Mahurin Honors College Capstone Experience/Thesis Projects
Department
Biology
Document Type
Thesis
Abstract
Invasive species serve as a threat to native biodiversity and ecosystem sustainability. Combatting the spread of invasive species requires long-term physical and monetary commitments. In Balule Nature Reserve of Greater Kruger National Park, South Africa, Opuntia ficus-inidica (the common prickly pear) has been a relentless invader, displacing the local flora and fauna. The goal of this project is to battle invasive species such as prickly pear using efficient and inexpensive technology: unmanned aerial vehicles (UAVs or drones) and multispectral sensors.
Using a 4-bandwidth Parrot Sequoia multispectral sensor in tandem with the DJI Phantom Pro 3TM UAV, images of land plots were collected in the summer of 2018 on Balule Nature Reserve and surrounding areas in South Africa. From the images collected, maps were created using the mapping software Pix4D Mapper. Vegetation indices were created in which certain properties of vegetation are highlighted, assisting in plant identification. Using geographical informational system (GIS) software, classifications will be performed in which the multispectral data serves an important role. Multispectral sensors capture images in varying bandwidths; by collecting images in the red, green, red edge, and near-infrared bandwidths, there is potential for creating unique spectral signatures specific to individual objects such as prickly pear. Once a spectral signature is determined, a computer can then potentially perform unsupervised classifications to identify prickly pear solely from aerial images.
Advisor(s) or Committee Chair
Michael Stokes, Ph.D.
Disciplines
Biology | Geographic Information Sciences | Other Ecology and Evolutionary Biology | Remote Sensing
Recommended Citation
Ahmed, Tithe, "Using Unmanned Aircraft Systems to Identify Invasive Species" (2020). Mahurin Honors College Capstone Experience/Thesis Projects. Paper 873.
https://digitalcommons.wku.edu/stu_hon_theses/873
Included in
Biology Commons, Geographic Information Sciences Commons, Other Ecology and Evolutionary Biology Commons, Remote Sensing Commons