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Maps, images, spatial displays - Always look at the data

Maps, images, spatial displays - Always look at the data responses, "Y" explanatories, "X". Y + X. Saskatchewan, Canada responses,"Y" explanatories,"X" polygon(), text(), library(maps),. Examples from the news Costa Concordia - Giglio.

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Maps, images, spatial displays - Always look at the data

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  1. Maps, images, spatial displays - Always look at the data responses, "Y" explanatories, "X" Y + X Saskatchewan, Canada responses,"Y" explanatories,"X" polygon(), text(), library(maps), ...

  2. Examples from the news Costa Concordia - Giglio

  3. Hetch Hetchy water route - pipelines and tunnels

  4. SF Chronicle centerfold

  5. Coal used for electricity circles(), polygon() NY Times 01/27/09

  6. Spatial process data. (s,t): geographic coordinates, e.g. (latitude, longitude), (x-coord,y-coord) y(s,t): real-valued e.g. available for s=0,...,S-1; t=0,...,T-1 (s,t) in A

  7. Height of 500mb surface S=64, T=32 1200 GMT January 1, 1986 data based on many observations, interpolated to grid display by contours over a world map

  8. overall mean subtracted map(), lines(), 2

  9. map(), image(...,add=T, col=)

  10. Starkey Reserve, Oregon - persp(), points()

  11. Ocean currents red: eastward blue: westward http://www.oscar.noaa.gov/ map(), arrows()

  12. Stacking. Galton - photos of faces electron micrographs crystal, purple membrane symmetries 160 "units" j=1160 yj(s,t)/160 stacking via FFT fft(), lines()

  13. micrographs not stacked and stacked J=1 J=160

  14. Data may be aggregate, e.g. over polygons coordinates of vertices choropleth plot: a thematic map in which areas are shaded map(), polygon() computational geometry, point in polygon library(splancs) Saskatchewan births, counts, rates

  15. polygon(,density=)

  16. perspective plot persp() hidden lines

  17. Contouring. Contour line, , (a function of two variables), is a curve connecting points where the function has the same value. Smooth function f: R2 R c: value f-1 (c) = x,y There may be more than one component

  18. One method. Suppose f(s,t) available for a regular grid Suupose wish f-1(c) Pick an edge, AB, of a pixel I. It will be intercepted if min{f(A),f(B)}cmax{f(A),f(B)} using this can learn all edges intercepted II. If one edge of a cell is intercepted, so is another one search in order E-S-W-N III. Get intersection coordinates by interpolation connect by line IV. Move to pertinent adjacent cell and continue

  19. Line process - set of lines {l1 , l2 , ls ,...} Point process {(p(l1),(l1)),(p(l2),(l2)),...} p: distance : angle

  20. Tesselation #{cells completely in set A} polygon()

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