Seafloor Habitat Mapping Nearshore San Diego County. Edward J. Saade 1

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1 1 INTRODUCTION Seafloor Habitat Mapping Nearshore San Diego County Edward J. Saade 1 The California State Coastal Conservancy (SCC), working in cooperation with the San Diego Association of Governments (SANDAG), contracted Thales GeoSolutions, (Pacific) Inc. (TGPI) to perform vessel and airborne data acquisition, processing and interpretation for evaluation of seafloor habitats and environmental resources in the San Diego near shore coastal zone (Figure 1). This zone is defined as the back of the beach to 36.6m (20 fathoms, or 120 ft) water depth. This is Phase II of the study, the first phase having adopted a habitat classification system, identified existing data sets and gathered them into a GIS database for Internet distribution. Figure 1. Survey Area Location 1 General Manager, Thales GeoSolutions (Pacific), Inc., 3738 Ruffin Road, San Diego, CA 92123; phone ; edward.saade@thales-geosolutions.com 1

2 Field survey operations to fill gaps in the Phase I database began in October 2002 and were completed over a five-month period. Multibeam echosounder data, including bathymetry and acoustic backscatter information, along with airborne digital multispectral imagery were acquired in order to obtain bathymetric values for the seafloor and to detect or infer habitat class. In addition, LIDAR data acquired from a previous Army Corps of Engineers (USACE) program, from Dana Point south to La Jolla, were also to be incorporated into the database. Ground truth observations were also included as part of the survey, comprising diver observations and underwater video by a marine ecologist. 1.1 Areas Surveyed and Data Types The survey area extends along 135km of coastline northward from the Mexican border, and ranges in width from 1km to 10km. Five distinct data types were planned to cover the survey area, as listed in Table 1. Table 1. Nearshore Data Types DATA TYPE APPROX WATER DEPTHS (m) From To Multibeam Bathymetry or 36.6 Multibeam Backscatter or 36.6 Digital Multi-Spectral Imagery Shore 8 to 10 LIDAR Bathymetry High Tide Mark 10 Ground Truth Observations Shore 36.6 Areas identified during the Phase I portion of the study as having adequate coverage were omitted from Phase II to optimize the budget for Phase II data collection. Specifically, a data set collected by Moss Landing Marine Laboratories around La Jolla was accepted in the Phase I study. Areas covered by kelp canopy at the time of the vessel operations were surveyed only within their sparser peripheries Multibeam Echosounder Bathymetry and Backscatter Due to budget constraints, it was not economically feasible to survey the entire multibeam portion of the study area. Therefore, the Steering Committee prioritized areas. The Plan of Work designated surveying high-priority areas first, with any remaining resources providing coverage of lower priority zones. In general, multibeam data were collected from 10m to 36.6m. Exceptions to this were: Offshore Camp Pendleton: designated an area of low priority; only 6 to 7 lines from 6m to 10m water depths were surveyed. La Jolla to Imperial Beach: no USACE LIDAR data coverage exists; multibeam data were acquired to the inshore limit of safe navigation for the weather and sea conditions at the time. 2

3 Point Loma to Imperial Beach: Deeper areas here designated low priority; only surveyed out to 27m isobath. To facilitate survey efficiency, data processing, and data quality control, the multibeam survey area was subdivided into individual survey sectors. During the survey, 2925 line kilometers of multibeam data were acquired Digital Multi Spectral Camera Digital Multi Spectral Camera (DMSC) data were obtained from the back beach to approximately 800m offshore. For the majority of the coast this provided coverage to approximately 8 to 10m water depths. One exception is the area off Imperial Beach, which remains shallower further offshore, as indicated in Figure 2. In this case, additional multibeam data were required to fill the gap in coverage (see Figure 3). Figure 2. Approximate DMSC Coverage at Imperial Beach 3

4 Figure 3. Multibeam Line Planning LIDAR LIDAR (LIght Detection And Ranging) bathymetric data available from a recent (2002) USACE survey covers the area from Dana Point south to La Jolla, from high tide to approximately 10m water depth Ground-Truth Observations Intertidal and subtidal ground-truth observations were carried out by Phase II marine ecologists at selected locations throughout the study area (Figure 4). This task was to aid and confirm acoustic and multi-spectral data interpretation into the Phase I habitat classes. Figure 4. Area showing Selected Ground-Truth Transects 4

5 Two types of Phase II ground truth operations have been defined in consultation with the Phase I team. The first is used to calibrate the interpretive models and the second is to verify the resulting interpretation. These steps apply to both the MBES acoustic imagery and the DMSC imagery. 2 DATA ACQUISITION 2.1 Multibeam Bathymetry and Backscatter Vessel The M/V Quicksilver, a 32-foot converted Bristol Bay fishing vessel, was used for the survey. The Quicksilver was equipped with the following primary equipment for execution of the survey (Figure 5): Reson SeaBat 8101 Multibeam Echosounder (MBES), hull mounted TSS Position and Orientation System 220 (POS MV) NovAtel GPS, CSI MBX-3 USCG Receiver & Thales GeoSolutions WinFrog Navigation for Differential GPS (DGPS) positioning Applied Microsystems Ltd. (AML) Smart Probes, for Sound Velocity Profile (SVP) measurement Triton Elics International (TEI) Isis Sonar, DelphMap & BathyPro Software Suite Figure 5. M/V Quicksilver Equipment Layout 5

6 Positioning Vessel positions were determined using a DGPS and WinFrog navigation software. The RTCM corrections (USCG) were acquired at one-second intervals using a CSI MBX-3 receiver. WinFrog Navigation software was used to calculate a position from the raw GPS information and RTCM corrections. This DGPS corrected position was then output as a reasonable estimate of vessel position to the Isis Sonar acquisition system. WinFrog navigation software, running on a Windows NT based PC, was used for vessel navigation and survey system positioning. WinFrog logged position information, along with motion sensor information, in its proprietary format, RAW and DAT files. WinFrog presented vessel position data in graphical and tabular format for QC purposes. The following display windows were used: Graphics the Graphics window showed navigation information in plan view. This included vessel position and orientation, survey lines, background plots, charts, and waypoints. Vehicle the Vehicle window was configured to show tabular navigation information. Typically this window was set to display position, time and date, line name, distance to start and end of line, distance off line, heading, course over ground, and speed as well as data logging and event status. Calculations the Calculation window was used to look at specific data items in tabular or graphical format. This window was typically used to show the status of the GPS solution Motion Sensor and Vessel Heading A POS MV 220 position and orientation unit measured vessel heading and dynamic motion (heave, pitch and roll). The system consists of a POS MV processor, an Inertial Measuring Unit (IMU), POS MV Controller software and two GPS antennae. The IMU was mounted 0.5m above the Reson SeaBat 8101 MBES. It uses a series of linear accelerometers and angular rate sensors that work in tandem to determine vessel attitude solutions. The GPS antennae were mounted aft of the vessel s bridge in a port/starboard configuration approximately 1m apart. The POS MV Processor uses the GPS data, along with data supplied by gyros in the IMU, to compute a dynamic heading alignment. This heading solution is further refined using a GPS Azimuth Measurement Subsystem (GAMS), wherein a vector is computed between the two GPS antennae using carrier phase ambiguity resolution subroutines. 6

7 Motion and heading data were sent to the Isis Sonar acquisition system and WinFrog Navigation system for data logging purposes Sound Velocity Profiles Sound velocity profile (SVP) data were acquired using Applied Microsystems Ltd. (AML) Smart Probes. AML Smart probes measure at a rate of eight velocity and pressure observations per second. For each cast, the probes were held at the surface for two minutes to reach temperature equilibrium. The probes were then manually lowered at the rate of about 1m/s to the seafloor and then raised to the surface at the same rate. Hyperterminal was used to log the velocity data Multibeam Echosounder The M/V Quicksilver, equipped with a hull-mounted Reson SeaBat 8101 (240kHz) MBES system designed to operate between water depths of 0m to 100m, was used to collect bathymetry (Figure 6) and backscatter data (Figure 7) from about 5m to 66m water depth during the survey. Figure 6. Multibeam Bathymetry Data 7

8 Figure 7. High-Resolution Multibeam Backscatter Mosaic Data received by the SeaBat sonar-processing unit was sent to Isis Sonar, where backscatter and bathymetry data quality were continually monitored during acquisition operations. Various windows displayed backscatter imagery, a 3D bathymetry profile, and swath coverage so that adjustments to sonar settings or vessel speed could be made, if appropriate, to improve data quality. A parameter window also displayed position, speed, attitude and heading data received from WinFrog and the POS MV, as well as data logging status. Isis Sonar was used to start and stop data logging in XTF file format, and to name lines. Power, gain, and range settings were controlled directly through the Reson user interface monitor. Survey line spacing was approximately 4x water depth for the survey. Line spacing was adjusted online to obtain overlapping data. Any remaining gaps identified during processing, were resurveyed to insure full coverage. 8

9 2.2 Digital Multi-Spectral Camera Ocean Imaging (OI) owns and operates a 4-channel aerial imaging sensor, the DMSC, manufactured by SpecTerra LTD of Australia. The unit incorporates four synchronized, progressive scan 1024x1024 CCD cameras with spectral range capability from 350 to 990nm. Data are captured in 12-bit format (Figure 8). The unit is integrated with a DGPS for synchronous frame location logging. The channel wavelengths are customized by the use of narrow-band (10-20nm) interference filters. Spectral sensitivity is also customizable through software-controlled shutter speed. Figure 8. Digital Multi-Spectral Photography The DMSC is a portable system suitable for mounting on a variety of aircraft. It acquires successive image frames at a rate automatically computed from the DGPSderived ground speed and user-specified frame-to-frame overlap margin Equipment and Procedures For this project, OI configured the DMSC with 10nm bandwidth filters corresponding to 450, 550, 600 and 643 center wavelengths. These were chosen based on previous submerged substrate mapping experience to allow good water penetration while providing sufficient spectral differences for separation of anticipated substrate types both in the intertidal and subtidal regions. 9

10 The DMSC was flown aboard a Partenavia twin-engine aircraft, specially equipped for aerial imaging. The pilot utilized a separate video camera system to precisely follow the coastline. In areas where the coast angle changed too rapidly to allow horizontal change of aircraft direction (i.e. without banking which would introduce excessive spatial distortion in the image data), the plane looped back and resumed data acquisition in the new direction. Successful image acquisition for submerged substrate mapping requires that a combination of factors coincides: cloudless weather, good water clarity, minimal waves and surge, and low tides occurring either during morning or afternoon hours when sun angles are below approximately 30º to prevent surface glint contamination. The tide versus sun angle requirements themselves limited data acquisition possibilities to approximately 5-6 days per month during the August-October, 2002 interval. Data were acquired over the entire area on the afternoon of October during moderately low tide. The coastline from North Pacific Beach to Dana Pt. was reflown on October , timed to coincide with the day s peak low tide (-1.2ft) in order to provide better imagery of the intertidal zone where some wave and whitewater interference was experienced on October 4. The duplicate data were combined to eliminate whitewater interference from the final product. 2.3 LIDAR The USACE Los Angeles District contracted their Joint Airborne LIDAR Bathymetry Technical Center of Expertise (JALBTCX), Mobile, AL, to fly the California coastline between La Jolla and Dana Point. This field operation was completed during the summer of 2002, using the SHOALS 400 marine LIDAR system. These data are to be provided to Scripps Institution of Oceanography in the near future. TGPI has arranged for a copy of these results for incorporation into this program s final data set. LIDAR bathymetry was processed by JALBTCX. 2.4 Ground-Truth Observations Ground-truth observations are designed to check and confirm interpretations from both the DMSC imagery and the MBES backscatter imagery. (Figure 9) DMSCinterpreted classifications covering the intertidal and shallower (to about 8m depth) subtidal zones of the survey area were checked by beach walk, wading, diving and underwater video transects. The MBES interpretation were checked by bounce dives, diving transects and underwater video transects. Deeper soft bottom (sedimentary) areas were checked locally by grab sampling of the seafloor material. 10

11 Figure 9. Ground-truth Types of Ground-Truth Operations Two types of Phase II ground-truth operations have been defined in consultation with the Phase I team. The first is used to calibrate the interpretive models and the second is to verify the resulting interpretation. These steps apply to both the MBES acoustic imagery and the DMSC imagery Calibration Phase In this initial ground-truth phase, specific locations for observation were identified from the processed imagery data sets. These locations represented either confirmation of a classification or resolution of an ambiguous or unknown imagery class. The results from the calibration ground-truth steps were applied to re-process or modify initial interpretations of habitat classes. This step also seeks to define the nature of habitats seen in the areas where DMSC and acoustic imagery overlap. The outcome of the ground-truth calibration is final habitat classification interpretations that can be merged to show the distribution of habitat throughout the surveyed area. This representation of nearshore habitat resources is then confirmed in a second ground truth phase. 11

12 Confirmation Phase An additional phase of ground-truth to verify the final nearshore habitat interpretation was conducted. This was done primarily using underwater video transects. The intent is to provide a statistical estimate of the accuracy of the final habitat mapping. This involves two measures: how correct are the identifications for each habitat classification, and what is the accuracy of the position and mensuration of the habitat boundaries. A large number of candidate transects were defined. These test the various habitat boundary combinations. Therefore, each transect can provide observations on at least two habitats, plus the position of their transition from one to the other. The numbers of the types of test transects are in proportion to the percentage occurrence of the various habitat types over the entire survey area. The resulting statistics verify the positional accuracy of the various boundaries, and the percentage of correct interpretations for the full range of habitat classes Equipment and Procedures Intertidal and shallow subtidal ground-truth information was obtained by marine ecologists making direct observations. Wading was done in shallow zones, especially to evaluate surf grass distribution. WAAS-enabled, hand-held GPS receivers provided coordinates for mapping and positioning intertidal features. Photography recorded habitat conditions for subsequent reference and comparison between sites. Diving by experienced marine ecologists was used to make direct underwater observations of habitats and habitat boundaries or transitions. Bounce dives with circle sweeps were done for observations in an individual habitat. In this case, a marker buoy was set at the desired location using DGPS and WinFrog for navigation, on TGPI s dive vessel. The divers swam to the buoy anchor and made habitat observations in a sweep around the anchor vicinity Multibeam Bathymetry Data Processing The XTF files were converted to CARIS HIPS format for bathymetry processing. Prior to each survey line being converted from XTF to CARIS s HIPS format, the vessel offsets, patch-test calibration values and static draft measurements were entered into the vessel configuration file. Once converted, the SVP files were loaded into each line and the line corrected for sound refraction. During SVP correction the bathymetry was also corrected for dynamic vessel heave, pitch and roll. The attitude, heading, navigation, and bathymetry data were examined for noise and gaps. Nadir beam filters were used to reject data from the outer reaches of the swaths. It should be noted that rejection does not mean deletion from the data set; soundings were simply flagged as rejected, and could be re-accepted if necessary. Typically, the nadir filter was set to

13 After each individual line was examined and cleaned in CARIS s Swath Editor, the tide file was loaded and the lines merged. During merging, tide and draft corrections were applied. Subsets were then created in CARIS s Subset Edit mode and adjacent overlapping lines of corrected bathymetry data examined to identify any tidal busts, sound velocity errors, motion errors, and data gaps. Any residual noise in the data set was also rejected at this time Multibeam Backscatter Data Processing Backscatter data were processed and mosaicked using TEI s Isis Sonar, BathyPro and DelphMap. Time Varied Gain curves (TVG) were set to compensate for signal strength variations. The resulting compensated data more accurately indicate the true variations in seabed reflectivity across the area surveyed. Data from the outer edges of the swath were clipped, where there was sufficient overlap, leaving only higher quality, near range data. Bottom tracking settings were adjusted to insure correct tracking of the seabed. Once the bottom tracking was correctly set, the water column was removed from the data set by applying a slantrange correction. Backscatter data were terrain-corrected in Isis Sonar. ASCII XYZ files of generated DTM grid nodes were exported from CARIS and imported into BathyPro, and a DTM was generated which could be recognized by TEI s software suite. The DTM was then used by Isis Sonar and DelphMap when mosaicking the backscatter data. Terrain correction takes account of the variation in seabed elevation in order to determine the true cross-line distance of a reflected pulse signal. Slant-range corrections made without using terrain correction assume a horizontal seabed and if the seabed is not horizontal then reflections will be assigned to incorrect positions, which are at the wrong distance from the survey track line. Mosaics of backscatter data were created using Isis Sonar and DelphMap. For habitat interpretation and classification, mosaics were created at best resolution, nominally 0.5m for on-screen digitizing. These mosaics were not required for final presentation and hence are only of draft quality. Five-meter-resolution mosaics were generated for ArcGIS presentation (Figure 10). 13

14 Figure 10. Multibeam Backscatter Interpretation DelphMap allows lines to be layered in any order; therefore, lines were mosaicked individually then put in the most desirable order before merging into final larger mosaics. Once a mosaic was finalized within DelphMap, it was exported in GeoTiff format. 2.5 Digital Multi-Spectral Camera Upon completion of each flight, image data were downloaded from the DMSV onto hard drives and back-up copies were burned on to CD. Pre-processing included a twostep procedure to eliminate slight band-to-band misalignment. This was done using customized software to first compute an overall shift of bands 1, 3 and 4 relative to band 2, and shifting the three bands by that amount in the x-y direction. Each 4-band image frame was then run through a Fast Fourier Transform (FFT)-based pattern recognition routine, which builds the image into 80-pixel sections and computes a secondary, regional pixel shift on each band. The pre-processed data were then imported into tnt-mips image-processing software for further manipulation. Each DMSC image frame contains in its metadata the DGPS-logged location of the frame center. This allows rapid auto-mosaicking of a multi-image set. However, the accuracy deemed necessary for this project necessitated further, manual geopositioning correction of each acquired frame (Figure 11). 14

15 Figure 11. Digital Multi-Spectral Photography The resulting image frames were manually georeferenced to a quality-controlled base layer. Initially, 1m USGS DOQQs were used. However, SANDAG made available, to TGPI and OI, 0.6m color orthophotos acquired in OI used the higher resolution orthophotos as the final base layer. The photos provided both on-land and underwater feature signatures that could be used as tie-points. The accuracy of the base layer was checked by field-testing the orthophoto locations against OI field-derived DGPS locations and control position obtained during the TGPI photo control survey at various locations. The base layer was found to be in agreement with the field positions within 4m RMS. Following georeferencing of the individual image frames, they were combined into a multi-banded image mosaic. For ease of processing, the entire coastal region was mosaicked into 12 sections. To reduce any frame edge effects (increased haze/aerosol attenuation near image edges, vignetting effects, etc.) only the innermost portions (approximately 35%) of each frame were retained for the final mosaic. The mosaic algorithm was run using the Piecewise Affine model which locks in place the utilized georeference pixels and distributes any georectification error progressively between them. This approach was found to retain the greatest spatial accuracy. Feathering was used to reduce the effects of image-to-image seams and to help with image-to-image radiometric balancing. These mosaics were then used to perform the habitat classification. 15