Jensen, JenniferLopez, Alexa2021-07-212021-07-212021-08Lopez, A. (2021). <i>An analysis of aquatic vegetation in the San Marcos River using sUAS</i> (Unpublished thesis). Texas State University, San Marcos, Texas.https://hdl.handle.net/10877/14040Recreational usage is one of the largest impacts to the endemic Texas wild-rice (TWR) on the San Marcos river (SMR). During the summer of 2020, the restricted use of public access points to the river systems allowed a unique view of how aquatic vegetation responds with little intervention from river users. This thesis utilized small unmanned aerial surveillance (sUAS) to capture ultra-high resolution imagery of the SMR. The method used for classification featured an object-based image analysis using random forest, an AI algorithm to classify the data. The classified data had an accuracy assessment done which indicated an accuracy range 75.72% - 80.57% with a Kappa range of .59 - .70. The classified imagery was then used in a change detection from July to August, August to September and July to September to determine the change in vegetation composition during the summer months. During the study period, there was expansion of stands that were identified as exclusively TWR, and the expansion of mixed vegetation stands, indicating the growth of the aquatic vegetation system. This study provided a continuous coverage of aquatic vegetation from a planar view using sUAS during a unique period where normally the river would have experienced its highest usage.Text91 pages1 file (.pdf)ensUASWater resourcesRemote sensingGISChange detectionClassificationRandom forestsRiverAquatic vegetationThesis