Soil Moisture Smart Sensor Web Concept Using Data Assimilation and Optimal Control

Abstract

We present a new concept for a smart sensor web technology for measurements of soil moisture that include spaceborne and in-situ assets. The objective of the technology is to enable a guided/adaptive sampling strategy for the in-situ sensor network to meet the measurement validation objectives of the spaceborne sensors with respect to resolution and accuracy. The sensor nodes are guided to perform as a macro-instrument measuring processes at the scale of the satellite footprint, hence meeting the requirements for the difficult problem of validation of satellite measurements. The science measurement considered is the surface-to-depth profiles of soil moisture estimated from satellite radars and radiometers, with calibration/validation using in-situ sensors. Satellites allow global mapping but with coarse footprints. The total variability in soil-moisture fields comes from variability in processes on various scales. Installing an in-situ network to sample the field for all ranges of variability is impractical. However, a sparser but smarter network can provide the validation estimates by operating in a guided fashion with guidance from its own sparse measurements. The feedback and control take place in the context of a data assimilation system. The design and demonstration of the smart sensor web including the control architecture, assimilation framework, and actuation hardware are the building blocks of this concept and will be introduced in the presentation. This technology, once developed, enables a guided/adaptive sampling strategy for generating optimal, statistically unbiased, calibration/validation data for space-based measurements.