Data on religion and politics in India
This table contains GIS coordinates and other spatial characteristics of polling booths in Madhya Pradesh
|ac_id_09||ID code of the assembly segment assigned by the Election Commission (identical with all other post-delimitation codes, hence the _09)|
|booth_id_14||ID code of the polling booth assigned by the Election Commission for 2014 booths (together with ac_id_09, this should suffice for matching with other tables)|
|booth_name_14||Name of the polling booth assigned by the Election Commission for 2014 booths|
|district_name_14||Name of the district into which this polling booth is supposed to fall in 2014 (could be used for cleaning the data)|
|modis||Urban area or not? Derived from MODIS polygon (see below)|
|modis_rank||How urban? MODIS Scalerank (see below)|
The 2014 data was originally scraped using the Firefox MozRepl plugin in conjunction with download.pl and the custom proxy server at proxy.pl on May 5, 2014 from "http://www.eci-polldaymonitoring.nic.in/psleci. The data used here is NOT cleaned up, and quality varies from district to district, so you need to be careful. The ID codes are the same used for the 2014 Lok Sabha elections. This dataset is identical with the data included in my (more comprehensive) GIS Shapefiles.
All three sets of point data were then dumped into CSVs, transformed into ESRI shapefiles using
ogr2ogr booths-locality.shp booths-locality.vrt and matched manually against the MODIS polygon from Naturalearth using QGIS. The result was then exported back into booths-locality-modis.sqlite.
The final table was put together using
cat transform.sql | sqlite3.
While the database in its entirety is subject to an ODC Open Database License, as explained in the main README and LICENSE files, the content of this specific table is factual data, and as such only subject to a simple ODC Database Contents License (at the time of scraping, the respective websites did not display any copyright information). Code used for crawling and compilation is subject to a CC-BY-NC-SA 4.0 license. If you use the modis and modis_rank variables, the original authors ask that you additionally attribute then:
Schneider, A., M. A. Friedl, D. K. McIver, and C. E. Woodcock (2003) Mapping urban areas by fusing multiple sources of coarse resolution remotely sensed data. Photogrammetric Engineering and Remote Sensing, volume 69, pages 1377-1386.