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.