Date of Award:

12-2021

Document Type:

Dissertation

Degree Name:

Doctor of Philosophy (PhD)

Department:

Civil and Environmental Engineering

Committee Chair(s)

Alfonso F. Torres-Rua

Committee

Alfonso F. Torres-Rua

Committee

Mac McKee

Committee

Lawrence HIpps

Committee

William P. Kustas

Committee

Niel Allen

Abstract

In recent years, satellites and unmanned aerial vehicles (UAVs) provide enormous amounts of spatially-distributed information for monitoring crop conditions by measuring crop’s reflected and emitted radiation at a distance. However, applications of high-resolution UAV imagery and its intermediate products for improving crop water use estimates are not well studied. In other words, the available approaches, methods and algorithms for determining how much water to apply for irrigation using remotely sensed data have been mostly developed at satellite spatial resolutions. High-resolution imageries that have been achieved by small UAVs open new opportunities for revisiting, re-evaluating, and revising available crop water use methods. In this study, different aspects of opportunities of UAV high-resolution imagery for enhancing remote sensing crop water use models, notably the Two-Source Energy Balance model (TSEB), over a commercial vineyard located in California are presented. In particular, this dissertation presents the impact of shadows, leaf area index (LAI) modeled from UAV 3D information, and higher-resolution temperature on the TSEB model. The high-resolution spatially-distributed crop water use derived by integration of UAV imagery into the TSEB model provides the capability to visualize spatial variations of crop water use at a compatible resolution with irrigation systems. This information is an essential part of scheduling irrigation with greater precision.

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