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

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in a multiband raster can be used to create RGB composites. When displaying image using RGB composites, obviously more information is conveyed from the dataset than in the case of one band. Figure 4.26: RGB composite from a three-band raster [35]. A satellite image, for example, commonly has multiple bands representing different wavelengths from the ultraviolet through the visible and infrared portions of the electromagnetic spectrum. Landsat imagery, for example, is data collected from seven different bands of the electromagnetic spectrum. Bands 1 to 7, including 6, represent data from the visible, near infrared and mid infrared regions. Band 6 collects data from the thermal infrared 4 region. 4.8 Pixel Types Figure 4.27: Multi-band raster image [35]. Besides band data, each band contains also information about nodata value and pixel type, which is a string value. Below are different pixel types supported in PostGIS Raster [6]: "1BB" = 1-bit boolean "2BUI" = 2-bit unsigned integer "4BUI" = 4-bit unsigned integer "8BSI" = 8-bit signed integer "8BUI" = 8-bit unsigned integer "16BSI" = 16-bit signed integer "16BUI" = 16-bit unsigned integer "32BSI" = 32-bit signed integer 4 http://en.wikipedia.org/wiki/Infrared. 41
"32BUI" = 32-bit unsigned integer "32BF" = 32-bit float "64BF" = 64-bit float 4.9 Nodata Values Cell values can be either positive or negative, integer or floating point. A noData value is used to represent cell values that are either unknown or meaningless. In the other words, a noData value represents the absence of data. Sometimes there are areas in a raster that user does not want to display. These can include borders, backgrounds or other data considered to not have valid values. In some cases, these areas are expressed as noData values, although in the other cases, they may have real values. When performing operations on raster data, there are typically two ways that noData are treated for each cell: noData value is returned for the position of corresponding cell, noData is ignored and can not be computed. So when calculating the statistics for a raster, user can decide to ignore or not any cells with noData value. Any analysis functions in PostGIS Raster always takes the nodata value into account. This means that the areas with nodata value will be omitted from the operation. For example in intersection operation, if a vector completely overlaps a nodata value area of one tile, the operation will set false for this tile and vector intersection and returns an EMPTY GEOMETRY result [8]. If the vector partially overlaps a nodata value area and intersect other parts of the tile, the operation will set true for this intersection and returns only parts of the tile with significant values, omitting parts with nodata values. Each raster band has its own noData value whose range depends on the associated band pixel type. The noData value is specified in the band information (see Figure ??). 4.10 Blocks or Tiles When importing a raster image into PostGIS database, users can choose to split the raster into small regular blocks by adding the -k option to the raster2pgsql.py Python loader, otherwise the entire raster is loaded into a single block. The block size is a parameter that follows just after the option -k (such as 128x128). All blocks are registered in a regular blocked table. Each block is stored in a row of the table and contains all data about itself (such as attribute information, georeference information, band information and band data) as the mother raster, except its size is equal the size of mother raster divided by block size. So each block by definition can be identified as a tile. This also means that in PostGIS Raster, there are no difference between rasters, tiles and blocks. Sometimes, the dimension size (row and column) of the mother raster may not be evenly divided by the block size. PostGIST Raster adds padding to the boundary blocks that do not have enough original cells to be completely filled. The padding cells have the same cell type as other cells and have values equal to zero. Padding makes each block have the same block size. Figure 4.28: Raster tiles [23]. 42
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 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: The multi-band conception is result
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
Page 69 and 70: ST_Present and ST_Passes predicates
Page 71 and 72: Chapter 5 User Guide Sometimes stor
Page 73 and 74: SELECT rast As origin, ST_Resample(
Page 75 and 76: • gvSIG plugin • MapServer thro
Page 77 and 78: SELECT ST_AsJPEG(rast) As rastjpg F
Page 79 and 80: FROM buff_temp GROUP BY id ORDER BY
Page 81 and 82: Chapter 6 Application Most of GIS a
Page 83 and 84: 6.2 Tools Figure 6.3: PostGIS conne
Page 85 and 86: Figure 6.6: Band area. controlled b
Page 87 and 88: Figure 6.10: The loading map parall
Page 89 and 90: Figure 6.14: Maps representing worl
Page 91 and 92: Figure 6.17: Maps with a color lege
Page 93 and 94: their levels of awareness of geogra
Page 95 and 96: [15] Jorge Arevalo. PostGIS Raster
Page 97 and 98: Appendix A PostGIS Raster Utilisati
Page 99 and 100: eturn "Version 0.1" def qgisMinimum
Page 101 and 102:
Appendix C Code Implementation C.1
Page 103 and 104:
name="" # Setting table name and mo
Page 105 and 106:
Figure D.1: Synthetic aperture rada
Page 107 and 108:
D.4 Digital Image Processing D.4.1
Page 109 and 110:
Figure D.4: Age of the sea floor. M
Page 111 and 112:
Appendix F Continuous Surfaces One
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