Officials at Arlington National Cemetery will use an Army-designed geospatial mapping system to manage cemetery operations, said the executive director of the Army National Cemeteries Program.
Kathryn A. Condon testified before the House Veterans Affairs Committee's disability assistance and memorial affairs subcommitee to provide an update on the progress made in rectifying long-standing management problems at Arlington National Cemetery.
Source: Arlington National Cemetary
"Arlington is no longer a paper-based operation. By producing a single electronic map of Arlington, the staff will assign, manage and track gravesites with an authoritative digital map," Condon said. "It will allow us to synchronize in real time our burial operations at Arlington."
The geospatial mapping system allows officials to synchronize burial operations with other daily operations, such as public ceremonies, infrastructure repair, grounds upkeep and public safety activities, Condon explained. The system is linked to Arlington's interment scheduling system, which allows schedulers to assign gravesites and assign procession routes. It also alerts Arlington staff of other activities in the area, she said.
Arlington is the first national cemetery to use this technology, Condon told the panel.
The geospatial mapping system will use the information collected and validated as part of the Army's gravesite accountability study. The gravesite accountability effort resulted in the first review, analysis and coordination of records kept in various ways at Arlington over the cemetery's history, Condon said.
The Gravesite Accountability Task Force physically examined and photographed 259,978 gravesites, niches and markers using a custom-built smartphone application and matched each photo with records in a database. Arlington officials are 84 percent complete in validating records, officials said, and are on track to finish this summer.
Once complete, Arlington's accountability effort will create a single, verifiable and authoritative database of all those laid to rest at Arlington, officials added, and it will be linked with Arlington's geospatial mapping system.
F4Devices, a subsidiary of F4 Tech and strategic partner with BAP Precisions, Taiwan, has introduced a new generation of high-precision GNSS devices for GIS field applications, the Flint rugged handheld. With the new Flint handheld, field workers requiring a rugged mobile handheld device have a unit that is lightweight, compact, rugged, and cost-effective, the company said. The Flint fits well into GIS field data collection markets such as municipalities, oil and gas and forestry, F4Devices said.
The Flint handheld offers a unique, one-of-a-kind combination of flexible GPS configurations, ranging from 1 to 3 meters to sub-meter accuracies, while supporting geotagging with the 5 megapixel autofocus camera as well as Wi-Fi, Bluetooth, and 3G data. There are two versions to choose from, the S812H (includes GPS, Bluetooth, Wi-Fi and 5 MP camera) and the S852H (includes GPS, Bluetooth, Wi-Fi, 5 MP camera and 3G data).
“The new Flint handheld impresses, from the first moment you see it. The ruggedness of the device, IP65, in this small of a package while achieving the GPS accuracies we have been able to achieve is something to acknowledge as a leader in its class,” said Brian Holley, director of Distribution for F4Devices. “Add in its high-resolution, sunlight-readable VGA screen, extendable data storage and Microsoft Office Mobile standard on all units, this makes it even more impressive.”
The Flint handheld is specifically designed for field professionals looking for a rugged, dependable feature-rich device, said F4Devices. The camera button is located as if the user was holding a camera. Combined with the GPS, it provides a powerful solution for precise geotagging. In tough environments, whether it is extreme weather or high multi-path, the Flint handheld is up to the challenge, the company said.
The F4Devices Flint is shock-proof, dust-proof, and waterproof. The battery supports the field users’ needs with at least 10 hours of performance.
F4Devices, along with BAP Precisions, is focused on supporting solutions providers by working with them directly to integrate their applications with the Flint handheld. Any feature or application in the Flint handheld is accessible to software engineers for full and complete integration, allowing a fully developed solution to be offered to their clients, the company said. API’s are available for solutions providers to access and communicate with the features they require.
The 3G data modem in the Flint handheld allows field users to stay in touch remotely, increasing productivity. This also allows real-time communications with the office for critical information upload. This also provides a level of safety for field users by easily staying in touch with supervisors or persons in charge.
A U.S. Army camp near Townsville’s suburban areas, circa 1944.
By Tracy Cozzens
Beneath the surface of a tropical paradise in the city of Townsville on Australia’s Sunshine Coast lies a hidden maze of tunnels and underground bunkers, once said to be used by General Douglas MacArthur. Learning the secrets of this labyrinth that was a major World War II staging point for battles in the Southwest Pacific is the passion of Kevin Parkes of Geo Positioning Services, Townsville.
Parkes’ main tool is historic aerial photography, coupled with hours of research in the National Australian Archives and the National Library of Australia. To that he adds geophysical surveys of the infrastructure. Parkes is undertaking the geophysical surveying and mapping using an Ashtech ProMark 100 GNSS receiver and a Willy Bayot PPM Mk 3 magnetometer. He used the magnetometer and GPS receiver in parallel, later processing both data sets.
After the attack on Pearl Harbor and the Japanese advance through Asia, Townsville’s population bloomed from 30,000 to 120,000 by mid-1943. The rapid military influx stretched resources to the breaking point.
The U.S. Army 5th Air Force established the largest aircraft repair and maintenance facility ever built in the southern hemisphere at Townsville, and the site became the technical hub of U.S. military aviation. Air Force Service Command Depot #2 at Townsville was capable of overhauling 300 aircraft engines per month and performed aircraft assemblies, modifications, overhauls, and maintenance. Major resources and facilities serviced the Royal Australian Air Force, Australian and U.S. Armies, Royal Netherlands Air Force, Royal Air Force, Canadian forces, Royal Navy, and other allied forces.
“A visitor to Townsville today would be forgiven in asking where the artifacts of this massive military facility are today,” Parkes said. “There is very little remaining in any built structures that give any idea of what happened in this city 70 years ago.”
Parkes realized that underground cave shelters were most likely used for warehousing and storage, to keep stores out of the weather and protected from enemy action.
He describes one area he investigated, a park in Townsville used as an officer’s accommodation camp. Preliminary magnetic anomaly surveys indicated linear anomalies were beneath the park surface. A high-resolution survey gave samples of about 1.5-meter resolution.
“The difficulty was reducing all noise levels down to a minimum, including the X/Y positioning, so the GPS requirements came down to survey quality,” Parkes said. “It is absolutely critical that the GNSS receiver and magnetometer keep in synchronization during data collecting runs including under the frequently encountered tree canopies.”
To improve accuracy, Parkes avoids using real-time kinematic survey equipment. “That would involve having another electronic device operating and emitting more noise in the signal spectrum,” he said. The need to position the GPS antenna in close proximity to the magnetometer sensor was a major issue with all on-pole RTK systems.
A U.S. Army air raid shelter under the officer’s accommodation camp, mapped with GPS and magnetometer data and using Surfer 3D surface mapping software.
With an Ashtech Promark 3, post-processed results were better than 100-millimeter X/Y coordinates. “The unit is lightweight and self-contained,” Parkes said. “The noise from the Ashtech survey-grade external antenna’s effect on the magnetometer data was insignificant.”
Still, this park had a grove of trees that defied every attempt to maintain GPS reception and consequently synchronize the magnetometer. Along came the Ashtech ProMark 100, a lightweight and self-contained receiver with external geodetic antenna with GPS and GLONASS. “My first attempt at surveying under the trees was spectacular to say the least,” Parkes said. “Synchronization with the magnetometer data was near perfect.”
The dual-constellation reception of the ProMark 100 became essential to the success of Parkes’ work. After more than a hundred data-collection passes with the magnetometer and ProMark 100 through the groves of trees, at no time did the Position Dilution of Precision (PDOP) rise to more than three, and at all times more than eight satellites were available. The ProMark 100 data is post-processed to improve accuracy. Parkes noted that ironically many of the most interesting finds have been collected under heavy tree canopy. Without the quality of the geographic positions enabled by the ProMark100 under tree canopy, Parkes said that much of his work would have been impossible to achieve.
Parkes’ surveying equipment includes a magnetometer and a ProMark 100 GNSS receiver.
In fact, when Parkes first began his mapping project in 2005, he used a single-constellation GPS system and post processed the results against the local International GNSS Service (IGS) reference station. The GPS-only system worked very well until a grove of trees would interfere with the sky. Now with the ProMark 100 GNSS receiver, Parkes surveys using GPS L1 and GLONASS in continuous kinematic mode at a one-second collection rate. He then post processes the data against another ProMark 100 used as a local reference station.
To date, Parkes has mapped an underground railway, artillery observation posts, several shelters, fuel terminals and other yet-to-be-identified pieces of the vast infrastructure.
During his Research, Parkes mapped a major magnetic anomaly in Cleveland Bay. In 1770 Captain James Cook in the HMS Endeavour mapped the east Australian coast. Venturing into Cleveland bay, Cook noticed his compass behaving erratically, and named one island Magnetic Island. Today, a 3D surface model reveals a large magnetic anomaly heading across Cleveland Bay and straight towards Magnetic Island, 7 kilometers from Townsville. Experts who have examined the data believe that it is a naturally occurring magnetic anomaly about 800 meters wide. “It would appear that Captain James Cook was indeed a very capable navigator and cartographer,” Parkes said.
The Earth’s surface is constantly shifting, being deformed as earthquake faults accumulate strain, and slip or slowly creep over time. Not long ago, scientists relied solely on seismometers to monitor the earth’s movements. Today, GPS has taken prominence as an indispensible tool.
PANGA, the monitoring network covering the Pacific Northwest, uses GPS to monitor this movement by measuring the precise position (within 5 millimeters or less) of stations near active faults relative to each other. By determining how the stations have moved, ground deformation can be determined.
If the plates near the coast or the Cascade Mountains move even a few centimeters, the scientists at PANGA know within seconds. The network is still being built, but eventually it’s expected that PANGA will be able to sense earthquakes faster and more accurately than traditional seismometers, and issue alerts to warn citizens of impending activity.
“GPS is helpful in distinguishing magnitude 8 from M9 earthquakes quickly,” explained Rex Flake, PANGA. “By design, seismometers only record high-frequency energy that becomes saturated during strong ground motion. Moreover, seismic data ‘clip’ at high magnitudes whereas GPS become more accurate. Seismographs are mainly intended to detect very small to moderately large earthquakes. GPS gives actual ground motions that in theory could be incorporated very quickly into tsunami models and warning systems. That is one of the things we are working on now.”
Volcano Watch. “A more speculative application is that some (not all by any measure) large earthquakes are preceded by slow creep events,” said Andrew Miner, PANGA. “While not really good enough to predict an earthquake, I think if we saw a very large transient creep event it would at least ring alarm bells. Unfortunately though, earthquakes are by their nature just not very predictable, at least to the level of a day or week that people could reasonably act on. On the bright side, volcanoes are reasonably predictable, and GPS is also an important tool in monitoring them. We work with the Cascade Volcano Observatory on several monitoring projects.”
PANGA is one of a series of earthquake monitoring networks stretching along the West Coast. The Pacific Northwest Geodetic Array is run by the PANGA Geodesy Laboratory at Central Washington University (CWU) in Ellensburg, and includes 300 continuously operating, high-precision GPS receivers located throughout the Pacific Northwest. Sixty more stations are expected to be installed this year. Trimble, Leica, Topcon, and Javad are the main receivers used in the region.
Data from these receivers is continuously downloaded, analyzed, archived, and disseminated. About one third of PANGA’s GPS stations are telemetered in real-time back to CWU, where the data are processed using NASA’s Jet Propulsion Laboratory’s GIPSY/OASIS II software for high-precision data analysis, and Trimble’s RTKNet Integrity Manager software for real-time analysis. The data provide relative positioning of several millimeters across the Cascadia subduction zone and its metropolitan regions. These real-time data are used to monitor and mitigate natural hazards arising from earthquakes, volcanic eruptions, landslides, and coastal sea-level hazards.
Sagging Bridges. The data are also used to monitor man-made structures such as Seattle’s sagging Alaska Way Viaduct, the State Route 520 and Interstate 90 floating bridges, and dams throughout the Cascadia subduction zone, including those along the Columbia River. For instance, for the S.R. 520 bridge, PANGA teamed up with Washington State Department of Transportation (WSDOT) to monitor movement of the 520 bridges during wind storms and seismic events.
The receivers continuously monitor and record structural deformation with about a millimeter precision. Raw GNSS satellite phase and pseudorange estimates are acquired and processed continuously into receiver positions estimated every 5 seconds and delivered with 10 and 30-second latencies. Daily-averaged receiver positions computed with predicted and post-processed satellite orbit and clock corrections are provided with 1-6 day latencies.
Seattle’s aging Alaska Way viaduct is one of several major man-made structures being monitored by PANGA’s GPS Network. (photos courtesty of CWU Geodesy Lab.)
Tremor Slips. The Northwest is at the forefront of earthquake-related GPS research, in large part because the area provides a lot to learn from GPS monitoring, Flake said. “For example, when we started it was strongly suspected but not definitely known that the Cascadia subduction zone was locked over parts of its surface and a major earthquake threat. Thanks to GPS monitoring we now have a pretty good idea not only exactly where it is locked, but also when parts of it do slip or creep.
“One important discovery made with GPS data, along this line, was that of the Episodic Tremor Slip (ETS) events that occur here in the Northwest U.S.,” Flake said. “Since the time duration of ETS motion takes place on the scale of days to weeks, these earthquake events were unrealized by traditional seismic detection methods.”
GPS data shed light on this peculiarly predictable earthquake phenomenon. “With these GPS data we can measure strain accumulation within the continental crust (where people live) and calculate the residual that can be expected to rebound in a large subduction zone earthquake,” Flake said.
“Even more detailed than that, we can use GPS data from past ETS events to constrain the locked zone of the subducting crustal plate by inferring the amount of slip at depth that best reproduces the observed GPS recordings — important in determining possible magnitude and location of the megathrust earthquakes (Mw = 8 to 9) that will someday occur. This is of obvious concern to society and is a major reason that we lead the geodetic applications of GPS research.”
Data Online. PANGA maintains a website that integrates daily GPS measurements from about 1,500 stations along the Pacific/North American plate boundary, ranging from Alaska to the U.S-Mexico border. Cleaned, network solutions from several arrays are merged and grouped into regional clusters.
Arrow on a Velocity Field Map of Oregon and Washington represent ground motion as measured by GPS at each particular location. The grey circles are 2 sigma error ellipses (click to enlarge.) (photos courtesty of CWU Geodesy Lab.)The PANGA team constructs a bedrock drill-brace geodetic monument at Howard Hanson Dam east of Auburn, Washington. (photos courtesty of CWU Geodesy Lab.)
The team installs a HARNS in the southern province of Basra. Since 2005, Iraqi engineers have attempted to recover HARNS, but many were destroyed by locals who thought they indicated buried treasure.
As a geodetic surveyor, I served in the U.S Army for 10 years. During that time, my team and I developed a nationwide GPS infrastructure system called the Iraqi Geospatial Reference System (IGRS). We installed Continuously Operating Reference Stations (CORS) and High Accuracy Reference Network Stations (HARNS), the first Iraqi owned and maintained system of its type.
As a native Arabic speaker, my role was to train the Iraqi engineers to install additional CORS, as well as update and maintain the IGRS as a part of the International GNSS Service (IGS) network to sustain the accuracy of engineering and mapping projects. The IGRS was critical to other major infrastructure projects in the effort of rebuilding the battered nation, such as telecommunications, public works, and natural resource management to name a few.
Some of the CORS we installed have Virtual Reference System (VRS) capability, a technology newly developed to establish real-time corrections in the field by using CORS as a base station for real-time kinematic (RTK) data collection.
Key coordinators for the installation included Wisam Al-Hassani of the Iraq Ministry of Water Resources, Paul McKenzie of the Canadian Army, Linda Allen of the U.S. State Department, and myself, representing the U.S. Army, in addition to representatives from National Geodetic Survey (NGS), National Geospatial-Intelligence Agency (NGA), and Trimble Navigation.
In addition to developing the IGRS, we performed several critical projects to assist in the rebuilding efforts as well as providing force protection, navigation, and mapping. My topographic engineering unit was responsible for providing coalition forces with GIS analysis, map production, and geodetic surveys.
GPS equipment collecting data on a reference benchmark used to monitor the deformation of the Haditha Dam.
For my second tour in Iraq (2007–2008), I was the platoon sergeant, which is equivalent to a project manager in a surveying firm. During the 15-month deployment, my team performed various survey projects including: 10 airport obstruction surveys, a dam deformation survey, more than 30 artillery and target-acquisition radar surveys, base-camp designs, site layouts, and ground-truth data collection for photogrammetry and remote sensing projects. We also established a nationwide database of all survey control stations in Iraq. The CORS was installed using Trimble NetRS receivers and Zephyr geodetic antennas. Trimble GPSNet and GPSBase software were used to process the continuous satellite data, for inclusion in the worldwide CORS network for public use. Field survey operations were conducted using Trimble 5700 GPS equipment.
Traveling in Iraq was a major obstacle for survey operations. We had a choice: either fly on helicopters or drive military vehicles. Flying in helicopters with survey equipment was a challenge because we could never fit all our personnel and equipment. However, it was much safer than ground transportation through the dangerous roads of Iraq. In one incident, we were building a bridge in Baiji to help Iraqis and coalition forces cross the Tigris River after the original bridge was destroyed during the 2003 invasion. Our vehicle hit an improvised explosive device (IED). Some of the survey equipment was damaged, but we went back the next day and eventually built the bridge.
Anas Malkawi served 10 years in the Army as a geodetic surveyor and senior technical engineer. He is currently enrolled in Old Dominion University’s Civil Engineering program while working at Transocean International Corporation as the Iraq program manager.
The initial plan of IGRS and placement of CORS/HARN through the Southern provinces.Soldiers establish geodetic control for an airport aeronautical survey.Soldiers survey airport navigational aids that require high geodetic accuracy.Malkawi discusses installation of Iraqi operated and maintained CORS with Al-Hassani.The result of traveling in military vehicles over roads infested with IED.Key coordinators for the installation of the first Iraqi owned and maintained Continuously Operating Reference Station (CORS.) From left are Hussein, Malkawi, McKenzie, and Allen.The 2005 U.S./British IGRS Team. Despite the difficulties, the soldiers I am honored to have served with stayed motivated and performed exceptionally every day by providing accurate data that saved lives.
The use of a precise wide-area positioning technique for airborne trajectory solutions for LiDAR surveys provides both relative and absolute accuracies similar to those derived from using a local GNSS reference station.
Airborne light detection and ranging (LiDAR) surveys are among the most advanced means of producing high-resolution, accurate surface elevation models used for many applications in surveying and civil engineering. Precise geolocation and orientation (or georeferencing) of the LiDAR instrument with a combination of on-board GNSS and inertial sensors at the times when the measurements are made provides the key to high-quality elevation products.
The usual practice deploys reference GPS/GNSS land receivers in the area where the aircraft will be flying, to obtain a precise trajectory by short-baseline differential GNSS techniques. This could mean installing and operating receivers at many sites during a flight mission if the area surveyed is a large one.
We have tried a different approach: using as reference receivers those of a sparse network of Continuously Operating Reference Stations (CORS) in New South Wales known as CORSnet-NSW, and a wide-area differential GPS technique for obtaining the aircraft trajectory with sub-decimeter accuracy even with baseline lengths of several hundred kilometers. This may be comparable in precision and accuracy to the short-baseline method, but without the cost and logistical complications. This opens up a new level of operational capability, allowing flexibility for weather conditions and priority response applications.
The tests described here were organized and conducted by the NSW government’s Land and Property Management Authority, in collaboration with the University of New South Wales, in June 2009. CORSnet-NSW consists, at this writing, of 46 stations and by 2012 will provide statewide GNSS positioning infrastructure across NSW with a planned 70 stations in operation.
Precise Wide-Area Positioning
We used a technique for long-baseline differential, off-line positioning, able to deliver centimeter precision for fixed receivers and sub-decimeter precision for moving receivers. This choice was dictated by three considerations:
The intended application was the geolocation of the data of an airborne scanning LiDAR sensor to be used in the generation of high-accuracy digital elevation models (DEM).
Off-line processing, where all the GNSS data collected during the flight are available for processing and (as in this case) there is no need for immediate results, is intrinsically more reliable than real-time processing, where the data are available only up to the present epoch, and accurate results must be obtained right away, with no chance for a second try.
Differential processing makes it possible to resolve the carrier-phase ambiguities using well-understood methods.
Technique. It is common practice in airborne LiDAR surveys to use GNSS both to position the instrument precisely, and to assist an inertial navigation system (INS) to obtain the orientation of the aircraft in space, as both position and orientation are needed to interpret the data properly. FIGURE 1 illustrates the relationship between the sensors used for airborne LiDAR surveys. The aircraft uses a GNSS antenna combined with an INS to georeference its trajectory. The bore-sight calibration process aligns the individual sensor orientations and standardizes the range measurements. However, if the survey is to achieve the now-expected high level of vertical accuracy (615 centimeters, 1 sigma), then the position of the GNSS/INS-derived aircraft trajectory for each laser swath must be determined with a relative precision in the order of just a few centimeters. This is achieved via differential GNSS post-processing of the kinematic airborne data together with static observations collected on precisely surveyed ground reference stations. The GNSS positions are then blended with high-frequency measurements taken by the onboard INS to produce the final trajectory and reference orientations.
Figure 1. Airborne LiDAR reference frame.
To such ends, the aircraft trajectory is usually determined by short-baseline differential GNSS, with ground receivers deployed near the intended flight path of the aircraft. In this way it is possible to use GNSS data analysis techniques that are both precise and quite straightforward to implement in software. The simplicity of these techniques is possible because, in short-baseline differential solutions, the data of the aircraft receiver and any nearby network receivers have much the same systematic errors (due to such things as satellite ephemerides errors, transmission delays, and so on) that cancel out — or nearly so — when their observations are differenced between them. This also makes it possible to resolve quickly and reliably the cycle ambiguities in the observed carrier phase, the most precise type of GNSS data, overcoming one of the main obstacles to obtaining good results. Furthermore, it is possible to get such results with single-frequency receivers, as ionospheric delay is one of the systematic effects that can be largely canceled out.
In wide-area solutions, those cancellations are not complete enough to ignore the systematic data errors, and they have to be included in the form of additional unknown parameters in the observation equations. Also, it is necessary to account for the ionospheric delays using dual-frequency data, which means using more expensive GNSS receivers and antennas.
Resolving the carrier-phase ambiguities is no longer straightforward or assured. The standard way of dealing with the ambiguities is to include them as unknowns in the observation equations and adjust them along with the other unknowns: this is often referred to as “floating the ambiguities.” Fixing (or resolving) those ambiguities to their most likely integer values in a matter of seconds to a minute is possible on occasion, when the aircraft is within less than 20 kilometers from a ground receiver, or very precise corrections for the ionospheric delay are available; otherwise slower techniques, that require tens of minutes, may be used. It is also necessary to correct as well as possible such things as the neutral atmospheric delay of the GNSS radio signals, the movement of the “fixed” stations due to plate tectonics, the solid earth tide using mathematical models, and, in the case of the tropospheric delay, estimating the error in the corrections made using a standard formula as an additional unknown per receiver.
Over the years all these difficulties have been gradually dealt with more effectively, more efficiently, more reliably and, from the user’s point of view, less painfully. Originally developed for the repeated determination of station positions to measure the slow tectonic deformations of the Earth’s crust, and to calculate precisely the orbit of Earth-observing satellites, these days, after nearly 30 years of steady progress, GNSS wide-area techniques and the corresponding software find many applications in science, engineering, and navigation, and are becoming widely used in remote sensing.
Software. We used the Interferometric Translocation (IT) wide-area positioning software developed by one of us for the long-baseline aircraft trajectory solutions and also to re-position in the IGS05 international reference frame some CORSnet-NSW stations, so their data could be used consistently in the differential wide-area solutions. These stations were originally given in the Geocentric Datum of Australia (GDA94). For both purposes we used the precise final GPS orbits computed and distributed by the IGS.
To validate the aircraft trajectories calculated with the wide-area method, we relied mainly on the quality of the LiDAR DEM results obtained with those trajectories. We also used commercial software to generate short-baseline differential solutions with receivers deployed near the intended aircraft flight-path, as is common practice in this type of survey, and compared them with the wide-area solutions (they turned out to be quite similar to short-baseline solutions obtained with the wide-area software).
Airborne Tests
This study has used data from two airborne LiDAR surveys conducted by the NSW Land and Property Management Authority (LPMA) in June 2009. The first took place near the township of Glen Innes, and the second was a bore-sight calibration flight near the city of Bathurst. For both LiDAR surveys, the following data were acquired:
Aircraft trajectory, raw dual-frequency GPS (1 Hz) and IMU data (200 Hz).
LiDAR (raw return data for each laser pulse).
GPS reference station data from local receivers and multiple CORSnet-NSW sites.
Glen Innes Test. This operational LiDAR survey established GND1 as the local reference station within the survey area. CORSnet-NSW data were collected for the test from GNSS receivers in Ballina (BALL), Grafton (GFTN), Nowra (NWRA), and Wagga Wagga (WGGA). FIGURE 2 shows the distribution of the reference stations and the flight runs.
Figure 2. Glen Innes survey of June 9, 2009, showing the distribution of reference stations with baseline lengths and the survey area with (numbered) flight runs.Bathurst Test. Bathurst Airport is LPMA’s LiDAR calibration site and has various arrays of accurate ground checkpoints. AIR2, near the runway of the Bathurst airport, is the locally established GNSS reference station. CORSnet-NSW data were collected for the test from receivers in Ballina (BALL), Dubbo (DBBO), Grafton (GFTN), Newcastle (NEWC), Nowra (NWRA), and Wagga Wagga (WGGA). FIGURE 3 shows reference-station distribution and a schematic of the flight runs.
Figure 3. Bathurst test of June 16, 2009, showing the distribution of reference stations with baseline lengths and the survey area with (numbered) flight runs.
Effect on LiDAR Data
Rather than simply comparing aircraft trajectories, this study aimed to determine what effect the use of wide-area GNSS positioning has on the actual LiDAR point data and associated elevation surfaces. In terms of the horizontal accuracy required for LiDAR surveys, initial tests showed that the differences between the horizontal positions of various trajectories was negligible; therefore, only the vertical component was considered in this analysis.
To quantify differences between LiDAR data generated from trajectories using various combinations of distant GNSS reference sites, we applied four types of analysis:
Comparison of trajectories — directly compare the locally computed trajectory (assumed to be truth) with each wide-area derived trajectory.
Relative LiDAR point comparison — compare the positions for a sample of LiDAR ground points derived from the locally computed trajectory with those derived from each wide-area derived trajectory.
DEM comparison — difference the raster surfaces derived from the locally computed trajectory and a wide-area derived trajectory to find the effect over a LiDAR run.
Absolute LiDAR ground control comparison — compare the LiDAR derived surface from various trajectories to the surveyed ground control (Bathurst Calibration test site only). This also involves vertically shifting the resulting surface so that its offset relative to the one used as control is zero, thus removing the effect of using different reference frames for the GNSS trajectories and the control surface.
Trajectory Comparison
The comparison between the locally determined and each wide-area derived trajectory was made along the entire trajectory for each flight. The importance of this step lies in the assumption that all LiDAR data are directly positioned from the trajectory and so any systematic effect in the trajectory should be reflected on the ground. For each test site the locally derived solution is assumed to be “truth” with the vertical difference computed against wide-area solutions for each combination of reference stations used (TABLE 1).
Glen Innes Test. FIGURE 4 shows the vertical comparison of two wide-area derived trajectories (using BALL and GFTN, and WGGA and NWRA, respectively) against the locally derived trajectory (using GND1). It can be seen that once the aircraft attained its stable operating altitude, the wide-area derived trajectories are generally within 5 centimeters of the locally derived solution.
Figure 4. Trajectory elevation differences for entire Glen Innes flight.
Bathurst Test. The Bathurst test differs from the Glen Innes test in that both the duration of the flight and the length of each run are significantly shorter. FIGURE 5 shows the vertical component of five wide-area derived trajectories, using several combinations of CORSnet-NSW reference stations, compared against the locally derived trajectory (using AIR2). The results once again show a remarkably consistent comparison with the locally derived solution. Data spikes showing up in the DBBO/WGGA/NEWC (yellow) solution were attributed to small data glitches at the DBBO CORSnet-NSW site. Unfortunately, LiDAR data were not collected at those instances; therefore, the effect on ground data could not be fully assessed.
Figure 5. Trajectory elevation differences for entire Bathurst calibration flight.
Relative Comparison
Regardless of the trajectory and orientation used to georeference LiDAR data, the same number of points will be created. It is therefore possible to create a LiDAR dataset using the same raw LiDAR data but different GNSS trajectories, and compare the results to determine the relative positioning differences on the ground.
Given the large number (many millions) of points in a LiDAR dataset, we used a representative sample of evenly spaced 10 2 10 meter areas each containing 50–100 points (on level ground) for statistical analysis. We calculated displacement vectors between points computed from the locally derived trajectory and those using wide-area trajectories. Results from flight run 002 at Glen Innes (see Figure 2) and run 7 at the Bathurst Calibration test site (see Figure 3) are presented here.
Glen Innes Test Run 002. The displacement vectors from 46 sample areas (4,620 points) are summarized in TABLE 2, being points computed using the two wide-area solutions compared with the locally derived solution using reference station GND1. Note the high accuracy achieved in the all important vertical component.
Bathurst Test Run 7. The displacement vectors from 25 sample areas (1,700 points) are summarized in TABLE 3, being points computed using the five wide-area solutions compared with the locally derived solution using reference station AIR2. Once again the results clearly show that the height values agree to within a few centimeters, even over baselines of more than 600 kilometers in length.
DEM Comparison
To investigate how the LiDAR surfaces derived from each trajectory compare across the entire data swath, we created raster surfaces from the LiDAR point data. Each surface was then subtracted from the local solution to create a difference surface. Visual inspection and interpretation was then used to discern any patterns or effects.
The result shown in FIGURE 6 (Bathurst Calibration flight run 7) was typical of the cyclical effect evident for all solutions. The magnitude of the difference was in the order of 2–3 centimeters and is in the direction of flight (north to south). If this cyclical variation is compared with the trajectory comparison for just the 33-second duration of flight run 7, a clear (expected) correlation with the variation in height is evident (FIGURE 7).
Figure 6. Subtraction surface for Bathurst Calibration run 7 (AIR2 vs. BALL).Figure 7. Trajectory comparison for Bathurst Calibration run 7 (031318).
No DEM comparison results are presented for the Glen Innes data because of significant variation in terrain and vegetation, making interpolation difficult and unreliable.
Absolute LiDAR Comparison
Ground control points serve two purposes in a LiDAR survey:
The calculation of statistics to describe vertical accuracy, that is, quantifying the match of the surface to the local height datum.
The calculation of a surface adjustment to enable transformation of the LiDAR points to fit the local height datum.
Additionally, ground control points with accurate heights are used to calibrate the sensor before use in active LiDAR surveys to account for internal electrical delays in the ranging and measurement system. LPMA maintains a calibration site at Bathurst Airport for this purpose, and regularly surveys the area to ensure the sensor is operating at maximum accuracy. It should be noted that the sensor was calibrated using Bathurst Airport ground control data prior to this study.
Surveyed Ground Control. The airport runway centerline vertical profile for the Bathurst Calibration site (FIGURE 8) was re-computed in terms of the same IGS05 reference frame determined for the LiDAR trajectories, thereby allowing an independent comparison with ground truth.
Figure 8. Runway vertical profile at the Bathurst Airport calibration site.
Point Comparison. Data from Bathurst run 7 were used to compare LiDAR results with the established ground control using a basic triangulated irregular network (TIN) surface comparison (FIGURE 9 and TABLE 4). In Figure 9, the TIN surface is indicated by the white line, while the ground control points are shown with yellow buffers.
Figure 9. Comparison of LiDAR surface and ground control points.
The first trajectory in Table 4 is the original calibration comparison using commercial software and orthometric height data. All wide-area solutions display a similar vertical offset, because of the use of different reference frames for the GrafNav and wide-area solutions (IGS05 vs. GDA94), and differences in the implementation in software of, for example, antenna corrections and atmospheric modeling. At first glance, the significant differences to the GrafNav trajectory caused the wide-area result to not satisfy the accuracy specifications for LiDAR. However, had the wide-area solutions been used for the sensor calibration, the figures would have been much closer to the ground truth.
Block-Shifted Data Comparison. In an operational environment, because of systematic errors in the resulting DEM relative to the local height datum, this mean vertical offset is a common occurrence with comparisons against ground control similar to those shown in FIGURE 10. Again, the TIN surface is indicated by the white line, and the ground control points are shown with yellow buffers.
Figure 10. Usual operational comparison of LiDAR surface and ground control points.
In standard LiDAR operations, the mean vertical offset between the initial results and the ground control, at the control points, produces a zero-mean offset. Following this procedure in this case results in the variation in the comparison of LiDAR data with ground truth now being well within the required limits of 615 centimeters (TABLE 5). The values show that after a block shift, trajectory solutions are virtually identical with a root mean square error of 32 millimeters. Thus, local GNSS reference stations can be replaced by distant CORS sites without loss of accuracy.
Conclusions
A precise wide-area positioning technique for airborne trajectory solutions provides both relative and absolute accuracies similar to those derived from usinga local GNSS reference station. Irrespective of which reference sites are used and once calibration and antenna modeling issues are addressed, the absolute comparison with ground control is well within the required accuracies. With the configuration of a GNSS network such as CORSnet-NSW (when complete, at least one site will always be within 150 kilometers of any point within New South Wales), an airborne LiDAR survey in the network’s service area can provide data for computation of an accurate sensor trajectory. This potentially negates the need to place and maintain ground reference stations close to the survey area — an exercise which not only requires significant resources but also reduces the operational flexibility of the aircraft.
The challenge for this technique in an operational environment is to define and maintain a precise reference frame for all CORSnet-NSW sites and observations, including the use of a stable ellipsoidal height datum with compatible geoid modeling in order to provide local orthometric elevation data. The knowledge base required for computation of wide-area GNSS solutions is significant and requires understanding of geodesy, GNSS positioning, absolute antenna modeling, application of precise ephemerides, and derivation of the other parameters inherent to successful ambiguity resolution over long distances.
Regardless of processing method, a LiDAR survey will always require independent ground surveys for collection of vertical checkpoints, which provide quality control to ensure the accuracy meets specifications, and the means to define any transformations necessary to fit LiDAR data with local height datum.
Manufacturer
NovAtel’s WayPoint GrafNav software was used for comparison purposes.
The ”IT” Software
Runs under Windows, Unix, Linux, and FreeBSD.
Source code compatible with most Fortran compilers.
Follows the IERS 2003 conventions.
Available mainly for collaborative research purposes, with a Free Software Foundation General Public Lice
nse.
Stop-and-go for rapid mobile surveys with pre-surveyed waypoints.
Differential, precise point positioning, mixed mode (precise differential + point positioning).
Data corrected for: Earth tide, neutral atmosphere radio signal delays, carrier phase windup, and so on.
Estimated parameters:
Receiver position in the IGS05 reference frame, with the WGS84 reference ellipsoid, earth spin-rate, light speed, GM constant.
Biases in ionosphere-free carrier-phase linear combination (“floated” ambiguities).
Neutral zenith delay correction error.
Broadcast orbit errors (allows precise differential near-real time solutions).
Integer ambiguity resolution available in differential mode, with short baselines up to 20 kilometers (in minutes), and baselines of unlimited length (in tens of minutes — or just minutes, with a precise ionosphere correction).
Oscar L. Colombo received a degree in electrical engineering from the National University of la Plata, Argentina, and a Ph.D. in electrical engineering from the University of New South Wales, Australia. He is an independent consultant.
Shane Brunker is an airborne LiDAR and imaging specialist working in a consulting capacity for specialized LiDAR survey company Network Mapping (United Kingdom).
Glenn Jones is a senior surveyor at the NSW Land and Property Management Authority in Bathurst, Australia.
Volker Janssen is a GNSS surveyor (CORS Network) in the Survey Infrastructure and Geodesy branch at the NSW Land and Property Management Authority in Bathurst, Australia. He holds a Ph.D. from the University of New South Wales.
Chris Rizos is head of the School of Surveying and Spatial Information Systems of the University of New South Wales, has a surveyor’s degree and a Ph.D. from the same university, and is an specialist in geodesy and GNSS positioning.
Trimble has introduced an innovative Global Navigation Satellite System (GNSS) reference receiver for infrastructure, precise scientific, and network applications. The Trimble NetR9 GNSS reference receiver is a Continuously Operating Reference Station (CORS) receiver that can support the demanding applications for the earth science community and for the surveying, construction, mapping, and agricultural industries, Trimble said, adding that the NetR9 was designed to provide the user with maximum features and functionality from a single receiver.
The Trimble NetR9 reference receiver offers 440 channels for robust GNSS constellation tracking. The receiver supports a wide range of satellite signals, including GPS and GLONASS signals. In addition, Trimble is committed to providing Galileo-compatible products in advance of Galileo system availability, the company said. In support of this plan, the Trimble receiver is capable of tracking the experimental Galileo GIOVE-A and GIOVE-B test satellites for signal evaluation and test purposes.
The Trimble NetR9 reference receiver can be used as a standalone receiver or as part of a network solution. Specific applications include high-accuracy positioning as part of a Trimble VRS network, as a mobile field base station or CORS for real-time kinematic (RTK) corrections, as a scientific reference station collecting information for specialized studies, as a field campaign receiver for post-processing applications, and as support for Differential Global Positioning System (DGPS) coastal beacons. In addition, the Trimble NetR9 reference receiver can be used for monitoring the integrity of VRS networks as well as the deformation of physical infrastructure such as bridges, dams, mines, oil platforms, and other natural and manmade structures.
The Trimble NetR9 reference receiver’s large internal memory (8 GB) allows post-processed results for base stations to be computed after survey completion, improving the accuracy of the survey. The highly compressed secure internal memory allows for more than 20 years of 15-second dual-frequency GPS data storage. In addition, the NetR9 also has USB logging capability for additional storage capacity, Trimble said.
The receiver supports the new CMRx communications protocol, which provides correction compression for optimized bandwidth and full utilization of all satellites in view. This gives the customer more robust positioning data and reliable positioning performance, Trimble said.
Optimized for field use with built-in rechargeable batteries, the NetR9 reference receiver consumes very little power and can be used for projects with remote connectivity and in extreme weather conditions. It has an IP67 rating, which means it is sealed against dust and can survive immersion in up to a meter of water for approximately 30 minutes. It also meets MIL-STD 810F standard for drops, vibration, and temperature extremes.
The Trimble NetR9 has its physical memory built into the circuit board, providing greater protection of data, particularly under extreme conditions. Multiple built-in serial ports supply communications and power to support field use, whether connecting to a radio for RTK surveys, direct communication with a satellite phone for remote operations, or for ancillary input devices such as inclinometers and meteorological sensors, and it offers Bluetooth communication with a cell phone for real-time data streaming. In addition, both power and Ethernet can be supplied over a single cable using Power over Ethernet (PoE) technology.
By Ana P. C. Larocca, Ricardo E. Schaal, and Augusto C. B. Barbosa, University of São Paulo
Multipath makes it difficult to detect very low-frequency structural vibrations, ranging from 0.05 to 1 Hz, important in characterizing dynamic loads and determining safe structural lifetimes. The authors have developed a phase-residual method for use with very high-frequency data to distinguish receiver noise, multipath, and the periodic displacements that are most structurally significant. The methodology can apply to bridges, tall buildings, and towers.
Civil engineers continuously seek reliable methods and tools to improve the quality and lifetime of large structures. Most studies in this field have been based on static loading. Nowadays, dynamic loading has become a particular concern, and GPS offers direct measures of dynamic displacements of large structures induced by traffic, wind, and earthquakes.
Precisely characterizing the vibrations that are a common behavior of large structures such as bridges, tall buildings, and towers undergoing dynamic loads facilitates structural analysis studies. It is feasible to detect structural vibrations using a computational model and GPS sensors. The critical vibration frequencies of bridges detectable with different GPS positioning techniques (real-time kinematic, static, quasi-static) range from 0 to 0.3 Hz.
However, the unavoidable presence of multipath signals in the same frequency range makes it difficult to detect very low-frequency vibrations, mostly ranging from 0.05 up to 1 Hz, for short- to medium-span bridges.
Our preliminary results show that the structural vibration measurements, mixed with random amplitude and frequency signals generated by electronics and the ionosphere, together with slowly varying signals generated by multipath, can be better detected with an oversampled GPS data set. This hypothesis relies on fact that the structure oscillation is reasonably stable during the data-collecting period.
The analyses of GPS time series used were done by mathematical addition of well-known sine waves in the raw phase of a 100-Hz data set collected from a short baseline. This strategy simulates the antenna vibrating vertically on a structure, for example at the deck’s midpoint of a bridge.
Methodology
The methodology used to collect and analyze GPS data was developed for providing low-cost high-accuracy monitoring with single-frequency GPS receivers. The technique is the interferometry method based on the analysis of the L1 double-difference phase residuals of regular static observations. In this data-processing, one satellite is considered as a reference, and its selection is according to the direction of the vibration to be measured. The satellite not taken as a reference — located in the same direction as the vibration movement — has the residual values that contain information about bridge deckvibrations (phase changes). In 2001, we named this the phase-residual method (PRM); see “Millimeters in Motion” in GPS World, January 2005.
The residuals incorporate all phase deviations from the adjusted double-difference position during the observation. These phase deviations are due to electronic receiver noise, multipath, small dynamic antenna movements, and other error sources. Converting the residuals to the frequency domain by the fast Fourier transform (FFT) associated with a continuous wavelet transform (CWT), it is possible to see the different behaviors of the receiver phase noise,
multipath, and periodic vibration, enabling the distinction between them. The periodic displacement presents a peak due to the fundamental vibration mode, while the receiver noise presents a white-noise spectrum, and the multipath presents a broad spectrum close to zero frequency. The last feature is very dependent on how the antennas “see” their vicinity. As PRM does not need well-known coordinates epoch-by-epoch to determine the amplitude and the frequency values of the oscillations, it is possible to get reliability.
The spectrum analyses were done by FFT, which provides a design of the vibration’s peak amplitude values; the CWT was used to detect the variation of the frequency value during the timespan of observations, and for validating the results.
Simulation and Filtering
The preliminary investigation was done by the mathematical addition of sine waves on satellite signals close to zenith, which are the most affected by a vertical amplitude vibration in a real situation. The double-difference phase was calculated, taking as reference the lowest satellite.
The mathematically generated sine wave had peak-to-peak amplitude of 1 millimeter and frequency values ranging from 0.06 Hz up to 1 Hz. The analyses for sine-wave detection were done by applying the FFT and the CWT with the Morlet Wavelet, which deserves a short description.
The CWT was used because structural vibration signals with small peak-to-peak amplitudes in the low frequency region are not well represented in time and frequency by the FFT methods. A particular wavelet, Morlet, was used and is defined as
(1)
where wo is dimensionless frequency and η is dimensionless time. When using wavelets for feature extraction purposes, the Morlet wavelet is a good choice, because it provides a good balance between time and frequency localization.
The idea behind the CWT is to apply the wavelet as a band-pass filter to the time series. The CWT of a time series (f (t),t = 1,…,N) with uniform time steps dt, is defined as the convolution of f (t) with the complex combination of the mother wavelet scaled and normalized, as:
(2)
where Wj,k(t) represents the similarity between wavelet function and the analyzed time series f (t); that is, the higher the value of Wj,k(t), the greater the similarity between the analyzed function and the mother wavelet function that modulates the analyzed signal. The CWT was implemented in MATLAB software.
100-Hz Phase Data
Regarding the detection of low frequencies due to a small peak-to-peak amplitude vibration, it is important to show the L1 double-difference residuals of a 100-Hz data rate (Figure 1) and its spectrum before mathematically adding the sine-wave signal due to periodic vibrations. The figure shows the raw phase residuals of 20 seconds of data between two satellites, SV05 (lowest) and SV20 (highest).
FIGURE 1. Raw L1 double-difference phase residuals from a time series at a 100-Hz data rate.
Figure 2 presents a 1-second data span for better visualization of peak-to-peak amplitude of the raw double-difference phase residuals, which is lower than 3 millimeters.
FIGURE 2. Residuals from L1 double-difference phase residual.
Figure 3 was produced to verify the variability of 100-Hz residuals and the probability of errors in the signal that can contribute to degrading the identification of the sine-wave vibration peaks. The resulting histogram is close to a bell curve of a Gaussian distribution, demonstrating the good quality of the 100-Hz data. Figure 4 shows the Morlet CWT computed to identify the low-frequency bias term and a high-frequency noise term. The 5-percent significance (95-percent confidence) level of significant signal-wave information is delimited by a thick contour. The signal information of double-difference phase residuals was used as a reference for supporting a better distinction between noise and sine-wave signals.
FIGURE 3. The Gaussian distribution of 100-Hz data rate residuals.FIGURE 4. Continuous Wavelet Transform of the residual time series. The 5-percent significance level of sine wave detection is shown as a thick contour.
Zero-Baseline Test
A zero-baseline test was performed to determine the correct operation of a GPS receiver, associated antennas, and cabling. The objective was to verify the precision of the receiver. A 1-minute data sample was collected. Figure 5 shows the residuals of L1 double-difference phase.
FIGURE 5. Zero baseline 100-Hz data rate residuals of L1 double-difference phase.
Figure 6 shows 5 seconds of the zero-baseline data; the peak-to-peak amplitude of residuals is very small, close to 2.0 millimeters. This information leads us to expect detection of very low-frequency vibrations, ranging up to 0.3 Hz with a 1-millimeter amplitude displacement peak-to-peak.
FIGURE 6. Residuals from a zero baseline with 100-Hz data.
Figure 7 shows the spectrum of the zero-baseline residuals; it is possible to observe the region close to zero strongly affected by multipath. This makes the detection of very low frequencies difficult.
FIGURE 7. Power spectrum of a zero-baseline residual.
The CWT was applied to decomposing the zero-baseline double-differenced residuals into a low-frequency bias term and a low-frequency noise term. Figure 8 shows the behavior of the residuals of the 100-Hz phase data, where red regions represent the most suggestive energy level of the measurement noise term.
FIGURE 8. Morlet CWT of zero-baseline residual time series. The 5-percent significance level of sine-wave detection is shown as a thick contour.
Preliminary Simulation Results
Figure 9 illustrates the raw L1 double-difference phase residuals with a periodic sine wave of 1 millimeter peak-to-peak amplitude mathematically added to the time series. It is possible to observe the presence of the periodic signal.
FIGURE 9. Raw L1 residual time series with a sine wave of 1-Hz frequency and 1-millimeter amplitude.
Figure 10 shows that the stronger energy is close to 1 Hz due to the 1-Hz sine wave, as expected. The resulting well-defined peak is due to the high sampling rate provided by 100-Hz receivers. Figure 11 shows details of the peak due to the sine wave of 1 Hz added to the residuals.
FIGURE 10. Spectrum of L1 double-difference phase residuals with a sine wave of 1 Hz and 1 millimeter.FIGURE 11. Close-up of region with the most power at 1 Hz.
We analyzed these data with the Morlet CWT to find events to compared when other low frequencies had been simulated, helping separate noise from signal. Figure 12 presents the standardized time-series residuals, showing a region with highest power level. The continuous red region corresponds to a 1-Hz sine wave, and the spread-out red-orange regions may be due to electronic noise and multipath. The region outside the cone, delimited by the thick contour, indicates the detection of significant signal information but without the 95-percent confidence.
FIGURE 12. Morlet CWT of time series of residuals with 1-Hz sine wave with 1 millimeter amplitude. The 5-percent significance level of sine-wave detection is shown as a thick contour.
0.5-Hz Sine Wave. The second sine wave generated had the same peak-to-peak amplitude, 1 millimeter, and the frequency value of 0.5 Hz. Figure 13 illustrates the raw L1 double-difference phase residuals with a periodic 0.5-Hz sine wave mathematically added to the time series.
FIGURE 13. Raw L1 double-difference phase residuals with a sine wave of 0.5 Hz.
Figure 14 shows an energy peak at a frequency of approximately 0.5 Hz, also with a well defined peak.
FIGURE 14. Spectrum of L1 double-difference phase residuals with a sine wave of 0.5 Hz.
Figure 15 shows details of the peak.
FIGURE 15. Close-up of region with the most power at 0.5 Hz.
The CWT in Figure 16 shows that the intensity energy level represented by the red continuous region and the spread-out red-orange regions are quite similar to those of the CWT of the 1-Hz sine wave (Figure 12). Note a decrease in energy intensity (orange-yellow) that occurs due to decreased signal sampling of the 0.5-Hz signal (10 cycles) in 20 seconds of data, compared to 1 Hz (12 cycles) in the same 20 seconds.
FIGURE 16. Morlet CWT of time series of residuals with 0.5 Hz sine wave with 1 mm amplitude. The 5-percent significance level of sine wave detection is shown as a thick contour.
0.1-Hz Sine Wave. The third sine wave mathematically generated had the same peak-to-peak amplitude, 1 millimeter, and a frequency of 0.1 Hz. Figure 17 illustrates the raw L1 double-difference phase residuals with the periodic 0.1-Hz sine wave mathematically added to the time series. Figure 18 shows the power at one frequency, approximately 0.10 Hz, still with a well-defined peak.
FIGURE 17. Raw L1 double-difference phase residuals with a sine wave of 0.10 Hz.FIGURE 18. Close-up of region with the most power at 0.10 Hz.
Figure 19 presents identification of the 0.1-Hz sine wave by CWT with the 5-percent significance level shown as a thick contour. A decrease of energy intensity (orange-yellow) occurs due to decreased signal sampling of 0.1 Hz (2.5 cycles) in 20 seconds of data compared to 0.5 Hz (10 cycles) in the same 20 seconds.
FIGURE 19. Morlet CWT of time series of residuals with 0.1-Hz sine wave with 1-millimeter amplitude; 5-percent significance level of sine wave detection shown as a thick contour.
0.08-Hz Sine Wave. We simulated a sine wave of this frequency (Figure 20). Figure 21 presents identification of the 0.08-Hz sine wave by CWT through the 5-percent significance level shown as a thick contour. A decrease in energy intensity (orange-yellow) occurs due to decreased signal sampling of 0.08 Hz (almost two cycles) in 20 seconds of data compared to 0.5 Hz (ten cycles) in the same 20 seconds.
FIGURE 20. Close-up of region with most power at 0.08 Hz.FIGURE 21. Morlet CWT of time series of residuals with 0.08 Hz sine wave with 1-millimeter amplitude; 5-percent level of sine-wave detection shown as a thick contour.
0.06-Hz Sine Wave. Finally, a 0.06-Hz sine wave was simulated and added to the residuals, but the FFT spectral analysis did not present the power peak. This can be attributed due to the sine-wave period providing only 1.5 cycles during 20 seconds and did not generate enough power to be detected by FFT.
Figure 22 presents a close-up view of 0.06-Hz sine-wave power spectrum of the residuals not indicating a significant peak close to the expected frequency region.
FIGURE 22. Power spectrum of double-difference phase residuals with 0.06-Hz sine-wave signal.
The investigation continued with a Morlet CWT. In Figure 23 it is possible to verify the presence of a faded red region close to the period corresponding to 0.06 Hz — at the bottom of figure and under the cone’s thick contour — signalling that the wavelet was able to detect a very low frequency even with a small sampling. However, due to small signal sampling, the detection is not within a 95-percent confidence. Otherwise, if the time series had lasted more than 20 seconds, certainly the sine wave would have been detected.
FIGURE 23. Morlet CWT of time series of residuals with 0.06 Hz sine wave with 1-millimeter amplitude.
These analyses suggest that longer time-series data would enable detection of very low frequencies with 95-percent confidence.
Conclusions
The lack of amplitude accuracy does not constitute a significant restriction in large structure monitoring, as the exactness of its natural oscillating frequency, harmonics, and response to external dynamic forces are more important for identification of a structural problem.
Using 100-Hz receivers to detect very low-frequency vibrations, the combination of 100-Hz data with filtering techiniques enables detection of signal vibrations of very low frequencies. The tests were conducted using a mathematical simulation of sine waves added to raw residuals of L1 double-difference phase.
The results of simulations and filtering techniques indicate that very low frequency vibrations can be detected when the sampling rate of GPS data and the sampling frequency of an embedded sine wave is large.
Additionally, zero baseline and static short baseline trials have been conducted to assess the noise of the receivers that is close to 2.5 millimeters — extremely low and contributing to detection of vibrations with low peak-to-peak amplitude.
Spectral analysis is a fundamental tool for engineering development. Despite such new analysis concepts as FFT and CWT used here, as well as higher-order spectra, basic frequency domain analysis will remain the practical analysis tool in the foreseeable future.
Future tests will be carried out collecting 100-Hz data, sufficient for having oversampling of sine-wave frequencies due to structural vibrations, and using a new methodology with just one GPS receiver.
Acknowledgments
Thanks to the JAVAD GNSS Moscow Research and Development team for providing a Triumph receiver and 100-Hz data through Michael Glutting, whom we also thank. The researchers received a sponsorship from the National Counsel of Technological and Scientific Development Government (CNPq) of the Brazil Federal Government to purchase a pair of 100-Hz data-rate GPS receivers.
Manufacturers
The 20 seconds of data were kindly provided by JAVAD GNSS Moscow Research and Development team and were collected using Javad GNSS Triumph receivers with JNS choke-ring antennas.
Ana P.C. LaRocca is a lecturer in the Department of Transportation Engineering of the Polytechnic School at the University of São Paulo (USP) and holds a Ph.D from that same institution.
Ricardo E. Schaal is an associate professor with a Ph.D. from USP.
Augusto C. B. Barbosa is a Ph.D candidate at the Institute of Astronomy, Geophysics and Atmospheric Sciences, at USP.
By Steven M. Di Naso, Vincent P. Gutowski, Harvey Henson, and Ryan Leonard
During the winter of 1838–39, the great Native American Cherokee Nation trekked across southern Illinois, in a forced removal by the U.S. government from their ancestral homeland in Tennessee. Harried, unequipped, and unsupported by their captors, thousands died on the Trail of Tears. Burial records were not kept, and burial locations remain lost to this day. Local history suggests that some Illinois settlers allowed the Cherokee to bury their dead on small plots of land adjacent to their own family cemeteries. One such plot, the Campground Presbyterian Church cemetery near Anna, Illinois, may contain unmarked Cherokee graves.
Researchers from Southern Illinois University and Eastern Illinois University used GPS to navigate and precisely map probes of a ground-penetrating radar (GPR) instrument in the cemetery. We monumented the geophysical survey grids using real-time kinematic (RTK) DGPS. Site topography was also mapped using GPS, as were the individual cemetery headstones. Adding geographic information systems (GIS) software to our mix to map cemetery headstone distribution and record headstone attributes (dates of death, names), we could determine chronological gaps within the cemetery that coincide with the probable emigration of the Cherokee.
GPR and electromagnetic conductivity produced contour plots of high-resolution magnetic gradient data. Small dipolar anomalies detected are typically related to disruptions within near-surface soil horizons and may correspond to locations of shallow graves: the lost final resting places of many Cherokee.
By close examination of the geophysical survey data and the anomalies produced from them, we were able to present plausible if not possible locations of several gravesites. However, at this time, and for obvious reasons, the actual location must remain secure and cannot be published.
The figure below shows a mosaic of amplitude depth slices at .30–.70 meter intervals from processed interpolated 250-MHz GPR profile data. White rectangles denote known graves. Most marked graves were imaged, although some were represented as more subtle anomalies on this display. Some possible unmarked graves were interpreted at UTM coordinates xxxx, yyyy.
The cemetery is within working distance of CORS station ILCB at Southern Illinois University. Two RTK GPS units communicating with the station via CDMA cellular radio used real-time differential corrections along a variable baseline length of approximately 28.5 kilometers, enabling mapping of the site at centimeter-accuracy resolution.
Survey data were edited, mapped, and analyzed with a GIS. Family genealogy polygons were generated using last names, to produce family distribution plots throughout the cemetery.
Manufacturers
The study, supported by a National Park Service grant with Southern Illinois University at Carbondale, used two Leica 1250 RTK GPS units, a Leica TC802 robotic total station, and Esri ArcGIS ArcInfo. Equipment was provided by Kara Company of Countryside, Illinois.
ABB has selected Intergraph for the development of an oil and gas pipeline network and relevant facilities in North Africa. The pipeline network will be built in the El Merk field, a remote, harsh desert location in Algeria.
According to Intergraph, geospatial-based pipeline infrastructure management solutions will enable ABB to more effectively design, construct and maintain pipelines and assets and demonstrate a comprehensive pipeline integrity program while reducing the cost of maintaining records. By storing records in a central geographic information system (GIS), the solution makes information readily available for a variety of applications, improving record keeping productivity while assuring compliance with regulatory requirements.
“An accurate, up-to-date view of all critical assets at any given time is a crucial component of any pipeline implementation project,” said Sergio Casati, ABB Project Manager. “Especially in such challenging terrain conditions, we need to keep our pulse on the status of all assets in near real-time. The strength of Intergraph technology and its more than 40 years of experience in the utilities sector, as well as market leadership in enterprise engineering software, were key factors in our decision to partner with the company on this project. Intergraph’s open, flexible technology platform was also desirable for an initiative like the El Merk project, which involves a consortium of multiple vendors.”
The announcement said that geospatial technology from Intergraph will play a significant role in the design and installation of the pipeline, field gathering stations, gas distribution manifolds, flow and trunk lines and water and gas re-injection facilities in El Merk. The technology will support the Pipeline Open Data Standard (PODS) model, the most widely implemented pipeline data model in the industry, and all data will be stored in an Oracle Spatial database. The implementation will also include a portal component for the seamless distribution of data to all parties, including field and remote users.
“The collaboration of Intergraph with ABB Italy on this project marks a significant milestone in Intergraph’s involvement in the oil and gas pipeline industry,” said Maximilian Weber, Utilities & Communications manager for Intergraph in EMEA. “Intergraph has worked with leading pipeline providers around the world including Spectra Energy and Northwest Energy in the U.S., E.ON Ruhrgas in Germany and Chongqing Gas in China. Additionally, our Process, Power & Marine division is the world’s leading provider of enterprise engineering software for the design, construction and operation of plants, pipelines, ships and offshore facilities. We are pleased that ABB has recognized our strength in this industry and has chosen us to ensure the accurate, efficient management of assets, as well as play a key role in protecting this infrastructure.”
WhiteStar Corp. announced it’s added a new layer of oil and gas pipeline data to its Unlimited Basemap Access (UBA) product. The new WhiteStar Oil & Gas Pipeline Layer will be a nationwide, georeferenced shapefile showing the locations of all lateral and transmission pipelines in the United States.
The Company said existing subscribers to the WhiteStar UBA product will begin receiving segments of the oil and gas layer at no extra charge with their regular third-quarter UBA update in October. The first segment of the layer will include pipelines in Texas, Oklahoma and the Gulf of Mexico. The layer includes attribute information, such as owner and operator data, for each pipeline.
WhiteStar said they are creating the new UBA layer primarily from a U.S. Department of Energy (DOE) pipeline map that is available in PDF format on the DOE Energy Information Administration’s website (www.eia.doe.gov). A rich source of pipeline information, this map has frustrated hydrocarbon companies for years because it can be downloaded only in a non-GIS compatible PDF format.
“We’ve converted the PDF to a shapefile and georeferenced it to align with all of the other cultural-feature layers in the UBA product, which is fully GIS compatible,” said WhiteStar President and CEO Robert White. “This new layer allows UBA clients to easily integrate pipeline maps and attribute details into their digital mapping projects.”
According to the company, the UBA product is a seamless nationwide digital mosaic of basemap information layers from U.S. Census Bureau TIGER Files (with optional TeleAtlas upgrades). Designed for any geospatial mapping project that requires an accurate digital base map, UBA contains 42 layers of cultural features – such as political boundaries, roads, water bodies, and environmentally sensitive areas – that can be ‘cookie cut’ according to a user-selected area of interest and downloaded into most popular digital mapping package.
WhiteStar said they developed UBA with an interface that lets the user select layers with a few mouse clicks and then delineate the area of interest by choosing a specific county, outlining the project area onscreen or entering its latitude/longitude corner points. UBA users can then export the data into a variety of popular mapping formats, including ESRI, MapInfo, GeoGraphix, Petra, AutoCAD, SMT Kingdom and Golden software. In addition, the data can be projected in either NAD27 or NAD83 coordinate systems, including all related state planes and UTM zones.
“Our clients use UBA to populate their maps with cultural features for investor presentations, exploration & production logistics planning, infrastructure siting, and permit submissions,” said White. “The new pipeline layer will enable operators to quickly determine which lateral and transmission lines run near their leases.”
WhiteStar said they will roll out regional segments of the UBA Oil & Gas Pipeline Layer until the seamless nationwide data set is completed. Following delivery of the Texas, Oklahoma, and Gulf Coast segment, WhiteStar will deliver the region of Ohio, Pennsylvania, and West Virginia that is producing from the Marcellus Shale formation. UBA clients can expect that one to ship in early 2010.
Capitol Appraisal Group Inc. (CAGI) has contracted with the Sidwell Co., asking it to provide a system to inventory, value, and keep track of oil and gas infrastructure and the land parcels on which they are built.
CAGI provides appraisal and information services to governmental entities primarily for the purpose of property taxation. It contracted with Sidwell after deciding to pursue a geographic information system that would facilitate the collection of field appraisal data.
This project will be completed in three phases, according to Sidwell and CAGI. The first phase includes review of the typical workflow for field data collection as performed by CAGI technicians, development of a prototype database design, creation of custom forms for ArcPad data capture, and the design and implementation of a system to associate digital camera images directly to records in the ArcPad database.
Phase Two will consist of refinement of the data capture forms and database design to enhance the data collection workflow, and on-site installation, configuration, testing, and training. Phase Three, the enterprise deployment of the entire system, will include installation and configuration of ESRI’s ArcGIS Server, data loading and tuning, technical consulting, and ArcGIS Server administrator training, according to Sidwell and CAGI.
