PostGIS Raster : Extending PostgreSQL for The Support of ... - CoDE

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5.6 Intersection of raster polygons [23]. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 5.7 Different temperature values in a polygon [23]. . . . . . . . . . . . . . . . . . . . . . . 70 5.8 Gird of cells of USA map [23]. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 5.9 Web GIS application [23]. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 6.1 QGIS interface. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 6.2 QGIS toolbars. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 6.3 PostGIS connection. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 6.4 Temporal raster window. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 6.5 Time travel interface. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 6.6 Band area. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76 6.7 The temperature color legend. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76 6.8 The color legend interface. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 6.9 The loading map sequential approach. . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 6.10 The loading map parallel approach. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 6.11 Maps representing world climate [7] are loaded once time. Their visibility is handled by turning on/off the check boxes list. . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 6.12 Media area. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 6.13 Single band rasters. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 6.14 Maps representing world climate are loaded as single band rasters. They are turned into color maps by loading a created color palette "worldclim.txt". . . . . . . . . . . . 80 6.15 Map is loaded as multi band raster. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 6.16 Visualisation of band number 2 of a multi band map. . . . . . . . . . . . . . . . . . . . 81 6.17 Maps with a color legend. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 D.1 Synthetic aperture radar image of Death Valley [37]. . . . . . . . . . . . . . . . . . . . 96 D.2 Relief map Sierra Nevada (Spain) [38]. . . . . . . . . . . . . . . . . . . . . . . . . . . . 98 D.3 William Smith’s geologic map of England,Wales, and southern Scotland. Completed in 1815, it was the first national-scale geologic map and by far the most accurate of its time [39]. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 D.4 Age of the sea floor. Much of the dating information comes from magnetic anomalies [40]. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 E.1 Raster data represented at different resolution or cell sizes [11]. . . . . . . . . . . . . . 101 F.1 Elevation represented in raster format [33]. . . . . . . . . . . . . . . . . . . . . . . . . 102 F.2 Source-concentration surface represented in raster format [33]. . . . . . . . . . . . . . . 103 1
Chapter 1 Introduction 1.1 Context Our daily life is full of situations that require us to make a choice among several alternative solutions, so-called decision process. For example, we have from simple situations such as shopping, voting to complicated situations that happen in government and business like resource management, urban planning and regional planning. But on what do we base to make the best choice ? Due to the complexity of many decisions in government and business that require us to think of different elements like stakeholders and categories, it leads to the need of using software for decision making process. Examples of such applications include environmental impact-assessment, geographic history, population and demographic studies, criminology and military planning. Among the elements that influence decision making, geographical information represents a relevant source to decision makers. Whether the issue is the location of a new public or the development of a new project, decision makers should consider such geographic information as location, character of environment and landscapes. Furthermore, in the private sectors, a large group of companies use geographic information as a tool for their locational decision making. These include retail marketing chains (for example, Dayton- Hudson, a major retail firm headquartered in Minneapolis), railroads (for example, Southern Pacific Railroad’s land division), electric power and gas utilities, international import-export firms, transportation and travel service organizations, publishing firms and real estate planners and investors [19]. 1.2 Goals Not all sources of geographic information are reliable. The precision of geographic information can be influenced indirectly through scholarly publications. These publications tend to influence decision makers’s understanding about climate issues. So it is important to have a useful tool, such as a geographic information system, that helps user to handle directly geographic information and thus guarantees the correctness of information. Most of the current geographic information systems provide a vector type for manipulating geographic information. However, there are very few attempts to support a data type that describes the distribution of physical phenomena that change continuously in time and space, so-called continuous fields. Example of such phenomena are temperature, pressure, precipitation, land elevation, land use, population density and etc. The main contribution of this thesis is to introduce a new data type PostGIS Raster that supports continuous fields in PostgreSQL database. In addition, it also describes an application that allows user to exploit the temporal feature of geographic data using PostGIS Raster. 2
Page 1 and 2: Faculté de Sciences Appliquées Se
Page 3 and 4: Abstract Nowadays, in many applicat
Page 5 and 6: 3.2.4 Overlapping Raster and Vector
Page 7 and 8: D.5 Geology, Geophysics and Geochem
Page 9: 4.9 Raster cell [16]. . . . . . . .
Page 13 and 14: Chapter 2 Geographic Information Sy
Page 15 and 16: 2.2.3 Imagery Figure 2.3: Polygon f
Page 17 and 18: Figure 2.8: Surface expressed by co
Page 19 and 20: 4-foot logo. The file size is the s
Page 21 and 22: 2.4.2 Data Theme Figure 2.14: Multi
Page 23 and 24: measures of latitude. Longitude mea
Page 25 and 26: 2.6 GIS Applications 2.6.1 Crime Ma
Page 27 and 28: 2.6.3 Traditional Knowledge GIS Tra
Page 29 and 30: These additional functionalities ma
Page 31 and 32: Figure 3.3: Physical storage of Geo
Page 33 and 34: DROP INDEX spain_images_idx; CREATE
Page 35 and 36: In summary, the intersection is muc
Page 37 and 38: Attribute information Table 4.1: Po
Page 39 and 40: Figure 4.2: Information representat
Page 41 and 42: for discrete data while floating-po
Page 43 and 44: the matrix are parallel to the x-ax
Page 45 and 46: Lines Figure 4.15: Raster point rep
Page 47 and 48: Choosing an appropriate cell size i
Page 49 and 50: The multi-band conception is result
Page 51 and 52: "32BUI" = 32-bit unsigned integer "
Page 53 and 54: Figure 4.30: Pyramids at different
Page 55 and 56: ectangular because there might be s
Page 57 and 58: Figure 4.39: Vector to raster conve
Page 59 and 60: Figure 4.42: Web application with o
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In this example, the dummy_rast tab
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One approach to make this intersect
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4.19 Intersection The fact that Pos
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Figure 4.51: Raster and raster inte
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ST_Present and ST_Passes predicates
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Chapter 5 User Guide Sometimes stor
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SELECT rast As origin, ST_Resample(
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• gvSIG plugin • MapServer thro
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SELECT ST_AsJPEG(rast) As rastjpg F
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FROM buff_temp GROUP BY id ORDER BY
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Chapter 6 Application Most of GIS a
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6.2 Tools Figure 6.3: PostGIS conne
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Figure 6.6: Band area. controlled b
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Figure 6.10: The loading map parall
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Figure 6.14: Maps representing worl
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Figure 6.17: Maps with a color lege
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their levels of awareness of geogra
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[15] Jorge Arevalo. PostGIS Raster
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Appendix A PostGIS Raster Utilisati
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eturn "Version 0.1" def qgisMinimum
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Appendix C Code Implementation C.1
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name="" # Setting table name and mo
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Figure D.1: Synthetic aperture rada
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D.4 Digital Image Processing D.4.1
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Figure D.4: Age of the sea floor. M
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Appendix F Continuous Surfaces One
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