Measuring Normalized Difference Vegetation Index for Agricultural Management using Unmanned Aerial Vehicles

Open Access
Author:
Disco, Connor Scott
Area of Honors:
Mechanical Engineering
Degree:
Bachelor of Science
Document Type:
Thesis
Thesis Supervisors:
  • Henry Joseph Sommer Iii, Thesis Supervisor
  • Zoubeida Ounaies, Honors Advisor
  • Henry Joseph Sommer Iii, Faculty Reader
Keywords:
  • Agriculture
  • Unmanned Aerial Vehicles
  • Image Processing
  • NDVI
  • Image Distortion Removal
  • Image Stitching
  • MATLAB
Abstract:
Healthy vegetation appears green because plant leaves reflect green light. Photosynthetic pigments in the leaves also reflect near infrared (NIR) light, with healthier pigments reflecting the highest amount of NIR light. Accordingly, by measuring a plant’s NIR reflectivity, it is possible to assess its health visually. The Normalized Differential Vegetation Index (NVDI) is a measurement of the amount of (NIR) light reflected from a plant’s leaves and has been used for decades as an assessment of plant health for various agricultural applications. The use of NDVI for health analysis is vastly impactful to the agricultural community but the specialized cameras currently used to measure NDVI are much too expensive to make the implementation of NDVI analysis widely accessible. As such, this research serves three purposes: to mimic the NDVI image-capturing process using less-expensive digital cameras, to develop unmanned aerial platforms which can easily be implemented by small-scale agriculturalists to perform aerial NDVI analysis, and to develop software to post-process images and provide an NDVI color map of the area of land analyzed. Developing an inexpensive and easy-to-use platform allows agriculturalists to affordably implement NDVI analysis to manage plant health and could revolutionize the agricultural industry as a whole.