Identification_Information: Citation: Citation_Information: Originator: Guy R. Cochrane Originator: Jodi Harney Originator: Pete Dartnell Originator: Nadine Golden Originator: Hank Chezar Publication_Date: 2005 Title: Glacier Bay Habitat polygons Edition: (Volume I, Version 1.0, 2005) Geospatial_Data_Presentation_Form: map Online_Linkage: http://pubs.usgs.gov/of/2006/1081/catalog.html Online_Linkage: http://pubs.usgs.gov/of/2006/1081/habitat.html/gbhab.tgz Larger_Work_Citation: Citation_Information: Originator: Guy R. Cochrane Originator: Jodi Harney Originator: Pete Dartnell Originator: Nadine Golden Originator: Hank Chezar Publication_Date: 2005 Title: Geologic characteristics of benthic habitats in Glacier Bay, southeast Alaska Edition: 1.0 Series_Information: Series_Name: Open-File Report Issue_Identification: USGS OFR 2006-1081 Publication_Information: Publication_Place: Western Coastal and Marine Geology, Santa Cruz, CA Publisher: U.S. Geological Survey, Coastal and Marine Geology Program Online_Linkage: http://pubs.usgs.gov/of/2006/1081/index.html Description: Abstract: In April 2004, more than 40 hours of georeferenced submarine digital video was collected in water depths of 15-370 m in Glacier Bay to (1) ground-truth existing geophysical data (bathymetry and acoustic reflectance), (2) examine and record geologic characteristics of the sea floor, and (3) investigate the relation between substrate types and benthic communities, and (4) construct predictive maps of seafloor geomorphology and habitat distribution. Common substrates observed include rock, boulders, cobbles, rippled sand, bioturbated mud, and extensive beds of living Modiolus (horse mussels) and scallops. Four principal sea-floor geomorphic types are distinguished by using video observations. Their distribution in lower and central Glacier Bay is predicted by using a supervised, hierarchical decision-tree statistical classification of geophysical data. Purpose: These data are intended for science researchers, students, policy makers, and the general public. The data can be used with geographic information systems (GIS) software to display geologic and oceanographic information. Supplemental_Information: Additional information about the field activities from which this data set was derived are available online at http://walrus.wr.usgs.gov/nearshorehab/ Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Although this Federal Geographic Data Committee-compliant metadata file is intended to document the data set in nonproprietary form, as well as in ArcInfo format, this metadata file may include some ArcInfo-specific terminology. Time_Period_of_Content: Time_Period_Information: Range_of_Dates/Times: Beginning_Date: 19990301 Ending_Date: 20000718 Currentness_Reference: Ground Condition Status: Progress: Complete Maintenance_and_Update_Frequency: As Needed Spatial_Domain: Bounding_Coordinates: West_Bounding_Coordinate: -136.402813 East_Bounding_Coordinate: -135.911540 North_Bounding_Coordinate: 58.757356 South_Bounding_Coordinate: 58.349164 Keywords: Theme: Theme_Keyword_Thesaurus: None Theme_Keyword: habitat Theme_Keyword: fisheries Theme_Keyword: seafloor Theme_Keyword: geology Theme: Theme_Keyword_Thesaurus: ISO 19115 Topic Category Theme_Keyword: biota Theme_Keyword: geoscientificinformation Theme_Keyword: imagereyBaseMapsEarthCover Theme_Keyword: oceans Place: Place_Keyword_Thesaurus: None Place_Keyword: Alaska Place_Keyword: Glacier Bay Access_Constraints: None Use_Constraints: Not suitable for navigation Point_of_Contact: Contact_Information: Contact_Person_Primary: Contact_Person: Guy R. Cochrane Contact_Organization: United States Geological Survey (USGS) Coastal and Marine Geology Program (CMGP) Contact_Position: Geophysicist Contact_Address: Address_Type: mailing and physical address Address: USGS, 400 Natural Bridges Drive City: Santa Cruz State_or_Province: CA Postal_Code: 95060-5792 Country: USA Contact_Voice_Telephone: (831) 427-4754 Contact_Facsimile_Telephone: (831) 427-4748 Contact_Electronic_Mail_Address: gcochrane@usgs.gov Data_Set_Credit: The authors would like to thank Gerry Hatcher, and Paul Carlson of the USGS Western Region Coastal and Marine Geology Program (in Santa Cruz and Menlo Park, CA) for field support and GIS assistance. Kevin O’Toole, Mike Boyle, Jerry O’Brien, and others at the USGS Marine Facility contributed equipment and logistical support. Ecologists Lisa Etherington, Jennifer Mondragon, and Alex Andrews from the Alaska Science Center (Gustavus and Juneau, AK) provided invaluable biological expertise during data collection. The R/V Gyre was expertly skippered by Jim De la Breure (also of the Alaska Science Center in Gustavus). Student assistants in Janine Bird and Angela Lam (in Santa Cruz, CA) contributed to GIS and laboratory analyses. Native_Data_Set_Environment: SunOS, 5.8, sun4u UNIX ArcInfo version 9.1 Cross_Reference: Citation_Information: Originator: United States Geological Survey (USGS), Coastal and Marine Geology (CMG) Publication_Date: 2005 Title: USGS CMG Glacier Bay, Alaska Habitat Metadata Online_Linkage: http://pubs.usgs.gov/of/2006/1081/ Larger_Work_Citation: Citation_Information: Originator: United States Geological Survey (USGS), Coastal and Marine Geology (CMG) Publication_Date: 2005 Title: USGS CMG InfoBank Online_Linkage: http://walrus.wr.usgs.gov/InfoBank Browse_Graphic: Browse_Graphic_File_Name: http://pubs.usgs.gov/of/2006/1081/images/fig2.html Browse_Graphic_File_Description: JPEG image of habitat polygons Browse_Graphic_File_Type: JPEG Data_Quality_Information: Attribute_Accuracy: Attribute_Accuracy_Report: Habitat polygons dervived in ArcGIS 9.1 from a georefereced sidescan sonar mosaic tiff. Logical_Consistency_Report: No additional checks for topological consistency were performed on this data. Completeness_Report: % gravel, sand, silt and clay and % fine grain for 1144 samples Lineage: Process_Step: Process_Description: -----------------------------Pete Dartnell started here----------------------------------------- Pete Dartnell prepared ERDAS image fourclass.img Geomorphic Classification Methods: The Glacier Bay multibeam data were first analyzed using a hierarchical decision-tree classification process. The classification used four images, the original backscatter-intensity image, seafloor slope, and two derivative raster images calculated from the original bathymetry and backscatter images; a 3x3-filtered bathymetry-variance image and a 3x3-filtered backscatter-variance image. Variance was calculated as the variability of bathymetry or backscatter within a kernel. An area with a large range of bathymetric relief, such as a rocky outcrop, would have a large bathymetry variance. A smooth area would have low bathymetry variance. Backscatter was parsed in a similar fashion; an area with high backscatter variability, such as an outcrop (high BS) with pockets of sediment (low BS) would have a large backscatter variance, whereas a flat, uniformly sedimented seafloor would have a low backscatter variance. The variance images were calculated by generating two intermediate images, a maximum image and a minimum image. The maximum image was calculated by running a filter (3x3 cells) that returned the maximum value within a kernel to the center cell. The minimum image was calculated by running a filter that returned the minimum value within a kernel to the center cell. The variance images were created from the difference between the maximum and minimum images. Unsupervised classifications run on the two variance images, on the original backscatter-intensity image, and on the seafloor slope image clustered the pixels into five groups numbering one to five, with one representing a very low variance/intensity/slope, 2 representing a low variance/intensity/slope, 3 representing a medium variance/intensity/slope, 4 representing a high variance/intensity/slope, and 5 representing a very high variance/intensity/slope. The four unsupervised classified images were then analyzed using a hierarchical decision-tree classification that is part of the ERDAS Imagine 8.4 software package (ERDAS, 1999). The classification is a rules-based approach that uses a hierarchy of conditions to parse the input data into a set of classes. The decision-tree framework was developed from empirically determined textural rules, variables, and hypotheses. An hypothesis is an output-geomorphic class, such as fine-grained homogeneous mud, a variable is a raster image of derived values (i.e. bathymetry variance), and a rule is a conditional statement about the variable’s pixel (data) values that describes the hypothesis. Because the four unsupervised classified images are co-registered with one another, rules can be established that relate pixel values within or between images that will ultimately classify a new seafloor geomorphic image. Multiple rules and hypotheses can be linked together into a hierarchy that describes the hypothesis. Rules for the decision-tree classification process were based on seafloor video observations. Rules were developed to correctly classify the seafloor over a camera transect. The areas that were previously unknown were similarly classified based on these same rules. Results: The combination of hypotheses, rules, and variables in the hierarchical decision tree produced a map of the Glacier Bay geomorphic provinces. Areas classified as ‘High complexity/high slope/boulder or cobble” correlated with very low- to very high-backscatter intensity (Table 1), low- to very high-backscatter variance, and medium- to very high-bathymetry variance. Areas of “High complexity/low slope/boulder or cobble” correlated with very low- to very high-backscatter intensity, low- to very high-backscatter variance, medium- to very high-bathymetry variance, and very low- slope. Areas of “fine-grained homogeneous mud” correlated with medium- to very low-backscatter intensity, medium- to very low-backscatter variance, and very high- to very low-bathymetry variance. Finally, areas of “unsorted, unconsolidated sediment, sand to boulder-sized glacial till” correlated with very low- to very high-backscatter intensity, very low- to very high-backscatter variance, and low- to very low-bathymetry variance. References: ERDAS Field Guide, 1999, ERDAS Inc, Atlanta Georgia. 672p. Process_Date: 20051501 Process_Step: Process_Description: -----------------------------Nadine Golden started here----------------------------------------- //trim grid Trimmed fourclass_grid using spatial analyst "trim by mask" tool. Used the extent of the multibeam data as the extent mask. //nibble grid 1) Reclassed data values: 0 --> NoData 1 --> 3 (hard) 2 --> 4 (hard) 3 --> 2 (mixed) 4 --> 1 (soft) //filtered grid Used spatial analyst tool "filter" one pass on low. Reclassified with spatial analyst "reclassify tool" to assign grid range values back to 1 through 4. Assigned filter values grid map: .5 - -1.5 = 1 1.5 - 2.5 =2 2.5 - 3.3 = 3 3.3 - 4.5 = 4 //converted grid to poly Used spatial analyst tool "raster to feature" to convert grid to polygon shapefile. //created bathy polygon of 3 contour values: 75 meters, 200 meters, 400 meters. Created polygon file from bathymetry grid using spatial analyst "raster to feature" tool. Selected for contours of 75 meters, 200 meters, 400 meters. Exported selected data to new polygon shapefile. //merged fourclass poly and contour poly Used spatial analyst "union" tool to merge fourclass polygon and 3 value contour polygon. Note: union intersects the polygons of the input grid_1 (fourclass) everywhere the input gid_2 (contour polygon) intersects. //manual edit and clean polygons Added bathymetry column to new, merged fourclass polygon using "Hawth's Tools--> Intersect Point Tool." Added all Green habitat code (1999) ID and definition columns to polygons. Used select by attribute, location, and manual tools to query and assign Green habitat code attributes. //eliminated border polygons remaining from filter Selected polygons with areas less or equal to 10 sq meters (note: I selected for area <=1, <=2, etc...up to <=10 and ran the eliminate tool for each selection set). Used the "Eliminate" tool from the "Data Management Tools" --> "Generalation" --> "Eliminate." Note: Eliminate tool merges the selected polygons with neighboring polygons with the largest area. Process_Date: 2005 Spatial_Data_Organization_Information: Direct_Spatial_Reference_Method: Vector Point_and_Vector_Object_Information: SDTS_Terms_Description: SDTS_Point_and_Vector_Object_Type: G-polygon Point_and_Vector_Object_Count: 10744 Spatial_Reference_Information: Horizontal_Coordinate_System_Definition: Planar: Map_Projection: Map_Projection_Name: NAD_1983_UTM_Zone_8N Polar_Stereographic: Straight-Vertical_Longitude_From_Pole: -135 Standard_Parallel: 0.999600 False_Easting: 500000.000 False_Northing: 0.000 Planar_Coordinate_Information: Planar_Coordinate_Encoding_Method: coordinate pair Coordinate_Representation: Abscissa_Resolution: 0.000064 Ordinate_Resolution: 0.000064 Planar_Distance_Units: meters Geodetic_Model: Horizontal_Datum_Name: North American Datum of 1983 Ellipsoid_Name: Geodetic ReferenceSystem 80 Semi-major_Axis: 6378137 Denominator_of_Flattening_Ratio: 298.2572222 Entity_and_Attribute_Information: Overview_Description: Entity_and_Attribute_Overview: FID Alias: Shape Data type: Geometry Width: 0 Precision: 0 Scale: 0 Definition: Feature geometry. Definition Source: ESRI FID Alias: FID Data type: Number Width: 6 Definition: Internal feature number. Definition Source: ESRI GRIDCODE Alias: GRIDCODE Data type: Number Width: 10 MEGA_ID Alias: MEGA_ID Data type: String Width: 10 BOTTOM_ID Alias: BOTTOM_ID Data type: String Width: 10 MSO_MCR_ID Alias: MSO_MCR_ID Data type: String Width: 10 MDFIR_ID Alias: MDFIR_ID Data type: String Width: 10 SLOPE_ID Alias: SLOPE_ID Data type: String Width: 10 COMPLEX_ID Alias: COMPLEX_ID Data type: String Width: 10 Area Alias: Area Data type: String Width: 200 COMMENT Alias: COMMENT Data type: String Width: 25 bathyclass Alias: bathyclass Data type: String Width: 50 MEGA Alias: MEGA Data type: Float Width: 19 Number of decimals: 11 BOTTOM Alias: BOTTOM Data type: String MSO_MCR Alias: MSO_MCR Data type: String Width: 50 MDFR Alias: MDFR Data type: String Width: 50 HAB_TYPE Alias: HAB_TYPE Data type: String Width: 50 SLOPE Alias: SLOPE Data type: String Width: 50 COMPLEXITY Alias: COMPLEXITY Data type: String Width: 50 Benthic habitat classification attributes: megahabitat, bottom induration, meso-macrohabitat, and modifiers from Green and others, 1999. CODE is a combination of the habitat attributes. MEGA_ID is I for “Inland seas, fjords.” BOTTOM_ID is h for hard bottom, m for mixed hard and soft bottom, or s for soft sediment bottom MSO_MRC_ID are macrohabitats described in Greene and others 1999. MDFR_ID are modifiers to describe the texture or lithology of the seafloor and appear in the code preceded by an underscore (_). Including; bimodal (_b), interface (_i), ripples (_r), heavily bioturbated (_t), nearshore bathy class >-75m(_x), and nearshore bathy class <= -75m and >-200m (_y). Entity_and_Attribute_Detail_Citation: Habitat attribute types are Modified after Greene, G.H., Yoklavich, M.M., Starr, R.M., O'Connell, V.M., Wakefield, W.W., Sullivan, D.E., McRea, J.E., and Cailliet, G.M., 1999. A classification scheme for deep seafloor habitats. Oceanologica Acta, 22, 663-678. Distribution_Information: Distributor: Contact_Information: Contact_Organization_Primary: Contact_Organization: United States Geological Survey (USGS) Coastal and Marine Geology Program (CMGP) Contact_Person: Guy R. Cochrane Contact_Position: Geophysicist Contact_Address: Address_Type: mailing and physical address Address: USGS, 400 Natural Bridges Drive City: Santa Cruz State_or_Province: CA Postal_Code: 95060-5792 Country: USA Contact_Voice_Telephone: (831) 427-4754 Contact_Facsimile_Telephone: (831) 427-4748 Contact_Electronic_Mail_Address: gcochrane@usgs.go Distribution_Liability: Please recognize the U.S. Geological Survey (USGS) as the source of this information. Although these data have been used by the U.S. Geological Survey, U.S. Department of the Interior, no warranty expressed or implied is made by the U.S. Geological Survey as to the accuracy of the data. The act of distribution shall not constitute any such warranty, and no responsibility is assumed by the U.S. Geological Survey in the use of this data, software, or related materials. Metadata_Reference_Information: Metadata_Date: 2005 Metadata_Review_Date: 2005 Metadata_Contact: Contact_Information: Contact_Organization_Primary: Contact_Organization: United States Geological Survey (USGS) Coastal and Marine Geology Program (CMGP) Contact_Person: Guy R. Cochrane Contact_Position: Geophysicist Contact_Address: Address_Type: mailing and physical address Address: USGS, 400 Natural Bridges Drive City: Santa Cruz State_or_Province: CA Postal_Code: 95060-5792 Country: USA Contact_Voice_Telephone: (831) 427-4754 Contact_Facsimile_Telephone: (831) 427-4748 Contact_Electronic_Mail_Address: gcochrane@usgs.gov Metadata_Standard_Name: FGDC Content Standards for Digital Geospatial Metadata ("CSDGM version 2") Metadata_Standard_Version: FGDC-STD-001-1998 Metadata_Access_Constraints: none