Calibration and Validation of Earth-Observing Sensors Using Deployable Surface-Based Sensor Networks

Abstract

Satellite-based instruments are now routinely used to map the surface of the globe or monitor weather conditions. However, these orbital measurements of ground-based quantities are heavily influenced by external factors, such as air moisture content or surface emissivity. Detailed atmospheric models are created to compensate for these factors, but the satellite system must still be tested over a wide variety of surface conditions to validate the instrumentation and correction model. Validation and correction are particularly important for arctic environments, as the unique surface properties of packed snow and ice are poorly modeled by any other terrain type. Currently, this process is human intensive, requiring the coordinated collection of surface measurements over a number of years. A decentralized, autonomous sensor network is proposed which allows the collection of ground-based environmental measurements at a location and resolution that is optimal for the specific on-orbit sensor under investigation. A prototype sensor network has been constructed and fielded on a glacier in Alaska, illustrating the ability of such systems to properly collect and log sensor measurements, even in harsh arctic environments.