Have you seen GHSL? https://ghsl.jrc.ec.europa.eu/data.php They have a robust methodology for UA identification across the globe inc India. Their India UA data is not perfect but beats most other public datasets.
On Wednesday, 14 October 2020 at 19:47:27 UTC+5:30 Aditya Medury wrote: > Hi, > > I am trying make sense of how to translate the definitions of urban > agglomerations/million-plus cities in the 2011 census. Census defines urban > agglomeration as follows: > > *An urban agglomeration is a continuous urban spread constituting a town > and its adjoining outgrowths (OGs), or two or more physically contiguous > towns together with or without outgrowths of such towns. An Urban > Agglomeration must consist of at least a statutory town and its total > population (i.e. all the constituents put together) should not be less than > 20,000 as per the 2001 Census. In varying local conditions, there were > similar other combinations which have been treated as urban agglomerations > satisfying the basic condition of contiguity. Examples: Greater Mumbai UA, > Delhi UA, etc.* > *Source: * > https://censusindia.gov.in/2011-prov-results/paper2/data_files/India2/1.%20Data%20Highlight.pdf > > Since they can be a combination of multiple towns/cities, outgrowths, > municipal corporations, identifying their sociodemographic and built > environment characteristics from other databases becomes a little > challenging. For instance, the breakdown of all UAs with more than 1 lakh > population is specified here: > > https://censusindia.gov.in/2011-prov-results/paper2/data_files/India2/Table_4_PR_UAs_1Lakh_and_Above_Appendix.pdf > > I can think of a few different ways in which I may be able to approximate > some boundaries associated with these UAs: > > - I could use the ADM3 shapefiles of sub-districts ( > https://earthworks.stanford.edu/catalog/stanford-rj389fh4679) and > picking locations based on visual inspections/overlap of city points. I > understand that municipal boundaries may or may not always match the > administrative divisions (not very clear on this) > - I could also base it off of pincode layers ( > https://github.com/justinelliotmeyers/INDIA_PINCODES) which might be > more fine-grained if I need additional flexibility in selecting small > regions at the periphery. > - I could go the population grid route and do some clustering to find > regions that might approximate the UA populations provided in the 2011 > census for some of the bigger cities. But this would get really crude with > no unique boundary solutions. > > Wondering if people have any thoughts on this. > > Thanks! > > Aditya > -- Datameet is a community of Data Science enthusiasts in India. Know more about us by visiting http://datameet.org --- You received this message because you are subscribed to the Google Groups "datameet" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To view this discussion on the web visit https://groups.google.com/d/msgid/datameet/31c8b0d0-0bbf-4f5b-ba12-5e934e7b7d84n%40googlegroups.com.
