Tile-Based Geospatial Information Systems: Principles and Practices / Edition 1 available in Hardcover
Tile-Based Geospatial Information Systems: Principles and Practices / Edition 1
- ISBN-10:
- 1441976302
- ISBN-13:
- 9781441976307
- Pub. Date:
- 11/02/2010
- Publisher:
- Springer US
- ISBN-10:
- 1441976302
- ISBN-13:
- 9781441976307
- Pub. Date:
- 11/02/2010
- Publisher:
- Springer US
Tile-Based Geospatial Information Systems: Principles and Practices / Edition 1
Hardcover
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$109.99Overview
Product Details
| ISBN-13: | 9781441976307 |
|---|---|
| Publisher: | Springer US |
| Publication date: | 11/02/2010 |
| Edition description: | 2010 |
| Pages: | 237 |
| Product dimensions: | 6.10(w) x 9.30(h) x 0.80(d) |
About the Author
Elias Z. K. Ioup is a Computer Scientist with the Naval Research Laboratory working on several geospatial research programs. He is the principal investigator for the GHUB Distributed Geospatial Repository program and a lead developer on the Geospatial Information Database (GIDB). These programs represent leading DoD efforts to leverage geospatial capabilities using Service Oriented Architectures and Web services. Elias Ioup received a Master’s degree in Computer Science from the University of New Orleans in 2006 and Bachelor's degrees in Mathematics and Computer Science from the University of Chicago in 2003. He is currently a Ph.D. candidate in Engineering and Applied Science at the University of New Orleans.
Table of Contents
1 Introduction 1
1.1 Background of Web-Based Mapping Applications 1
1.2 Properties of tile-based mapping systems 2
1.3 Book Organization 2
2 Logical Tile Schemes 5
2.1 Introduction 5
2.2 Global Logical Tile Scheme 7
2.3 Blue Marble Example 10
2.4 Mercator-Based Schema 11
2.5 Variable Start Tile Schemes 12
2.6 Standardized Schema 15
References 15
3 Tiled Mapping Clients 17
3.1 Tile Calculation 17
3.1.1 Discrete Map Scales 18
3.1.2 Continuous Map Scales 20
3.2 Tile Retrieval 22
3.2.1 Local Tile Storage 23
3.2.2 Network Tile Retrieval 23
3.3 Generating the Map View 25
3.3.1 Discrete Scales Map View 25
3.3.2 Continuous Scales Map View 26
3.4 Example Client 28
3.5 Survey of Tile Map Clients 28
4 Image Processing and Manipulation 35
4.1 Basic Image Concepts 35
4.2 Geospatial Images 37
4.2.1 Specialized File Formats 37
4.3 Image Manipulation 39
4.3.1 Interpolation 1: Nearest Neighbor 44
4.3.2 Interpolation 2: Bilinear 45
4.3.3 Interpolation 3: Bicubic 46
4.4 Choosing Image Formats for Tiles 51
4.5 Choosing Tile Sizes 57
4.6 Tuning Image Compression 65
References 79
5 Image Tile Creation 81
5.1 Tile Creation from Random Images 82
5.2 Tile Creation Preliminaries 83
5.2.1 Bottom-Up Tile Creation 83
5.2.2 Choosing the Base Level for a Set of Source Images 83
5.2.3 Pull-Based Versus Push-Based Tile Creation 87
5.3 Tile Creation Algorithms 88
5.3.1 Scaling Process for Lower Resolution Levels 89
6 Optimization of Tile Creation 97
6.1 Caching Tile Sets in Memory to Improve Performance 97
6.2 Partial Reading of Source Images 99
6.2.1 Reading Random Areas from Source Images 100
6.2.2 Tile Creation with Partial Source Image Reading 103
6.3 Tile Creation with Parallel Computing 103
6.3.1 Multi-Threading of Tile Creation Algorithms 104
6.3.2 Tile Creation for Distributed Computing 105
6.4 Partial Updating of Existing Tiled Image Sets 108
References 116
7 Tile Storage 117
7.1 Introduction to Tile Storage 117
7.2 Storing Image Tiles as Separate Files 118
7.3 Database-Based Tile Storage 121
7.4 Custom File Formats 121
7.5 Comparative Performance 122
7.5.1 Writing Tests 123
7.5.2 Reading Tests 124
7.6 Storage of Tile Metadata 126
7.7 Storage of Tiles in Multi-Resolution Image Formats 126
7.8 Memory-Cached Tile Storage 127
7.9 Online Tile Storage 127
8 Practical Tile Storage 133
8.1 Introduction to Tile Indexes 133
8.2 Storage by Zoom Level 136
8.3 Introduction to Tile Clusters 138
8.4 Tile Cluster Files 139
8.5 Multiple Levels of Clusters 140
8.6 Practical Implementation of Tile Clusters 141
8.7 Application to Memory Cached Tiles 142
8.8 Application to Distributed Computing 142
8.9 Performance Optimizations of Tile Cluster Method 142
9 Tile Serving 151
9.1 Basics of HTTP 151
9.2 Basic Tile Serving 152
9.3 Tile Serving Scheme with Encoded Parameters 153
9.4 Tile Serving Scheme with Encoded Paths 155
9.5 Service Metadata Alternatives 156
9.6 Conclusions 157
References 164
10 Map Projections 165
10.1 Introduction to Datums, Coordinate Systems, and Projections 165
10.1.1 The Shape of the Earth 165
10.1.2 Datums 166
10.1.3 Coordinate Systems 169
10.2 Map Projections 169
10.2.1 Different Map Projections 170
10.2.2 Cylindrical Equidistant Projection 171
10.2.3 Cylindrical Equal-Area Projection 172
10.2.4 Mercator 172
10.2.5 Universal Transverse Mercator 172
10.3 Point Reprojection 175
10.4 Map Reprojection 177
10.4.1 Affine Transforms 177
10.4.2 Interpolation 179
10.4.3 Point-wise Reprojection 180
10.4.4 Tablular Point-Wise Reprojection 182
10.5 Map Projections for Tiled Imagery 184
10.5.1 Storing Tiles in the Geodetic Projection 184
10.5.2 Storing Tiles in the Mercator Projection 185
10.5.3 Other Projections 186
10.5.4 Which Projection for a Tiled-Mapping System? 187
10.6 Conclusion 188
References 191
11 Tile Creation using Vector Data 193
11.1 Vector Data 193
11.2 Tile Creation 194
11.3 Queries 196
11.4 Storage 196
11.4.1 Database Storage 197
11.4.2 File System Storage 200
12 Case Study: Tiles from Blue Marble Imagery 205
12.1 Pull-Based Tiling 205
12.2 Push-Based Tiling 207
12.3 Results 207
13 Case Study: Supporting Multiple Tile Clients 221
13.1 KML Server 221
13.1.1 Static KML Example 221
13.1.2 Dynamic KML Example 223
13.2 WMS Server 223
13.2.1 WMS Servlet Implementation 224
References 233
Index 235