Household Income and Expenditure Survey (HEIS) is one of the most important surveys of the Statistical Center of Iran, the
main parameters of which are spatially correlated. When there is a spatial correlation between the units of population, the
classical way of selecting independent sampling units is challenging due to the lack of basic condition for the independence.
Using spatial sampling is a solution to encounter this problem. Implementation of spatial sampling has received less attention
in official statistics due to the lack of access to a suitable framework. In this paper we review a design-based model assisted
method for optimal spatial stratification of the target population. At present, spatial information of population units are
not available in the framework of HEIS, but access to spatial information of some sample units has been achieved by the
Statistical Center of Iran for this study. The production of spatial data is one of the main components in the modernization of
the statistical system which is considered by Statistical Center of Iran. In this paper, the sampling frame is simulated based
on the HEIS data and then application of optimal spatial stratification based on a generalized distance is performed. The
results demonstrate an increase in the efficiency of the mentioned sampling method compared to simple random sampling at
the level of geographical areas. Also, simulation of grids with different sizes and correlations reflects the better performance
of this method compared to the current method of HEIS.