Habitat_poly - prediction of benthic habitat distribution.

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Metadata:

Identification_Information:
Citation:
Citation_Information:
Originator: Guy R. Cochrane
Originator: Yael Sagy
Publication_Date: 2007
Title:
Habitat_poly - prediction of benthic habitat distribution.
Edition: Version 1.0, 2007
Geospatial_Data_Presentation_Form: map
Online_Linkage: <https://pubs.usgs.gov/ds/320/habitat/Habitat_poly.tgz>
Larger_Work_Citation:
Citation_Information:
Originator: Jonathan Warrick
Originator: Guy R. Cochrane
Originator: Yael Sagy
Originator: David Finlayson
Originator: Jodi Harney
Publication_Date: 2007
Title:
Sea-Floor Mapping and Benthic Habitat GIS at the mouth of the Elwha River, Washington.
Series_Information:
Series_Name: USGS Data Series
Issue_Identification: 320
Publication_Information:
Publication_Place: Santa Cruz, CA
Publisher: U.S. Geological Survey
Online_Linkage: <URL:https://pubs.usgs.gov/ds/320/>


Description:
Abstract:
Polygon shape file with modified Greene et al 1999 habitat attributes. See methods for detailed description
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/research/projects/benthic_hab.html/>
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: 20040316
Ending_Date: 20040318
Currentness_Reference: Ground Condition

Status:
Progress: Complete
Maintenance_and_Update_Frequency: As Needed

Spatial_Domain:
Bounding_Coordinates:
West_Bounding_Coordinate: -123.636116
East_Bounding_Coordinate: -123.542824
North_Bounding_Coordinate: 48.170257
South_Bounding_Coordinate: 48.137078

Keywords:
Theme:
Theme_Keyword_Thesaurus: None
Theme_Keyword: benthic habitat
Theme_Keyword: video sled observations
Theme_Keyword: fisheries
Theme_Keyword: ecosystem
Theme_Keyword: U.S. Geological Survey
Theme_Keyword: USGS
Theme_Keyword: Coastal and Marine Geology Program
Theme_Keyword: CMGP
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: Washington
Place_Keyword: North Pacific Ocean
Place_Keyword: Northern Pacific Ocean
Place_Keyword: USA
Place_Keyword: Olympic National Park
Place_Keyword: Freshwater Bay
Place_Keyword: Elwha River
Place_Keyword: Ediz Hook
Place_Keyword: Juan de Fuca Straits
Place_Keyword: Port Angeles

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, Larry Kooker, Mike Boyle, Gerry Hatcher, Dave Hogg, and Hank Chezar at the USGS Marine Facility (Redwood City, CA) contributed field support and logistical support. Andrew Stevenson from the USGS Coastal and Marine Program. The R/V Karluk was piloted by Katherine Peet from NOAA.
Native_Data_Set_Environment:
SunOS, 5.8, sun4u UNIX ArcInfo versions 9.1
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:
The classification scheme comprehensively includes 62% of the total survey area, in its western side. All pixels in this part of the survey area have been classified, 59549 samples.
Positional_Accuracy:
Horizontal_Positional_Accuracy:
Horizontal_Positional_Accuracy_Report: Highly variable on the order of 10 meters.

Lineage:

Process_Step:
Process_Description:

General description: Habitat_poly was created using bathymetry and backscatter grids, as the input grids. The processing steps for the creation of those grids are described in the Meta-Data files of those grids. All grids mentioned in the following are ESRIGRID format unless mentioned otherwise. The bathymetry (1m pixel) and backscatter (0.25 m pixel) grids (bat_total and amp2texscal respectively) were clipped to encompass just the west side of the survey area, where we chose to perform the supervised classification.
********************Processing of the bathymetry grid***************************************** Creating a rugosity grid from bat_total using Benthic Terrain Modeler (to down load from the internet if needed). Chose Rugosity Builder and create rugosity grid output: bat_tw_rug. Rugosity can best defined as the ratio of surface area to planar area. Basically, rugosity is a measure of terrain complexity or the "bumpiness" of the terrain. In benthic environment, rugosity ca be used to aid in the indentification of areas with high biodiversity, depending on the scale of the input bathymetry.
********************Processing of the backscatter grid*****************************************
*** Step 1: import (to rouse)**************************************************
General file = /work4/ysagy/K-1-05-PS/new_proc/amp_2_texscal_1.tif Size (bytes) = 418578958
Output dataset = /work4/ysagy/K-1-05-PS/new_proc/amp_2_texscal Image file = /work4/ysagy/K-1-05-PS/new_proc/amp_2_texscal.img Size (bytes) = 418457330 Type = UNSIGNED_BYTE
Parameters selected :
TIFF = Yes
*** Step2: filter (applying a low pass filter of 3 by 3)***********************
Input dataset = /work4/ysagy/K-1-05-PS/new_proc/amp_2_texscal Image file = /work4/ysagy/K-1-05-PS/new_proc/amp_2_texscal.img Size (bytes) = 418457330 Type = UNSIGNED_BYTE
Output dataset = /work4/ysagy/K-1-05-PS/new_proc/amp_filt Image file = /work4/ysagy/K-1-05-PS/new_proc/amp_filt.img Size (bytes) = 418457330 Type = UNSIGNED_BYTE

Parameters selected : LPF = Yes LPFZ = No LPFV = No HPF = No DIV = No TRIM = No NOISE = No
NL = 3 NS = 3 LOW = 0 HIGH = 255 PRESERVE = No PERCENT = 0 MULT = 1
*** Step3: Stretch*************************************************************
Input dataset = /work4/ysagy/K-1-05-PS/new_proc/amp_filt Image file = /work4/ysagy/K-1-05-PS/new_proc/amp_filt.img Size (bytes) = 418457330 Type = UNSIGNED_BYTE
Output dataset = /work4/ysagy/K-1-05-PS/new_proc/amp_filt_strch Image file = /work4/ysagy/K-1-05-PS/new_proc/amp_filt_strch.img Size (bytes) = 418457330 Type = UNSIGNED_BYTE
Parameters selected : UBYTE = Yes SWORD = No UWORD = No FLOAT = No STRETCH = 157;1 219;255
Number of Lines 15079, Number of samples 27751
*** Step4: texscal ***********************************************************
Program: TexScal vers. 2e USGS Guy R. Cochrane gcochrane@usgs.gov W = 11 D = 2 Input Matrix filename: amp_filt_strch.img LINES: 15079 SAMPLES: 27751
bmin = 0 bmax = 255 emin = 0.000000 emax = 5.654908 hmin = 0.000000 hmax = 1.762250 entropy correction = 44.916747 homogeneity correction = 144.133918
*** Step5: texgen ************************************************************
Program TexGen vers. 2e USGS Guy R. Cochrane gcochrane@usgs.gov
Input Matrix filename: amp_filt_strch.img
Entropy minimum value: 0.000000 Homogeneity minimum value: 0.000000
Entropy correction value: 44.916747 Homogeneity correction value: 144.133918
Output Entropy filename: amp_filt_strchent.img Output Homogeneity filename: amp_filt_strchhom.img
LINES: 15079 SAMPLES: 27751 W = 11 D = 2

*** Step6: creating a new set of grids from amp_2_texscal.img with 1 m pixel size****
Using scale we divide the number of cells by four, and enter those numbers to scale program as follow,
****************************** scale ****************************** Execution date: Thu Oct 26 13:39:18 2006
Output dataset = /work4/ysagy/K-1-05-PS/new_proc/amp_ag_1m Image file = /work4/ysagy/K-1-05-PS/new_proc/amp_ag_1m.img Size (nl,ns) = 3770,6938 Type = UNSIGNED_BYTE
Input dataset = /work4/ysagy/K-1-05-PS/new_proc/amp_2_texscal Image file = /work4/ysagy/K-1-05-PS/new_proc/amp_2_texscal.img Size (nl,ns) = 15079,27751 Type = UNSIGNED_BYTE
Parameters selected : NN = No AVERAGE = Yes NL = 3770 NS = 6938 LSCALE = 0.2500165793487632 SSCALE = 0.2500090086843718
*** Step7: Stretch*************************************************************
Input dataset = /work4/ysagy/K-1-05-PS/new_proc/amp_ag_1m Image file = /work4/ysagy/K-1-05-PS/new_proc/amp_ag_1m.img Size (bytes) = 26156261 Type = UNSIGNED_BYTE
Output dataset = /work4/ysagy/K-1-05-PS/new_proc/amp_1m_strch Image file = /work4/ysagy/K-1-05-PS/new_proc/amp_1m_strch.img Size (bytes) = 26156261 Type = UNSIGNED_BYTE
Parameters selected : UBYTE = Yes SWORD = No UWORD = No FLOAT = No STRETCH = 159;1 216;255
Number of Lines 3770, Number of samples 6938
*** Step8: texscal ***********************************************************
Program: TexScal vers. 2e USGS Guy R. Cochrane gcochrane@usgs.gov Process Started 10/26/2006 13:53:03 W = 5 D = 1 wd=6 wd2=3 Input Matrix filename: amp_1m_strch.img LINES: 3770 SAMPLES: 6938
bmin = 0 bmax = 255 emin = 0.406397 emax = 5.531759 hmin = 0.000898 hmax = 1.857363 entropy correction = 49.557474 homogeneity correction = 136.819181 Process Finished 10/26/2006 14:25:55
*** Step9: texgen *********************************************************** Program TexGen vers. 2e USGS Guy R. Cochrane gcochrane@usgs.gov 10/30/2006 09:21:13 Input Matrix filename: amp_1m_strch.img Entropy minimum value: 0.406397 Homogeneity minimum value: 0.000898 Entropy correction value: 49.557474 Homogeneity correction value: 136.819181 Output Entropy filename: amp_1m_strchent.img Output Homogeneity filename: amp_1m_strchhom.img LINES: 3770 SAMPLES: 6938 W = 5 D = 1 Valid pixels processed: 12102714.000000
*** Step10: export ************************************************************
The following files were exported to .tiff and later on imported to ArcMap
Input: amp_filt_strch.img, Output: amp_w11_strch.tiff Input: amp_filt_strchhom.img, Output: amp_w11_hom.tiff Input: amp_filt_strchent.img, Output: amp_w11_ent.tiff Input: amp_1m_strch.img, Output: amp_1m_strch.tiff Input: amp_1m_strchhom.img, Output: amp_1m_hom.tiff Input: amp_1m_strchent.img, Output: amp_1m_ent.tiff
The file were exported using the export command, here is an example
**************************** export ******************************
Input dataset = /work4/ysagy/K-1-05-PS/new_proc/amp_filt_strch Image file = /work4/ysagy/K-1-05-PS/new_proc/amp_filt_strch.img Size (bytes) = 418457330 Type = UNSIGNED_BYTE
General file = /work4/ysagy/K-1-05-PS/new_proc/amp_w11_strch.tiff Size (bytes) = 418459165
Parameters selected : TIFF = Yes

Process_Date: 2007
Process_Step:
Process_Description:
Processing for all habitat polygon regions:
1. ArcGIS Create signatures tool: Created signature polygon file by identifying areas of verified (through video observation) hard, mixed, soft, and san waves bottom. Used 7 layer in the stack of files to create signatures. Layers included (and in that order): -euclidean distance grid of track lines -rugosity (derived from mosaiced bathy using the Benthic Terrain Modeling Tools Rugosity Builder) -enthropy from backscatter at 1 meter resolution -homogeneity of backscatter at 1 meter resolution -mosaiced backscatter at 0.25 meter resolution -enthropy from backscatter at 0.25 meter resolution -homogeneity of backscatter at 0.25 meter resolution
2. Using the output from the first round of the ArcGIS Create Signatures Tool, we edit some of the polygons in the signature file, and add 2 additional classes: nadir soft and nadir rock. Also we created a buffer of no data along the track line (nadir), which has been converted to a grid. Used same above 7 layers and re ran Create Signatures Tool. Using the new output file, assigned classes nadir rock and nadir soft to signature soft.
3. Painted out residual rocky noises and sand-wave noises, using Arc Scan and Raster Painting tool. Since this tool can only work with binary files (and no data is also a value), we reclassified the grid, then used "clean up" tool to erase, once the areas of rock, and once the areas of sand-waves. Later on we re-merged all the grids together (the ones without the rock and the sand-waves classification with the ones we just painted out (edited)).
4. Filling in the areas of no data in the grid by merging ("mosaic to new raster") other grids which were computed using Block statistics (under Spatial Analyst), select Neighbrhood, rectangle of 5 by 5, and statistic type: Majority. Repeat this step to creates grids of 10 by 10, 20 by 20, 30 by 30 and so on, until all the areas of no data will be interpolated (i.e. no areas of no data in the final mosaiced grid).
3. Converted 4 class (soft, mixed, rock, and sand-waves) grid to polygon. This is done using Raster to Poly in 3D Analyst (make sure that "Simplify Polygon" is UNCHECKED!).
6. In order to decrease the number of polygons, i.e., we want to remove polygons from classes 1, and 2 (soft and mixed) that are smaller than 25 sq meters but to keep classes 3 and 4 (which are rock and sand-waves respectivley), we: Added field Area and in XToll Pro used Table operation to calculate Area (we chose only meter and area for calculation).Then we select by Area and GRIDCODE and calculated GRIDCODE = 0.
7. Added all Green et al. (1999) habitat code ID and definition columns to polygons. Used select by attribute, location, and manual tools to query and assign habitat code attributes. The following steps follow the Deep-water Marine Benthic Habitat Classification Scheme (modified after Green et al., 1999) and provide the detail to add all Greene code fields to the newly classified, edited, and aggregated polygon. 8 fields will be added to the Attribute Table. Use uppercase letters for filed names All field types will be txt Length of all fields is 10 (except for the HAB_TYPE field which will be 20) Add fields in the following order: MEGA_ID, BOTTOM_ID, MSO_MRC_ID, SLOPE_ID, COMPLEX_ID, DEPTH_ID, GEO_UNIT, HAB_TYPE.
MEGA_ID (Megahabitat) This category is based on depth and general physiographic boundaries and is used to distinguish regions and features on a scale of 10s of kilometers to kilometers. Depth ranges listed for category attributes in the key are given as generalized examples. This first category is denoted with a capital letter.
Using the Field Calculator right-click option (for all rows in this column), enter the specific capital letter describing the megahabitat: A = Aprons, continental rise, deep fans and bajadas (3000-5000 m) B = Basin floors, Borderland types (floors at 1000-2500 m) F = Flanks, continental slope, basin/island-atoll flanks (200-3000 m) I = Inland seas, fiords (0-200 m) P = Plains, abyssal (>5000 m) R = Ridges, banks and seamounts (crests at 200-2500 m) S = Shelf, continental and island shelves (0-200 m)
BOTTOM_ID (sea-floor induration) Bottom induration refers to substrate hardness and is depicted by the second letter (a lower-case letter) in the code. Designations of hard, mixed, and soft seafloor can be further subdivided into distinct sediment types, and are then listed immediately afterwards in parentheses in alphabetical order or in order of relative abundance.
Select by Attributes: Select all rows for gridcode = 1. Use Field Calculator right click option to enter h for hard bottom, rock outcrop, relic beach rock or sediment pavement. Select all rows for gridcode = 2. Use Field Calculator right click option to enter m for mixed (hard & soft bottom). Select all rows for gridcode = 3. Use Field Calculator right click option to enter s for soft bottom, sediment covered. Add the Sediment types where there are video observations to verify that a polygon contains a specific sediment type. Add all sediments types that apply (were observed for each polygon). Use parentheses after the lower case sea-floor induration type of h, m, or s. Sediment types (for above indurations): (b) = boulder (c) = cobble (g) = gravel (h) = halimeda sediment, carbonate (m) = mud, silt, clay (p) = pebble (s) = sand Check that there is no cell left without a value. To check for no empty values use the Select by Attributes and select BOTTOM_ID: Get Unique Value.
MSO_MRC_ID (Meso/Macrohabitat) This distinction is related to scale of the habitat and consists of seafloor features ranging from 1 kilometer to 1 meter. Meso/Macrohabitats are noted as the third letter (a lower-case letter) in the code. If necessary, several Meso/Macrohabitats can be included alphabetically or in order of relative abundance and separated by a backslash.
Add the Meso/Marohabitat where there are video observations to verify that a polygon contains a specific habitat. Add all habitat types that apply. Habitat may also be applied based on knowledge of the area. a = atoll b = beach, relic c = canyon d = deformed, tilted and folded bedrock e = exposure, bedrock f = flats g = gully, channel i = ice-formed feature or deposit, moraine, drop-stone depression k = karst, solution pit, sink l = landslide m = mound, depression n = enclosed waters, lagoon o = overbank deposit (levee) p = pinnacle r = rill s = scarp, cliff, fault or slump t = terrace w = sediment waves y = delta, fan z# = zooxanthellae hosting structure, carbonate reef 1 = barrier reef 2 = fringing reef 3 = head, bommie 4 = patch reef
Note: To classify all the polygons that falls in a certain polygon region like a Fan Delta, use the Select By Location option: Select Feature from habitat poly shapefile that Have their center in the current layer and select from current selection.
MODIFIER_ID The fourth letter in the code, a modifier, is noted with a lower-case subscript letter or separated by an underline in some GIS programs (e.g., ArcView). Modifiers describe the texture or lithology of the seafloor. If necessary, several modifiers can be included alphabetically or in order of relative abundance and separated by a backslash.
Determine using the same deduction methods as Meso/Macrohabitat. Use an underscore before the lowercase letter. _a = anthropogenic (artificial reef/breakwall/shipwreck) _b = bimodal (conglomeratic, mixed [includes gravel, cobbles and pebbles]) _c = consolidated sediment (includes claystone, mudstone, siltstone, sandstone, breccia, or conglomerate) _d = differentially eroded _f = fracture, joints-faulted _g = granite _h = hummocky, irregular relief _i = interface, lithologic contact _k = kelp _l = limestone or carbonate _m = massive _p = pavement _r = ripples _s = scour (current or ice, direction noted) _u = unconsolidated sediment _v = volcanic rock

SLOPE_ID (Seafloor Slope) The fifth category, listed by a number following the modifier, denotes slope. Slope is calculated for a survey area from x-y-z multibeam data.
Create a slope raster using the Spatial Analyst drop down toolbar, Spatial AnalystSurface AnalysisSlope, to create a slope grid from the bathy raster. Add a new, temporary text field to the habitat polygon shapefile called TempID. Using the right-click Field Calculator option, populate the filed with the values from the FID column (the FID does not show up as an option for the zone field so we have to create a text version of that field). Open the Zonal Statistics tool from the Spatial Analyst Toolbar (not from ArcToolboxs), Spatial AnalystZonal Statistics: The Zone dataset is the habitat polygon shapefile. The Zone field is the tempID field. The value raster is the slope raster. Make sure that Ignore NoDate in calculation is checked on. The table generated can be joined to the original habitat grid if you check the box to join the output table and the zone layer (in this case the output table is the habitat polygon and the habitat polygon table may need to be closed and reopened to refresh and show the join). Uncheck the chart statistics box to make the tool run faster. Create a new text field called "SLOPE_ID." Select the column from the joined MEAN zone field for each of the slope classifications (1-5) and populate the new field with the appropriate number. For example, from the Selection menu use Select by Attribute; layer is the habitat polygon; method is to Create a new selection; choose the MEAN field; and in the equation box enter MEAN <= 1 AND MEAN >= 30; view the selected rows only and use the right click Field Calculator option to populate the selected rows of SLOPE_ID field with the number 2.
1 = Flat (0-1º) 2 = Sloping (1-30º) 3 = Steeply Sloping (30-60º) 4 = Vertical (60-90º) 5 = Overhang (> 90º)
When completed for each of the five SLOPE_ID categories, remove the join from the habitat table by right clicking on habitat polygon shapefile and selecting Join and Relates Remove Joins Remove All Joins


COMPLEX_ID (sea-floor complexity) Complexity is denoted by the sixth letter. Complexity is calculated from rugosity data using neighborhood statistics and reported in standard deviation units. Rugosity value based on the bathy is a better measurement of the seafloors complexity than the bathy value.
The COMPLEX_ID is obtained from the rugosity raster in a similar process to how the SLOPE_ID is obtained from the slope raster. The one difference is that the complexity classifications are based on standard deviation of the rugosity raster and not mean values. Use the same tempID field in the Zonal Statistics dialogue box for the join.
If you have not already created a rugosity raster, use the Benthic Terrain Modeler tool to calculate rugosity. The tool can be obtained on-line at: <http://dusk2.geo.orst.edu/djl/samoa/tools.html>. The install is fast and is explained in the accompanied ReadMe file. After the Benthic Terrain Modeler is installed and the toolbar visible, create the rugosity raster using Benthic Terrain Modeler Rugosity Builder. Depending o the size of the file, the Rugosity Builder tool can take anywhere from 30 to 90 minutes to complete for one bathy raster. Open the Zonal Statistics tool from the Spatial Analyst Toolbar (not from Toolboxes), Spatial AnalystZonal Statistics. The Zone dataset is the habitat polygon shapefile. The Zone field is the tempID field. The value raster is the rugosity raster. Make sure that Ignore NoDate in calculation is checked on. The table generated can be joined to the original habitat grid if you check the box to join the output table and the zone layer (in this case the output table is the habitat polygon and the habitat polygon table may need to be closed and reopened to refresh and show the join). You can uncheck the chart statistics box to make the tool run faster. The chart is not used). Create a new text field called "COMPLEX_ID." Select from the joined STD zone value field (you may want to remove the other fields or just leave them until you remove the entire join) for each of the complexity classifications (A, B, C, D, E) and populate the new field with the appropriate letter. For example from the Selection menu use Select by Attribute; layer is the habitat polygon; method is to Create a new selection; choose the STD field; in equation box enter STD >= 0 AND STD <= 1; view selected only and use the right click Field Calculator option to populate the selected rows of COMPLEX_ID field with the letter B.
A = Very Low Complexity (-1 to 0) B = Low Complexity (0 to 1) C = Moderate Complexity (1 to 2) D = High Complexity (2 to 3) E = Very High Complexity (3+)
When completed for each of the five COMPLEX_ID categories, remove the join form the habitat table by right clicking on habitat polygon shapefile and selecting Join and Relates Remove Joins Remove All Joins.
DEPTH_ID (Seafloor Depth) Depth is denoted by the seventh place holder and is listed using numbers in curly brackets. Depth is calculated from the bathy depth values.
DEPTH_ID calculation is done differently than SLOPE_ID and COMPLEXITY_ID. A visualization of the final depth classes will create a clear visual boundary between the four classes. Classify the bathy raster using the DEPTH_ID categories: {1} = Intertidal (<0) {2} = Intertidal (<0) 30m {3} = 30m 100m {4} = 100m 200m Create a new raster using the reclassify option in Spatial Analyst with the 4 depth classes above. Convert the new, reclassified bathy raster to a polygon shapefile using favorite method. Using the Select by location tool from the Selection drop down menu, select for all the polygons in the habitat polygon shapefile that are within each of the classes. Add appropriate DEPTH_ID values using the Field Calculator. For example, using the Select by Attribute option from the Selection menu, select all the polygons that have a value of 2 representing DEPTH_ID < =0 and DEPTH_ID >= 30. Then use the Select by Location option form the Selection menu and select features from the habitat polygon shapefile that are contained by the bathy depth polygon (the selected polygons from the bathy depth polygons will automatically be the subset used).
HABITAT TYPE The Habitat Type or HAB_TYPE field is the concatenation of all of the fields derived so far. The HAB_TYPE value can be obtained using the right click Field Calculator option. For example right click on the HAB_TYPE column for Filed Calculator option. In calculator list each field name (keep in the exact order of the fields as they appear in the attribute table) and the & symbol for concatenation between each filed: [MEGA_ID]&[BOTTOM_ID]&[SLOPE_ID]&[COMPLEX_ID]&[DEPTH_ID] The fields with no value will appear as a space in the code string using above method. There are several ways to deal with this: 1) Write an Access Database expression that escapes spacesI have not yet done this successfully 2) Concatenate in subsets: First concatenate for all rows that have a value for all fields. Next concatenate for all rows that are missing values in the same column and leave that column out of the concatenation string. Repeat concatenating for rows with the same data fields missing until all rows have been calculated.
GEO_UNIT When possible, the geologic unit is determined and listed in the habitat classification table but not in the final code. Geologic Unit is determined by scientist.

8. Calculated the percentage of area of the polygons for each CODE, using Analysis Tool, Summary Statistics, select table field area - stat = sum, then select "case field" = code. Calculate statistics separately for each unique attribute.
Process_Date: 2007


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: 59549

Spatial_Reference_Information:
Horizontal_Coordinate_System_Definition:
Planar:
Grid_Coordinate_System:
Grid_Coordinate_System_Name: Universal Transverse Mercator
Universal_Transverse_Mercator:
UTM_Zone_Number: 10
Transverse_Mercator:
Scale_Factor_at_Central_Meridian: 0.999600
Longitude_of_Central_Meridian: -123.000000
Latitude_of_Projection_Origin: 0.000000
False_Easting: 500000.000000
False_Northing: 0.000000
Planar_Coordinate_Information:
Planar_Coordinate_Encoding_Method: coordinate pair
Coordinate_Representation:
Abscissa_Resolution: 0.000002
Ordinate_Resolution: 0.000002
Planar_Distance_Units: meters
Geodetic_Model:
Horizontal_Datum_Name: D_WGS_1984
Ellipsoid_Name: WGS_1984
Semi-major_Axis: 6378137.000000
Denominator_of_Flattening_Ratio: 298.257224

Entity_and_Attribute_Information:
Overview_Description:
Entity_and_Attribute_Overview:

FID Alias: FID Data type: OID Width: 4 Precision: 0 Scale: 0 Definition: Internal feature number. Definition Source: ESRI
Shape Alias: Shape Data type: Geometry Width: 0 Precision: 0 Scale: 0 Definition: Feature geometry. Definition Source: ESRI
ID Alias: ID Data type: Number Width: 10
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
MDFR_ID Alias: MDFR_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
DEPTH_ID Alias: DEPTH_ID Data type: String Width: 10
GEO_UNIT Alias: GEO_UNIT Data type: String Width: 10
CODE Alias: CODE Data type: String Width: 20
temp Alias: temp Data type: String Width: 5
Sum_Area Alias: Sum_Area Data type: Number Width: 9
Area_perce Alias: Area_perce Data type: Number Width: 9 Number of decimals: 7
Code_sumar Alias: Code_sumar Data type: Float Width: 19 Number of decimals: 11
Code_perce Alias: Code_perce Width: 19 Number of decimals: 11

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 S for Shelf. 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; anthropogenic (_a).
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 sea-floor 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.gov

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: 2007
Metadata_Review_Date: 2007
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
Metadata_Use_Constraints: none



Generated by mp version 2.9.3 on Wed Jul 25 15:20:43 2007