Demographic data is usually represented by choropleth map, where the statistical data is aggregated to areal units. This type of representation has several limitations associated with spatial analysis and distribution. A common alternative to display statistical data in meaningful spatial zones is the dasymetric mapping technique. Though dasymetric mapping has existed for many decades, the open source GIS tools to explore dasymetric mapping methods are scarce. In this paper, a Geographical Information System (GIS) open source application was developed in QGIS software that applies the dasymetric mapping method to the Portuguese Guimarães municipality 2011 Census block-group populations and using Corine Land Cover Data Set to redistribute the block-group populations into a 25-m grid. The application employs a simple centroid sampling approach (supported by the Addresses theme obtained in the INSPIRE ATOM Download Service from the Portuguese National Statistics Institute, INE) to acquire information on the population densities for different land use classes, and it uses the ratio of class densities to redistribute population to sub-source zone areas. Several tools available from QGIS and Geographic Resources Analysis Support System (GRASS) GIS were employed to generate a resident population dasymetric map. The application development was supported by Python 2.7 language and PyQt4 API. The plugin developed for the QGIS is an innovative tool that allows the population mapping to any case study that has statistical data and the Corine Land Cover layer. To test the results obtained from the tool, census block populations were compared with the dasymetric map. The results indicate that dasymetric mapping produce more accurate population distributions than the choropleth approach.