IDR: Development of a Monitoring System Using UAVs for Forest Management

这项提议的目的是开发部署无人驾驶飞行器所需的新算法，以便更好地了解与火灾风险评估有关的森林生态系统结构。这些算法将使无人机能够帮助识别给定区域的高火灾风险区域，帮助消防管理人员实时监测和应对火灾传播，并绘制大片区域地图，以便进行火灾后评估。方法是1)开发用于使用遥感工具创建地表燃料地图的算法，2)开发近似算法和启发式算法以有效地分配资源并规划车辆的运动，以便在期望的时间内访问需要监视的区域。智力优势：在遥感方面，拟议的方法将提供一种负担得起的方式，以获得目前无法获得的森林表面和树冠燃料的准确估计。在资源分配和运动规划方面，这些方法将推动快速、次优算法的发展。更广泛的影响：消防管理人员将能够使用开发的工具迅速确定给定地区的火灾高风险区域，并有效地实时应对火灾传播。受控燃烧具有生态、社会和经济效益：增强了依赖火的生态系统的生态过程，减少了灾难性火灾的风险，减少了财产损失和生命损失。该项目将为学生提供从不同学科学习工具的机会，并为遥感和机器人课程提供宝贵的教材。

The objective of this proposal is to develop novel algorithms that are required to deploy unmanned aerial vehicles for better understanding the structure of forest ecosystems in relation to fire risk assessment. The algorithms will enable unmanned aerial vehicles to assist in identifying high fire-risk regions in a given area, aid fire managers to monitor and respond to fire propagation in real-time and map large areas for post-fire assessment. The approach is to 1) develop algorithms for creating surface fuel maps using tools by remote sensing, 2) develop approximation algorithms and heuristics to efficiently allocate the resources and plan the motion of the vehicles such that the regions that need to be monitored are visited within a desired time. Intellectual Merit: With regards to remote sensing, the proposed methods will provide an affordable way of obtaining precise estimates of forest surface and canopy fuels that is currently not available. With regards to resource allocation and motion planning, the methods will advance the state of art in the development of fast, sub-optimal algorithms. Broader impacts: Fire managers will be able to swiftly identify high fire-risk regions in a given area using the developed tools and efficiently respond to fire propagation in real-time. Controlled burning has ecological, societal and economic benefits: enhanced ecological processes in fire-dependent ecosystems, abated risk of catastrophic fires, reduced property damage and loss of life. This project will provide an opportunity for students to learn tools from diverse disciplines and valuable teaching material for courses in remote sensing and robotics.