Integration of LIDAR Data in CARIS HIPS for NOAA Charting Carol McKenzie *, Bill Gilmour, Lieutenant Edward J. Van Den Ameele, Mark Sinclair

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1 Integration of LIDAR Data in CARIS HIPS for NOAA Charting Carol McKenzie *, Bill Gilmour, Lieutenant Edward J. Van Den Ameele, Mark Sinclair * Carol McKenzie, Data Center Supervisor, Thales GeoSolutions (Pacific), Inc., 3738 Ruffin Rd., San Diego, CA, 92123, Phone: (858) , Fax: (858) , Carol.McKenzie@thales-geosolutions.com Bill Gilmour, Survey Manager, Thales GeoSolutions (Pacific), Inc., 3738 Ruffin Rd., San Diego, CA, 92123, Phone: (858) , Fax: (858) , Bill.Gilmour@thales-geosolutions.com Lieutenant Edward J. Van Den Ameele, Operations Officer, NOAA Ship RAINIER, edward.j.vandenameele@noaa.gov Mark Sinclair, Manager, Survey, Tenix LADS Corporation Pty Ltd, Second Avenue, Technology Park, Mawson Lakes, SA 5095, Australia, Phone: , Fax: , Mark.Sinclair@tenix.com Abstract The LADS based LIDAR system was used extensively for support of NOAA Charting requirements along the Alaska Peninsula in The LADS Mk.II Laser Airborne Depth Sounder system was operated in an extremely challenging environment in conjunction with ship based operations using Reson 8101 and 8111 Multibeam echo sounder systems. It was considered beneficial to NOAA to have both data sets available in a single product throughout the survey area so a converter was built to read the LADS data into CARIS. This enables the LADS and multibeam data to be compared and potentially merged to provide continuous data from deep water to approximately 10 meters above the low water datum. The data is available in HDCS and hence all the HIPS quality control tools are available to the user. This paper briefly describes the operations and focuses on how the two data sets were converted and analyzed in CARIS HDCS. INTRODUCTION In 1995, NOAA's Office of Coast Survey developed a nautical chart maintenance plan to provide priority support to marine commerce. Survey areas were prioritized according to critical factors such as commercial traffic volume, potential hazardous material or petroleum transport, and vessels with low under-keel clearance. Over 40% of all critical survey areas are in Alaska. Many of these areas portrayed on nautical charts have never been adequately surveyed and nearly half the depths published on current charts were

2 measured using lead line techniques before In order to increase survey efficiency and safety in such remote and poorly charted areas, NOAA made the decision to integrate LIDAR (Light Detection and Ranging) survey with its more common vessel mounted multibeam survey work. Thales GeoSolutions (Pacific), Inc., have successfully been conducting multibeam hydrographic surveys in Alaska for NOAA since During the 2001 survey season, Thales and NOAA performed a joint operation predominantly in the Chignik Bay area and the Semidi Islands, on the Southern Peninsula. Tenix LADS (Laser Airborne Depth Sounder) were contracted by Thales to collect LIDAR data in support of these operations. The LIDAR system collects 864 soundings per second and data is corrected for sea surface conditions and tide to produce final reduced depths and heights within the LADS processing system. LADS can fly at altitudes of 1800ft down to 1200ft, in 100ft increments, to combat low cloud cover. Due to weather conditions in Alaska, much of the survey work was conducted at lower altitudes. Depending on water clarity and sea surface state, the LADS system is capable of charting from 70m deep to approximately 10m above mean sea level. In Alaska maximum depths of around 30m were achieved, with most of the area being covered to 20m. Drying heights over topographic features were also covered. This allows LIDAR data to be used to establish or verify shoreline information including the MLLW (Mean Lower Low Water) and MHW (Mean High Water) lines. Both Thales and NOAA needed a way to QC and produce final deliverables from LADS LIDAR data. The idea was developed to bring this data in to CARIS. NOAA and Thales already extensively used the software and tools it provided, and all processed multibeam data existed in this system. This would allow for seamless integration of the two data sets. Prior to survey in Alaska, a test LIDAR data set was collected in Puget Sound, Seattle, where NOAA had a thoroughly mapped multibeam reference surface. The purpose of testing was to prove LADS suitability for application in complex waters of marginal clarity. THE CARIS CONVERTER The outline of the LADS to HDCS converter was developed through discussions between Thales GeoSolutions (Pacific), Inc. and the Tenix LADS Corporation. The goal was to be able to view the data within CARIS HDCS subset mode, along with mulitbeam data collected from another source. This was thought to be a more powerful solution for merging the two data sets than merely importing XYZ s of LIDAR soundings to a DTM. Having the data in subset mode would allow for better visualization and a direct comparison of actual data points, using tools already familiar to both Thales and NOAA. For the converter to be successful, it was necessary to identify the information available within the LADS processing system and associate this with the information required by HDCS. CARIS requires at least navigation position, heading and depth information. The depth information also needed to appear as if it had come from a mulitbeam swath transducer, to allow CARIS to assign the regular profile and beam numbers. An

3 additional requirement was to be able to reapply updated tide information once the data was within CARIS. However, the LIDAR data as it exists within the LADS processing system, is not regularly available within this format. Data here exists in a frame, scan row and column system as shown in Figure 1. One central position is used to locate all the data within a frame. Due to the nature of this referencing in the LADS system, heading information is not necessary and therefore does not exist. Output 3 Format To accommodate the information needed, LADS generated a new output format, Output 3. The format has header information from the LADS system about datum, projections and survey limits. This data is essentially ignored by CARIS, as the CARIS Vessel Configuration File has to have these parameters specified. This is followed by a Run Header, which contains the line name from the LADS system, e.g This will be the line name used by CARIS also, but the. will be replaced with _ to read 2_0_5_2. This differs from most CARIS converters, which would use the name of the file being converted (*.OPD). However, the Output 3 format can contain many lines in one file, so it is necessary to use the name contained in the Run Header. Below the Run Header is the Scan Header. This has the center of the scan position, which corresponds to column 24 (see Figure 1), along with time and a tide value. Below each scan header are the Sounding Entries. Each Sounding Entry is tagged with one of 4 attributes, detailed in Table 1. Attribute Description Represented in CARIS S3 P3 N3 Secondary Sounding (Final accepted data point in LADS system) Primary Sounding (Soundings not accepted during LADS validation of data) No Bottom At (A depth can be assigned by the hydrographer, such that lesser depths are considered unlikely) Accepted Rejected by Disabled Beam Examined (Maintains the value of the assigned NBA depth) X3 No Bottom Detected Rejected by Depth Gate Table 1: Attributes associated with Soundings in the LADS Output 3 Format

4 How the Data Appears in CARIS Position & Gyro The center position from the Output 3 Scan Header is used to construct the navigation information. So for each scan there is a navigation position. From each consecutive navigation point a false gyro value is generated by CARIS upon conversion. Along track and across track values for the soundings are then computed for each XYZ using the center scan navigation point, and false gyro information. Depth & Tide Each sounding entry in the Output 3 format is a reduced depth. Therefore, upon conversion to CARIS, the tide from the relevant scan header is removed from every Z value to create the observed depths file. The tide values are subsequently used to generate the tide file. This allows newer verified tide data to be reapplied to the soundings in CARIS at a later date if necessary, without having to go back to the LADS system. A processed depth file is also created on conversion making direct use of the Lat Lon Z available in the Output 3 file. Attributes One of 4 attributes is assigned to each sounding, as shown in Table 1. Data attributed as No Bottom At, are flagged as examined, rather than rejected, as it may be necessary to bring them in to a CARIS File for coverage purposes. Although actual depths are not present, they show that an area has been surveyed and lesser depths are considered unlikely. Figure 1 shows the correlation between the LADS format and the CARIS format. Once the outline for the converter was established, the information was sent to the programmers at CARIS in Fredericton, who developed the converter that now exists on NT, Sun Solaris and SGI/IRIX.

5 Figure 1: Relationship between LADS & CARIS Formats

6 ESTABLISHING DATA QUALITY IHO Compliance For every NOAA contract there is a pre-defined minimum standard for depth accuracy, which reduced depth data should meet. These vary between contracts, but are based on the IHO accuracy specifications laid out in SP44 (4 th Edition, April 1998), such that the error should not exceed: ± ( b ) 2 a 2 + d where d is water depth and values for a and b are as shown in Table 2. IHO Order a b Table 2: IHO Depth Accuracy Specification Prior to surveying in Alaska, a LADS test data set was collected in Shilshole Bay, Puget Sound, Seattle as shown in Figure 2. The tests in Seattle had several purposes, including proof of LIDAR depth accuracy and identification of the spot spacing to be used in Alaska. The LADS LIDAR system can collect data based on the laser beam spot spacings given in Table 3, below. However the spot spacing used will affect the size of identifiable target and seafloor coverage. The 4x4 and 4ax4a spot patterns both provide a 4 meters spot density, but have different swath widths and survey speeds. The increased survey speed of the 4ax4a pattern is more suitable in the event of strong tail winds. LIDAR data was flown over multiple days at various spot spacings. Area 1 in Figure 2 was flown at 4x4m laser spot spacing with 200% coverage. Area 2, which had been thoroughly surveyed by NOAA using a RESON 8101 multibeam echo sounder, was also flown at 2x2m (6 lines over some main features), 3x3m, 4ax4am and 5x5m. Cross lines were flown at each spot spacing. Sounding Density (m) Swath Width (m) Survey Speed (Knots) 5 x x a x 4a x x Table 3: LADS Laser Spot Spacings

7 Figure 2: Seattle LIDAR Test Area

8 The LADS LIDAR data was tested for IHO compliance in 3 distinct ways: 1. The 4x4m data, which covered the larger survey area, was tested using the method typically used for establishing data quality during a NOAA multibeam contract. An irregular DTM of a LADS cross line was compared to survey line soundings with the same laser spot spacing, using the makehist utility in CARIS HIPS. A Quality Control Report was then generated based on the IHO depth accuracy specification for Order 1 and 2 surveys. However the values of a and b in the makehist.cla file were multiplied by 2 since a variance from a difference rather than a mean was being used. All QC tests performed on the LADS 4x4 laser beam spot spacing confirmed that IHO Order 1 standards had been achieved. 2. For the 2x2m spot spacing, all the main survey lines were used to generate a regular 4m DTM with a search radius of 1. The 2x2m spot spacing tie line was then imported as a checkline and the makehist facility was used to generate a QC Report. In this instance the DTM was presumed to be a mean surface, so a and b were not multiplied by 2. This was repeated for all spot spacings and their relevant cross lines, except in the case of the 5x5m data which had no cross line, so the 4x4m cross line was used instead. The 2x2m and 3x3m spot spacings were also found to achieve IHO Order 1. The 4x4m, 4ax4a and 5x5m data sets achieved IHO Order 1 for most beams, with the exclusion of beams 12 to 15 and 36 to 40. However, all of these spot spacings used the same 4x4m cross line. Upon further inspection it can be seen that these beams form steep slopes for the majority of the cross line as shown in Figure 3. Thus the coincidence of beam failure is most likely due to the nature of this particular line: the steepness of the slope in shallow water. When viewed in subset mode, it can be seen that the tie line data looks acceptable (see Figure 4). 3. The LIDAR cross line soundings were also compared to a 2m DTM with a search radius of 1, created using NOAA s multibeam reference data. Results indicated that for water depths less than 15m, IHO Order 1 was achieved. For LIDAR data deeper than 15m, all data complied with IHO Order 2 and many beams also complied with IHO Order 1. It should be noted that the accuracy of LIDAR data is largely affected by environmental factors, such as water clarity. So while data quality appeared to alter around 15 meters in Shilshole Bay, it may be much deeper in clearer water conditions. The results of all three tests indicate that the LADS LIDAR data complies with IHO survey standards.

9 Beams 12 to 15 Beams 36 to 40 Figure 3: LADS 4x4m Cross Line in Swath Editor

10 Width of slope is approx. 2.2m Figure 4: LADS 4x4m Cross Line in Subset Mode Target Detection & Coverage Along with providing information on depth accuracy, the tests done in Seattle were also to aid in the decision of what spot spacing should be flown in Alaska for target detection and coverage purposes. Typically, in water depths less than 40 meters, NOAA specifications require that a 2x2x1 meter object can be detected. Due to efficiency factors such as swath width, it was initially thought that LIDAR data for Alaska would be flown at 4x4m spot spacing with 200% coverage. The 200% coverage allowed for increased data density and some data redundancy, and any areas that then warranted further investigation could be re-flown, if necessary, using 3x3m or 2x2m spot spacing. To test whether the 4x4m spot spacing was agreeable, the Seattle multibeam reference surface was binned at 1m and some obvious targets were selected and measured (see Figure 5 and Table 4). The 4x4m LIDAR data was then compared to this. As can be seen from Figure 6, the LIDAR data covers only part of the reference surface due to water depth restrictions, as the area drops off below 20m. Some of the targets are difficult to pick out on the DTM of the LIDAR data. Thus the shoalest reduced LIDAR

11 depth for each target location was used as a comparison to the multibeam reference surface. Results are listed in Table 4, and show that most targets were mapped by the LIDAR system. Some smaller targets such as H were not detected. However in practice this would be ignored, due to the proximity to Target G, which would more likely be chosen for charting. 300m Figure 5: Multibeam Reference Surface DTM with Targets

12 B B J Figure 6: 4m & 2m DTM of LIDAR 4x4m Spot Spacing Data over Multibeam Reference Area

13 Feature Diameter from Multibeam (m) Height above Seafloor from Multibeam (m) Reduced Depth from Multibeam (m) Height above Seafloor from LIDAR 4x4 spot spacing (m) Reduced Depth from LIDAR 4x4 spot spacing (m) A L=60, W= N/A ** NBA * =10 B L=56, W= C L=20, W= N/A NBA =10 D N/A 20.3 / NBA=10 E F N/A NBA=10 G H I J K L M N O N/A Table 4: Targets Observed with Multibeam and LADS LIDAR in Seattle 21.5 / NBA=10 ** Height above seafloor is N/A as surrounding depths are flagged as NBA. * NBA = 10 implies the data has been flagged as No Bottom At and depths less than 10m are considered unlikely.

14 As stated in the depth accuracy section, LIDAR data is affected by environmental factors, such as water clarity. So while target detection can be seen in Table 4 to slowly degrade in depths greater than approximately 16 meters, this may be much deeper in clearer water conditions. Figure 6 indicates, even binned at 2m, the 4x4m spot spacing flown with 200% coverage, shows good seafloor continuity, with only occasional 2m gaps. Also noticeable from the 4x4m spot spacing data set, is the ease at which complex shallow water areas can be mapped. This can be seen in Figure 7, which depicts a marina, breakwater and channel entrance. The busy marina in particular would take much time and patience to map with multibeam from a small launch. Figure 7: Marina, Breakwater and Channel at Shilshole Bay, Seattle

15 INTEGRATION OF MULTIBEAM AND LIDAR DATA IN THE FIELD - ALASKA During field operations in Alaska, the intention was for LADS to send NOAA preliminary data prior to near shore multibeam operations, in order to increase safety for NOAA s survey launches, but also to make multibeam operations more efficient. As the water gets shallower, the swath width reduces and more multibeam lines are needed to obtain full coverage. NOAA s hope has been for LIDAR to cut down the time-consuming near shore survey work in order to maximize the efficiency of its survey vessels. The usual limit of hydrography is the 4 meter contour; NOAA hopes to be able to move that limit out to 20 meters or greater if LIDAR can provide the coverage. The original intention for the 2001 field season was for LADS to provide NOAA with data around the Semidi Islands. LADS s production was hampered by weather, and data processing took much longer than expected due to heavy concentrations of kelp. Thus the Semidi project was not complete by the time the NOAA Ship Rainier was scheduled to commence survey. NOAA really wanted LIDAR data prior to survey operations, for the reasons mentioned above, safety and efficiency, as well as to assess the effectiveness and accuracy of the data since it was NOAA s first experience with LIDAR in Alaska. A compromise was reached and LADS s initial priorities, and the Rainier s 2001 operating area, were moved to the surveys around Kak, Nakchamik, and Atkulik Islands. The Rainier s directive was to overlap 5 meters with LADS data; in other words, if the LIDAR consistently reached a depth limit of 20 meters, NOAA were to survey with multibeam to 15 meters. In areas such as Atkulik, not much overlap is apparent, since it is a steep slope and there is not much horizontal separation in 5 meters of depth change. LIDAR data for all areas was flown at 4x4m spot spacing with 200% coverage, with the exception of Lighthouse Rocks, which was flown at 5x5m spot spacing (200% coverage), and later revisited at 3x3m spot spacing (100% coverage) to discount the possibility of fish contacts. In practice, the LIDAR data was effective for finding rocks along the shoreline both submerged and exposed. This was useful both for launch safety, as well as for charting the shoreline. NOAA investigated or ground-truthed all LIDAR soundings that appeared to be rocks or pinnacles, and found that there was a high success rate. Only a small percentage of points turned out to be returns from kelp. While processing and examination of the data was not complete at the time of this paper, it appears NOAA has discovered no shoals which were not mapped by LIDAR. Although NOAA expects that field verification of spurious LIDAR soundings will likely always be a necessity, it should make the shoreline mapping effort more efficient, reducing the amount of near shore multibeam required. In summary, the operation can be regarded as a success. CONCLUSIONS Having LIDAR data available within CARIS is useful for many reasons. Without knowing anything about lasers or ever stepping on a plane, it makes this type of data accessible to anyone with a CARIS system, and enables them to view data in a familiar manner. For Thales, this streamlined processing flow, allowing final products for the LIDAR data to be created by an established and efficient method. For NOAA, it enabled the use of tools already available offshore, to plan survey operations, make near shore survey

16 safer and more efficient, and aid in shoreline mapping. No new tools were necessary for either survey party. The visualization of the data in subset mode was also found to be beneficial by LADS. However, it had limited functionality without access to the raw waveforms. From the tests carried out in Seattle, it is clear that LADS LIDAR data meets standard survey accuracy specifications as laid out by IHO. Also apparent was the ability to detect small 2m targets using the 4x4 laser spot spacing with 200% coverage. Initial indications from the field show the integrated approach of LIDAR and multibeam to have been a success. REFERENCES International Hydrographic Organization, IHO Standards for Hydrographic Surveys Special Publication No. 44, 4 th Edition, April Tenix LADS Corporation, Draft Format Specification for the Ground System Output Data Function, Internally Controlled Document, 9 th April 2001 Tenix LADS Corporation, Case Studies NOAA, Seattle, Washington, World Wide Web Site NOAA, Office of Coast Survey, National Survey Plan, November NOAA, The Nautical Charting Plan, 4 th Edition, August 1999