Unique in its focus, this book outlines optimal sensor placement strategies for parameter identification in dynamic distributed systems modeled by partial differential equations. The author focuses on practical applications, particularly in environmental processes, as well as on the development of new techniques and algorithms, and methods that have been successful in the related fields of optimum experimental design. Optimal Measurement Methods for Distributed Parameter System Identification places emphasis on determining the best way of guiding moving and scanning sensors, and of making the solutions independent of the parameters being identified. The text includes extensive numerical results that show the efficiency of the proposed algorithms. Case studies involving the design of air quality-monitoring networks and network design for groundwater pollution problems are also presented to show the strength of the proposed approach in studying practical problems. Features, Analyzes existing approaches and proposes a wide range of original solutions to sensor location problems, Provides engineers and researchers with a sound understanding of sensor location techniques, Offers a step-by-step guide to the theory, the practical design, and the methods of sensor location, backed by numerous case studies, Includes detailed numerical examples that demonstrate the effectiveness of the approach Book jacket.