Determination of green leaves density using normalized difference vegetation index via image processing of in-field drone-captured image
College
Gokongwei College of Engineering
Department/Unit
Electronics And Communications Engg
Document Type
Article
Source Title
Journal of Telecommunication, Electronic and Computer Engineering
Volume
9
Issue
2-6
First Page
1
Last Page
5
Publication Date
1-1-2017
Abstract
Normalized Difference Vegetation Index (NDVI) is a technique which utilizes the near-infrared and visible bands of the electromagnetic spectrum in order to quantify the vegetation density in a specific area. This study presents a method to determine the NDVI levels of a certain rice paddy through the use of images captured using unmanned aerial vehicle (UAV) and a camera system. The camera system is developed from two action cameras, one with its infrared filter removed and replaced with blue notch filter. It is then attached to a UAV for capturing aerial images of a certain field. The images were then processed in a program written in MATLAB® . A total of 30 samples were selected in a rice field. Each sample is a 1x1-meter area. The NDVI values of the samples were first measured using Oklahoma State University (OSU) Greenseeker prototype, then the images of these samples were taken using the camera system developed. The images were then processed to get the NDVI values. Overall, the measurement of the camera system showed good consistency. The F-test conducted also implied that the system is reliable and can be used as an alternate in determining the NDVI levels in the field.
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Recommended Citation
Orillo, J., Bansil, G., Bernardo, J., Dizon, C., Imperial, H., MacAbenta, A., & Palima, R. (2017). Determination of green leaves density using normalized difference vegetation index via image processing of in-field drone-captured image. Journal of Telecommunication, Electronic and Computer Engineering, 9 (2-6), 1-5. Retrieved from https://animorepository.dlsu.edu.ph/faculty_research/3988
Disciplines
Electrical and Computer Engineering
Keywords
Image processing; Drone aircraft in remote sensing; Vegetation surveys
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