It is often said that the real estate market is divided geographically in such a manner that the value of attributes of real estate properties is different for each area. This study proposes a new approach to the investigation of the geographical segmentation of the real estate market. We develop a price model with many regional explanatory variables, and implement the generalized fused lasso - a regression method for promoting sparsity - to extract the areas where the valuation standard is the same. The proposed method is applied to rental data of apartments in the Tokyo metropolitan area, and we find that the geographical segmentation displays hierarchal patterns. Specifically, we observe that the market is divided by wards, railway lines and stations, and neighbourhoods.