A circumnavigational photogrammetric sampling of the sands on the island of Hawai’I was done using the photogrammetry program pyDGS. The island of Hawai’i provides a perfect landscape to test the viability of pyDGS since it is a small island whose beaches are accessible, and which are subject to predictable weather and climate effects. A total of 18 beaches were chosen, taking photographs of transects at each beach. After calibrating standards and comparing them to the sands on Hawaii, this study found that pyDGS is a viable alternative to conventional grain-size analysis techniques, when correctly tuned and adjusted. Moreover, key findings conclude that weather and climate are driving factors in sand distribution, grain size, beach slope, sorting, skewness, and kurtosis on the island, with each statistical moment offering insight into weather and energy effects. Compositional and mineralogical data showed differences in sands throughout several beaches accounting for the large diversity of color ranging from black or green sand (volcanic) to tan and white sands (carbonate) to some mixture of the two. These compositional differences also affect grain size distribution, and several survey locations show a more bimodal distribution. To further test pyDGS, four photographs from Mars taken by the Curiosity Rover were applied and compared to previously published data.