NTDB & NTMS Specifications (250K & 100K)
Updated: 1 December 2007
Section 1 - TOPO250K and TOPO100K National Topographic Databases Structure and Specifications
1. Scope of this document
This Section of the Technical Specifications clarifies the aspects of the feature based models used for TOPO250K and TOPO100K National Topographic Databases (NTDBs) as well as the model used in the 1:25 000 data capture program. It provides information on a variety of topics relating to the model design and population principals including:
The TOPO250K and TOPO100K NTDBs are managed by the Oracle Relational Database Management System (RDBMS) and ESRI's ArcSDE software and contain all the relevant data tables and indexes. Revision, capture and maintenance of these databases may occur either in an ESRI ArcSDE versioned environment or via independent geodatabases detached from the SDE environment. The 1:25 000 data capture program will be conducted via preliminary personal geodatabases used to store the initial capture of data prior to loading into a standardised ESRI ArcSDE environment.
The 1:250 000 scale NTDB spatial data was sourced from the Series 2 TOPO250K GEODATA vector product and its associated working databases produced by Geoscience Australia between the years 1997 and 2005. This data has been concatenated to form a Geodatabase at 1:250 000 scale, titled "TOPO250K", with uninterrupted layers covering the entire nation. The specification covers the maintenance and revision aspects related to the TOPO250K NTDB.
The 1:100 000 scale NTDB spatial data will be progressively constructed, loaded and concatenated to form a semi-seamless geodatabase at 1:100 000 scale, titled "TOPO100K" . The TOPO100K will contain layers covering the majority of urban and urban fringe areas as well as areas required for strategic planning purposes. The population of the 1:100 000 NTDB has commenced and is in its early stages of preparation. The component data is derived from published 1:100 000 topographic maps updated with information from Geoscience Australia and other agencies, together with a range of various digital data sources. The bulk of these source maps are from the National Topographic Map Series (NTMS) published by Geoscience Australia / AUSLIG and the Royal Australian Survey Corps. However, where agreements have been made with state mapping agencies, the state mapping paper or digital data products may have precedence for use as the main source dependant on a number of factors.
The 1:25 000 data capture program is being conducted in concert with state and other federal government agencies with a focus on information required for emergency response purposes and the capture of detailed hydrology information. This work is constantly evolving as requirements change.
2. The NTDB Model
2.1 The Feature-Based Data Model
The TOPO250K and TOPO100K NTDBs as well as the 1:25 000 data capture model are feature-based data models. The following definitions describe the components of these feature-based data models:
An entity is a real world phenomenon not divisible into phenomena of the same kind.
A feature instance is an abstraction of an entity represented in digital form. The description of a feature instance encompasses only selected properties of that entity. Feature instances can also be referred to as features.
A specific property of a feature instance within a Feature Type and its associated Feature Class requiring discrimination.
A subset of coded feature instances within a Feature Class that identify the type of topographic feature being represented, sharing common geometry and specific like characteristics.
A collection of Feature Types with unique properties and behaviour, sharing the same type of geometry i.e. point, line or polygon.
A collection of Feature Classes that share topological relationships.
An attribute is a particular property of a feature or of a feature's property. Attributes can be spatial (or locational) and aspatial (or non-locational).
Attribute value is the value assigned to an attribute, either for a feature instance or its attributes.
A group of entities of the same kind, matching the members of a feature class.
The structure of a feature instance in the feature based data model can be summarised as:
Where spatial object and attribute object are defined as:
SPATIAL OBJECT: The addition of all the locational attributes of the feature instance in the form of geometrical objects such as points, lines or polygons. Spatial objects carry a spatial address that consists of one or more couplets (x, y) or triplets (x, y and z) of coordinates. In the feature-based data model, topological relationships will be carried as part of the spatial object whenever the transfer formats support them. Real- world features are modelled in the NTDBs using Points, Lines and Polygons. Multi-Polygons can also exist in the databases. These types of spatial objects are described below:
ATTRIBUTE OBJECT: The non-locational information about a feature instance. This data identifies the Feature Type as well as the aspatial attributes of a specific instance of the Feature Type. The attribute object is composed of one or more attributes.
2.2 Data Aggregation
The spatial object and attribute object as defined above are the primitive components of data. These data objects are grouped together in a hierarchy which is used for the capture, manipulation and transfer of the data.
2.2.1 Feature Datasets
The digital spatial data contained in the TOPO250K and TOPO100K NTDBs, as well as in the 1:25 000 data capture model, are primarily derived from a combination of existing map production material, base digital data, imagery and authorised reference and supporting material. This data may be divided into themes, each theme containing logically related geographic information. On entry to these NTDBs and data capture models, features are grouped under Feature Datasets which bring together those features sharing a close topological relationship and common "theme" i.e. features are broadly categorised according to their physical or cultural similarities.
There are twenty two different Feature Datasets used within the 1:25 000 data capture model, TOPO250K and TOPO100K NTDBs. While the majority of these are used in all schemas some are database specific. The feature datasets are:
2.2.2 Feature Classes
All TOPO250K and TOPO100K NTDB vector data is topologically structured and this is reflected in the way the data is released to the public. Feature classes are composed of different spatial objects and convey the topological relationships of the data. There are one hundred and ten feature classes in the TOPO250K NTDB, whereas both the TOPO100K NTDB and 1:25 000 data capture models contain one hundred and twenty one feature classes. Each feature class contains numerous aspatial attribute fields which may be required by users to populate.
The TOPO250K and TOPO100K NTDBs as well as the 1:25 000 data capture model may contain four types of feature classes:
Annotation feature classes contain blob elements representing textual information required for map face production purposes.
Linear feature classes contain chain features representing entities such as windbreaks or pipelines.
Polygon feature classes contain areas (which may be bounded by linear feature classes) representing features such as lakes or built-up areas.
Point feature classes contain point features representing entities such as buildings or lighthouses.
2.2.3 Related Tables
The TOPO100K NTDB and the 1:25 000 data capture models contain two additional tables outside of the feature classes, namely:
These tables can be accessed independently from the features classes, when required, however they have been designed to be revised in concert with two defined feature classes within the data models, these being:
These tables provide the ability to store multiple records of aspatial information related to a singular spatial polygon object. They have primarily been included in the TOPO100K NTDB and the 1:25 000 data capture models to record data capture accuracy metadata over field inspection areas and data maintenance over work package areas.
For more information on the structure of the Related Tables and associated relationship classes see Section 3 4.4 Related Tables.
3. Data Capture Accuracy, Integrity and Extent
The TOPO250K NTDB vector data is topologically structured with fully maintained complex inter-relationships. Additional metadata about the features in the TOPO250K NTDB capture are conveyed by attributes held at the feature level.
The TOPO100K NTDB is topologically structured with selective inter-relationships maintained. Additional metadata about features in the TOPO100K NTDB capture are held within two metadata indexes and their related tables
The 1:25 000 data capture program model is topologically structure with selective inter-relationships maintained when both features forming the inter-relationship are captured/revised/maintained at the same time. Additional information about features are held by either:
The TOPO250K and TOPO100K NTDBs as well as the 1:25 000 data capture model vector data share a number of common formats and characteristics which are set out below.
3.1 Datum, projection and co-ordinate extents
The datum used in the TOPO100K and TOPO250K NTDBs as well as the 1:25 000 data capture model is GDA94, and the coordinate system is geographicals i.e. latitudes and longitudes. A single spatial index is used with a grid of side length 0.5 degrees, for all Feature Classes except the Sea, Mainland, Hypsometric Areas and Settlement Density Index feature classes as well as any feature class containing annotation. The Sea, Mainland, Hypsometric Areas and Settlement Density Index feature classes have a side length of 1.5 degrees. Annotation feature classes have a side length of 1000.
While the spatial domain is larger, the designated extent of the TOPO250K NTDB is specified as 0 to -48 degrees of latitude and 108 to 156 degrees of longitude. Only features within these limits will be acceptable.
While the spatial domain is larger, the designated extent of the TOPO100K NTDB and 1:25 000 data capture model is designated as 0 to -48 degrees of latitude and 96 to 168 degrees of longitude. The designated extent has been expanded to take into account Lord Howe Island, Norfolk Island, Christmas Island and Cocos Islands. Only features within these limits will be acceptable.
3.2 Data projection and editing
It is important to note that in most cases (i.e. when carrying out spatial data adjustments), it will be necessary to project "on-the fly" the GDA94 Geographical data to GDA94 UTM (MGA) coordinates when editing, in order to ascertain and comply with the correct linear length and polygon area requirements of the Specification. It is essential that when such projection and editing is conducted, it is performed with respect to the correct UTM zone eg. where a linear feature requires spatial editing and that linear feature straddles two UTM zones, for example zones 52 and 53, it is essential that the projection takes into account where the feature crosses the zone limit otherwise spatial distortion can occur.
3.3 Precision, Resolution and Tolerance
The TOPO100K and TOPO250K NTDBs as well as the 1:25 000 data capture model will be held in High (Double) Precision. This means each integer coordinate is stored using 53 bits rather than the 31 bits used Low (Single) Precision databases.
The XY Resolution is defined as the number of decimal places or significant digits used to store feature coordinates (in both the x and y direction). The TOPO100K and TOPO250K NTDBs as well as the 1:25 000 data capture model will have a defined XY Resolution of '0.0000005' degrees, which equates to approximately 0.05 metres on the ground.
The XY Tolerance is minimum distance between two coordinate sets, under which they are considered equal. The TOPO100K and TOPO250K NTDBs as well as the 1:25 000 data capture model will have a defined XY Tolerance of '0.000001' degrees, which equates to approximately 0.1 metres on the ground.
The spatial domain is defined by a combination of the XY Resolution and the XY Coordinate System. The Spatial Domain determines the extent of the data and is described in coordinate system units.
In the TOPO100K and TOPO250K NTDBs as well as the 1:25 000 data capture model the Spatial Domain is set as:
Minimum X: -400
The coordinate resolution of all features in the source geodatabase supplied for production purposes should be maintained i.e. coordinates will not be rounded in the supplied geodatabase or following subsequent feature editing. (Note: The previous GEODATA requirement to round coordinates does not apply to the NTDB geodatabase model or the 1:25 000 data capture program model.)
3.4 Point Density Reduction
Point density is controlled so that the locational information is conveyed by the minimum number of points while still retaining the smooth shape of the source information. In certain cases, such as Limit of Data features, a minimum density is required to ensure positional accuracy in a geographic representation for a feature captured in a projected MGA UTM environment.
The following specifications apply for data point reduction for data captured during the 1:25 000 data capture program:
The following specifications apply for data point reduction in the TOPO100K NTDB:
The following specifications apply for data point reduction in the TOPO250K NTDB:
In addition the following rules apply for data point density regardless of database or Geoscience Australia Stakeholder agreements:
3.5 Persistent/Production Identifier Attribute and Incremental Update
The use of an identifier attribute and the process of maintaining a history of revision activities differs between all database models (TOPO100K and TOPO250K NTDBs as well as the 1:25 000 data capture model). This variation is caused by the current status in the life cycle of all the models and the evolution of supporting software and Geoscience Australia's external stockholder requirements
3.5.1 TOPO250K NTDB Persistent Identifier Attribute and Incremental Update
The Persistent Identifier Attribute and Incremental Updates, will in the short term, only apply to the TOPO250K NTDB
The TOPO250K NTDB will use a Persistent Identifier (PID) attribute to identify individual features inside the NTDB. This PID will be unique on a national basis and is expected, in conjunction with two other fields named Creation Date and Retirement Date, to facilitate the efficient incremental update of database features.
The Persistent Identifier will be assigned to each feature as the database is populated. The PID will be maintained when a feature's attributes change. The PID will only be retired as a result of changes when this is unavoidable eg. when a linear feature is split into two features or when two features are merged. The PID will be maintained when the spatial representation of the feature changes but logically the feature is the same.
When a feature changes and the PID can be maintained, the feature will be retired from the database and a new feature with same PID and a new Creation Date generated. There may therefore be multiple representations of a feature in the database histories but only one will be valid at any point in time. Creation Date will have no relation to the date on which the feature physically came into existence, for example, the date of completion of a building. Creation Dates will be populated for all features.
A feature will be retired when it no longer exists in the real world, is being replaced by a new feature instance due to change to the feature, or otherwise is no longer required in the active data. In general, it will have no relation to the date on which the feature was physically destroyed, for example, the date of demolition of a building. The Retirement Date will be when the feature is marked as retired. Retirement Dates will be populated for all features other than active features, and be null for active features. There will be only one active instance in the data at any time for any given feature.
The combination of PID, Creation Date and Retirement Date will be unique within the TOPO250K NTDB. The Creation Date and Retirement Date will be system generated. The intention is for the PID to also be system generated and therefore, at this stage, producers are not required to populate this item. In addition producers should not actively modify these fields as this would cause difficulties with the automated incremental update process.
Note: When information in the TOPO250K NTDB is being 'refreshed' from the TOPO100K NTDB (e.g. for Horizontal Control Points), the TOPO100K PID (Production Identifier Attribute) will not be translated into the TOPO250K PID (Persistent Identifier Attribute) field.
3.5.2 TOPO100K NTDB Production Identifier Attribute and Maintenance
The TOPO1000K NTDB will use a Production Identifier (PID) attribute to identify individual features inside the NTDB. This PID will be unique on a national basis and is expected, in conjunction with a field named Revised to maintain a currency status of edits in the database during its formation.
The Production Identifier will be assigned to each feature as the databases are populated. The PID will be updated as a feature is altered in any manner. e.g. if the shape is adjusted during revision or an attribute is revised.
The TOPO100K NTDB will not undergo 'Incremental Update' in the short term. However it will use a field named 'Revised' to provide information on the date a feature was loaded into the database. When a feature is altered in any manner this 'Revised' field will be updated to the date when that change occurred. The 'Revised' date will have no relation to the date on which the feature physically came into existence or was physically altered.
The combination of PID and Revised fields will be unique within the TOPO100K NTDB and will be system generated. Therefore, at this stage, producers are not required to populate these items. In addition producers should not actively modify these fields as this would cause difficulties with the automated processes.
3.5.3 1:25 000 Data Capture Model and Maintenance
While the items of PID and Revised are available in the 1:25 000 data capture model, they will not be activated in the short term. However once information starts to be supplied to producers, with these items populated in the 1:25 000 data capture model, it is important that they remain unaltered during the revision process, wherever possible.
3.6 Feature Metadata
Metadata about a feature's spatial and aspatial accuracy, as well as reliability, are dealt with in different ways in the various scale geodatabases (TOPO100K and TOPO250K NTDBs as well as the 1:25 000 data capture program model). Information on the definition and use of fields detailing feature metadata can be obtained in Section 1 Chapter 3.6.1 "Feature Metadata Fields".
The TOPO250K NTDB stores metadata at a feature level. This means the metadata about a feature's spatial and aspatial accuracy as well as reliability and source are held against its row record in the associated feature class attribute table. Apart from the standard system generated attribute fields, the following fields will always apply for each feature, at the feature level:
The TOPO100K NTDB stores feature metadata via a Metadata Index feature class named "WorkPackageIndex" and an associated table named "FeatureClassesRevised". This method defines a polygon within the Metadata Index feature class which represents an area where data has been captured, or revised, using a consistent process. Information about the processes and sources used for the revision of data within the area are held with the Metadata Index feature Class. The defined polygon is provided with a unique code which relates to row records within the associated table. A row record in the associated table exists for each feature class which has been revised and defines the metadata about the processes resultant spatial and aspatial accuracy as well as reliability for that feature class. The following Metadata fields are used within the associated table:
The 1:25 000 data capture program model uses a combination of the Feature Metadata methodologies detailed above. In general, it will use the same methodology as used for the TOPO100K NTDB storing feature metadata via a Metadata Index feature class named "WorkPackageIndex" and an associated table named "FeatureClassesRevised". However for certain revision processes where Geoscience Australia's stakeholders require additional detail, feature level metadata will be used. Therefore the following fields have been applied to feature classes, within the 1:25 000 data capture model, which may require feature level metadata to be captured:
NOTE: Feature Level Metadata should only be applied in the 1:25 000 data capture program model upon direction from Geoscience Australia via project instructions to the producers.
3.6.1 Feature Metadata Fields
A standard set of fields exist which define the metadata of a feature. While not all fields are used in each model (TOPO100K and TOPO250K NTDBs as well as 1:25 000 data capture program model), when they are used their definition and required content is standard. The following fields are used to define the Metadata of a feature.
3.6.2 Attribute Reliability and Attribute Source
The attribute reliability date and attribute source fields will only be updated if one, or more, of the attributes listed in the table below are added, revised or confirmed. When an existing feature is investigated, a new attribute date and source will be applied once one or more of its attribute/s from the list below are confirmed, regardless of whether the feature needed its attributes updated on inspection.
The attribute reliability date and attribute source are inter-linked. The date of the primary source, used to update the attribute/s from the table below, will be the date used to complete the attribute reliability field entry for that feature.
If more than one source is used to update or confirm a features attributes then the most recent source is used to populate both the 'Attribute Source' and the 'Attribute Reliability' fields. The only exception to this rule is when two, or more of, the sources used have reliability dates within a year of each other. In this case the source used to populate the 'Attribute Source' and 'Attribute Reliability' fields will be that used to populate the item of the highest priority in the table (1 being the highest priority and 61 being the lowest)
Where a reliability date for a particular source is incomplete (eg has the month and year but no day or the year but no day or month), than it should have the earliest date.
Note: Updating of the 'Attribute Reliability' and 'Attribute Source' fields associated with modifications to the TextNote field will only occur when the altered content is not generic information derived from the definition of the FeatureType or other fields within the record.
3.7 Positional Accuracy
The positional accuracy of spatial data is a statistical estimate of the degree to which planimetric coordinates and elevations of features replicate the location of the real world phenomenon that they represent. The positional accuracy is estimated by modelling the propagation of errors in the data production process or by directly comparing the coordinate locations in the completed data against a source of significantly higher known accuracy. Geoscience Australia models their positional and vertical accuracy based on a Gaussian (Normal) distribution and a one-dimensional (linear) method.
For a linear distribution, the standard deviation is computed by squaring all the residual errors, adding the squared values, dividing by the numbers of errors (less one), and taking the square root:
In a Gaussian (Normal) distribution, 68.27% of the features would be within 1 standard deviation. The following conversion factors can be used to determine the percentage of features which fall with a multiple of the standard deviation.
The positional accuracy attainable in the TOPO100K and TOPO250K NTDBs as well as the 1:25 000 data capture model will be composed of errors from three sources:
Not all data revision/capture/conversion activities will generate errors from all three sources. The following table lists the different activities and their related error sources:
The positional accuracy of each feature instance (stated in metres) is given at either the feature level or via a Metadata Index feature class (see '3.6 Feature Metadata' for more details). The standard value assigned for the positional accuracy of features will be the absolute standard deviation (or the root mean square of the standard deviations of the applicable errors) unless the source of the feature is known to have a different accuracy (higher or lower), in which case the value adopted will reflect the expectation. The values to be assigned to these accuracy items should preferably be given at constant metre intervals (e.g. 5, 10, 15) where possible, with provision for smaller intervals in the higher accuracy values (e.g. 1,2,5) etc.
The TOPO100K and TOPO250K NTDBs as well as the 1:25 000 data capture model's positional accuracy is not restricted to well-defined points but encompasses a feature's entire spatial representation, including locations along a linear feature or the boundary of a polygon feature. This means that point features or point locations along linear features have a 68.27% probability of being within the stated accuracy of the true position of the phenomena they represent. A value of 9999 is used when the positional accuracy of the feature is not definable or not applicable. For example, the coordinates of a connector feature do not carry any meaning with respect to positional accuracy and so the value of planimetric accuracy given is 9999.
Where a feature exists with a populated planimetric accuracy value and is subject to positional change as a result of editing, the respective planimetric accuracy value will be updated accordingly with the appropriate value. This value may be sourced from existing base/reference material metadata or as a result of direct capture or digitising from approved reference material eg. a road feature with attributes of "position approximate" (default planimetric value of 9999) in the unrevised database may, upon spatial revision in the NTDB from recent imagery or large scale data sources, have its planimetric attribute updated to a higher value of 100.
3.7.1 The Positional Accuracy of the Base/Reference Material
This specification cannot prescribe a figure for the positional accuracy of the base/reference material designated for the capture of the digital representation of features in the TOPO100K and TOPO250K NTDBs as well as the 1:25 000 data capture model. This information should be supplied with each revision work package as required.
However there is an expectation that the base/reference material at least complies with the following statement in relation to the scale for which it is being utilised.
Not more than 10% of well defined points will be in error by more than 0.5mm measured on the source material.
Well defined points are those points which are readily identified on the ground and in the data and have not been offset to allow for symbolisation of surrounding features. They are usually at intersections.
Statistically, this relates to a standard deviation at map scale (Sm) of 0.31 mm.(eg 77.5m at 1:250 000, 31m at 1:100 000 and 7.75m at 1:25 000.)
New features will be captured to at least comply with this statement.
3.7.2 Errors Due to the Conversion/Capture Processes
The errors due to the conversion/capture process depend on the accuracy of the variety of factors dependant on the type of activity being undertaken. Some of these factors include requested digitising accuracy off imagery/aerial photography, method of raster to vector conversion, digitising table set-up or the scanner resolution, systematic errors in the equipment, errors due to software and errors specific to the operator.
As well as the errors in the conversion process outlined above, linear features may also be subject to filtering as part of the point density reduction process. If the filtering parameters are not carefully selected the resulting linear feature may not retain sufficient likeness to the base/reference material. To ensure linear features which are faithful to the shape and length of the base/reference material, the following specification will be satisfied.
The separation between the feature instance on the base/reference material and its digital representation in the database will not be greater than 0.2 mm at base/reference material scale i.e. 50m for the TOPO250K NTDB, or 20m for the TOPO100K NTDB.
The following is an example of the equation to determine the standard deviation of the conversion/capture process:
When table digitising the accepted standard is that the line accuracy should be within half a line width. As majority of symbolised features in topographic mapping have a line width of 0.2 mm or greater, then half the line width is taken as 0.1 mm and this is interpreted as one standard deviation Sdata for the distribution of errors.
The standard deviation of distribution errors in setting up the digitisation table is determined by the square root of the sum of all residual errors at each of the registration locations squared over the number of registration locations (minus one). For this example the resultant standard deviation measurement Stest is estimated to also be 0.1mm (at map scale).
The errors of the digitising process and the registration system are combined using root-mean-square-error formula to obtain a standard deviation for the entire conversion/capture process 'Slimit' which is a propagation of the known errors.
In this example the standard deviation for the entire conversion/capture process is Slimit = 0.14 mm, and thus two standard deviations, which 95 % of points should lie within, is 0.28 mm. The mean of the errors between the data and the test points should be zero, since there should be no bias in the errors, such as a consistent offset in the position of features. A sample of well defined points in data will be compared with their coordinates derived from the base/reference material and a test statistic of the mean plus two standard deviations must not be greater than 0.28 mm.
3.7.3 Errors Due to the Manipulation Processes
Errors due to the manipulation process should be kept at a minimum. Examples of these errors include separating vector contours which have merged in the raster to vector process, correcting topological structure rules such as dangles and intersect errors and as an extreme case smoothing vegetation boundaries after conversion of raster vegetation anaylsis data.
As a general rule, the processes used during data manipulation should not introduce an error greater than 10% of the vector capture error (e.g Sdata in the example above).
The standard deviation for the error due to the manipulation processes are termed 'Sman'.
3.7.4 Absolute Planimetric Accuracy
A formula is used to obtain the total statistical error from the three errors sources (base/reference material, conversion/capture process and manipulation process). The formula is listed below and an example given where:
This examples results in a standard deviation of 0.34mm which is approximately what was used to originally capture the TOPO250K NTDB and should be used as a guide for other GA activities.
At scale, this represents an error of 85m on the ground for 1:250 000 data, 34m for 1:100 000 data and 8.5m for 1:25 000 data.
Alternative and equal ways of expressing this error, after using the Gaussian Normal Distribution conversion factors is:
3.7.5 Absolute Elevation Accuracy
The accuracy of the points captured for the Relief layer varies with the source material and the point determination of each particular point. The following table summarises these accuracies.
The accuracy of the contours is defined as 1/2 of the contour interval, for example ± 25 metres for a 50 metre contour interval and ± 10 metres for a 20 metre contour interval.
3.7.6 Minimum Planimetric And Elevation Accuracies Requirements
The table below defines the minimum planimetric accuracies, where applicable, that must be met for a feature to be allowed to be included in specific Geoscience Australia's scale databases. Where features are captured more precisely than the minimum planimetric and elevation accuracies stated in the specifications this may be indicated by a more reflective value entered into the relevant field. All the planimetric accuracies are defined in metres.
A value of 9999 is used when the positional accuracy of the feature is not definable or not applicable. While the majority of features can be captured with a defined accuracy, others are captured via subjective or arbitrary means. An example of a feature that is captured in a subjective manner is 'Forest Or Shrub' which is based on an individual's interpretation of foliage coverage density. An example of a feature that is captured in an arbitrary manner is a junction between a watercourse area and the sea, this is a defined line by man for which there is no evidence, on the ground, in reality.
A value of 9999 is used when the elevation accuracy of the feature is not applicable.
Where a producer is unable to achieve the minimum planimetric and elevation accuracies with the base material/digital data, reference and supporting material provided an Action Request should be directed to Geoscience Australia requesting additional direction on how to proceed.
3.8 Item formatting and attribution
The TOPO100K and TOPO250K NTDBs as well as the 1:25 000 data capture program model's items will be populated in accordance with the following table and the population requirement codes set out in Appendix A Data Attributes Rules for each feature type (see 'An explanation of the feature type dictionary's layout and components. '2. Structure of an Entry'' ).
Where a string field allows Null entries and no information is available to populate that attribute, it must remain as a Null value and not be false 'blank' entry (e.g. a space). In addition, in the same circumstances when an existing attribute value becomes obsolete it should revert back to a Null value.
All date fields should be stored in the Standard Australian Format of DD/MM/YYYY (e.g. 24/10/1999).
Parenthesis should not be included in text strings unless they already exist as part of a defined domain or if they are part of the official or gazetted name. In several states it has become a practice to include an alternate name inside parenthesis as part of the official or gazetted names. This is common during a transition between the replacement of anglo-saxon names with their original indigenous titles, for example 'Tjuwaliyn (Douglas) Hot Spring Park, Uluru (Ayers Rock).
Note: The following list represents the total number of items existing for all Feature Classes in the TOPO100K and TOPO250K NTDBs as well as the 1:25 000 data capture program model. Therefore, more items are shown than what would normally appear against each individual Feature Class. Users should note that only user-defined items are included and listed below i.e. Default Geodatabase items associated with individual Feature Classes are not included e.g. items such as SHAPE_LENGTH, SHAPE_AREA, ELEMENT and ZCODE will not appear. Individual Feature Classes are not identified in this table (for a fuller description of the TOPO100K and TOPO250K NTDBs as well as the 1:25 000 data capture program model's Data Structure, see Section 3 Chapter 4.0 The National Topographic Database Structure). This list is intended to provide information on the format and attribution of all attribute items in the databases. The items are alphabetically ordered for ease of reference, and are not shown in the order they appear in the NTDBs models.
Case is to be assigned as per the following abbreviations in the table:
Named features will be attributed with the name in full including the type of feature where it is part of the official name. For example 'ESK RIVER', 'ORANGE AERODROME', etc. Usually the type of feature will not be part of the name for Railway Stations, Populated Places and Place Names that identify centres of population.
Abbreviations must not be used.
In the naming of localities, the terms 'Mission' and 'Aboriginal Community' should be avoided. Source material for the names of Indigenous communities will be determined by Geoscience Australia.
Plural names associated with a group of features should be assigned to every feature in the group unless the individual features have a name in their own right.
In the case of conflicting names, the incompatibility should be resolved and the features named accordingly. The National Gazetteer of Australia will be used to resolve incompatibilities.
Unnamed river anabranches will carry the river's name. Where a river anabranch is named in its own right it will carry its name (e.g. EDWARD RIVER).
Apostrophes should not be included in the NAME field e.g. where a name such as "Mary's Peak" is identified in the approved source material, it will be attributed as MARYS PEAK on entry to the database.
Proper names should not be incorrectly abbreviated or truncated eg. where a name such as "MacDonald River" is identified in the approved source material, it will be attributed as MACDONALD RIVER (not MCDONALD RIVER) on entry to the database.
Terms such as Mount and Saint shall be entered in full unless the official authorised name includes these terms as abbreviations e.g. The official name of a locality in Queensland is 'St George' whereas the official name of a locality in Victoria is 'Saint Albans East'.
The generic words "Mount" and "Mountain" should not be abbreviated when used to populate or complete Mountain names eg. the proper names "Mount Frederick" and "Jackson Mountain" should, on entry to the database, be fully attributed as MOUNT FREDERICK and JACKSON MOUNTAIN (not MT FREDERICK or JACKSON MTN).
3.9 Edge Match
This chapter relates only to the TOPO100K and TOPO250K NTDBs. Edgematching will not be conducted in the 1:25 000 data capture model unless requested of producers within the project file, when this occurs they should follow the theory detailed below.
The process of edge matching features in the TOPO100K and TOPO250K NTDBs involves the examination of the spatial and attribute properties of features either side of the Limit Of Data feature, work package/unit extents or across mismatches caused by spatial extent of revision material and, where appropriate, merging them into a single feature.
Linear and polygon features should be spatially joined across the Limit Of Data feature, work package/unit extents or across mismatches caused by spatial extent of revision material, if they are the same entity, and within 140m at 1:250 000 or 56m at 1:100 000 of each other in the data. The older data should be adjusted to match the most recent data, taking into account any locational reference material available such as imagery or digital photography. The adjustments made should result in a smooth transition of the join without hard bends appearing in the line work. The objective is to improve or establish continuity of features inside the NTDBs.
Some feature mismatches are unable to be immediately resolved and edge matched on entry to the databases for various reasons eg. Lack of sufficiently accurate source revision material, suitably revised data is unavailable for matching with the database area as it is currently being revised etc - hence the requirement for the Limit Of Data features.
All cases of mismatches need either a production note or error note associated with them dependant on the identifier or creator of the mismatch (e.g. through internal NMD personnel or those acting in a similar role/capacity an error note should be used however external producers should note these cases by using a production note). Systematic causes of spatial mismatches, such as the application of the incorrect datum when loading should be noted by only sufficient notes to identify the full extent of the problem.
3.10 Spatial Data Integrity
TOPO250K and TOPO100K NTDBs as well as the 1:25 000 data capture program model vector data will comply with the following rules for spatial data integrity. The rules for maximum allowable errors are described in Appendix J. These rules will be enforced with a 95% confidence level.
The spatial data will have no overshoots, undershoots, broken lines, pseudo nodes or other artefacts of the data capture process. These possible errors in the data are illustrated below. Pseudo nodes will be acceptable where features attributes vary with the exception of feature level metadata (e.g. feature reliability).
Undershoot in data.
Correct Representation Incorrect Representation
Overshoot in data.
Correct Representation Incorrect Representation
Pseudo-node in data
Same feature with identical attribute values.
Broken line in data
Correct Intersection Incorrect Intersection Incorrect Intersection
Linear Feature Spike in Linear Feature
Artefacts such as spikes and deviations of a linear feature from its expected position will be removed from the data to the extent that they will not be visible when the data is plotted or displayed at half its nominal scale i.e. 1:125 000 for 1:250 000 data, or 1:50 000 for 1:100 000 data.
3.10.1 Valid Intersections
An intersection in digital data will contain the same number of nodes as shown on the source material. An intersection node will be within 1/6 of the line width of the centre position of the intersection. The first vertex in each direction from the intersection node will be at a distance greater than three times the line width unless there is a bend in the road before this distance.
Valid and Invalid Intersections
3.10.2 Data Acquisition and Positioning of Features
When capturing data from imagery and photography as well as other sources such as GPS readings, wherever possible a:
4. Quality Information
Quality information allows the users of the data to make informed decisions about the fitness of the data for their application.
4.1 Product Quality Information
Product Quality Information will provide information which is specific to the NTDB. Geoscience Australia will provide the Product Quality Information. This will include a history of the source material, a description of the data capture process, and the quality aspects inherent in the NTDB such as positional accuracy, attribute accuracy, logical consistency and completeness.
5. Data Arrangement
The TOPO250K and TOPO100K NTDBs form part of a national, digital, spatial data environment for use by all users of digital spatial data. The features included in the NTDBs structure are arranged in Feature Datasets, Feature Classes and Feature Types as detailed in Section 3 of the Specification (see Section 3 Chapter 4.0 The National Topographic Database Structure)
For more information on feature classes and associated attributes see Appendix A.
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