Advances in sensing and communication technology make sensor networks a convenient and cost effective tool for collecting data in hard to reach and hazardous areas Increasingly, sensor networks are used to monitor the environment and enable swift and accurate intervention. Environmental monitoring is characterized by the facts that the area under surveillance tends to be large whereas incidents tend to be both sparse in time and localized. In this research, we investigate means by which we get good coverage, so that we do not miss events of interest, and low cost, so that we do not deploy too many sensors in areas where nothing is happening. We propose to use a combination of static and mobile sensors. Initially, the nodes are randomly deployed. While the static sensors remain in place until they die out, mobile sensor nodes are constantly evaluating their position, scouting for "interesting" events. They move to areas where they can contribute useful and relevant information. As the dynamics of the events move, so do the mobile nodes. In this paper, we present the decision making process mobile nodes go through in order to adaptively adjust coverage. This process is simulated and the results presented.