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req coretiled-data
Target type Operations
Dependency Various XML schema
Requirement 64 req
corevector-dataset-limit
Requirement 65 reqcore
latitude-directory-name
Requirement 66 reqcore
longitude-directory-name
Requirement 67 reqcoreuref-directory-name
3.6.1 Tiled Dataset Types
There are three principal types of tiled datasets: 1. Raster Datasets
2. Vector Datasets 3. Model Datasets
3.6.1.1 Raster Datasets
Data elements within a tile are organized into a regular grid where data elements are evenly positioned at every XUnit
LOD
and YUnit
LOD
as described in Section 2.1.2, Tile Levels-of-Detail Tile-LODs. This type of organization is referred to as a Raster Dataset. Raster Datasets
always have a fixed number of elements corresponding to the number of units shown in Table 2- 4: CDB LOD versus Tile and Grid Size. An example of a raster dataset is terrain imagery.
Note: Partially-filled Tile-LODs are not permitted in a compliant the CDB data store. In the
case where data at the Tile-LOD’s resolution does not fully cover the Tile-LOD’s geographic footprint, the modeler or the tools should fill the remainder area of the
Tile-LOD with the “best available” data. There are two cases to consider:
Case I: In the case where coarser LODm data exists for the remainder area of the Tile-
LODn, the LODm data should be interpolated to LODn.
Case II: In the case where coarser LODm does not exist for the remainder area of the Tile-
LODn, then the remainder area of Tile-LODn should be filled with the default value for this dataset.
3.6.1.2 Vector Datasets
The point features, the lineal features, and the polygon features of the CDB are organized into several Vector Datasets and into levels of details.
The level-of-detail organization of the Vector Datasets mimics the concept of map scaling commonly found in cartography for example a 1:50,000 map. If we pursue the analogy with
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cartography, increasing the LOD number increasingly finer detail of a dataset is equivalent to decreasing the map’s scaling 1:n map scaling where n is decreasing. As is the case with
cartography, the Tile-LOD number provides a clear indication of both the positional accuracy and of the density of features. Consequently, the CDB specifies an average value for the density
of features for each LOD of the Vector Dataset hierarchy. Table 3-27 below defines these values. For each CDB LOD, the table provides the maximum number of points allowed per Tile-
LOD and the resulting average Feature Density.
Table 3-27: CDB LOD versus Feature Density CDB LOD
Maximum Number of Points per Tile
Approximate Tile Edge Size meters
Average Point Density pointsm
2
-10 1
1.11319 × 10
+05
8.06977 × 10
-11
-9 1
1.11319 × 10
+05
8.06977 × 10
-11
-8 1
1.11319 × 10
+05
8.06977 × 10
-11
-7 1
1.11319 × 10
+05
8.06977 × 10
-11
-6 4
1.11319 × 10
+05
3.22791 × 10
-10
-5 16
1.11319 × 10
+05
1.29116 × 10
-09
-4 64
1.11319 × 10
+05
5.16466 × 10
-09
-3 256
1.11319 × 10
+05
2.06586 × 10
-08
-2 1024
1.11319 × 10
+05
8.26345 × 10
-08
-1 4096
1.11319 × 10
+05
3.30538 × 10
-07
16384 1.11319 × 10
+05
1.32215 × 10
-06
1 16384
5.56595 × 10
+04
5.28861 × 10
-06
2 16384
2.78298 × 10
+04
2.11544 × 10
-05
3 16384
1.39149 × 10
+04
8.46177 × 10
-05
4 16384
6.95744 × 10
+03
3.38471 × 10
-04
5 16384
3.47872 × 10
+03
1.35388 × 10
-03
6 16384
1.73936 × 10
+03
5.41553 × 10
-03
7 16384
8.69680 × 10
+02
2.16621 × 10
-02
8 16384
4.34840 × 10
+02
8.66485 × 10
-02
9 16384
2.17420 × 10
+02
3.46594 × 10
-01
10 16384
1.08710 × 10
+02
1.38638 × 10
+00
11 16384
5.43550 × 10
+01
5.54551 × 10
+00
12 16384
2.71775 × 10
+01
2.21820 × 10
+01
13 16384
1.35887 × 10
+01
8.87281 × 10
+01
14 16384
6.79437 × 10
+00
3.54912 × 10
+02
15 16384
3.39719 × 10
+00
1.41965 × 10
+03
16 16384
1.69859 × 10
+00
5.67860 × 10
+03
17 16384
8.49297 × 10
-01
2.27144 × 10
+04
18 16384
4.24648 × 10
-01
9.08576 × 10
+04
19 16384
2.12324 × 10
-01
3.63430 × 10
+05
20 16384
1.06162 × 10
-01
1.45372 × 10
+06
21 16384
5.30810 × 10
-02
5.81489 × 10
+06
22 16384
2.65405 × 10
-02
2.32595 × 10
+07
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16384 1.32703 × 10
-02
9.30382 × 10
+07
Requirement 64
http:www.opengis.netspeccdb1.0corevector-dataset-limit
For positive LODs, each Tile-LOD of the vector datasets SHALL have no more than 16,384 points to describe the features, whether the file contains point, lineal, or polygon
features. For negative LODs, this limit SHALL be recursively divided by 4 until it reaches the value 1.
3.6.1.3 Model Datasets
