There are generally five accepted elements of image interpretation: color, texture, pattern, shape, size, and location. From my readings, it appears that these principals were first documented the 1940s. Makes perfect sense as World War II and the subsequent Cold War resulted in the rapid development of military remote sensing capabilities. Coupled with this increase in capabilities was the need to thoroughly understand what principals should guide a photointerpreter. If remote sensing is considered to be both an art and a science, the trade craft employed by the military photointerpreters during these early days was certainly an art form.
I would like to put forth the argument that the advent of digital image processing techniques caused some sectors of the remote sensing community to focus too much on science of remote sensing, and less on the art form. In short, the trade craft was lost. No where was this more evident than the widespread use of pixel-based classifiers, such as the unsupervised and supervised routines that were commonly employed to extract land cover information from digital imagery.
When one considers the elements of image interpretation, it is clear that techniques that rely solely on the spectral (color) values associated with individual pixels violate the very principals of image interpretation. Perhaps much of this was due to the limitations of the technology at the time. After all, it was not until Definiens introduced their object-oriented software a decade ago that the shift towards object-based image analysis (OBIA) techniques that better replicated the human cognitive process, began. Nevertheless, when examining the literature over the past decades in which pixel-based classifiers where used, rarely do I see a disclaimer along the lines of "these techniques violate the very principals of image interpretation, but they are the best tools we have."
OBIA requires one to understand the elements of image interpretation. Perhaps the "art" is back in remote sensing.