Population mapping, in general, has two purposes: firstly, to cartographically portray the extent and density of population across an area of interest, and secondly, to derive a quantitative estimation of population density for use in subsequent spatial analytical modeling tasks. A cartographic portrayal of population traditionally has the form of a choropleth map. This kind of mapping is very simple, but despite its simplicity, choropleths maps have limited utility for detailed spatial analysis of population data, especially where human populations are concentrated in relatively small numbers of villages, towns and cities. One way to avoid this limitation is to transform the administrative units into smaller and more relevant map units through the process known as dasymetric mapping. The dasymetric technique maps a quantitative variable according to boundaries derived from the character of the data distribution. It is a form of an areal interpolation that uses ancillary data to transform population data from one set of spatial units to another. This paper demonstrates the use of satellite derived ancillary land cover data to map population densities using dasymetric mapping. The three dasymetric methods presented, revealed the interregional variation in population density more realistically, in particular, among urban and rural areas. The methods were tested for Mazovia Region. The binary method, the simplest, is easy to implement in GIS and gives a better view of population distribution over a given area than conventional choropleth maps (fig. 1). The only drawback is the delimitation of uninhabited areas. The areal weighting aggregation method uses land cover data as limiting variable and a typology of communes as a correlation variable. We a priori assign the percentage of people attributed to each land cover type and groups of communes. Subjectivity of these decisions is considered the drawback of the method. The results are detailed enough and portray population density very realistic (fig.2). The areal weighting correlation method presents a new way of calculating weighting coefficients. This is based on the method proposed by Gallego and Peedell (2001), but is adapted to Polish conditions by grouping land cover classes, stratifying communes and computing coefficients (tab.1). This dasymetric mapping method is based on the assumption that the ratio between the population density of two land cover categories is the same for any given commune. This method, on contrary to previous ones, does not preserve pycnophylactic property of statistical data, so it is necessary to evaluate the results. Relative errors were computed for evaluating the modified areal weighting method. The analyse of a comparison between attributed population and population data known from statistical measurements indicate that the population value attributed to most of the communes is approximately in agrement with the statistical data (fig.4). The coefficients seem to be too high for a few urban communes and too low for some rural areas. The areal weighting correlation method provides realistic view of population distribution in the Mazovia Region (fig 3). The dasymetric population map was visualized according to choropleth map rules in such a way that it focuses on the relationship between settlement and the natural environment. The information generated from a dasymetric population density map could provide useful assistance to district administrations, especially those responsible for regional or city development and land management.