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

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Finally, ST_Min and ST_Max, as indicate their names, return the temporal rasters that have respectively a minimum or maximum timestamp instant. To find the temporal rasters that have the minimal timestamp instant, firstly this minimum timestamp instant is found from a loop. Then a second loop choose only those that match this timestamp as output. Pseudo code of ST_Min: WHILE r timestamp of temporal raster r minTime = timestamp of temporal raster r WHILE r
Chapter 5 User Guide Sometimes storing data using raster is the only choice such as imagery is only available in raster format. Moreover, users can get many other advantages resulting from the nature of raster data, which is a matrix of cell values. For example, this simple data structure offers the ability to represent continuous surfaces as a grid of cell values and so enables easy spatial and statistical surface analysis. The ability to uniform storage as points, lines and polygons, which are all vector features, could also be stored using raster data. The following section introduces instructions about how to execute some basic operations such as importing, exporting raster data, conversion and intersection between raster and vector data, along with other abilities that PostGIS Raster could offer to users. 5.1 Store and Manage Rasters 5.1.1 Import Rasters User can import rasters from existing raster images stored in file system using raster2pgsql Python loader: (1) raster2pgsql.py -r "c:/temp/mytiffolder/*.tif" -t mytable -s 4326 -o table_name.sql (2) psql -d postgisdb -f table_name.sql -U -W The first command (1) generates a sql file that loads file_name.tif with SRID 4326 into a new table called mytable. The second command (2) runs the SQL script for loading the data into postgisdb. Or users can create their own rasters from SQL command: CREATE TABLE dummy_rast(rid integer, rast raster); INSERT INTO dummy_rast(rid, rast) VALUES -- Raster: 5 x 5 pixels, 3 bands, PT_8BUI pixel type, NODATA = 0 (1,(’01000003009A9999999999A93F9A9999999999A9BF000000E02B274A4 1000000007719564100000000000000000000000000000000FFFFF FFF050005000400FDFEFDFEFEFDFEFEFDF9FAFEFEFCF9FBFDFEFEF DFCFAFEFEFE04004E627AADD16076B4F9FE6370A9F5FE59637AB0E 54F58617087040046566487A1506CA2E3FA5A6CAFFBFE4D566DA4C B3E454C5665’)::raster); 5.1.2 Get and Set The Raster Properties • Upper left corner coordinates and transformation parameters –Get the upper left corner coordinates of all rasters in the table: 62
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Faculté de Sciences Appliquées Se
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Abstract Nowadays, in many applicat
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3.2.4 Overlapping Raster and Vector
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D.5 Geology, Geophysics and Geochem
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4.9 Raster cell [16]. . . . . . . .
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Chapter 1 Introduction 1.1 Context
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Chapter 2 Geographic Information Sy
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2.2.3 Imagery Figure 2.3: Polygon f
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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
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: ST_Present and ST_Passes predicates
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
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Page 95 and 96: [15] Jorge Arevalo. PostGIS Raster
Page 97 and 98: Appendix A PostGIS Raster Utilisati
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Page 101 and 102: Appendix C Code Implementation C.1
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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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