Presentation Title

Evaluating the Reliability and Efficacy of Unmanned Aerial Vehicle Based Normalized Difference Vegetation Index Crop Mapping Techniques

Format of Presentation

Poster to be presented Friday March 31, 2017

Abstract

The use of unmanned aerial vehicles (UAVs) in agriculture is a relatively new and rapidly expanding concept. By using UAVs equipped with multispectral near infrared sensors, farmers and land managers are able to detect intra-field crop variability which enables adjustments to be made to crop applications and other management decisions. This type of management has been termed precision agriculture and employs the development of various crop indices such as the normalized difference vegetation index (NDVI). In this study I investigated the abilities of two sensors, the MicaSense Red Edge and a modified DJI Zenmuse X3 camera, onboard a DJI Inspire 1 UAV with respect to their ability to generate reliable NDVI orthomosaics using Pix4D software. Through evaluation of these orthomosaics, the MicaSense Red Edge was found to produce a broader range of NDVI values as well as produce data that was more representative of the study site than the modified DJI Zenmuse X3 camera.

Department

Natural Resource Science

Faculty Advisor

John Church

This document is currently not available here.

Share

COinS
 

Evaluating the Reliability and Efficacy of Unmanned Aerial Vehicle Based Normalized Difference Vegetation Index Crop Mapping Techniques

The use of unmanned aerial vehicles (UAVs) in agriculture is a relatively new and rapidly expanding concept. By using UAVs equipped with multispectral near infrared sensors, farmers and land managers are able to detect intra-field crop variability which enables adjustments to be made to crop applications and other management decisions. This type of management has been termed precision agriculture and employs the development of various crop indices such as the normalized difference vegetation index (NDVI). In this study I investigated the abilities of two sensors, the MicaSense Red Edge and a modified DJI Zenmuse X3 camera, onboard a DJI Inspire 1 UAV with respect to their ability to generate reliable NDVI orthomosaics using Pix4D software. Through evaluation of these orthomosaics, the MicaSense Red Edge was found to produce a broader range of NDVI values as well as produce data that was more representative of the study site than the modified DJI Zenmuse X3 camera.