Biological Systems Engineering

 

First Advisor

Derek M. Heeren

Second Advisor

Wayne E. Woldt

Date of this Version

Fall 12-2021

Citation

Kashyap, Suresh Pradhyun, "High-Frequency Unmanned Aircraft Flights For Crop Canopy Imaging During Diurnal Moisture Stress" (2021). Biological Systems Engineering--Dissertations, Theses, and Student Research.

Comments

A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Master of Science, Major: Agricultural and Biological Systems Engineering, Under the Supervision of Professor Derek M. Heeren. Lincoln, Nebraska: December 2021.

Copyright (c) 2021 Suresh Pradhyun Kashyap

Abstract

Previous research has used unmanned aerial vehicle (UAV) technology for calculating CWSI (Crop Water Stress Index) values in the context of irrigation scheduling. Typically, these estimations were taken at one time of day, usually near shortly after solar noon. A significant limitation with these CWSI values is that the UAV thermal imagery captured at this point in time can be affected by various factors like atmospheric air temperature, solar radiation, wind speed, relative humidity, and other micrometeorological disturbances in the air. In order to address these temporal effects, high-frequency UAV flights were conducted over different daylight hours to analyze and compare the CWSI values to create a better understanding of the crop dynamics to irrigation events. In addition, another stress index that requires fewer input data, the Degrees Above Non-Stressed (DANS), was also compared to CWSI values. This research was carried out at three different field research sites in Nebraska: Two at the Eastern Nebraska Research and Extension Center (ENREC), Mead, NE, and one at the Irmak Research Laboratory (IRK) in South Central Agricultural Laboratory (SCAL), Clay Center, NE. All fields were growing soybean with various levels of irrigation and rainfed treatments. A DJI M600 UAV was used with MicaSense RedEdge multispectral camera and a FLIR Duo Pro R thermal camera to capture imagery, flying at an altitude of 400 m above ground level. In addition, local meteorological data and ground-based IRT (Infrared Thermometer) data were collected. In order to calculate CWSI and DANS, a thermal calibrated linear regression model developed by NU-AIRE Lab, UNL, NE, was also used to improve the accuracy of the thermal imagery data. NDVI and NDRE values were also computed to find any correlation between affecting CWSI values. Both thermal and multispectral imagery is used to analyze the spatiotemporal dynamics of the crop.

Advisors: Derek M. Heeren and Wayne E. Woldt

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