Increasing urbanization and the rapid development of cities has resulted in the conversion of several green spaces into built up structures and excessive destruction of the natural ecosystem. Green space with its ecological, social and economic functions has an important role in improving the quality of life in cities and in achieving to a sustainable city. The amount of urban green space is one of the most important criteria in the welfare of citizens. Urban green spaces offer a numerous of direct and indirect consumptive values, such as recreation, air purification, noise reduction, and non-consumptive value (the intrinsic value) that are not traded in the formal and informal markets. Therefore, it is often felt that the socioeconomic value of ecological factors is not sufficiently reflected in policy priorities. If the economic value of green spaces can be demonstrated through a premium on house price, this strengthens the position of existing green areas in the policy decision process. This study aims to quantify a set of landscape metrics to estimate and describe green spaces in Isfahan city and to estimate the degree to which real estate values vary with ecosystem functions of green spaces. In this study we seek to determine whether individuals in their decision to purchase a home are taking into account attributes of green spaces function as approximated by indices of landscape pattern. This study focuses on two municipality zones (including zone.6 and zone.8 with the highest and lowest per capita green spaces) in Isfahan city. In this study the Hedonic pricing method was used to estimate the contribution of green spaces pattern to the price of a house. This value can then be used to infer an individual’s marginal willingness to pay for the ecological benefits of green spaces. The ArcGIS 10 and FRAGSTATS 3.3 software were used for calculation of landscape metrics including NP (Number of Patches), PLAND (Percentage of Landscape), and ED (Edge Density). The influence of the view to the green spaces and distance from parks, and noise pollution factors were also estimated on the price per square of residential units in the study area. The results revealed that in the hedonic models, some of the landscape variables such as patch size and edge density were statistically significant. Variables associated with patch size that are positive in sign indicate a preference for larger green spaces. Edge density variables that are positive indicate a preference for rougher, more natural patches. In zone.6 by increasing each additional 10 ha in the patch area of green spaces the price per square of residential units increases by 1800 thousand Rials, and in zone.8 by increasing each additional ha in area of green spaces the price per square of residential units increases by 850 thousand Rials. The findings of this study could be applicable in the designing and maintaining of urban green spaces in Isfahan city. Keywords : Urban green spaces, Landscape metrics, Hedonic pricing method, Isfahan.