We discuss a new technique to generate high-resolution digital terrain models (DTMs) and to quantitatively derive and map slope-corrected thermophysical properties such as albedo, thermal inertia, and surface temperatures. This investigation is a continuation of work started by Kirk et al. (2005), who empirically deconvolved Thermal Emission Imaging System (THEMIS) visible and thermal infrared data of this area, isolating topographic information that produced an accurate DTM. Surface temperatures change as a function of many variables such as slope, albedo, thermal inertia, time, season, and atmospheric opacity. We constrain each of these variables to construct a DTM and maps of slope-corrected albedo, slope- and albedo-corrected thermal inertia, and surface temperatures across the scene for any time of day or year and at any atmospheric opacity. DTMs greatly facilitate analyses of the Martian surface, and the MOLA global data set is not finely scaled enough (128 pixels per degree, ???0.5 km per pixel near the equator) to be combined with newer data sets (e.g., High Resolution Imaging Science Experiment, Context Camera, and Compact Reconnaissance Imaging Spectrometer for Mars at ???0.25, ???6, and ???20 m per pixel, respectively), so new techniques to derive high-resolution DTMs are always being explored. This paper discusses our technique of combining a set of THEMIS visible and thermal infrared observations such that albedo and thermal inertia variations within the scene are eliminated and only topographic variations remain. This enables us to produce a high-resolution DTM via photoclinometry techniques that are largely free of albedo-induced errors. With this DTM, THEMIS observations, and a subsurface thermal diffusion model, we generate slope-corrected maps of albedo, thermal inertia, and surface temperatures. In addition to greater accuracy, these products allow thermophysical properties to be directly compared with topography.