Report of the subpanel on resampling functions

The state of the art and anticipated requirements for resampling in applications of remote sensing are examined. It is noted that the wide range of potential applications and expanded needs for resampling versatility in new imaging sensors leads to a concern for creating standardized test data sets and ground training sites. Several research areas are defined including the development of (1) a theory for defining an input psf of an instrument such that upon resampling of the processed data into the desired output grid the radiometric and geometric properties are a best estimate of the true upwelling radiances; (2) algorithms for estimating missing data or for ignoring missing data; (3) optimal resampling functions; (4) standard data sets; and (5) merit functions for assessing resampling techniques.