A raster-based method for determining complex view factor patterns is presented (HURES model). The model uses Johnson and Watson's view factor analysis method for fisheye lens photographs. The entire sphere is divided into 13 different view factors: open sky; sunny and shaded building walls, vegetation (trees) and ground surfaces above and below 1.2 m from the ground surface. The HURES model gave reasonable view factor results in tests at two urban study sites on summer days: downtown Nanaimo, B.C., Canada and Changwon, Republic of Korea. HURES gave better estimates of open sky view factors determined from fisheye lens photographs than did ENVI-met 3.1 and RayMan Pro. However, all three models underestimated sky view factor. For view factor analysis in outdoor urban areas, the 10° interval of rotation angle at 100 m distance of annuli will be suitable settings for three-dimensional computer simulations. The HURES model can be used for the rapid determination of complex view factor patterns which facilitates the analysis of their effects. Examples of how differing view factor patterns can affect human thermal sensation indices are given. The greater proportion of sunny view factors increased the computed predicted mean vote (PMV) by 1.3 on the sunny side of the street compared with the shady side during mid-morning in downtown Nanaimo. In another example, effects of differing amounts of open sky, sunny ground, sunny buildings and vegetation combined to produce only slight differences in PMV and two other human thermal sensation indices, PET and UTCI.