Asher, Sam, Tobias Lunt, Ryu Matsuura, and Paul Novosad. "Development research at high geographic resolution: an analysis of night-lights, firms, and poverty in India using the shrug open data platform." The World Bank Economic Review 35, no. 4 (2021): 845-871.
@article{almn2021,
title={Development research at high geographic resolution: an analysis of night-lights, firms, and poverty in India using the shrug open data platform},
author={Asher, Sam and Lunt, Tobias and Matsuura, Ryu and Novosad, Paul},
journal={The World Bank Economic Review},
volume={35},
number={4},
year={2021},
publisher={Oxford University Press}
}
About
A set of open-source maps for towns/villages, subdistricts, districts, state, and shrid boundaries. All shapes except shrids represent 2011 Population Census locations. Note that shapefile versions have truncated variable names.
Geographic Coverage
National
Aggregations
Shrid, Village/Town, Subdistrict, District
Producer
Development Data Lab
Source URL
Notes
The key novelty of our open-source geospatial data is that our geometries span almost the entire set of 600,000 villages and 8000 towns in the 2011 Population Census, and include 2011 Census identifiers. While there are a few other similar datasets out there, they are either proprietary or incomplete.
These maps are stitched together from multiple open-source maps, all of which were incomplete in and of themselves. Sources include the SEDAC data center at Columbia (which hosts 1991 and 2001 maps, which we carried forward using our SHRUG town and village keys), Bharatmaps, Datameet, and the Administrative Atlas of India.
The maps have a number of limitations, which are common to virtually all spatial data in India that we have seen. First, village and town boundaries are best understood to represent true boundaries with 0–1 km of measurement error. This seems to be the state of play with Indian village maps — every village map (open or proprietary) that we have come across has had at least this level of inaccuracy. As such, we suggest caution in using these boundaries to identify differences along narrow spatial dimensions, like neighboring village boundaries.
We linked these sources through common location codes, georeferenced when necessary, and geometrically harmonized them to the best of our ability. We are aiming to produce the best possible open-access map of Indian administrative units.
Geospatial data is available in .shp (ESRI shapefile) and .gpkg (GeoPackage) formats. For more details about the data, refer to this post
For more information about SHRUG spatial statistics, please refer to this page.