Date of Award
9-21-2018
Document Type
Thesis
Degree Name
Agriculture, MSA
First Advisor
Peter Larbi
Committee Members
Gregory Phillips; Peter Larbi; Steven Green
Call Number
LD 251 .A566t 2018 V46
Abstract
This project aimed at demonstrating the utility of using unmanned aerial system (UAS) based remote sensing to assess percentage weed coverage and cash crop vegetative coverage development corresponding to cover crop (cereal rye) termination at different growth stages. A UAS equipped with an RGB (visible bands) camera was used to acquire aerial imagery of cover crop integrated soybean plots. The specific objectives were: 1) to discriminate crop and weed vegetation based on (a) spectral information and (b) location relative to the crop rows; (2) to verify optimum timing for cover crop termination using vegetative cover development based on visible spectroscopy and relating yield data to visible spectroscopy. According to the image data output, weed vegetation was low in Z49-60 treatment at the time of soybean planting and was higher in control plot followed by Z25-27-day treatment. Vegetation coverage of soybean was highest equally in the Z25-27, Z33-39, and Z49-60 and lowest in the Z71-75 treatments. However, there were no significant differences in soybean crop yield among the treatments.
Rights Management
This work is licensed under a Creative Commons Attribution 4.0 International License.
Recommended Citation
Vemula, Shailaja, "UAS-Based Remote Sensing for Weed Identification and Cover Crop Termination Determination" (2018). Student Theses and Dissertations. 488.
https://arch.astate.edu/all-etd/488
