Document Type

Thesis - Open Access

Award Date

2018

Degree Name

Master of Science (MS)

Department

Electrical Engineering and Computer Science

First Advisor

Songxin Tan

Abstract

Study of vegetation is of great importance to the improvement of agriculture and forest management. Although there have been various attempts to characterize vegetation using remote sensing techniques, polarimetric lidar is a novel remote sensing tool that has shown potential in vegetation remote sensing. In this thesis, a near-infrared polarimetric lidar at 1064 nm was used to investigate the effects of seasonal change and water stress condition on plant leaves. Two variables, time and water content, affected the plant leaf laser depolarization ratio measurement. The first study focused on the maple tree in order to figure out how seasonal change affected the maple leaf depolarization. Seasonal trendline was obtained and revealed an overall downward trend over time. In the second study, the leaves from maple, lemon, and rubber trees were investigated to study the effect of water stress on the depolarization ratio. It was discovered that the leaf depolarization ratio increased for more water content and went down for less water content. In addition, leaf samples were collected in the morning, afternoon, and evening, respectively, to study the diurnal change. Statistical analysis suggested that depolarization ratio did not change significantly for the different times of a day. It was suggested that the seasonal change had a greater effect on depolarization than the diurnal change. This study demonstrates that the near-infrared polarimetric lidar system has an ability to remotely characterize the vegetation internal conditions that may not be visible to the human eyes. Furthermore, the lidar system has the potential to differentiate the various plant species based on the depolarization ratio. In conclusion, the polarimetric lidar system at 1064-nm is an effective and sensitive enough remote sensing tool which can be widely used in active remote sensing.

Description

Includes bibliographical references

Format

application/pdf

Number of Pages

108

Publisher

South Dakota State University

Rights

In Copyright - Educational Use Permitted
http://rightsstatements.org/vocab/InC-EDU/1.0/

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