Landsat, with its wide swath and high resolution, fills an important mesoscale gap between atmospheric variations seen on a few kilometer scale by local surface instrumenta-tion, and the global view of coarser resolution satellites such as MODIS. In this important scale range, Landsat reveals radiative effects on the few hundred meter scale of common photon mean-free-paths, typical of scattering in clouds at conservative (visible) wavelengths, and even shorter mean-free-paths of absorptive (near infrared) wavelengths. Landsat also reveals shadowing effects caused by both cloud and vegetation, that impact both cloudy and clear-sky radiances. As a result, Landsat has been useful in development of new cloud re-trieval methods, and new aerosol and surface retrievals, that account for photon diffusion and shadowing effects. This paper discusses two new cloud retrieval methods, the nonlocal independent pixel approximation (NIPA) and the normalized difference nadir radiance method (NDNR). We illustrate the improvements in cloud property retrieval enabled by the new low gain settings of Landsat 7, and difficulties found at high gains. Then we review the recently developed 'path radiance' method of aerosol retrieval and clear sky correction, using data from the Department of Energy ARM site in Oklahoma. Nearby clouds change the solar radiation incident on the surface and atmosphere, due to indirect illumination from cloud sides. As a result, if clouds are nearby, this extra side-illumination causes clear pixels to appear brighter, which can be mistaken for extra aerosol or higher surface albedo. Thus cloud properties must be known in order to derive accurate aerosol and surface properties. A 3-dimensional Monte Carlo radiative transfer simulation illustrates this point, and sug-gests a method to subtract the cloud effect from aerosol and surface retrievals. The main conclusion is that cloud, aerosol, and surface retrievals are linked, and must be treated as a combined system. Landsat provides the range of scales necessary to observe the 3-dimensional cloud radiative effects that influence joint surface-atmospheric retrievals.