Hello sir great thinking. I suggest to do it with LULC data. We have color coded raster data of area (Red for urbanised or populated area).
we can extract polygon from LULC data for Boundaries. regards On Wed, 14 Oct, 2020, 7:47 pm Aditya Medury, <amed...@gmail.com> 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 datameet+unsubscr...@googlegroups.com. > To view this discussion on the web visit > https://groups.google.com/d/msgid/datameet/da0f619a-9d2a-4161-b3e8-d04ecbd334fbn%40googlegroups.com > <https://groups.google.com/d/msgid/datameet/da0f619a-9d2a-4161-b3e8-d04ecbd334fbn%40googlegroups.com?utm_medium=email&utm_source=footer> > . > -- 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 datameet+unsubscr...@googlegroups.com. To view this discussion on the web visit https://groups.google.com/d/msgid/datameet/CA%2B4SsQD76Yz0SdmXw5ZFVEhne-5nGZK6NnLAAzR_z12HMRUZiA%40mail.gmail.com.
