In typical location fingerprinting systems a tracked terminal reports sampled Received Signal Strength (RSS) values to a location server, which estimates its position based on a database of pre-recorded RSS fingerprints. So far, poll-based and periodic RSS reporting has been proposed. However, for supporting proactive Location-based Services (LBSs), triggered by pre-defined spatial events, the periodic protocol is inefficient. Hence, this paper introduces zone-based RSS reporting: the location server translates geographical zones defined by the LBS into RSS-based representations, which are dynamically configured with the terminal. The terminal, in turn, reports its measurements only when they match with the configured RSS patterns. As a result, the number of messages exchanged between terminal and server is strongly reduced, saving battery power, bandwidth and also monetary costs spent for mobile bearer services. The paper explores several methods for realizing zone-based RSS reporting and evaluates them simulatively and analytically. An adaption of classical Bayes estimation turns out to be the best suited method.