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An autonomous unmanned aerial vehicle-based imagery system development and remote sensing images classification for agricultural applications.

机译：基于农业的自动无人驾驶航空影像系统开发和遥感影像分类。

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摘要

This work concentrates on the topic of remote sensing using a multispectral imaging system for water management and agriculture applications. The platform, which is a light-weight inexpensive runway-free unmanned aerial vehicle (UAV), namely, AggieAir, is presented initially. A major portion of this work focuses on the development of a light-weight multispectral imager payload for the AggieAir platform, called GhostFoto. The imager is band-reconfigurable, covering both visual red, green, and blue (RGB) and near infrared (NIR) spectrum, and interfaced with UAV on-board computer. The development of the image processing techniques, which are based on the collected multispectral aerial images, is also presented in this work. One application is to perform fully autonomous river tracking for applications such as river water management. Simulation based on aerial multispectral images is done to demonstrate the feasibility of the developed algorithm. Other effort is made to create a systematic method to generate normalized difference vegetation index (NDVI) using the airborne imagery. The GhostFoto multispectral imaging system based on AggieAir architecture is proven to be an innovative and useful tool.
机译：这项工作集中在使用多光谱成像系统进行水资源管理和农业应用的遥感主题上。首先介绍的平台是一种轻巧廉价的无跑道无人机（UAV），即AggieAir。这项工作的主要内容集中在为AggieAir平台开发轻型多光谱成像仪有效载荷（称为GhostFoto）上。该成像仪是可重新配置波段的，涵盖可见的红色，绿色和蓝色（RGB）以及近红外（NIR）光谱，并与无人机车载计算机接口。这项工作还介绍了基于收集的多光谱航拍图像的图像处理技术的发展。一种应用是对诸如河流水管理之类的应用执行完全自主的河流跟踪。进行了基于航空多光谱图像的仿真，以证明该算法的可行性。做出了其他努力来创建一种使用机载图像生成归一化差异植被指数（NDVI）的系统方法。事实证明，基于AggieAir架构的GhostFoto多光谱成像系统是一种创新且有用的工具。

著录项

  • 作者

    Han, Yiding.;

  • 作者单位

    Utah State University.;

  • 授予单位 Utah State University.;
  • 学科 Engineering Agricultural.Engineering Electronics and Electrical.
  • 学位 M.S.
  • 年度 2009
  • 页码 72 p.
  • 总页数 72
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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