Lightweight Unmanned Aerial Vehicles (UAVs) for Forestry and Ecological Applications

这项研究旨在促进无人驾驶飞行器(UAVs，也称为无人机)在林业和生态应用中的使用。无人机是遥感科学的一项重要新发展，它弥合了实地观测与从卫星和有人驾驶飞机获得的高空数据之间的差距。与传统的遥感平台相比，无人机具有几个重要的优势，包括灵活的低成本传感器部署，安全的近地表操作，以及极高分辨率的成像能力。然而，我们正处于无人机研究的早期，存在着大量的技术和操作不确定性。该项目将针对以下几个目标：(1)深入了解影响无人机运行的环境因素，并突出最佳数据采集的条件；(2)确定数据处理和预处理的基本最佳做法；(3)开发能够进行有效环境监测的程序和软件工具；(4)测试即将推出的无人机传感器。这项工作的成果将有助于将无人机用作有效的环境监测平台，旨在帮助任何在林业或生态背景下处理遥感技术的人。作为这项研究的一部分接受培训的高素质人员将带着这项重要新技术的技能和经验进入加拿大的劳动力大军，预计这将是未来十年加拿大地理空间行业增长最快的部门之一。

This research is designed to advance the use of unmanned aerial vehicles (UAVs, also known as drones) in forestry and ecological applications. UAVs are an important new development in remote-sensing science, bridging the gap between field observations and high-altitude data acquired from satellites and piloted aircraft. UAVs have several important advantages over traditional remote-sensing platforms, including flexible low-cost sensor deployment, safe near-surface operation, and extraordinarily high-resolution imaging capabilities. However, we are in the early days of UAV research, and a great deal of technical and operational uncertainties exist. This project will address several objectives designed to (i) gain insight into the environmental factors affecting UAV operation, and highlight the conditions for optimal data acquisition; (ii) determine fundamental best practices for data handling and pre-processing; (iii) develop procedures and software tools designed to enable effective environmental monitoring; and (iv) test forthcoming UAV sensors. The results of this work will contribute to the use of UAVs as platforms for effective environmental monitoring, and is intended to assist anyone dealing with remote sensing technology in a forestry or ecological context. Highly qualified personnel trained as a part of this research will enter Canada's workforce with skills and experience in this important new technology, which is expected to be among the fastest-growing sectors of the Canadian geospatial industry over the next decade.