The continued escalation of manageable, wireless enabled devices with immense storage capacity and powerful CPUs are making the wide spread use of mobile databases a reality. Mobile devices are increasingly used for database driven applications such as product inventory tracking, customer relationship management (CRM), sales order entry etc. In some of these applications Location Dependences Data (LDD) are required. The applications which use LDD are called Location Dependent Information Services (LDIS). These applications have changed the way mobile applications access and manage data. Instead of storing data in a central database, data is being moved closer to applications to increase effectiveness and independence. This trend leads to many interesting problems in mobile database research and cache replacement policies. In mobile database system caching is an effective way to improve the performance, query delay and save bandwidth since new query can be partially executed locally. However, variable data sizes, data updates and frequent client disconnections make cache management a challenge. The conventional method of cache replacement is Least Recently Used (LRU) which takes into account only temporal characteristics of data items. This paper takes into account the parameters like minimum access probability, maximum distance and scope invalidation for cache replacement. These parameters are used and an enhanced version of Prioritized Predicted Region based Cache Replacement Policy (PPRRP) is simulated for the temporal and spatial characteristics. The implementation of both the policies has been done using java. The simulations of both policies reveal the outperformance of PPRRP over LRU.