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Remote sensing observations of the cryosphere, like any other target of interest, require ground-based measurements for both calibration and validation, as inversion algorithms are usually underdetermined and uncertainties in the retrieval are needed for application. Field-based observations are performed in selected representative locations, and typically involve both direct in situ measurements of the physical properties of interest, as well as ground-based remote sensing techniques.

New state-of-the-art modern techniques for measuring physical properties rapidly and at high spatial resolution have recently given us a new view of spatiotemporal variability. These are important, as large variability at scales below the typical footprint of spaceborne sensors often exists. Simulating remote sensing measurements using ground-based sensors provides the ability to perform both in situ and remote sensing measurements at the same scale, providing insight into the dominant physical processes that must be accounted for in inversion models and retrieval schemes.

While direct in situ measurements provide the most accurate information about the properties of interest, they are time-consuming and expensive and are, therefore, only practical at relatively few locations, and often with low temporal resolution. Spatial sampling strategies, designed specifically for the remote sensing observation of interest, can reduce uncertainties in comparisons between ground-based and airborne/spaceborne estimates. Intensive remote sensing calibration and validation campaigns, often associated with an upcoming or recent satellite launch, provide unique opportunities for detailed characterization at a wide range of scales, and these are typically large international collaborative efforts.

This chapter reviews standard in situmanual field measurements for snow and ice properties, as well as newer high-resolution techniques and instruments used to simulate airborne and spaceborne remote sensing observations. Sampling strategies and example applications from recent international calibration and validation experiments are given. Field measurements are a crucial component of remote sensing of the cryosphere, as they provide both the necessary direct observations of the variables of interest, as well as measurements that simulate the particular remote sensing technique at scales that can be characterized accurately. Ground-based observations provide the information needed to:

  1. improve and develop new retrieval algorithms;
  2. calibrate algorithms; and
  3. validate results to provide accurate uncertainty assessments.

Copyright Statement

This document was originally published in Remote Sensing of the Cryosphere by Wiley. Copyright restrictions may apply. doi: 10.1002/9781118368909.ch14