Abstract
Terracettes, a step-like microtopographic feature primarily caused by livestock hoof action and grazing on hillslopes, are found throughout semi-arid rangelands of the United States. They have been shown to alter soil moisture, sediment transport, infiltration rates, and coincident vegetation patterns. The spatial extent of terracettes is currently unknown and therefore their landscape-scale hydrologic influence is absent in modeling and land management decision making. When viewed in very high-resolution satellite imagery, terracettes appear as repetitious parallel lines within a specific frequency range. Here, we use frequency-based image analysis via the 2D Discrete Fourier Transform to detect terracettes based on their distinct patterning and orientation. An automated workflow was created to detect terracettes using freely available software and satellite imagery. Results show a detection accuracy of 77%.