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

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2.3 Geographic Data Representation Traditionally, real objects in geographic data can be stored into two forms: discrete objects (such as roads, houses, trees) using vector and continuous fields (such as rainfall amount, elevations) using raster. A new hybrid method of storing data identifies point clouds, combines three-dimensional points with RGB information at each point and returns a 3D color image. However, the following Section focus only on vector and raster representation. 2.3.1 Vector Images Vector images use geometrical primitives like points, lines, curves and polygons, which are all based on mathematical expressions to represent images in computer graphics. Each geometric primitive is presented by lines and surfaces. All lines, individually, are defined by characteristic points that define its equation. These characteristic points form a vector. Thus, the vector representation is expressed in terms of characters of line and color of the surface. This leads to the notion of drawing multiple layers where planes curves can be overlaid. This phenomenon can not happen in raster representation since there is only one layer, then each new point overwrites the previous point. The advantage of a vector representation is the delicacy and precision of the results. Every line can be edited very quickly and all at once. Indeed, this representation involves a limited number of graphical objects, so these graphics files are very light. Resolution As vector images are defined by mathematical expressions, they can be zoomed in or out without any loss of quality. Concretely, the mathematical description of the object is simply multiplied by a zooming factor. For example a 1 inch square object will be multiplied by a factor of 2 in order to double in size. The mathematical expression is thus recalculated to produce an object twice the size of the original. So vector images can be output at any resolution that a printer is capable of producing. Unlike raster images, quality of vector images is not limited by scanning resolution. This is a big reason that vector images are so popular for clip art. Color Figure 2.11: Vector image at various scales. Since vector images are composed of objects, coloring vector objects is similar to coloring with crayons in a coloring book. Using drawing program, users can easily change the color of individual objects by clicking inside this object and define its color, along with defining width of lines. Coloring vector images is much easier than coloring raster images. File Size Storing vector images need to keep only mathematical descriptions. For this reason vector files are very small in file size. A 2-inch by 4-inch logo based vector will be the same files size as a 2-foot by 9
4-foot logo. The file size is the same because the only difference in file is one number defining the size of the file. Most vector-based logos are going to be under 100 KB. For this reason, vector files are ideally suited for transfer over the Internet. File Formats Common vector formats include EPS (Encapsulated PostScript), WMF (Windows Metafile), AI (Adobe Illustrator), CDR (CorelDraw), DXF (AutoCAD), SVG (Scalable Vector Graphics) and PLT (Hewlett Packard Graphics Language Plot File). Modern displays and printers are raster devices, vector formats have to be converted to raster format before they can be displayed or printed. Or in graphic work, devices such as cameras and scanners produce essentially continuous-tone raster graphics that are impractical to convert into vectors. So an image editor will operate on the pixels rather than on drawing objects defined by mathematical expressions. 2.3.2 Raster Images A raster image (or bitmap) is a 2-dimensional array data structure representing a rectangular grid of pixels, or dots or points of color. A raster image is characterized by its width and height in pixels and by the number of bits per pixel. This number determines the number of colors can be represented in the image. Resolution The resolution of a raster image is expressed in terms of the dots per inch or dpi. Printer resolution is also measured in dots per inch. Typical desktop laser printers print at 300 - 600 dpi. Printers with higher dpi are capable of producing smoother and cleaner output. Nevertheless, the quality of a raster image depends on its resolution (dpi) and the capabilities of the printing technology [9]. For example, a 300 dpi raster image will output at the same quality on a 300 dpi laser printer as on a 2,500 dpi printer. By increasing size of a 300 dpi raster image, the tiny pixel squares will become bigger and create jaggy edges as no additional information is added. In this case, the raster image losses quality. Exammple in Figure 2.12 shows the jaggy edges of raster image through zooming effect. In contrast, When decreasing the size, the squares get smaller and the image retains its original edge without jaggies. Figure 2.12: The original vector image is on the left side. The upper-right image illustrates magnification of 7x as a vector image. The lower-right image illustrates the same magnification as a raster image [29]. Color As raster images are reproduction of real world, a large number of colors will be required to render raster images accurate as their original sources. For example, if scanner works at 24-bit color (16 million colors), most human eyes could not distinct the difference between the original image and the scanned raster image. In contrast, if a smaller color palette with 256 colors is used, it would be 10
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 and 10: 4.9 Raster cell [16]. . . . . . . .
Page 11 and 12: Chapter 1 Introduction 1.1 Context
Page 13 and 14: Chapter 2 Geographic Information Sy
Page 15 and 16: 2.2.3 Imagery Figure 2.3: Polygon f
Page 17: Figure 2.8: Surface expressed by co
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
Page 61 and 62: In this example, the dummy_rast tab
Page 63 and 64: One approach to make this intersect
Page 65 and 66: 4.19 Intersection The fact that Pos
Page 67 and 68: 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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