zone14_up10

Metadata also available as

Metadata:


Identification_Information:
Citation:
Citation_Information:
Originator: The University of Texas, Bureau of Economic Geology
Publication_Date: 8/6/2003
Title: zone14_up10
Geospatial_Data_Presentation_Form: vector digital data
Publication_Information:
Publication_Place: Austin, Texas
Publisher: The University of Texas, Bureau of Economic Geology
Online_Linkage: <http://www.beg.utexas.edu/coastal/download.htm>
Description:
Abstract:
This dataset is a compilation of shorelines from many different years and decades of the middle and lower Texas Gulf of Mexico coast and bays. They are projected in UTM zone 14, NAD83. The shorelines were created by digitizing paper maps, transferring shorelines from aerial photographs to paper maps using optical transfer methods, mapping from digitally rectified aerial photographs, ground GPS survey, and LIDAR.
Purpose:
The shorelines were originally created for shoreline change analysis. They were compiled into this dataset to present to the public via the internet.
Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date:
REQUIRED: The year (and optionally month, or month and day) for which the data set corresponds to the ground.
Multiple_Dates/Times:
Single_Date/Time:
Calendar_Date: 1854
Single_Date/Time:
Calendar_Date: 1857
Single_Date/Time:
Calendar_Date: 1859
Single_Date/Time:
Calendar_Date: 1860
Single_Date/Time:
Calendar_Date: 1866
Single_Date/Time:
Calendar_Date: 1867
Single_Date/Time:
Calendar_Date: 1879
Single_Date/Time:
Calendar_Date: 1880
Single_Date/Time:
Calendar_Date: 1881
Single_Date/Time:
Calendar_Date: 1882
Single_Date/Time:
Calendar_Date: 1930
Single_Date/Time:
Calendar_Date: 1931
Single_Date/Time:
Calendar_Date: 1934
Single_Date/Time:
Calendar_Date: 1935
Single_Date/Time:
Calendar_Date: 1937
Single_Date/Time:
Calendar_Date: 1938
Single_Date/Time:
Calendar_Date: 1941
Single_Date/Time:
Calendar_Date: 1952
Single_Date/Time:
Calendar_Date: 1954
Single_Date/Time:
Calendar_Date: 1956
Single_Date/Time:
Calendar_Date: 1957
Single_Date/Time:
Calendar_Date: 1958
Single_Date/Time:
Calendar_Date: 1959
Single_Date/Time:
Calendar_Date: 1960
Single_Date/Time:
Calendar_Date: 1965
Single_Date/Time:
Calendar_Date: 1969
Single_Date/Time:
Calendar_Date: 1974
Single_Date/Time:
Calendar_Date: 1975
Single_Date/Time:
Calendar_Date: 1982
Single_Date/Time:
Calendar_Date: 1990
Single_Date/Time:
Calendar_Date: 1991
Single_Date/Time:
Calendar_Date: 1995
Single_Date/Time:
Calendar_Date: 1998
Single_Date/Time:
Calendar_Date: 2000
Currentness_Reference: ground condition
Status:
Progress: Complete
Maintenance_and_Update_Frequency: As needed
Spatial_Domain:
Bounding_Coordinates:
West_Bounding_Coordinate: -97.787022
East_Bounding_Coordinate: -95.995061
North_Bounding_Coordinate: 28.787745
South_Bounding_Coordinate: 25.861182
Keywords:
Theme:
Theme_Keyword_Thesaurus: none.
Theme_Keyword: shoreline
Place:
Place_Keyword: Texas
Place_Keyword: Gulf of Mexico
Access_Constraints: none
Use_Constraints: none
Point_of_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Jim Gibeaut
Contact_Organization: The University of Texas at Austin, Bureau of Economic Geology
Contact_Position: Research Associate
Contact_Address:
Address_Type: mailing address
Address: University Station Box X
City: Austin
State_or_Province: TX
Postal_Code: 78722
Country: USA
Contact_Voice_Telephone: (512) 471-0344
Contact_Facsimile_Telephone: (512) 471-0140
Contact_Electronic_Mail_Address: jim.gibeaut@beg.utexas.edu
Data_Set_Credit:
The shorelines were compiled and edited by Rachel Waldinger, the University of Texas, Bureau of Economic Geology
Native_Data_Set_Environment:
Microsoft Windows 2000 Version 5.0 (Build 2195) Service Pack 3; ESRI ArcCatalog 8.2.0.700

Data_Quality_Information:
Logical_Consistency_Report: Breaks in lines are not necessarily "snapped" together.
Completeness_Report:
Lines have a varying degree of completeness. Most of the lines were created for only a small portion of the Texas Gulf coast or a single bay. There are also gaps caused by factors such as cloud cover or lack of ground control.
Positional_Accuracy:
Horizontal_Positional_Accuracy:
Horizontal_Positional_Accuracy_Report:
The accuracy of the shorelines varies. Each shoreline was created using the best method at the time for creating accurate shoreline maps.

Accuracy of shorelines derived from paper maps: In general, the accuracy of a particular map is related to its date. Recent maps are more accurate than older maps. Error can also be introduced by physical changes such as shrinking and swelling in material on which the original data appear.

Accuracy in the interpretation of shorelines derived from aerial photographs: older aerial photographs are often of poor quality, especially along the shore. The beach and swash zone may both appear bright white as a result of their high albedo. The shoreline must be projected through these areas, resulting in the probable introduction of some error.

Accuracy of LIDAR: Selected portions from each lidar data set are used to generate a 1m x 1m digital elevation model (DEM). Data estimated to have a horizontal accuracy of 0.01-0.03 m from ground surveys using kinematic GPS techniques are superimposed on the lidar DEM and examined for any mismatch between the horizontal position of the ground GPS and the corresponding feature on the lidar DEM. Horizontal agreement between the ground kinematic GPS and the lidar was within the resolution of the 1m x 1m DEM.

Error introduced through optical transfer methods: minor errors may be introduced during optical transfer. The error may increase where there is a lack of recognizable features that can be used for guiding the projected image to exactly the right place on the map.

Error introduced through digital rectification: Error may be introduced during the digital rectification process when there is lack of ground control that can tie an aerial photograph to the base map, or when a photograph is particularly distorted.

Many of the shorelines were derived from USGS Digital Orthophoto Quads (DOQs), and all of the digitally rectified aerial photographs are based on them. The DOQ horizontal positional accuracy and the assurance of that accuracy depend, in part, on the accuracy of the data inputs to the rectification process. These inputs consist of the digital elevation model (DEM), aerotriangulation control and methods, the photo source camera calibration, scanner calibration, and aerial photographs that meet National Aerial Photography Program (NAPP) standards. The vertical accuracy of all DEMs are equivalent to or better than a Level 1 or 2 DEM, with a root mean square error (RMSE) of no greater than 7.0 meters. Field control is acquired by third order class 1 or better survey methods sufficiently spaced to meet National Map Accuracy Standards (NMAS) for 1:12,000-scale products. Aerial cameras have current certification from the USGS, National Mapping Division, Optical Science Laboratory. Test calibration scans are performed on all source photography scanners. Adjacent DOQs, when displayed together in a common planimetric coordinate system, may exhibit slight positional discrepancies across common DOQ boundaries. Linear features, such as streets, may not be continuous. These edge mismatches, however, still conform to positional horizontal accuracy within the NMAS. The Horizontal_Positional_Accuracy Value (see below) is an root mean square error (RMSE) of image positions to ground coordinates as determined by the orthorectification software used. (Source: Metadata for USGS DOQs, 1995) RMS error for georectified images are generally less than 7 meters.

Vertical_Positional_Accuracy:
Vertical_Positional_Accuracy_Report:
Accuracy of LIDAR: Ground GPS surveys are conducted within the lidar survey area to acquire ground "truth" information. The ground survey points are estimated to have a vertical accuracy of 0.01-0.05 m. Roads or other open areas with an unambiguous surface (a barren beach is an unambiguous surface) are surveyed using kinematic GPS techniques. A lidar data set is sorted to find data points that fell within 0.5 m horizontally of a ground GPS survey point. The mean elevation difference between the lidar and the ground GPS is used to estimate and remove an elevation bias from the lidar. The standard deviation of these elevation differences provides estimates of the lidar precision. This standard deviation is less than 0.15 m.
Lineage:
Source_Information:
Source_Citation:
Citation_Information:
Title: Multiple sources. See process step.
Process_Step:
Process_Description:
Process for shorelines derived from digitally rectified aerial photography: The shorelines were interpreted as the contact between wet and dry sand. Lines were digitized in GIS software from georectified aerial photographs at a scale of 1:3,000. Georectification of the aerial photographs involves the establishment of ground control points that link each image to its corresponding aerial coverage on a USGS digital orthophoto quarter quad (DOQQ). Points are chosen on the image that can be matched to points on the DOQQ. Road intersections and other cultural features are preferred as reference points rather than natural features. However, in many cases cultural features are lacking and features such as trees, shrubs, and the edges of water bodies are used. Where possible, points are evenly spaced across the image with special emphasis on the edges of the image and on areas near to the shoreline. The number of ground control points used for each image varies depending on how distorted the image is, and on the availability of suitable reference features. The average range is approximately 30 to 60 points per image. Once all the ground control points have been established, the image is rectified. Most images are rectified using a high-order polynomial algorithm, while some underwent a delaunay triangulation algorithm. Once the rectification was complete, the image was made semi-transparent and overlain on the DOQQ. In some areas a "double image" would occur, indicating that either more ground control points were needed, or that one or more existing ground control points had been placed incorrectly. In these cases, images were reprocessed to correct any remaining distortion.

Process for shorelines derived from Digital Orthophoto Quarter Quads (DOQQ): The shorelines were interpreted as the contact between wet and dry sand, and were digitized at a scale of 1:3000 using GIS software. DOQQs are differentially corrected photographs, each one covering one-quarter of the area covered by a USGS topo sheet. The DOQQs that make up the area being studied were flown in 1995 and 1996 at a scale of 1:40,000. They are color infrared and 1 meter resolution.

Process for shorelines derived from lidar: 1. Transfer data sets to NT workstation: a) raw ALTM 1225 [serial number: 99D117 (May 2000) or 99D118 (all others)] flight data recorded/downloaded using Exabyte 8mm tape drive, b) airborne GPS data collected at 1 Hz using Novatel (May 2000) or Ashtech Z12 (all others) receiver, and c) ground-based GPS data collected at 1 Hz using Trimble 4000SSI or Ashtech Z12 receivers. 2. Generate lidar point file from above three data sets using Optech's REALM 2.27 software (Optech Inc., 2000). This is a 9-column ASCII dataset with the following data format: time, first pulse easting, northing, and height of ellipsoid (HAE), last pulse easting, northing, and HAE, first pulse intensity, last pulse intensity. 3. View decimated lidar point file using Surfer or TerraModel software to check data coverage (i.e., sufficient overlap of flight lines and point spacing). 4. Collect and process GPS ground data within target area(s) for ground control checks and for elevation bias correction estimation. 5. Compute base station coordinates using National Geodetic Survey's PAGES software. Compute precise aircraft trajectories for all base stations using National Geodetic Survey's KINPOS software. Coordinates for base stations and trajectories are in the International Terrestrial Reference Frame of 1997 or 2000 (ITRF97 or ITRF00) datum. Trajectories merged based upon baseline length (distance from base station) and solution RMS. Transform merged trajectory solution from ITRF97 or ITRF00 to North American Datum of 1983 (NAD83). 6. Use POSProc software (Applanix Corp., 1999) to compute an optimally accurate navigation solution and trajectory for the data files. 7. Substitute POSProc aircraft trajectory and navigation solution into REALM 2.27 and regenerate lidar point file. 8. Extract calibration area data set from lidar point file for quality control/instrument calibration checks. If necessary, iteratively adjust calibration parameters (pitch, roll, and scale) and reprocess sample data set. Then regenerate entire lidar point file (9-column ASCII dataset). 9. Transfer lidar point file from NT workstation to UNIX. 10. Parse the 9-column LIDAR point file into smaller 3.75-minute quarter-quad components. 11. Grid the quarter-quad point files with software written in-house. We are able to grid simultaneously the four following attribute data: a. first return z b. first return intensity c. second return z d. second return intensity ...and output the data into one of two formats: a. an ArcInfo ASCII raster file. Using this format, each one of the four attributes listed above must be output to a separate file for import into ArcView (must have Spatial Analyst extension) or ArcInfo. This format consists of a matrix of attribute values preceded by six lines of header information including: 1. number of columns 2. number of rows 3. x coordinate of the lower-left cell 4. y coordinate of the lower-left cell 5. cell size 6. null value. b. a raw 4-byte binary raster file. Using this format, we can generate multi-band, band interleave files containing one, two, three, or all four of the attribute data referred to above. Additionally, we output a header file in ERMapper's ".ers" format for each of the binary files so that the data can be viewed in ERMapper or ArcView, with the appropriate ECW plug-in. These header files contain the same information as the ArcInfo-format header files (except the coordinate values are of the upper-left cell) plus datum and projection information. The gridding software written in-house uses a weighted inverse distance algorithm to interpolate cell values. 12. Convert from Height Above Ellipsoid (HAE) to North American Vertical Datum of 1988 (NAVD88) by subtracting the GEOID99 geoid model from the internal HAE array before writing to output. Also add a local mean sea level correction to final grid based upon tide gauges within the study area. 13. Extract +0.6m local mean sea level contour. The grids generated above are opened in ERMapper and a 0.6m contour line is calculated and displayed. This contour polyline is very complex in places, so it is used as a guide to digitize a new 0.6m contour line, which is the shoreline provided.

Process for shorelines derived from optical transfer methods: The shoreline was interpreted as the boundary between wet and dry sand. Using a zoom transfer scope, Saltzman projector, or reducing pantograph, aerial photographs are either enlarged or reduced to the precise scale of a topographic map, and are mechanically projected onto the map using light and mirrors. the shoreline is drawn directly onto the map using a pencil. The shorelines may then be digitized for use in GIS software.

Process for shorelines derived from maps: Mean high water lines, which closely correspond to wet/dry lines visible on photographs, are digitized directly from paper maps using a digitizing tablet and GIS software.

Process for shorelines derived from GPS: Shorelines derived from GPS were surveyed using a dual-antenna real-time kinematic differential global positioning system (DGPS) mounted on a four-wheel-drive all-terrain vehicle. Kinematic refers to the continuous movement of the GPS antenna as the vehicle is driven along the beach, and real-time differential means that the corrected position of the GPS antenna is received at the time of the survey. During kinematic beach surveys, horizontal positions were collected at a 1-s sampling interval, which translates to an average alongshore spacing of approximately 15 ft at high speed and 10 ft at low speed. Static positions were recorded for 5 min at the beginning and end of each beach segment. Beach segments were limited in length by natural features, such as large drainage channels, or physical barriers, such as cables or revetments across the beach, that prevented continuous lateral movement. Within a beach segment, way points were recorded to mark the positions of prominent (reference) features (drainage channels or houses on the beach) or the locations where the surveyed shoreline feature changed from one type to another. Most of the way points were photographed, and field notes were recorded for future reference. The entire 1996 DGPS survey of the shoreline took 4 days. The segment between Sabine Pass and Bolivar Roads was conducted on February 7 and 9, whereas the segments between Bolivar Roads and the Brazos River were completed on May 14 and 15. The raw DGPS data were converted to State Plane, South-Central Zone, NAD 27 datum, survey feet. Several files of positions were collected in a nondifferential mode when the differential receiver was unable to provide corrected positions. These files were corrected in postprocessing using differential corrections from the Texas Department of Transportation Houston Area Regional Network station.

Sources

BLACK AND WHITE PHOTOMOSAICS: Tobin Research Inc.

AERIAL PHOTOGRAPHS: U. S. Dept. Agriculture, U. S. Army Corps Engineers, Texas Highway Department, Natl. Oceanic and Atmospheric Administration, Texas Forest Service, Texas General Land Office, Environmental Protection Agency, International Boundary and Water Commission, Jack Ammann

MAPS: Natl. Oceanic and Atmospheric Administration, U. S. Army Corps Engineers, U. S. Geological Survey

Process_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Jim Gibeaut
Contact_Organization: The University of Texas Bureau of Economic Geology
Contact_Position: Research Associate
Contact_Address:
Address_Type: mailing address
Address: Univesity Station Box X
City: Austin
State_or_Province: TX
Postal_Code: 78722
Country: U. S.
Contact_Voice_Telephone: (512) 471-0344
Contact_Facsimile_Telephone: (512) 471-0140
Contact_Electronic_Mail_Address: jim.gibeaut@beg.utexas.edu
Process_Step:
Process_Description: Metadata imported.
Source_Used_Citation_Abbreviation: C:\DOCUME~1\WALDIN~1\Temp\xml1C9.tmp
Process_Step:
Process_Description: Metadata imported.
Source_Used_Citation_Abbreviation: C:\DOCUME~1\WALDIN~1\Temp\xml1C0.tmp
Process_Step:
Process_Description: Metadata imported.
Source_Used_Citation_Abbreviation: C:\DOCUME~1\WALDIN~1\Temp\xml252.tmp
Process_Step:
Process_Description: Metadata imported.
Source_Used_Citation_Abbreviation: C:\DOCUME~1\WALDIN~1\Temp\xml29C.tmp

Spatial_Data_Organization_Information:
Direct_Spatial_Reference_Method: Vector
Point_and_Vector_Object_Information:
SDTS_Terms_Description:
SDTS_Point_and_Vector_Object_Type: String
Point_and_Vector_Object_Count: 6549

Spatial_Reference_Information:
Horizontal_Coordinate_System_Definition:
Planar:
Grid_Coordinate_System:
Grid_Coordinate_System_Name: Universal Transverse Mercator
Universal_Transverse_Mercator:
UTM_Zone_Number: 14
Transverse_Mercator:
Scale_Factor_at_Central_Meridian: 0.999600
Longitude_of_Central_Meridian: -99.000000
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: 0.000512
Ordinate_Resolution: 0.000512
Planar_Distance_Units: meters
Geodetic_Model:
Horizontal_Datum_Name: North American Datum of 1983
Ellipsoid_Name: Geodetic Reference System 80
Semi-major_Axis: 6378137.000000
Denominator_of_Flattening_Ratio: 298.257222

Entity_and_Attribute_Information:
Detailed_Description:
Entity_Type:
Entity_Type_Label: zone14_up10
Attribute:
Attribute_Label: FID
Attribute_Definition: Internal feature number.
Attribute_Definition_Source: ESRI
Attribute_Domain_Values:
Unrepresentable_Domain:
Sequential unique whole numbers that are automatically generated.
Attribute:
Attribute_Label: Shape
Attribute_Definition: Feature geometry.
Attribute_Definition_Source: ESRI
Attribute_Domain_Values:
Unrepresentable_Domain: Coordinates defining the features.
Attribute:
Attribute_Label: Id
Attribute:
Attribute_Label: DATE_
Attribute_Definition: Date of source material
Attribute:
Attribute_Label: DECIMAL_YR
Attribute_Definition: Year and julian day in decimal format
Attribute:
Attribute_Label: YEAR
Attribute_Definition: Year of source data
Attribute:
Attribute_Label: DECADE
Attribute_Definition: Decade of source data
Attribute:
Attribute_Label: SOURCE
Attribute_Definition: Each number represents a type of source
Attribute:
Attribute_Label: REVISED
Attribute_Definition: Date of revision of shoreline (where applicatble).
Attribute:
Attribute_Label: PUBLISHED
Attribute_Definition: Year of publication of shoreline
Overview_Description:
Entity_and_Attribute_Overview:
The "decimal year" is calculated by taking the julian day for a given date and dividing it by 365. That number is added to the year. For example, 1/12/1996 was the 12th day in 1996, so it would be 1996.033.

Meaning of "source" values: 1. Shoreline derived from aerial photographs that have had their shorelines transferred to a topo sheet using optical transfer devices. 2. Shoreline derived from digitally rectified aerial photographs. 3. Shoreline derived from a USGS Digital Orthophoto Quad (DOQ). 4. Shoreline derived from LIDAR data. 5. Shoreline derived from ground GPS survey. 6. Shoreline derived from a paper map.

Dates: The exact date was not known for all of the lines. Some have only a year, others have a month and year but no day.


Distribution_Information:
Distributor:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: The University of Texas, Bureau of Economic Geology
Resource_Description: Downloadable Data
Standard_Order_Process:
Digital_Form:
Digital_Transfer_Information:
Transfer_Size: 3.355
Ordering_Instructions:
Dataset is available free on the internet: <http://www.beg.utexas.edu/coastal/download.htm> it can be previewed at this Arc/IMS site: <http://www.beg.utexas.edu/coastal/imsindexNew.htm>

Metadata_Reference_Information:
Metadata_Date: 20030903
Metadata_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Rachel Waldinger
Contact_Organization: The University of Texas at Austin, Bureau of Economic Geology
Contact_Organization_Primary:
Contact_Organization:
REQUIRED: The organization responsible for the metadata information.
Contact_Person: REQUIRED: The person responsible for the metadata information.
Contact_Position: Research Scientist Associate
Contact_Address:
Address_Type: mailing address
Address: University Station Box X
City: Austin
State_or_Province: TX
Postal_Code: 78722
Country: USA
Contact_Voice_Telephone: (512)475-9551
Contact_Facsimile_Telephone: (512) 471-0140
Contact_Electronic_Mail_Address: rachel.waldinger@beg.utexas.edu
Metadata_Standard_Name: FGDC Content Standards for Digital Geospatial Metadata
Metadata_Standard_Version: FGDC-STD-001-1998
Metadata_Time_Convention: local time
Metadata_Extensions:
Online_Linkage: <http://www.esri.com/metadata/esriprof80.html>
Profile_Name: ESRI Metadata Profile
Metadata_Extensions:
Online_Linkage: <http://www.esri.com/metadata/esriprof80.html>
Profile_Name: ESRI Metadata Profile
Metadata_Extensions:
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Profile_Name: ESRI Metadata Profile
Metadata_Extensions:
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Profile_Name: ESRI Metadata Profile
Metadata_Extensions:
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Profile_Name: ESRI Metadata Profile

Generated by mp version 2.7.3 on Wed Sep 03 16:15:31 2003