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 the 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. In this paper we survey recent research in mobile database caching strategies based on temporal, spatial and temporal-spatial characteristics. The conventional method of cache replacement is Least Recently Used (LRU) which takes into account only temporal characteristics of data items. The Furthest Away Replacement (FAR) is spatial in nature and the selection of victim for replacement is based on the locations which are not in the moving direction and furthest from the user will not be visited in near future. 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...