Population census data is one of the most important variant for disaster risk assessment and also has numerous applications in different geospatial domain. Significant difficulties are encountered in the use of choropleth map using the census data especially for spatial analysis with the modifiable areal unit problem. Therefore it has been necessary for researchers to use ancillary information from census area and their boundaries in order to distribute population count into regular grid units for dasymetric mapping. This paper reviews the current population distribution models and presents an alternative population weighted centroid distribution algorithm. The gridded representation of population census data was done using urban land cover data as ancillary information. A comparative evaluation of the results at different grid resolutions in terms of accuracy, precision, scale and ease of use is presented. This work demonstrates several application of such gridded population data especially in disaster risk assessment where unique spatial overlay analysis is required and cannot be addressed using irregular area-based census data.