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The estimation of sensible heat flux, H, using large aperture scintillometer (LAS) under varying surface heterogeneity conditions was investigated. Surface roughness features characterized by variable topography and vegetation height were represented using data derived from the highly accurate light detection and range (lidar) techniques as well as from traditional vegetation survey and topographic map methods. The study was conducted at the Cibola National Wildlife Refuge, Southern California, over a riparian zone covered with natural vegetation dominated by tamarisk trees interspersed with bare soil in a region characterized by arid to semiarid climatic conditions. Estimates of H were obtained using different representations of surface roughness features derived from both traditional and lidar methods to estimate LAS beam height [z(u)] at each increment u along its path, vegetation height (h(c)), displacement height (d), and roughness length (z(0)) combined with the LAS weighing function, W(u), along the path. The effect of the LAS 3D footprint was examined to account for the contribution from the individual patches in the upwind direction, hence on the estimates of H. The results showed better agreement between LAS and Bowen ratio sensible heat fluxes when lidar-derived surface roughness was used, especially when considering the LAS 3D footprint effects. It was also found that, under certain conditions, the LAS path weighted h(c) and d obtained using the LAS weighting function W(u) is a good approximation of the 3D weighted footprint values.