Open-Access Geospatial Data for India
Development Data Lab is releasing a new set of open boundaries for all of India.
The key novelty here 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. We are aiming to produce the best possible open-access map of Indian administrative units.
Geospatial data is increasingly becoming a critical component of policy-making and resource planning in India, with several large-scale government programs relying on accurate location data for making key decisions on resource allocation. Remarkably, there is no official open dataset describing geometries for towns and villages. (The Survey of India recently released a set of village shapefiles — a step in the right direction — but as far as we can tell, they are incomplete and do not have Census identifiers. Nothing would please us more than if the government would release a dataset that puts ours to shame!)
We put these maps together as part of SHRUG 2.0, a major overhaul of our socioeconomic data platform for India. We’re still a month or two away from releasing SHRUG 2, so we decided to post the shapefiles straight away. These are keyed to PC11 Census identifiers; future versions will be released that are keyed to constituencies and shrids. We’ve included state, district, and subdistrict maps in the package; these are more widely available, but it may be useful to have versions of these that are well-aligned with our village/town maps. All boundaries are referenced to EPSG:4326 and are available in both shapefile and geopackage format.
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. We linked these sources through common location codes, georeferenced when necessary, and geometrically harmonized them to the best of our ability.
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.
Second, a number of locations in India appear to be represented in official data only as points, not as polygons — for instance, in forest areas and in the northeast. Where we only had point geometries, we generated boundaries using Thiessen polygons, constraining the size of each unit to its spatial area according to the village directory. We validated boundaries against several external sources including satellite imagery as well as OpenStreetMap data. However, India is huge and of course we could not validate every village; some errors are likely to remain.
This is an early release, so it is currently undocumented; more details on data construction will be available when SHRUG 2.0 is released in 1–2 months. If there are other better open source maps out there or if you have better maps that you can share, please get in touch with us at info@devdatalab.org. We think the DDL India maps are currently the best available open geometries, but we plan to keep on improving them as new and better open data sources arise.
For more information on open data in India, follow us on Twitter @devdatalab, visit our web site www.devdatalab.org, and check our our India Policy Forum paper “Big, Open Data for Development: A Vision for India.” SHRUG 2 is coming soon!
