Google Maps Projection, and how to use it for clustering

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    Google Maps Projection, and how to use it for clustering - Presentation Transcript

    1. Google Maps Projection And how to use it for clustering
    2. Me = Lode Blomme  Software Engineer @ RouteYou  Blog: http://blog.lodeblomme.be  Twitter: http://twitter.com/lodeblomme  LinkedIn: http://www.linkedin.com/in/lodeblomme
    3. RouteYou  Products : • Community website: http://www.routeyou.com • Online recreational route planning • Maps for outdoor navigation for Garmin devices  Elevator Pitch : http://www.techcrunch.com/2008/10/24/elevator- pitch-friday-routeyou-makes-it-easy-to-find-the- perfect-driving-hiking-or-biking-route/
    4. I presume everybody knows Google? GOOGLE
    5. Any method of representing the surface of a sphere on a plane MAP PROJECTION
    6. Map Projection  (pseudo)cylindrical  (pseudo)conical  azimuthal  hybrid
    7. Map projections can preserve one or more of the earth's properties, though not all of them simultaneously AREA SHAPE DIRECTION BEARING DISTANCE SCALE
    8. Lambert Conformal Conic Projection
    9. Cylindrical Projection
    10. Cylindrical Equal-Area Projection
    11. Mercator Projection
    12. Google Maps : Zoom Level 0 256 px 256 px
    13. Google Maps : Zoom Level 1 512 px
    14. Google Maps : Zoom Level 1
    15. Google Maps : Zoom Levels • 1 tile (2(0*2)) 256 x 256 pixels = 65 536 pixels 0 • 4 tiles (2(1*2))  512 x 512 pixels = 262 144 pixels 1 • 16 tiles (2(2*2))  1024 x 1024 pixels = 1 megapixel 2 ... • 17 179 869 184 tiles (2(17*2))  33.5 x 33.5 megapixels = 1 122 megapixels 17 ... • 274 877 906 944 tiles (2(19*2))  134 x 134 megapixels = 18 000 megapixels 19
    16. Assigning an n-tuple of numbers to each point in an n-dimensional space COORDINATE SYSTEMS
    17. Spherical Coordinate System
    18. Cartesian Coordinate System
    19. Everybody knows WGS 84 and pixels WGS 84  PIXELS
    20. Mercator Projection : The Math $x = ($radius * deg2rad($lon)) - $falseEasting $y = (($radius / 2.0 * log((1.0 + sin(deg2rad($lat))) / (1.0 - sin(deg2rad($lat))))) - $falseNorthing) * -1
    21. Radius 256 px 256 px $tiles = pow(2, $zoom); $circumference = 256 * $tiles; $radius = $circumference / (2 * pi());
    22. Radius 512 px
    23. False Easting & False Northing 256 px 256 px $falseEasting = -1.0 * $circumference / 2.0; $falseNorthing = $circumference / 2.0;
    24. False Easting & False Northing X:0 X:1 Y:0 Y:0 X:0 X:1 Y:1 Y:1
    25. Partitioning of a data set into subsets, in which the data share some common trait - often proximity according to some defined distance measure CLUSTERING
    26. I thought we had a moment there HAPPY ENDING
    27. Scale
    28. Scale

    + lodeblommelodeblomme, 12 months ago

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    How Google presents the world with Google Maps, and more

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