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Thejesh GN

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Dec 8, 2017, 2:30:14 AM12/8/17
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Interesting considering both Susewind and Ramani are part of DataMeet community. It would be great to have an how-to. Either audio or text. 


Quote from from the article:

Social anthropologist Raphael Susewind’s work on Gujarat was used to arrive at this. Dr. Susewind merges NASA’s urban-rural classifications (MODIS data) based on satellite information and the Election Commission’s polling booth data to identify if a booth is located in a rural or an urban setting. MODIS data classifies urban areas into highly urban, semi-urban, etc. in a scale of 1 to 9 (the lower number corresponds to higher urbanity). Sixty five per cent of the electorate voted in booths in rural areas while the rest in various urban classifications.

Thej
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Thejesh GN  ತೇಜೇಶ್ ಜಿ.ಎನ್
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Raphael Susewind

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Dec 8, 2017, 4:42:42 AM12/8/17
to data...@googlegroups.com, Thejesh GN, Srinivasan Ramani
Dear Thej,

there is not much of a howto - I took my polling booth locality
shapefiles (https://pub.uni-bielefeld.de/data/2674065) as well as the
MODIS data that is available in convenient format from Naturalearth
(https://pub.uni-bielefeld.de/data/2674065), put both into QGIS, and
used their 'Join attributes by location' function. That's that. A
somewhat more involved processing chain underpins the polling booth
shapefile as such - all described in the link above...

Srini could probably chip in with more detail on how he ran the analysis
per se?

Hope that helps,
Raphael

On 12/08/2017 07:30 AM, Thejesh GN wrote:
>
>
> http://www.thehindu.com/elections/gujarat-2017/voting-trends-show-a-clear-rural-urban-divide-for-cong-bjp-in-gujarat/article21285328.ece
>
>
>
> Interesting considering both Susewind and Ramani are part of DataMeet
> community. It would be great to have an how-to. Either audio or text. 
>
>
> Quote from from the article:
>
> Social anthropologist Raphael Susewind’s work on Gujarat was used to
> arrive at this. Dr. Susewind merges NASA’s urban-rural classifications
> (MODIS data) based on satellite information and the Election 
> <http://www.thehindu.com/tag/1369-1349/election/?utm=bodytag>Commission’s polling
> booth data to identify if a booth is located in a rural or an urban
> setting. MODIS data classifies urban areas into highly urban,
> semi-urban, etc. in a scale of 1 to 9 (the lower number corresponds to
> higher urbanity). Sixty five per cent of the electorate voted in booths
> in rural areas while the rest in various urban classifications.
>
> Thej
> --
> Thejesh GN *⏚* ತೇಜೇಶ್ ಜಿ.ಎನ್
> http://thejeshgn.com
> GPG ID :  0xBFFC8DD3C06DD6B0
>
> --
> Datameet is a community of Data Science enthusiasts in India. Know more
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Noor Hasan

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Dec 8, 2017, 5:41:49 AM12/8/17
to data...@googlegroups.com, Thejesh GN, Srinivasan Ramani

Dear Susewind R,

Great work! I really appreciate the above analysis and come out wonderful results.

Accuracy doesn’t matter, but I am interesting to know about the algorithms and process for whole study

and how that this analysis found the vote rate distribution in among the polling booths.

Can you please help me out to analysis and share the algorithms for the same.

I have download all the shape file of Gujrat’s constituencies and booth locations.

Thank you so much kind sharing.


Best Regards

Noor Hasan

GIS Analyst.


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Srinivasan Ramani

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Dec 8, 2017, 6:51:16 AM12/8/17
to Raphael Susewind, data...@googlegroups.com, Thejesh GN
Dear Thej,

Adding to Raphael's email.. for the article, we picked those polling booths with urbanity values (null for rural booths), cross tabbed with polling booth data for 2014 elections and found out urban-rural classification wise vote share information for BJP and Congress... Rest of the work was comparing this with 2015 civic polls and the only opinion poll currently that gives a rural-urban-region wise breakup. 

Best
Srini

Arun Ganesh

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Dec 8, 2017, 7:38:34 AM12/8/17
to datameet, Raphael Susewind, Thejesh GN
Such an amazing dataset of polling booths, thank you for putting this together Raphael.

Have uploaded this to Mapbox if anyone wants to try to visualize it: https://www.mapbox.com/studio/tilesets/planemad.a5gilqlq/


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