This study determined winter and summer shading coefficients for six commonly used landscape trees in Tucson using a photographic dot-matrix method. Tree types were developed from this data reflecting canopy density, shape, and foliage periods, then applied to SPS and MICROPAS computer programs to model effects of tree shade on annual energy loads for three residential construction types. Statistical analysis showed pruning to have a significant effect for 5 of the 6 species tested. Significant differences were also found among species and within species due to seasonal effects in foliage density. Shading scenarios manipulated the number and location of tree types were modeled. Greatest net annual savings were from 3 African sumac trees located on the west side of a masonry house typical of the 1950s (121). Shade from tree species found to have significantly different shading coefficients (10%) did not substantially increase energy savings ($5-12).