Quantitative integration of remote sensing data requires accurate co-location of pixels between data from different sensors. A technique has been developed, based on a simple spherical Earth model, to map ground resolution cells pertaining to pixel/grid points in a coarse-resolution sensor into an image acquired by a fine-resolution sensor. Pixels from the fine-resolution sensor, located within the coarse-resolution cells, can then be identified and their radiometric information can be compared to or combined with the coarse-resolution observations to improve the utility of both data sets. The technique is presented along with examples to demonstrate potential applications such as: (1) correlation between sensors radiometric parameters, (2) validation of products from a coarseresolution sensor using sub-pixel information from a coincident fine-resolution data set, and (3) contribution of ground target heterogeneity within a single pixel to observed radiometric parameters. Successful application of the technique, however, requires accurate geo-location of both data sets at the pixel level.