88 heights in southern Louisiana and other parts of the Gulf Coast of the United States are influenced by subsidence. NAPGD2022 will provide a more efficient and cost-effective way to maintain consistent orthometric heights. Once again, evaluating the relative accuracy of the gravimetric geoid model is critical to the implementation of NAPGD2022.