- Magic spotlights vector
- Magic wand vector
- Magic background vector
- Mystic magic symbols set vector
- Magic wand vector
- Magic mirror vector
- Magic hat with wand vector
- Magic rainbow lights vector
- Magic place ethnic vector
- Magic stick vector
- Magic suit vector
- Magic icon set vector
- Golden magic wand vector
- Magic pencil vector
- Magic gift box vector
- Magic floral background vector
- Magic light effects vector
- Magic art logo vector
- Magic potions vector
- Magic icon vector
- Magic wand with stars vector
- Magic book icon icon cartoon vector
- Magic composition vector
- Magic hat vector
- Magic sky tree vector
- Magic cartoon icons set vector
- Magic lamp vector
- Magic music notes vector
- Holiday magic vector
- Holiday christmas background with a red magic box vector
- Magic gadget logo vector
- Magic book logo vector
- Magic sound logo vector
- Magic hat logo vector
- Magic potion banners vector
- Magic waves ringlets vector
- Magic flat icons set vector
- Magic smilies vector
- Magic clover vector
- Magic sale hat vector
- Magic wand objects set vector
- Golden magic wand vector
- Curvy element of magic sign vector
- Magic horizontal banners vector
- Flat magic frame vector
- Magic unicorn vector
- Magic show isometric vector
- Magic icon blue vector
- Magic hat vector
- Golden magic star vector
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|Matrix is the first movie approaching grids|
Gridding is a way to simplify the representation of data on a large scale. It can be a useful way to “resample” the vision of a territory if you work on bigger units. These units, usually squares, are comparable, on the contrary to administrative units. If you can omit the administrative units, gridding is a way to get an homogeneous view of your territory. The larger your area of interest will be, the bigger the squares from your grid you might configure.
|hexagons look ecologic, triangles ecclesiastic|
Also, you could prefer hexagonal units to square units for more harmony. Some prefer triangles. Anyway, the number of possible shapes are limited.
Land Cover of Paris & surroundings
I wanted to visualize the land cover of Ile-De-France width a grid. Ile-de-France is a region that includes Paris at its center. Precisely, I decided to study the repartition of urban , agricultural and natural (forests, gardens, etc…) areas, that is 3 variables over the whole area.
|the best diagram I’ve ever made, even if pie charts are the worst|
The question was : how to represent 3 variables at a time on each square unit ? One answer could have been “diagrams”, that is pie charts, histograms on the map
But I found it cooler to use an RGB representation.
|A Freemason way of seeing data|
Let’s suppose R means urban, G Natural and B Agricultural. If the color of a square approaches red, then it means urban; if it is purple, it means urban & agricultural areas dominate but not natural; if it is desaturated, it means the 3 types of cover are equally mixed.
|I remember a mushroom im my parents’garden had the same shape|
For the land cover of Ile-de-France, we have a nice 2012 Corine Land Cover GeoTiff.
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|Laurent Manadou exploring data|
I wondered if one could adopt a dynamic view that goes from the global view to the zonal one in a sort of “data diving”.
|beware of the logarithmic launching pad|
I wondered what series of sizes to adopt. I decided to generate 100 images. 1km would be the minimum unit and we would reach the BIG square covering all the region, the width of Ile-De-France being precisely 154 451 km according to GÉOFLA. The distribution, as illustrated, will be logarithmic.
|The same sensation appears when you dive head first in a municipal pool|
Above is a GIF presenting the different calculation canvases.
Dancing on Land Cover from datagistips on Vimeo.
Here is the video with land cover percentages encoded as colors, with reversed order, from the biggest to the smallest unit. The changing colors make it kind of animated dancefloor.
This illustration, that I had made for a GéoTribu post, illustrates the usual workflow I adopt, from production to design. I generated the distinct grids associated with the land cover percentage values with R. I designed all the layers with QGIS. With the same tool, I generated an atlas. With this atlas, I created a video with ffmpeg.
The QGIS part may interest the QGIS fans as it uses a new QGIS 2.12 functionnality : data defined control over map layers and style presets
Generation : R
I created a function in R that generates a grid. The hack consists in polygonizing a raster layer, of which the resolution determinates the square size :
Vector Magic Archives 2017
The extract function crosses the vector grid and the 2012 CLC raster. The table function gives the number of pixels of each category :
The prop.table calculates the proportion of urban, natural and agricultural areas :
Design : QGIS
|color RGB code from columns, named “R”, “G”, and “B”|
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An expression defines the color of each square depending on its column values :
I saved the QML style file, then used the multiQML plugin to apply it to the 99 other layers.
|Data defined control over map layers and style presets|
To get a static coverage layer, I duplicated my area of interest as many times as the number of pages (or layers) and assigned the square size value to the layer names. In the latest version of QGIS, you can generate an atlas with a list of layers on each page defined by an expression.
Also, I used some generative design tricks to get the animated halo effect around the IDF region.
|Shapeburst fill and cellpadding='0' cellspacing='0'>|
|riding the wave of generative design|
|sin wave shade distance|
while a sin function defines the shade distance. This way, we get a “flame” effect with increasing then decreasing shade width. scale_linear(sin(scale_linear(@atlas_featurenumber,1,100,0,pi()*2)),0,1,5,10)
Video making: ffmpeg
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Finally, this command line generates the video from images :
ffmpeg -framerate 25 -r 10 -i output_%d.jpg -vcodec mpeg4 -b 50000k -qscale:v 1 dancingVideo.avi