Presentation given at Big Data from Space at ESA ESRIN

1. Global&Deforesta-on&through&Time&
Big$Data$Meets$Scalable$Visualiza2ons$|$Javier$de$la$Torre$;$CartoDB$

3. MAKE BEAUTIFUL MAPS - BUILD GEOSPATIAL APPLICATIONS - LET YOU GAIN INSIGHT FROM YOUR DATA

30. http://en.wikipedia.org/wiki/Bakun_Dam

31. Geo-temporal visualizations
CartoDB and Torque

34. Datacubes
•BI/Finance analysis
•multidimensional
•summary data
•binned variables

36. WITH%hgrid%
%%%%%AS%(SELECT%Cdb_rectanglegrid(Cdb_xyz_extent(8,%12,%5),%
%%%%%%%%%%%%%%%%Cdb_xyz_resolution(5)%*%4,%
%%%%%%%%%%%%%%%%%%%%%%%%%%%Cdb_xyz_resolution(5)%*%4)%AS%cell)%
SELECT%x,%
%%%%%%%y,%
%%%%%%%Array_agg(c)%vals,%
%%%%%%%Array_agg(d)%dates%
FROM%%%(SELECT%St_xmax(hgrid.cell)%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%x,%
%%%%%%%%%%%%%%%St_ymax(hgrid.cell)%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%y,%
%%%%%%%%%%%%%%%Count(i.cartodb_id)%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%c,%
%%%%%%%%%%%%%%%Floor((%Date_part('epoch',%built)%Q%Q10418716800%)%/%32837875)%d%
%%%%%%%%FROM%%%hgrid,%
%%%%%%%%%%%%%%%us_po_offices%i%
%%%%%%%%WHERE%%St_intersects(i.the_geom_webmercator,%hgrid.cell)%
%%%%%%%%GROUP%%BY%hgrid.cell,%
%%%%%%%%%%%%%%%%%%Floor((%Date_part('epoch',%built)%Q%Q10418716800%)%/%32837875)%
%%%%%%%)%f%
GROUP%%BY%x,%
%%%%%%%%%%y

37. {
%%rows:%[
%%{
%%%%x:%0,
%%%%y:%0,
%%%%vals:%[2],
%%%%dates:%[457]
%%},
%%{
%%%%x:%1,
%%%%y:%0,
%%%%vals:%[1,1,4],
%%%%dates:%[2,3,4]
%%%%}
%%]
}

38. 1
10
100
1000
3mb 70mb 300mb
1.5
2
1.2
300
70
3
Raw Datacube
Payload sizes

41. Geo-temporal visualizations
We have defined a format to transfer data cube “data” to the
browser.
One or many dimensions: use of coded images or JSON
Geo-temporal visualizations and data cubes are a great
way of understanding how spatial data changes
We can handle millions of vector data or processed rasters

42. Global&Deforesta-on&through&Time&
Big$Data$Meets$Scalable$Visualiza2ons$|$Javier$de$la$Torre$;$CartoDB$