Aimed at the conflict between load balancing for user access services and sequentially reading for disk storage services, a user-driving storage and organization strategy for spatial data is proposed, which takes a comprehensive consideration of the strategy of data placement and load balance (CSDL). This scheme mines the users' behaviors and computes the correlations among all data so as to distribute and store the popular data into different storage nodes to realize load balancing. Then, the concurrency degree is also computed among the data stored in the same storage node and which can be used to store some data in contiguous disk space to realize continuous reading. The CSDL method proposed in this paper tries to organize spatial data storage from two aspects of load balancing and lower disk efficiency at the same time, so as to improve the service efficiency of GIS. Experimental results show that our scheme improves the performance of average request response time by 45.2%-245.3% and also improves the performance of load balance degree by 0.5%-440.9%, which can meet the requirements of large scale distributed environments.