Poverty Mapping: Access to Health Care

Formulated the concept of using GIS tool to analyse the distance of healthcare units with actual settlements using customized settlement detection algorithm, helping better evidence based policy decision.


Socio-economic data sets are available at varying levels of granularity but they cannot be easily visualized on a map or correlated with other data sets for deeper analysis. Moreover, population density is also not known for arbitrary regions.


Developed an easy-to-use online tool to present survey data (MICS, LFS) and GIS data (boundaries and imagery). Created population density estimation layer using automatic (or manual) settlement detection and computed access to education and healthcare using location of facilities and road network. Composite indices for vulnerability, urbanization, etc. were also developed.