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
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