Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected aboard NOAA Ship Hiialaka'i and R/V AHI. Bathymetry values shallower than 25 m were derived by gauging the relative attenuation of blue and green spectral radiance as a function of depth. A multiple linear regression analysis of linearized blue and green band spectral values against depth determined the variables of y-intercept, blue slope and green slope values. Variables then used in multivariate slope intercept formula to derive depth. Variables were adjusted to improve the statistical accuracy and spatial coverage of the final derived bathymetry product. Digital image processing to derive depths conducted with the ENVI 4.5 software program while data editing and integration was performed using ArcGIS 9.3. This dataset is for the shelf environment of Tutuila Island, American Samoa, USA.
The data were derived in support of NOAA Coral Reef Conservation Program goals. Goal 1 is to map all U.S. Coral Reef Ecosystems. This data set specifically addresses Objective 1 and 4: to develop high-resolution benthic maps and to characterize priority deep water reefs and associated habitats. This integration of derived bathymetry with multibeam sonar data provides a GIS layer with expanded spatial coverage that may be used for benthic and essential fish habitat characterization, and for the study of geologic features. By combining the dataset with other bathymetry, backscatter, derivatives, and in situ data, they collectively compose benthic habitat maps designed to be used to understand and predict shallow depth (0m to 150m) benthic habitats for organisms that inhabit coral reef ecosystems.
Gridded multibeam data were collected aboard the Hi'ialakai, a 218' United States National Oceanographic and Atmospheric Administration (NOAA) research ship, and aboard the R/V AHI (Acoustic Habitat Investigator), a 25' survey launch owned and operated by the NOAA Pacific Islands Fisheries Science Center in Honolulu, HI. The metadata for the bathymetry is documented in the product metadata, Tutuila_5m.asc.txt http://www.soest.hawaii.edu/pibhmc/pibhmc_amsamoa_tutuila.htm Original IKONOS imagery was purchased to support the Pacific Islands Geographic Information System (GIS) project and National Ocean Service's (NOS) coral mapping activities. Orthographically corrected IKONOS Imagery was provided by NOAA's National Centers for Coastal Ocean Science, Center for Coastal Monitoring and Assessment. The metadata for this IKONOS imagery is documented in the original product metadata, po_60736_metadata.txt, po_61091_metadata.txt, PO_65904_METADATA.txt, PO_65907_METADATA.txt and PO_65909_METADATA.txt. (http://www.soest.hawaii.edu/pibhmc/)
ground condition
These data are not to be used for navigation purposes. Please acknowledge NOAA Pacific Islands Fisheries Science Center, the Joint Institute for Marine and Atmospheric Research (JIMAR) University of Hawaii and Davey Jones Locker GIS Laboratory Oregon State University as the sources of this information.
http://www.soest.hawaii.edu/pibhmc/amsamoa_images/Tut_bathymetry_mb&IKONOS_445.jpg
NOAA PIFSC CRED, the Pacific Islands Benthic Habitat Mapping Center and Davey Jones Locker GIS Laboratory Oregon State University
Data are collected for resource management and research purposes and are tested for internal consistency; however, no effort is made to compare these data to external references or to other published data.
These data are believed to be logically consistent though no tests were performed
Complete
Horizontal positioning system: GPS C/A Horizontal position accuracy: 25 meters
Range resolution of sonar: varies with depth Raw sounding resolution: varies with depth Vertical accuracy of gridded sonar product: ~ 1% of water depth Vertical accuracy of derived bathymetry product: 5 meter range
Multiple tools in ENVI 4.5 were used to complete the following processing steps: Data conversion from digital number to radiance, correction for atmosphere and water surface reflection, linearization of spectral decay as function of depth, masking of non-applicable values, and bathymetric derivation using variables from multiple linear regression analysis. Multiple tools in ArcGIS 9.3 were used for dataset integration and to extract values for the multiple linear regression analysis and subsequent error analyses. The statisitcs program S-Plus was used for the multiple linear regression analysis to provide original variables for depth derivation. The multivariate slope intercept formula used to derive depth was Depth=Yint+(Mblue)(Xblue)+(Mgreen)(Xgreen). Seventeen derived products, four from the image otutu_msi_61091.img (Tut091), two from the image otutu_msi_60736.img (Tut736), four from the image otutu_msi_65904.img (Tut904), three from the image otutu_msi_65907 (Tut907) and four from the image otutu_msi_65909.img (Tut909), were integrated to expand spatial coverage. The original MLR variables for Tut091 were Yint=19.7602, Mblue=-1.6871, and Mgreen=12.3928. The product derived from these variables (Tut091_DB) was mosaiced with three additional products derived using increasingly reduced Y-intercept values as follows: Yint=15.7602 (Tut091_DB4), Yint=11.7602 (Tut091_DB8), Yint=7.7602 (Tut091_DB12). This was done to increase coverage in shallow areas. More information on this integration process is provided in the product error analysis, availble from PIBHMC upon request. The original MLR variables for Tut736 were Yint=-4.3919, Mblue=-8.6422, and Mgreen=12.2726. The product derived from these variables (Tut736_DB) was mosaiced with one additional product (Tut736_DB4) with a decreased Y-intercept value of -8.3919. This was done to increase coverage in shallow areas. More information on this integration process is provided in the product error analysis, availble from PIBHMC upon request. The original MLR variables for Tut904 were Yint=2.8541, Mblue=-18.3048, and Mgreen=25.7446. The product derived from these variables (Tut904_DB) was mosaiced with three additional products derived using increasingly reduced Y-intercept values as follows: Yint=-1.1459 (Tut904_DB4), Yint=-5.1459 (Tut904_DB8) and Yint=-9.1459 (Tut904_DB12). This was done to increase coverage in shallow areas. More information on this integration process is provided in the product error analysis, availble from PIBHMC upon request. The original MLR variables for Tut907 were Yint=-5.4039, Mblue=-13.7452, and Mgreen=18.3747. The product derived from these variables (Tut907_DB) was mosaiced with two additional products derived using increasingly reduced Y-intercept values as follows: Yint=-9.4039 (Tut907_DB4), Yint=-13.4039 (Tut907_DB8). This was done to increase coverage in shallow areas. More information on this integration process is provided in the product error analysis, availble from PIBHMC upon request. The original MLR variables for Tut909 were Yint=17.1093, Mblue=-1.2295, and Mgreen=11.0006. The product derived from these variables (Tut909_DB) was mosaiced with three additional products derived using increasingly reduced Y-intercept values as follows: Yint=13.1093 (Tut909_DB4), Yint=9.1093 (Tut909_DB8) and Yint=5.1093 (Tut909_DB12). This was done to increase coverage in shallow areas. More information on this integration process is provided in the product error analysis, availble from PIBHMC upon request. The derived bathymetry from each image was in turn mosaiced prioritizing image data in the following order (highest to lowest): Tut091, Tut909, Tut907, Tut736 and Tut904. Data with better statistical accuracy was given higher "priority" so that they replaced concurrent data with lower accuracy during the mosaic process. This mosaiced derived bathymetry product (Tut_DBall) was then resampled to a 5 meter grid and integrated with the multibeam sonar data, with sonar data prioritized over the derived data, to create the final product (Tut_DBMB). A detailed description of all processing steps is available at: http://dusk.geo.orst.edu/djl/theses/kyle/Cookbook_042108.pdf An error analysis of each derived bathymetry grid used is available upon request.
104 Wilkinson Hall, Oregon State University
These data are not to be used for navigational purposes. NOAA makes no warranty regarding these data, expressed or implied, nor does the fact of distribution constitute such a warranty. NOAA cannot assume liability for any damages caused by any errors or omissions in these data, nor as a result of the failure of these data to function on a particular system.
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