Table of Contents
Identification_Information Abstract Purpose Supplemental Information Data_Quality_Information Spatial_Data_Organization_Information Entity_and_Attribute_Information Detailed Description Overview Distribution_Information Metadata_Reference_Section
Identification_Information
Citation_Information Originator: Environmental Systems Research Institute, Inc. Publication_Date: 1993 Title: Digital Chart of the World Edition: 1 Geospatial_Data_Presentation_Format: database Publication_Information Publication_Place: Publisher: ESRI Online_Linkage: http://www.esri.com/Description Abstract This is a low resolution (resampled) dataset from the Digital Chart of the World. Polygons indicate regions of inland water, ice, or wet sand. Further information on this dataset can be obtained from http://atlas.geo.cornell.edu Purpose This coverage is included in the database to provide a geographic context in which to display and analyze geologic and geophysical data. The U.S. Defense Mapping Agency Operational Navigation Chart (ONC) series and the Jet Navigation Charts (JNCs) for Antarctica are the primary sources for the Digital Chart of the World (DCW) database. The ONC series is designed to support medium altitude en route navigation; it is also widely used for mission planning/analysis and intelligence briefings (ESRI Dictionary). Supplemental_Information Procedures_Used Data were copied from the ESRI Digital Chart of the World, with two changes: the library was reorganized from 2,094 tiles to 4 tiles, and polygons of area less than 0.2 degrees square (in geographic coordinates) were deleted. The procedure description below is from the ESRI dictionary. Part A relates specifically to this coverage and part B relates to all DCW data. (A) this coverage (inland water, ice, and sand) 1) Special automation techniques All drainage polygon features were automated in conjunction with drainage line features from positive source manuscripts containing both feature types. In many cases, nonperennial inland water features were depicted on source manuscripts with dashed line boundaries. These lines were made continuous by manually connecting the dashed lines into solid line features prior to automation. Water bodies were coded using a semiautomated process of scanning water body mask separates, automatically outlining the solid features with vectorization software, building polygon topology, and copying precoded labels to the composite drainage coverage. This process was followed by extensive quality control checks to verify that polygon features were labeled correctly. Text information was removed from the vector data through a combination of symbol trapping and manual editing. All drainage line and area features, and coastlines, were processed in a single coverage through cartographic and attribute code quality control steps. 2) Feature coincidence All drainage polygon features intersect drainage lines at single, coordinate coincident points. All shared boundaries between drainage polygon features and city outlines have coordinate coincident representations. Drainage polygon features were treated as the primary source for common boundaries. That is, in cases where drainage polygons were in contact with the other area features on the source, the shared boundary between them was always contributed by the drainage polygon features. 3) The minimum feature size is 0.12 inch (circumference measure), except where lake features are comprised of more than one line primitive, as when two different streams intersect a lake. The boundaries of some nonperennial water bodies are coded as being made up of both shorelines and streams. This occurs when streams were depicted on the source manuscripts as superseding a shoreline. Boundaries between ocean area features in the PONET_POLY coverage and water bodies in the DNET2 coverage were captured based on differences in tints on the source manuscripts. Under-construction reservoirs are captured as perennial lake features with indefinite shorelines. Centerline streams are retained in these cases. Due to DIAM65-18 coding conventions where some large inland seas are included as part of PONET_POLY coverage ocean aggregations, visually anomalous cases of DNET2 polygons within ocean areas do occur occasionally. These are most prevalent in regions where shorelines exhibit large seasonal fluctuations (e.g., the Caspian Sea). (B) all Digital Chart of the World data General Production Process All DCW coverages are derived from copies of color/feature film separates on 7-mil stable Mylar or acetate prepared from original Defense Mapping Agency (DMA) negatives that are used in the Operational Navigation Chart (ONC) lithographic production process. The number of separates available for each source chart varied from 7 to 30 pieces. Following reproduction, separates underwent an extensive map preparation process to verify registration tic coincidence between separates and to inventory the data present on each sheet. Where necessary, data represented with broken line symbols on the source were manually connected into continuous lines to facilitate the automation process. For example, the dash/dot symbols used to represent intermittent drainage were connected with drafting ink to become continuous, smooth flowing lines. Map preparation tasks were verified through independent quality control inspection. Following map preparation, the data were automated. Point features were manually digitized using large format CalComp 9100 digitizing boards. All line features were captured through optical scanning on a SCAN- GRAPHICS CF1000 scanner at a resolution of 500 dots per inch (dpi). Nearly all data were vectorized using SCAN-GRAPHICS RAVE software resident on a DEC VAX 6320 minicomputer. Some utility line data were captured using Hitachi CadCore Tracer software in conjunction with 300- dpi scanned images. Vector output files were converted to a DXF format and transferred to the main processing environment. Following scanning/vectorization, the data were converted into an ARC/INFO coverage format (ver 5.0.1) in a SUN SPARC processing environment. After being converted to ARC/INFO, all coverages were transformed into a common inch coordinate space using an affine coordinate transformation. Manually digitized coverages were registered to this same tic set prior to digitizing, also using an affine transformation. Next, preliminary edits were performed to eliminate obvious errors, after which the data were plotted out at scale using a CalComp 1044 pen plotter and subjected to a comparison to source review for positional accuracy, topological correctness, completeness, and cartographic presentation quality. Positionally, all data were required to fall within a line width of their position on the source manuscript. Topologically, all line data were required to be connected where intended, all polygons had to be closed, and no duplicate features were tolerated. This comparison to source review was performed by staff independent of the editing process and was implemented in a iterative cycle until all known errors were resolved. One-hundred percent of the data were checked in this fashion. All edits were verified. Attribute codes were assigned by registering source manuscripts on digitizing boards, selecting features individually and in groups, and assigning numeric codes for the various attributes represented. Point and text features were coded interactively at the time of initial data capture. Following completion of initial attribute code assignment, all data were plotted and independently reviewed against source manuscripts for correctness. This process was implemented iteratively until all known errors were resolved. One-hundred percent of the data were checked in this fashion. All edits were verified. Annotation text string assignment was checked in a manner identical to that described above. Following finalization of cartographic features and associated attributes, all data (except for hypsography features) were plotted in a single composite plot on a CalComp 58000 color electrostatic plotter. This composite plot was compared to source lithographs by staff independent of the editing process to review the between layer relationships of features and to eliminate final attribution errors. After this initial review/edit step, a second plot was sometimes generated to verify changes, depending on data density and the number of errors identified on the first plot. Not all features were explicitly tested at this stage. A set of automated checks was also applied to the data at this time, including tests for: attribute code value validity, attribute code consistency, topology errors, attribute field definition correctness, and internal data structure correctness. Next the data were transformed into real world coordinates (Lambert Conformal, Polar Stereographic or Transverse Mercator, depending on source characteristics) using an affine coordinate transformation, and inverse projected into decimal degrees. Lambert Conformal and Polar Stereographic projection processing was performed using the ARC/INFO PROJECT library, which draws on standard United States Geological Survey (USGS) General Cartographic Transformation Package (GCTP) algorithms. Transverse Mercator (TM) projections were performed using algorithms developed by ESRI. TM-based charts occur only below -60 degrees latitude. The data were then clipped to remove overlap areas between sheets in preparation for edgematching. Edgematching of features was done manually by quality control staff who marked the required connections on special color-coded electrostatic plots of border areas. The edgematch plot was then given to processing staff who matched the features indicated on the edgematch plots in the actual database. All edgematch processing was reviewed by quality control staff. If features along edges were irreconcilable in terms of position or attribution because of source characteristics, overlap areas on source manuscripts were utilized to resolve the discrepancies where possible. For features that were irreconcilable positionally, overlap areas on adjacent source charts were used to determine the definite positional relationship between features to be matched. Features were then physically moved in the database in order to establish a cartographically pleasing match, except in those cases where such a match would disturb the between layer relationship of data in one of the modules. When it was necessary to alter feature position during edgematching, data from the less accurate sheet was always moved to match that on the more accurate one (as defined by DMA chart histories). Where physical movement of arcs was not possible, but a clear definition as to which features should be matched existed, a section of the processing module border was inserted to maintain connectivity. These segments were explicitly coded as connectors. If two modules showed a difference in compilation date and the overlap area in the more recent sheet indicated greater connectivity for roads and railroads than the less recent module from which the data was automated, data from the more recent module was added to reflect this increased connectivity. These additions were explicitly coded as connectors. All other discrepancies between adjacent source sheets, including discrepancies in attribution that were not resolvable using the methods described above, were captured as is. Following edgematching, all of the data were physically merged and split into five-degree by five-degree tiles using ARC/INFO Librarian software. Former processing module boundaries were then removed from polygon coverages using an ARC/INFO DISSOLVE operation. All polygon coverages were subjected to an additional automated process to ensure that features terminating at tile boundaries ended precisely at those boundaries. This was accomplished by identifying companion edge features on either side of each tile boundary, and snapping them to a common position along an ideal common boundary. Following these processes, a quality review was implemented to ensure that they had been performed correctly. This included interactive reviews of tiles, individually and in groups, and reviews of small scale, library-wide plots of all coverages. Statistics were also generated at this times as to number of features, attribute code frequency, and topological characteristics within each tile. This latter information was used throughout the data conversion process to verify data completeness. General Information The following are statements of general information on library data characteristics. All data were registered using an affine transformation. Maximum allowable Root Mean Square Error (RMSE) was 0.004 inch, although values of 0.007 inch were accepted in some isolated incidences (comprising no more than 5 percent of the cases). All line data were generalized using the ARC/INFO GENERALIZE command with a tolerance of 0.0039 inch. Minimum polygon feature size within the library is 0.12 inch (perimeter measure). This tolerance was applied using perimeter rather than area criteria to minimize the obstacles to polygon topology construction during data process operations. All line data have undergone coordinate densification at 0.55 inch following generalization (see above) to maintain data integrity throughout projection processing. All line data have been processed using a maximum fuzzy tolerance of 0.002 inch. All area features from the various DCW coverages were first physically integrated and then separated into their respective feature classes. As a result, the coordinates for area features, regardless of which coverage they reside in, have identical coordinate representations along common borders. To facilitate the integration, a hierarchy was established to define the feature classes from which common borders would be extracted. The hierarchy in order of precedence is as follows: 1) coastlines and inland water bodies (from the POAREA and DNAREA features classes respectively), 2) city outlines (the PPAREA feature class), and 3) land cover (the LCAREA feature class). Elevation contour lines and associated polygon zones have not been integrated with other coverages. Data from sheets with less than 10 percent land area were captured from paper lithograph materials (rather than film separates). These were most prevalent in the South Pacific Ocean region. Explicit identification of data derived from paper lithographs is provided in the DQ coverage. Revisions Reviews_Applied_to_Data Related_Spatial_and_Tabular_Data_Sets References_Cited ESRI Fact Sheet = Fact Sheet about the Digital Chart of the World, from the ESRI website: http://www.esri.com ESRI Dictionary = ESRI, 1993, Data Dictionary for The Digital Chart of the World for use with ARC/INFO. Notes Cornell layername Cornell covername DCW covername (library) ~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~ cities_point pppoint pppoint cities_poly pppoly pppoly cities_poly_gen pppoly_gen pppoly countb_costl ponet_arc ponet (line) countb_costl_gen ponetgen_arc ponet (line) lakes dnet2 dnnet (poly) lakes_gen dnnet_gen dnnet (poly) landocean ponet_poly ponet (poly) landocean_gen ponetgen_poly ponet (poly) railroad rrline rrline railroad_gen rrline_gen rrline rivers dnline dnnet (line) rivers_simple rivers dnnet(line) roads rdline rdline roads_gen rdline_gen rdline_gen gmines_dcw lcpoint Time_Period_of_Content Currentness_Reference "The DCW database was originally published in 1992. Data currency varies from place to place depending on the currency of the ONC charts. Chart currency ranges from the mid 1960s to the early 1990s." (ESRI Fact Sheet) Status Progress: published Maintenance_and_Update_Frequency Spatial_Domain Bounding_Coordinates West_Bounding_Coordinate: East_Bounding_Coordinate: North_Bounding_Coordinate: South_Bounding_Coordinate:
Keywords Theme Theme_Keyword_Thesaurus: None Theme_Keyword: Place Place_Keyword_Thesaurus: None Place_Keyword: global Stratum Stratum_Keyword_Thesaurus: None Stratum_Keyword: Temporal Temporal_Keyword_Thesaurus: None Temporal_Keyword:
Access_Constraints Digital Chart of the World data are copyrighted by Environmental Systems Research Institute, Inc. (ESRI). Use_Constraints Point_of_Contact: See Distribution_Information for contact information.
Data_Set_Credit "The primary source for this database is the US Defense Mapping Agency (DMA) Operational Navigation Chart (ONC) series that is produced by the United States, Australia, Canada, and the United Kingdom." (ESRI Fact Sheet) Security_Information Security_Classification_System: None Security_Classification: UNCLASSIFIED Security_Handling_Description: None
Native_Data_Set_Environment: SunOS UNIX, ARC/INFO version 7.2.1
Cross_Reference Originator: Publication_Date: Publication_Time: Title: Edition: Geospatial_Data_Presentation_Form: Series_Information Series_Name: Issue_Identification: Publication_Information Publication_Place: Publisher: Other_Citation_Details: Online_Linkage: Larger_Work_Citation:
Data_Quality_Information
Attribute_Accuracy Attribute_Accuracy_Report: See Entity_Attribute_InformationQuantitative_Attribute_Accuracy_Assessment Attribute_Accuracy_Value: See Explanation Attribute_Accuracy_Explanation: Attribute accuracy is described, where present, with each attribute defined in the Entity and Attribute Section.
Logical_Consistency_Report: Polygon topology present.
Completeness_Report Positional_Accuracy Horizontal_Positional_Accuracy Horizontal_Positional_Accuracy_Report:
Vertical_Positional_Accuracy Vertical_Positional_Accuracy_Report: Lineage: See Supplemental_Information for overview.Process_Steps Process_Step Process_Description: MARISA MAPJOIN DNPOLY1-1 POLY TICS Source_Used_Citation_Abbreviation:None Process_Date: 19970102 Process_Time: 1825 Source_Produced_Citation_Abbreviation: None Process_Step Process_Description: MARISA COPY DNPOLY1-1 /MENU2/MENU/DATA/GEOGRAPHY/DNNET_DIR/TILE1/DNNET Source_Used_Citation_Abbreviation:None Process_Date: 19970110 Process_Time: 1539 Source_Produced_Citation_Abbreviation: None Process_Step Process_Description: MARISA INDEX DNNET Source_Used_Citation_Abbreviation:None Process_Date: 19970203 Process_Time: 1352 Source_Produced_Citation_Abbreviation: None Process_Step Process_Description: SEBER INDEX DNNET Source_Used_Citation_Abbreviation:None Process_Date: 19970207 Process_Time: 1107 Source_Produced_Citation_Abbreviation: None Process_Step Process_Description: SEBER RENAME DNNET DNET Source_Used_Citation_Abbreviation:None Process_Date: 19970606 Process_Time: 1831 Source_Produced_Citation_Abbreviation: None Process_Step Process_Description: SEBER COPY DNET DNET2 Source_Used_Citation_Abbreviation:None Process_Date: 19970620 Process_Time: 1653 Source_Produced_Citation_Abbreviation: None Process_Step Process_Description: SEBER COPY DNET2 /ACE3/MENU/DATA/GEOGRAPHY/LIBRARIES_DIR/TILE1/DNET2 Source_Used_Citation_Abbreviation:None Process_Date: 19980227 Process_Time: 1143 Source_Produced_Citation_Abbreviation: None Process_Step Process_Description: SEBER DOCUMENT DNET2 COPY /ACE3/MENU/DATA/GEOGRAPHY/LIBRARIES_DIR/TILE1/DNNE Source_Used_Citation_Abbreviation:None Process_Date: 19980303 Process_Time: 944 Source_Produced_Citation_Abbreviation: None
Spatial_Data_Organization_Information
Direct_Spatial_Reference_Method: Vector
Point_and_Vector_Object_Information SDTS_Terms_Description SDTS_Point_and_Vector_Object_Type: Point Point_and_Vector_Object_Count: 126615 SDTS_Point_and_Vector_Object_Type: String Point_and_Vector_Object_Count: 385759 SDTS_Point_and_Vector_Object_Type: GT-polygon composed of chains' Point_and_Vector_Object_Count: 127175
Spatial_Reference_Information
Horizontal_Coordinate_System_DefinitionProjection: Unknown
Entity_and_Attribute_Information
Detailed_Description Entity_Type Entity_Type_Label: DNET2.PAT Entity_Type_Definition: tells type of drainage feature (perennial inland water, wet sand, etc.) Entity_Type_Definition_Source: ARC/INFO Attribute: Attribute_Label: - Attribute_Definition: tells type of drainage feature (perennial inland water, wet sand, etc.) Attribute_Definition_Source: ARC/INFO Attribute_Domain_Values Enumerated_Domain Enumerated_Domain_Value: - Enumerated_Domain_Value_Definition Enumerated_Domain_Value_Definition_Source: Attribute: Attribute_Label: AREA Attribute_Definition: Area of poly/region in square coverage units Attribute_Definition_Source: Computed Attribute_Domain_Values Enumerated_Domain Enumerated_Domain_Value: Positive real numbers Enumerated_Domain_Value_Definition Enumerated_Domain_Value_Definition_Source: Attribute: Attribute_Label: PERIMETER Attribute_Definition: Perimeter of poly/region in coverage units Attribute_Definition_Source: Computed Attribute_Domain_Values Enumerated_Domain Enumerated_Domain_Value: Positive real numbers Enumerated_Domain_Value_Definition Enumerated_Domain_Value_Definition_Source: Attribute: Attribute_Label: DNET2# Attribute_Definition: Internal feature number Attribute_Definition_Source: Computed Attribute_Domain_Values Enumerated_Domain Enumerated_Domain_Value: Sequential unique positive integer Enumerated_Domain_Value_Definition Enumerated_Domain_Value_Definition_Source: Attribute: Attribute_Label: DNET2-ID Attribute_Definition: User-assigned feature number Attribute_Definition_Source: User-defined Attribute_Domain_Values Enumerated_Domain Enumerated_Domain_Value: Integer Enumerated_Domain_Value_Definition Enumerated_Domain_Value_Definition_Source: Attribute: Attribute_Label: DNPYTYPE Attribute_Definition: code for drainage feature type Attribute_Definition_Source: Attribute_Domain_Values Enumerated_Domain Enumerated_Domain_Value: 1,2,3,4,9 Enumerated_Domain_Value_Definition Enumerated_Domain_Value_Definition_Source:Overview_Description Entity_and_Attribute_Overview DNPYTYPE--code for drainage feature type 1 = Perennial inland water. Includes perennial lakes and streams, estuaries, lagoons, unsurveyed perennial streams, reservoirs, and navigable canals. 2 = Nonperennial inland water. Includes nonperennial and seasonally fluctuating lakes and streams, wadis, sabkhas, and abandoned navigable canals. 3 = Wet sand. Includes wet sand and sand deposits in and along riverbeds. 4 = Snowfield, glacier, ice field, or ice caps. 9 = None. This code is used for any area that is not water, wet sand, snowfield, glacier, ice field, or ice cap. Polygons with this code would include the background polygon, islands within inland water or ice areas, land areas enclosed by stream or river courses, or ocean areas. (Note: in the Cornell/INSTOC menu system, only type 1 polygons-- perennial inland water--are selected.) Entity_and_Attribute_Detail_Citation: Not Available
Distribution_Information
Metadata_Reference_Section
Metadata_Date: 19980303 Metadata_Contact: Contact_Information: Contact_Person_Primary: Contact_Person: Muawia Barazangi Contact_Organization: Cornell University / INSTOC Contact_Position: Senior Scientist Contact_Address: Address_Type: mailing and physical address Address: Cornell University Snee Hall Department of Geological Sciences City: Ithaca State_or_Province: NY Postal_Code: 14853 Country: U.S.A. Contact_Voice_Telephone: (607)255-6411 Contact_Facsimile_Telephone: (607)254-4780 Contact_Electronic_Mail_Address: barazangi@geology.cornell.edu Hours_of_Service: 8:00 - 17:00 Eastern time Metadata_Standard_Name: FGDC Content Standards for Digital Geospatial Metadata Metadata_Standard_Version: 19940608 Metadata_Time_Convention: Local Time Metadata_Security_Information: Metadata_Security_Classification_System: None Metadata_Security_Classification: UNCLASSIFIED Metadata_Security_Handling_Description: None
Last modified: 98-09-10.17:12:29.Thu