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.
Figure 1 – Vertical Control used to establish heights in the NAVD 88 General Adjustment – It should be noted that nearly all of the leveling in the 1960s were performed after the 1964 earthquake (figure from a presentation titled “Achieving Great Heights: Toward a Better Vertical Reference System in Alaska” by Michael Dennis (National Geodetic Survey) and David B. Zilkoski (Geospatial Solutions by DBZ), March 28, 2014, 48th Annual Alaska Surveying and Mapping Conference, Fairbanks, Alaska)
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:
Suito, H., and J. T. Freymueller, A viscoelastic and afterslip postseismic deformation model for the 1964 Alaska earthquake, J. Geophys. Res., doi:10.1029/ 2008JB005954, 2009.
The model predictions are available in three different formats:
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.
2. A set of three netcdf grid files for use with GMT, for the east, north and vertical components. Interpolated values for any location can be generated easily with the GMT grdtrack program.
o East component: Suito_east.grd.
o North component: Suito_north.grd.
o Vertical component: Suito_vert.grd.
3. A MATLAB .mat file, visco_1964_SF2009.mat containing a structure with model velocity predictions at GPS sites in Alaska and the surrounding area.
Figure 3 – Post seismic Vertical Deformation Movement after the 1964 Alaska Earthquake (Suito, H., and J.T. Freymueller, “A viscoelastic and afterslip postseismic deformation model for the 1964 Alaska Earthquake, J. Geophy. Res,” ArcGIS raster layer was developed using grid values obtained from this website.The NGS (formally the Coast and Geodetic Survey) releveled the area effected by the earthquake in 1965. Today, leveling is very expensive so estimating new heights of benchmarks after earthquakes really needs to be accomplished using GNSS surveys. However, as stated in my first column, June 2015, GNSS surveys provide accurate ellipsoid height when the appropriate procedures are followed, but an accurate geoid height is required to estimate an accurate GNSS-derived orthometric heights. Therefore, the question that needs to be addressed is how accurate is the geoid model in Alaska. As described in the last column, the GPS on benchmarks program is one method of evaluating the GNSS/Leveling/Geoid combined system.
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.
Figure 4 – GPS on Benchmark Residuals Using Geoid12B in the State of Alaska – {GPS on BMs Residual = [GEOID12B value – (NAD 83 (2011) ellipsoid height value – NAVD 88 orthometric height value)]}. The Residuals are Depicted by Symbols (units = cm)Figure 5 – GPS on Benchmark Residuals Using Geoid12B in the State of Alaska –{GPS on BMs Residual = [GEOID12B value – (NAD 83 (2011) ellipsoid height value – NAVD 88 orthometric height value)]}. The Value of the Residuals are Labeled (units = cm)Figure 6 – GPS on Benchmark Residuals Using Geoid12B in the Haines and Skagway, Alaska, Region {GPS on BMs Residual = [GEOID12B value – (NAD 83 (2011) ellipsoid height value – NAVD 88 orthometric height value)]}. (units= cm)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 – GPS on Benchmark Residuals Using xGeoid16b in the State of Alaska – Referenced to IGS08 (units = cm) – {GPS on BMs Residual = [xGEOID16b value – (IGS08 ellipsoid height value – NAVD 88 orthometric height value)]}. Green Line Represents the Leveling LinesFigure 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.
Figure 8 – GPS on Benchmark Residuals Using xGeoid16b in the State of Alaska – Referenced to IGS08 with a trend removed– {GPS on BMs Residual = [xGEOID16b value – (IGS08 ellipsoid height value – NAVD 88 orthometric height value)]}. (units = cm) – Green Line Represents the Leveling LinesThe 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.
Figure 9 – GPS on Benchmark Residuals Using xGeoid16b in the State of Alaska – {GPS on BMs Residual = [xGEOID16b value – (IGS08 ellipsoid height value – NAVD 88 orthometric height value)]}. Referenced to IGS08 with a trend removed (units = cm) – “up” blue arrows indicated a positive residual and a “down” red arrow indicates a negative residualWhat 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.
Figure 10 – GPS on Benchmark Residuals Using xGeoid16b in the State of Alaska –– [GPS on BMs Residual = [xGEOID16b value – (IGS08 ellipsoid height value – NAVD 88 orthometric height value)]. Referenced to IGS08 with a trend removed (units = cm) – Residuals greater than 20 cm are labeled.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 11 – GPS on Benchmark Residuals Using xGeoid16b in the Matanuska-Susitna Borough, Alaska, Region – Large Difference between two relatively closely spaced stations (TT2313 and TT2332) – Referenced to IGS08 with a trend removed – {GPS on BMs Residual = [xGEOID16b value – (IGS08 ellipsoid height value – NAVD 88 orthometric height value)]}. (units = cm)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.
Figure 12 – GPS on Benchmark Residuals Using xGeoid16b in the State of Alaska with an Overlay of Fault Lines – Residuals are referenced to IGS08 with a trend removed – {GPS on BMs Residual = [xGEOID16b value – (IGS08 ellipsoid height value – NAVD 88 orthometric height value)]}. (units = cm)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 13 – Vertical Velocity estimated at GNSS Station in Alaska using UNAVCO’s GPS Velocity-Viewer Program: Figure generated from this website.
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 14 – GPS on Benchmark Residuals Using xGeoid16b in the Matanuska-Susitna Borough, Alaska, Region with an overlay of Fault Lines – Large Difference between two relatively closely spaced stations (TT2313 and TT2332) – Referenced to IGS08 with a trend removed – {GPS on BMs Residual = [xGEOID16b value – (IGS08 ellipsoid height value – NAVD 88 orthometric height value)]}. (units = cm)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 15 – GPS on Benchmark Residuals Using xGeoid16b in Yukon-Koyukuk Borough, Alaska, region with an Overlay of Fault Lines – Large Difference between two relatively closely spaced stations (TT3571 and TT3557) – Referenced to IGS08 with a trend removed – {GPS on BMs Residual = [xGEOID16b value – (IGS08 ellipsoid height value – NAVD 88 orthometric height value)]}. (units = cm)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.
Figure 16 – GPS on Benchmark Residuals Using xGeoid16b in the Skagway, Alaska, Region with an Overlay of Fault Lines – Referenced to IGS08 with a trend removed – {GPS on BMs Residual = [xGEOID16b value – (IGS08 ellipsoid height value – NAVD 88 orthometric height value)]}. (units = cm)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.
Fleet Complete, a global Internet of Things (IoT) provider of fleet telematics and mobile workforce technology, acquired BigRoad, an hours-of-service (HOS) and regulatory compliance solutions provider.
BigRoad will continue to operate and sell directly to owner-operators and fleets, and the integrated Fleet Complete BigRoad platform will be offered through their North American partner channels, AT&T and Telus.
According to Fleet Complete, BigRoad was founded to address the new HOS regulations imposed on the commercial motor vehicle industry. BigRoad released a mobile HOS application, BigRoad Mobile App, as well as DashLink, an engine-connected electronic logging device.
This acquisition aligns with the company’s goal of expansion, Fleet Complete says. The company also expanded into Europe in 2015 and Australia in 2016.
“BigRoad is an impressive organization that has had a laser focus on creating the industry’s leading product for ELD compliance,” said Tony Lourakis, CEO of Fleet Complete. “Outperforming the competition in usability and connectivity, BigRoad’s driver-friendly and feature-rich application will be a great complement to our integrated platform, giving Fleet Complete customers the most reliable top-of-the-line HOS solution.”
Esri released “Peaks and Valleys,” a 3D Story Map that displays the highest and lowest point on the planet.
The map features the heights and descriptions of these points. It takes viewers on a journey through mountain ranges and valleys in the Americas, Africa, Europe, Australia, Antarctica and the Pacific — from Mount Everist to the Challenger Deep.
“Our planet’s peaks and valleys represent some of its most hostile, remote and beautiful environments,” the website reads. “These extreme locations continue to hold a strange allure to explorers and adventurers. To those of us who are adventurers of the armchair type, and who are unlikely to experience these vertiginous locales first-hand, we present this virtual tour of Earth’s highs and lows.”
Monitor, manage and evaluate monitoring data, optionally trigger alarms
The Delta Solutions deformation monitoring system uses several software and hardware components — Delta Link, Delta Log, Delta Watch, Delta Sat and the Topcon MS AXII total station — to provide accurate and reliable monitoring measurements and associated reporting for asset protection. Delta Watch delivers accurate and reliable data in a variety of reporting formats to fit a project’s needs. Data from the total station, GNSS receivers, leveling devices and sensors can be processed and analyzed individually or as a network-adjusted solution. Delta Watch’s optional Delta Sat GNSS processing module allows for stand-alone GNSS monitoring or combined GNSS and total-station network adjustments. Delta Link provides hardware support communication for autonomous operation in the field, managing each power source to maximize system availability, while Delta Log provides an intuitive interface to manage observations, target types and measurement scheduling.
GPS data collector for utilities, mining, forestry, agriculture
The SXPad 1000P is an affordable, rugged handheld GPS data collector specifically designed for mobile GIS users in applications such as water, electric and gas utilities, transportation, mining, agriculture and forestry. The high-performance 1000-MHz device is designed to give professionals the power needed to work with maps and large data sets in the field. It has an IP67 waterproof seal and can survive 5-foot (1.5-meter) drops to concrete. Its 3.7-inch color touchscreen (full VGA) is sharp and is sunlight readable. Standard features include a battery life of more than 10 hours on a charge, 8-GB internal storage, and slots for MicroSD cards and SIM cards as well as Windows Mobile 6.5. The SXPad 1000P also offers a 3.5G cellular modem, Wi-Fi, Bluetooth, video capture and a 5-megapixel camera. It is optimized for GPS/GIS field data collection using its 1-to-3-meter accuracy internal GPS receiver or one of Geneq’s high-performance SXBlue GPS receivers for sub-meter and centimeter-level accuracy.
Glean and share insight from big data, internet of things
Esri ArcGIS 10.5 offers next-generation analytics technology by helping organizations glean insight from enterprise data, big data and the Internet of Things (IoT) and share that insight in intuitive ways. It includes improved capabilities for handling large-scale analytics and big data; a drag-and-drop interface that streamlines the creation of spatial analysis through maps, charts and graphs; and collaboration features to connect and analyze information across the enterprise. The new release is powered by Esri ArcGIS Enterprise, a significant evolution of the technology formerly known as ArcGIS for Server. ArcGIS Enterprise has been updated with improved power to process and analyze large, disparate datasets.
Entry-level device for construction, public safety
The Faro FocusM 70 is an entry-level laser scanner for construction building information modeling (BIM) and public safety forensics. Features include an IP54 rating for use in high particulate and wet weather, high-dynamic-range imaging, an acquisition speed of almost 500,000 points per second and extended temperature range. Data captured can be used with various third-party software packages. The Faro FocusM 70 is specifically designed for both indoor and outdoor applications that require scanning up to 70 meters and at an accuracy of +/– 3 millimeters.
The solution also features configurable software, allowing the addition of support for GNSS and sensing.
According to the companies, Dragonfly NB1 leverages Ceva’s long heritage of low power DSPs and modem design and Astri’s experience in RF and IC design technologies. Dragonfly NB1 has the ability to reduce the time taken to get NB-IoT products certified and also provides low-power wide-area SoC designers with a flexible, software-upgradeable platform with key benefits in terms of die size and power consumption, the companies added.
The Dragonfly NB1 solution is enabled by a Ceva-X1 IoT processor and incorporates highly power-efficient multi-standard RF with embedded PA, LNA, DC-DC and DCXO technology for NB-IoT and GNSS (GPS and BeiDou). It is specifically designed to operate with embedded flash by incorporating an optimized low latency memory subsystem with a dedicated cache controller.
“In the coming years, NB-IoT will become the dominant technology for low power wide area connectivity,” said Michael Boukaya, vice president and general manager of Ceva’s Wireless Business Unit. “For most companies, understanding how to develop this technology is a daunting task. To overcome this, we have worked relentlessly with ASTRI to develop a complete solution from the ground up, that removes the design burden and allows SoC designers to add NB-IoT connectivity to their product designs. We’re extremely excited to announce this solution and demonstrate our leadership in IP for NB-IoT.”
Ceva and ASTRI have also teamed up with GMV, a major player in navigation systems and solutions, to offer an integrated GNSS solutions for smart devices with location tracking of logistics, assets, wearables and more. According to the companies, the GNSS IP is available as an add-on software that runs on the Ceva X1 together with the NB-IoT and leverages ASTRI’s GNSS RF IP that is embedded in the solution.
Djibouti, a country located in the Horn of Africa with a population of about 850,000 citizens, adopted what3words as the addressing standard for its postal service.
what3words is a global addressing system that provides a fixed address for every 3-by-3 meter square in the world.
According to what3words, Djibouti is the fifth country in the world to accept its addresses. The country only has a few named streets, so delivering mail is a struggle for La Poste Djibouti, the nation’s official postal system, what3words added.
In addition, until recently, home delivery was restricted to express mail in Djibouti City, the capital of the republic. Any other post would be delivered to P.O. Boxes, where the recipient was responsible for collecting it. what3words provides an easy reference for international mail and enables home delivery for the country.
“Thanks to our partnership with what3words, every place in the country now has a fixed, accurate and immediately assigned address,” said Bahnan Ali Maidal, CEO at La Poste Djibouti. “Each inhabitant living in Balbala or Arhiba, Ali Sabieh or Obock, Randa or Assa Geyla will be able to quickly determine any address, write it on an envelope or communicate it by telephone.”
Available in thirteen languages, including English, French and Spanish, what3words is used by individuals, delivery companies, navigation tools, governments, logistics firms, travel guides and NGOs.
The event, which will take place at the Calgary Telus Convention Centre in Calgary, Alberta, Canada, incorporates elements from the past Tecterra Geomatics Showcase event and continues to add to the Canadian technology landscape, the company says.
It will focus primarily on technology, innovation and commercialization, as well as capitalize on Canada’s position in geospatial technology.
Tecterra is a technology innovation support center focused on enabling the development and commercialization of innovative geospatial technologies.
The Open Geospatial Consortium (OGC) is requesting information from interested parties to inform a Concept Development Study (CDS) that will assess the current state and future direction of information standards for modeling, mapping and managing underground infrastructure. Organizations with an interest in underground infrastructure are invited to respond before March 15.
According to OGC, the study will define the scope of a multi-phase underground infrastructure interoperability project. It will also provide an in-depth understanding of the components necessary to enable infrastructure data interoperability and standards in an underground environment.
The CDS is initially focused on urban landscape, but it is extendable, OGC adds. This request for information is the first step in the CDS process.
“In a digitally based society, the lack of comprehensive and reliable data relating to above and particularly below ground assets, will prove to be a barrier to the effective operation of those assets through digital systems,” says Rollo Home, strategic product manager for Ordnance Survey. “We recognize that establishing data as an infrastructure capability will be key to managing assets within an open, secure context. Geospatial data, in particular, can act as the framework within which the inter-relationships across these domains can be identified, modeled and managed.”
According to ION, JNC is the largest U.S. military positioning, navigation and timing (PNT) conference of the year with joint service and government participation. The event will focus on technical advances in PNT, emphasizing joint development, test and support of affordable PNT systems, logistics and integration.
From an operational perspective, the conference will focus on advances in battlefield applications of GPS; critical strengths and weaknesses of field navigation devices; warfighter PNT requirements and solutions; and navigation warfare.
The event, which will feature a technical exhibit and showcase of guidance, navigation and control technology products, will include more than 200 operational presentations, ION reports.
The ION Joint Navigation Conference will take place at the Dayton Convention Center, as well as a classified environment on June 8 at the Air Force Institute of Technology.
Strategically Occupying Stations to Support NGS’ GPS on Bench Marks Program
This is the 11th segment in my series on “Establishing Orthometric Height Using GNSS.” Each column has focused on a specific topic and provided procedures and tools for analyzing that topic. The columns are meant to build on each other. When addressing a topic that has been discussed in a previous column, web links are provided so the reader can review the previous columns.
The last column, December 2016, highlighted NGS plans for the 2022 Vertical Reference Datum and provided approximate height differences that users can expect to see. It also provided a little history behind the differences between the NGVD 29 and NAVD 88, and how each replacement of the United States’ National vertical reference datum is improving the user’s ability to obtain the most accurate orthometric height. The October 2016 column demonstrated how to use the GPS on BMs dataset to identify potential issues in published NAVD 88 and NAD 83 (2011) heights. It focused on analyzing the NGS’ GPS on BM data set that was used to create NGS’ GEOID12B hybrid geoid model. It provided procedures that users could employ when analyzing the differences between the modeled geoid values and the computed geoid values using GNSS/Leveling data (GNSS-derived ellipsoid height minus leveling-derived orthometric height). The October 2016 column provided several examples of large relative differences in residuals between neighboring stations. Each example represented stations that should be investigated based on different reasons, such as a weak NAVD 88 leveling network design in the region, the station’s published height attribute code implies that the station was not rigorously adjusted into the NAVD 88, and station pairs have different adjustment dates indicating a possible adjustment distribution correction issue or movement.
The following questions still need to be addressed: (1) Is the large difference due to an issue with the NAVD 88 orthometric height or the NAD 83 (2011) ellipsoid height? and (2) Should the station be included in the development of NGS’ hybrid geoid models? This column will provide 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. This information will be useful to NGS when developing hybrid geoid models and the 2022 Vertical Transformation model.
At this moment, the user is limited to what they can do to assist in identifying the problem. There are basically two options: (1) perform precise leveling observations between two or more stations and/or (2) perform accurate GNSS observations between two or more stations. Performing geodetic leveling between two stations is the desired option but is very expensive and time consuming; however, performing accurate GNSS observations between the two stations is relatively inexpensive and, if NGS’ OPUS-Projects is used to process the data then it is relatively simple to determine accurate NAD 83 (2011) ellipsoid heights and height differences. Even if the project is not submitted to NGS for inclusion into NAD 83 (2011), OPUS-Projects provides a easy and traceable mechanism for others to analyze the results and make their own decision.
First, let’s look at what NGS provides the user on their GPS on Bench Mark Program. The October 2016 column discussed the GPS on Bench Mark dataset used to create GEOID12B. It provided basic information about the program and provided links to websites that address the program. This column will provide additional information that will be useful for those individuals that desire to participate in the GPS on Bench Mark program. The website provides information on bench mark reconnaissance and recovery. NGS outlines to the user how to use their data files to perform a desktop reconnaissance. They provide eight steps that they believe will be helpful to the user when supporting the GPS on Bench Mark program. (See box titled “NGS’ Suggested Eight Steps for Users to Follow When Participating in the GPS on Bench Mark Program.”)
North American Vertical Datum of 1988 (NAVD 88) consists of a leveling network on the North American Continent, ranging from Alaska, through Canada, across the United States, affixed to a single origin point on the continent:
Desktop reconnaissance
Reconnaissance materials
Reconnaissance equipment
Bench Mark Hunting
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Observe and record
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North American Vertical Datum of 1988 (NAVD 88) consists of a leveling network on the North American Continent, ranging from Alaska, through Canada, across the United States, affixed to a single origin point on the continent:
1. Desktop reconnaissance
Bench marks of First and Second order leveling are targeted for GPS observations. Identify where you are looking for survey control. Generally surveyors try to tie into the NSRS without traveling too far from their project areas. Once you have determined your area of interest, use mapping applications to find marks that meet your criteria. The two recommended mapping applications are the NGS Data Explorer and DSWorld. The NGS database does not always get updated when geocachers recover marks on their web site, but DSWorld does provide information from their web site by showing a when it has been recovered.
To help assist surveyors and geocachers we have also created an ArcGIS Map Package , a zip file for non ArcGIS users and an ArcGIS Online (AGOL) Web Map available using the links below. The Web Map Application is available using any browser and the Map Package and zip file is for users interested in performing their own analysis.
GPS on Bench Marks AGOL Map
NGS GPS on Bench Marks Esri Map Package (~178 MB)
NGS GPS on Bench Marks Shapes/rasters (~88 MB)
These datasets provide the bench marks that were used in the creation of Geoid12B as well as the new GPS on bench marks that have been incorporated into NAD 83 (2011) since the creation of Geoid12B. This is useful information for those that want to occupy different bench marks than those previously observed with GNSS, and it is especially useful for identifying areas of the country that do not have enough bench marks occupied by GNSS. However, as I mentioned in my October 2016 column, the GPS on Bench Mark dataset can also be useful for identifying issues with NAVD 88 orthometric heights and NAD 83 (2011) ellipsoid heights. In the October 2016 column, I recommended that users perform an analysis of the differences between the published Geoid12B values and computed values from the NGS datasheet. (See box titled “Excerpt from October 2016 column – Analyzing Stations in the GPSBM Table.”)
Excerpt from October 2016 column – Analyzing Stations in the GPSBM Table.
So, what should the user do with the GPSBM table? I recommend that users perform the following steps when analyzing the stations in the GPSBM table.
Compare the modeled GEOID12B (N12B) value to the computed GPS/Leveling (h minus H) value using the following formula: Published N12B from the NGS data sheet minus (ellipsoid height from the GPSBM table minus orthometric height from the GPSBM table). We discussed this procedure a year ago in column 3 (October 2015). It should be noted that the orthometric height in the GPSBM table may be different than the published NAVD 88 height on the NGS data sheet if the station has been readjusted since the GPSBM table was created.
Repeat the procedure in Step 1 using the latest NGS experimental geoid model, e.g. xGeoid16b. At this time, NGS only provides the experimental geoid models referenced to IGS08 so the user will have to use NGS’ xGeoid16 web tool to obtain the station’s IGS08 ellipsoid height and xGeoid16b value. The input to the tool is the station’s NAD 83 (2011) coordinates (latitude, Longitude, and ellipsoid height). [An example of using the xGeoid16 web tool is provided in the box titled “Example of Using NGS xGeoid16 Web Tool.”] As discussed in column 3 (October 2015), the user will have to remove a bias and trend based on the differences in the region.
Use the station’s data sheet to identify how the station’s orthometric height was determined; for example, was it rigorously adjusted into the NAVD 88 (published height attribute – Adjusted). We discussed the attributes of the NGS data sheet in column 5 (February 2016). A summary of the attributes from the NGS data sheet DSDATA.TXT file is provided in the box titled “Extracted from NGS’ DSDATA.TXT.” I have highlighted the most common attributes of the stations involved in making GEOID12B.
Use the station’s NGS data sheet to determine the adjustment date of the station’s published NAVD 88 orthometric height. We discussed this in column 7 (June 2016). As mentioned in column 7, if the station has a different adjustment date than other stations nearby, there could be inconsistencies due to adjustment distribution corrections and/or movement.
If you download the Zip file or the Esri Map Package, you should have a layer titled “NGS_Bench_Marks.” This layer contains all the bench marks from the NGS database that have NAVD 88 orthometric heights with the attribute “ADJUSTED.” It should be noted that this is not the complete list of stations used to create the hybrid geoid model GEOID12B. This file only contains bench marks that were established using precise geodetic leveling procedures and incorporated into NAVD 88 using NGS’ leveling adjustment program. The list of attributes and their meaning was provided in my February 2016 column. The ArcGIS NGS_Bench_Marks layer contains a NAVD 88 orthometric height, a Geoid12B value, and an ellipsoid height if the station was occupied in a GNSS project. The ArcGIS user can select all bench marks that have a NAD 83 (2011) ellipsoid height in their state by using an ESRI query builder statement; for example, “STATE” = ‘NC’ AND “DATUM_TAG” = ‘(2011)’ AND “POS_DATUM” = ‘NAD 83’. Now the user can compute the GPS on BMs residual using the following formula: GPS on BMs Residual = Geoid12B value minus [NAD 83 (2011) Ellipsoid Height – NAVD 88 Orthometric Height)]. The user can perform this operation in the ESRI ArcGIS program or download the ArcGIS “NGS_Bench_Marks.dbf” file into Excel (or another spreadsheet program) and compute the computation in that spreadsheet program. The user can then import the file back into ArcGIS or their own GIS software. Once you have the GPS on BMs Residuals you can plot them and look for outliers. This is what I denote as “Strategically Occupying Stations to Support the GPS on Bench Mark Program.” I performed the above operation for the entire “NGS_Bench_Marks” file.
So, what do I really mean by strategically occupying station to support the GPS on Bench Mark Program. Once you plot the GPS on Bench Marks residuals, the user should use the plots to identify stations that should be re-occupied because of large residuals or new stations that should be occupied in areas void of control. Figure 1 is an example of the GPS on BMs residuals for the State of North Carolina.
Figure 1 – GPS on Bench Marks Residuals using GEOID12B computed using NGS GPS on Bench Marks Shapes/rasters
Looking at figure 1, the reader should notice some large red circles (negative GPS on BMs residuals) are located near some large blue circles (positive GPS on BMs residuals). In my opinion, these regions should be analyzed to determine if stations should be re-observed during a GPS on Bench Mark campaign. This doesn’t mean that if other stations are occupied that they will not help improve the hybrid geoid model and the NAVD 88 transformation model to the new 2022 Vertical Reference Datum, it just means that these previously occupied stations are questionable and re-observing these stations may help to explain why the residuals are so large. I’ve provided a couple of examples in North Carolina to explain what I mean.
Figure 2 depicts a station with a large negative residual (-7.9 cm) surrounded by stations with smaller residuals (mostly positive residuals). This station’s published NAVD 88 height may be an invalid height; that is, the station may have moved after the leveling-derived orthometric height was determined. In my opinion, this station should not be used in the development of a hybrid geoid model or any transformation model from NAVD 88 to another vertical reference datum. It would be useful information to know if the NAVD 88 orthometric height is invalid. In this example, the user could re-observe station Z 183 (PID = FA0997) with a long GNSS session, or simultaneously observe station FA0997 and another nearby station (such as AH5641) during the same long session. The second option allows the user to estimate a new ellipsoid height difference between the two stations that can be compared with the published ellipsoid height difference.
Figure 2 – Large Negative Residual Surrounded by Smaller Residuals – Station FA0997
The ArcGIS NGS_Bench_Marks layer includes when the station was first recovered (e.g.,1967) and last recovered (e.g., 2009), and the condition of the station (e.g., good condition). The NGS dataset provides the network and local accuracies for published NAD 83 (2011) stations. (See box titled “Excerpt from NGS’ Datasheets for Stations FA0997 and AH5641.”) We discussed NGS’ datasheet and published local and network accuracy values in the August 2015 column.
The stations’ local and network accuracy values are highlighted in the box titled “Excerpt from NGS’ Datasheets for Stations FA0997 and AH5641.” Station AH5641 local ellipsoid standard error value (0.51 cm) is much better than station’s FA0997 value (2.47 cm). Next, we should look at the local network accuracies to determine which stations were simultaneously observed during a GNSS survey. Once again, these options on the NGS’ datasheets were discussed in the August 2015 column.
The box titled “Excerpt from NGS’ The Local and Network Accuracy Data Sheet for Stations FA0997 and AH5641” provides the local and network accuracy data sheet for stations FA0997 and AH56412. The readers should notice that Station FA0997 only has one local accuracy to another station and that station is not AH5641. This implies that these two stations were not observed during the same session. The large relative difference in residual could be due to an invalid NAVD 88 orthometric height but it could also be due to an undetected error in the ellipsoid height due to a weak GNSS survey design. Let’s look at another example where there’s more than one outlier in a small group.
Figure 3 depicts two stations (AI7070 and AI7073) that appear to be inconsistent with their neighboring stations (FB3216 and FB3222). If we look at the datasheets for these stations, it can be determined that stations AI7070 and AI7073 were observed in the same session but neither station was occupied in a session with FB3216 or FB3222. The datasheets do indicate that FB3216 and FB3222 were observed during the same session. In this case, I would recommend simultaneously observing stations FB3222 and AI7073 to determine an accurate ellipsoid height difference to determine if the relative ellipsoid height difference computed from the published ellipsoid heights are really as accurate as their published network and local accuracy values. If these stations do not get re-observed, I would not recommend using stations AI7070 and AI7073 in the hybrid geoid model.
Figure 3 – Several Large Negative Residual Surrounded by Smaller Positive Residuals – Stations AI7070 and AI7073
I have focused on North Carolina but this analysis can be performed on any state or region. Figure 4 is a plot of GPS on BMs residuals using Geoid 12B for the State of Florida. Looking at figure 4, there appears to be a lot of stations with large GPS on Bench Mark residuals.
Figure 4 – GPS on BMs residuals using GEOID12B for the State of Florida
Figure 5 is a plot of the GPS on Bench Mark residuals using GEOID12B in the Lynn Haven, Florida, area. Looking at figure 5, the reader can see that station BE1497 has a large relative difference between its neighbors (BE0604 and AA9918). This station and one of its neighboring station should be re-observed in a GNSS survey. In my opinion, if this station is not re-observed then it should be rejected and not included in the development of the hybrid geoid model.
Figure 5 – GPS on BMs residuals using GEOID12B for Lynn Haven, Florida, Area
Some States have enough bench marks that have been occupied by GPS that re-observing a station may not improve the hybrid geoid model. It may be sufficient to reject the station so it doesn’t distort the hybrid geoid model. Figure 6 is a plot of the GPS on BMs for the State of Missouri. If you compare figure 1 (plot of GPS on BMs in North Carolina) with figure 6 (plot of GPS on BMS in Missouri), it’s obvious that the State of North Carolina has more bench marks occupied by GPS than Missouri. Most of the residuals in figure 6 seem reasonable but the user should investigate those stations that are greater than +/- 5 cm. An example of a station that should be re-observed is station C 10 (KD0210). Figure 7 is a plot of the GPS on BMs surrounding station C 10 (KD0210). The NGS data sheet for station C 10 states that the station was incorporated into NAD 83 (2011) in May 2015; therefore, it wasn’t used in the creation of GEOID 12B. The data sheet also provides the Network and Local Accuracy values for the station. [See the box titled “Excerpt from NGS’ Datasheets for Station KD0210.”] The network and local ellipsoid height accuracy values (6.49 cm) are larger than most published NAD 83 (2011) stations.
Figure 6 – GPS on BMs residuals using GEOID12B for the State of MissouriFigure 7 – GPS on BMs residuals using GEOID12B Surrounding Station KD0210 (C 12)
This is an area that is void of GPS on bench mark control so this station is extremely important. However, this station has a large GPS on BM residual and a large local accuracy value which makes the station’s published orthometric height and ellipsoid height questionable. I would recommend that this bench mark and several nearby bench marks be observed in a GNSS survey to provide additional estimates of the relationship between the NAVD 88 orthometric heights and NAD 83 (2011) ellipsoid heights in this area. Saying that, it is very important that users perform procedures that result in an accurate GNSS-derived ellipsoid height. This means that users may have to observe stations for several hours and repeat observations on different days and at different times of the day. Of course, I realize that this may be too expensive for most surveyors but the end result may not be sufficient to determine why the station has a large GPS on BM residual.
I stated in my October 2016 column that step 2 was to use the latest experimental geoid model in the analysis. (See box titled “Excerpt from October 2016 column – Analyzing Stations in the GPSBM Table.”) I have focused this column on using data that can easily be obtained from the NGS’ website. Saying that, in my next example I have computed the GPS on Bench Marks residuals using a detrended xGeoid16b that is consistent with NAD 83 (2011) [i.e., a bias and trend has been removed from the differences]. This information is not currently available from NGS’ website but I want to show the differences between the hybrid model residuals and the experimental geoid model, xGeoid16b.
It’s very difficult, if not impossible, to identify how much the hybrid geoid model has been distorted to fit a GPS/Leveling station by looking at published data from NGS data sheets. Figures 8 and 9 demonstrate how some large GPS on Bench Marks residuals using GEOID12B may be distorting the hybrid geoid model. Figure 8 is a plot of the GPS on BM residuals using GEOID 12B in an area in Rockbridge County, Virginia, and Figure 9 is a plot of the same stations using a detrended scientific geoid model xGeoid16b that is consistent with NAD 83 (2011). Looking at figure 8, stations GW2113 and GW0934 appear to be large outliers, -8.8 cm and 11.8 cm, respectively. Station GW0934 was rejected by the geoid team. However, looking at figure 9, using a detrended xGeoid 16b model, the GPS on BM residual of station GW2113 is -19.3 cm and the residual of station GW0934 is only 3.4 cm. What is very important to notice on figure 8 is that nearby stations GW1042 and GW0822 residuals are only -3.3 cm and -2.0 cm, respectively; but, on figure 9, using the detrended xGeoid16b model, the residuals of stations GW1042 and GW0822 are -12.2 cm and -11.5 cm, respectively. Some of these stations need to be re-observed to determine if the NAVD 88 orthometric heights are no longer valid or if there are undetected errors in the published ellipsoid heights. This is why the experimental geoid model should also be used when analyzing GPS on Bench Mark residuals; and why some GPS on BM stations that are inconsistent with their neighboring stations should not be included in the development of a hybrid geoid model. This means that analyzing GPS on Bench Marks residuals using just the hybrid geoid model will only identify outliers that are significantly different from their neighbors. Some outliers will be missed but the procedure does help to prioritize those stations that should be re-observed to help support NGS’ GPS on Bench Mark Program.
Figure 8 – GPS on BMs residuals using GEOID12B for a Large Outlier in Rockbridge County, Virginia (PID =GW2113)
Figure 9 – GPS on BMs Residuals Using a Detrended GEOID16b [consistent with NAD 83 (2011), bias and trend removed] for a Large Outlier in Rockbridge County, Virginia (PID =GW2113)It should be noted that many of these large GPS on BM residuals could be due to an invalid NAVD 88 published height because the bench mark moved since the last time the height of the bench mark was adjusted and published, and/or an undetected error in an ellipsoid height due to a weak GNSS project design. Either way, in my opinion, most of these stations with large GPS on BMs residuals don’t accurately represent the current NAVD 88. When performing a geodetic survey, these stations would be identified as bench marks with invalid heights when following the appropriate Federal geodetic survey guidelines, procedures, and specifications. These bench marks should not be used in the hybrid geoid model just like they would not be used in controlling geodetic surveys. I want to emphasize that I’m not criticizing 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. I am trying to emphasize to users the importance to strategically occupy stations to help support the GPS on Bench Marks Program and create a hybrid geoid model that accurately represents the current NAVD 88.
This column focused on addressing the following questions: (1) Is the large GPS on BM residual due to an issue with the NAVD 88 orthometric height or the NAD 83 (2011) ellipsoid height? and (2) Should stations with large GMS on BM 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. This information will be useful to NGS when developing hybrid geoid models and the 2022 Vertical Transformation model.
![[INSERT FIGURE 3] Figure 3 – Post seismic Vertical Deformation Movement after the 1964 Alaska Earthquake (Suito, H., and J.T. Freymueller, “A viscoelastic and afterslip postseismic deformation model for the 1964 Alaska Earthquake, J. Geophy. Res,” ArcGIS raster layer was developed using grid values obtained from website: http://www.gps.alaska.edu/jeff/SF2009_postseismic.html)](https://stage.globalpositioningnews.com/wp-content/uploads/2017/04/GPS_World_Newsletter_12_Fig_3.jpg)
![Figure 4 – GPS on Bench Mark Residuals Using Geoid12B in the State of Alaska – {GPS on BMs Residual = [GEOID12B value – (NAD 83 (2011) ellipsoid height value – NAVD 88 orthometric height value)]}. The Residuals are Depicted by Symbols (units = cm)](https://stage.globalpositioningnews.com/wp-content/uploads/2017/04/GPS_World_Newsletter_12_Fig_4.jpg)
![Figure 5 – GPS on Bench Mark Residuals Using Geoid12B in the State of Alaska –{GPS on BMs Residual = [GEOID12B value – (NAD 83 (2011) ellipsoid height value – NAVD 88 orthometric height value)]}. The Value of the Residuals are Labeled (units = cm)](https://stage.globalpositioningnews.com/wp-content/uploads/2017/04/GPS_World_Newsletter_12_Fig_5.jpg)
![Figure 6 – GPS on Bench Mark Residuals Using Geoid12B in the Haines and Skagway, Alaska, Region {GPS on BMs Residual = [GEOID12B value – (NAD 83 (2011) ellipsoid height value – NAVD 88 orthometric height value)]}. (units= cm)](https://stage.globalpositioningnews.com/wp-content/uploads/2017/04/GPS_World_Newsletter_12_Fig_6.jpg)
![Figure 7 – GPS on Bench Mark Residuals Using xGeoid16b in the State of Alaska – Referenced to IGS08 (units = cm) – {GPS on BMs Residual = [xGEOID16b value – (IGS08 ellipsoid height value – NAVD 88 orthometric height value)]}. Green Line Represents the Leveling Lines](https://stage.globalpositioningnews.com/wp-content/uploads/2017/04/GPS_World_Newsletter_12_Fig_7.jpg)
![Figure 8 – GPS on Bench Mark Residuals Using xGeoid16b in the State of Alaska – Referenced to IGS08 with a trend removed– {GPS on BMs Residual = [xGEOID16b value – (IGS08 ellipsoid height value – NAVD 88 orthometric height value)]}. (units = cm) – Green Line Represents the Leveling Lines](https://stage.globalpositioningnews.com/wp-content/uploads/2017/04/GPS_World_Newsletter_12_Fig_8.jpg)
![Figure 9 – GPS on Bench Mark Residuals Using xGeoid16b in the State of Alaska - {GPS on BMs Residual = [xGEOID16b value – (IGS08 ellipsoid height value – NAVD 88 orthometric height value)]}. Referenced to IGS08 with a trend removed (units = cm) - “up” blue arrows indicated a positive residual and a “down” red arrow indicates a negative residual](https://stage.globalpositioningnews.com/wp-content/uploads/2017/04/GPS_World_Newsletter_12_Fig_9.jpg)
![Figure 10 – GPS on Bench Mark Residuals Using xGeoid16b in the State of Alaska –– [GPS on BMs Residual = [xGEOID16b value – (IGS08 ellipsoid height value – NAVD 88 orthometric height value)]. Referenced to IGS08 with a trend removed (units = cm) – Residuals greater than 20 cm are labeled.](https://stage.globalpositioningnews.com/wp-content/uploads/2017/04/GPS_World_Newsletter_12_Fig_10.jpg)
![Figure 11 – GPS on Bench Mark Residuals Using xGeoid16b in the Matanuska-Susitna Borough, Alaska, Region – Large Difference between two relatively closely spaced stations (TT2313 and TT2332) - Referenced to IGS08 with a trend removed – {GPS on BMs Residual = [xGEOID16b value – (IGS08 ellipsoid height value – NAVD 88 orthometric height value)]}. (units = cm)](https://stage.globalpositioningnews.com/wp-content/uploads/2017/04/GPS_World_Newsletter_12_Fig_11.jpg)
![Figure 12 – GPS on Bench Mark Residuals Using xGeoid16b in the State of Alaska with an Overlay of Fault Lines – Residuals are referenced to IGS08 with a trend removed – {GPS on BMs Residual = [xGEOID16b value – (IGS08 ellipsoid height value – NAVD 88 orthometric height value)]}. (units = cm)](https://stage.globalpositioningnews.com/wp-content/uploads/2017/04/GPS_World_Newsletter_12_Fig_12.jpg)
![Figure 14 - GPS on Bench Mark Residuals Using xGeoid16b in the Matanuska-Susitna Borough, Alaska, Region with an overlay of Fault Lines – Large Difference between two relatively closely spaced stations (TT2313 and TT2332) - Referenced to IGS08 with a trend removed – {GPS on BMs Residual = [xGEOID16b value – (IGS08 ellipsoid height value – NAVD 88 orthometric height value)]}. (units = cm)](https://stage.globalpositioningnews.com/wp-content/uploads/2017/04/GPS_World_Newsletter_12_Fig_14.jpg)
![Figure 15 – GPS on Bench Mark Residuals Using xGeoid16b in Yukon-Koyukuk Borough, Alaska, region with an Overlay of Fault Lines – Large Difference between two relatively closely spaced stations (TT3571 and TT3557) - Referenced to IGS08 with a trend removed – {GPS on BMs Residual = [xGEOID16b value – (IGS08 ellipsoid height value – NAVD 88 orthometric height value)]}. (units = cm)](https://stage.globalpositioningnews.com/wp-content/uploads/2017/04/GPS_World_Newsletter_12_Fig_15.jpg)
![Figure 16 – GPS on Bench Mark Residuals Using xGeoid16b in the Skagway, Alaska, Region with an Overlay of Fault Lines - Referenced to IGS08 with a trend removed – {GPS on BMs Residual = [xGEOID16b value – (IGS08 ellipsoid height value – NAVD 88 orthometric height value)]}. (units = cm)](https://stage.globalpositioningnews.com/wp-content/uploads/2017/04/GPS_World_Newsletter_12_Fig_16.jpg)
![Figure 9 – GPS on BMs Residuals Using a Detrended GEOID16b [consistent with NAD 83 (2011), bias and trend removed] for a Large Outlier in Rockbridge County, Virginia (PID =GW2113)](https://stage.globalpositioningnews.com/wp-content/uploads/2017/02/DBZ_Newsletter_11_Fig_9.jpg)