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The rapid overpopulation of White-Tailed Deer (Odocoileus virginianus) has severely harmed the Northeast region of the United States. Affected regions have seen increased environmental degradation due to overbrowsing, increased instances of deer-vehicle collisions, and an uptick in Lyme Disease contraction. The overpopulation of White-Tailed Deer (WTD) is mainly due to anthropogenic causes such as the overhunting and over regulation of the primary predators of WTD. Therefore, fully understanding the severity of the WTD overpopulation is crucial in combating the issue and making informed management decisions. The scope of our study focuses on determining the most effective image types and image processing techniques in regards to analyzing census data on mammalian wildlife populations. We will be conducting a UAV-based drone survey of WTD in the Binghamton University Nature Preserve collecting both thermal and hyperspectral data. We will then recruit approximately 100-150 untrained college students, split them into two groups, and have each group review a different drone flight. Each student will individually estimate the amount of deer in the data set they were provided. By placing the student estimates on a bell curve for each flight, we will be able to identify which image type is most effective for counting deer with an eye untrained in image analysis. The results of this experiment will allow us to create a novel methodology that will help us, as well as other scientists, utilize drone-based surveys to more accurately gather census data on WTD.



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Comparison Between Thermal and Hyper-spectral Image Analysis: White-tailed Deer Population Monitoring in the Binghamton University Nature Preserve