Master's Theses

Department

Biology

Degree Name

Master of Science (MS)

Abstract

Implementation of unmanned aerial system (UAS) in conservation biology has allowed researchers to extend their surveying range for monitoring wildlife. Wildlife biologists have started using UAS technology for detecting large species (i.e. elk, manatees) within their surveying range and monitoring changes and disturbance in the landscape. Despite this technological advancement, there are few studies that target smaller species (reptiles, rodents, amphibians) for UAS surveys. The primary reason for this is that these organisms are simply too small for detection for aerial surveying. However, certain species are restricted in their range because they have specific environmental requirements, and the target for UAS survey could change focus from detection of species to detection of their habitat. The Lesser Earless lizard (Holbrookia maculata) is smaller species of lizard that inhabits arid, rocky regions in the southwest United States, which is known to occupy areas of sparse vegetation and rocky or loamy soils. Although this species would be difficult to detect in aerial surveys, their habitat can easily be distinguished in aerial imagery. For this project, aerial surveys performed by UAS technology and ground surveying of H. maculata were analyzed in combination to generate a predictive model of H. maculata presence within a landscape. Three survey areas were assigned for this project: one to generate the predictive model from data collected from ground and aerial surveys, and two were assigned to assess the accuracy of the predictive model based off ground and aerial surveys.

Keywords

UAV, drone, reflectance, earless, predicting

Advisor

Dr. William Stark

Date of Award

Spring 2018

Document Type

Thesis

Rights

© The Author(s)

Comments

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