RAPID: Collaborative: Data Driven Post-Disaster Waste and Debris Volume Predictions using Smartphone Photogrammetry App and Unmanned Aerial Vehicles

这项提议的目标是利用智能手机和无人驾驶飞行器(UAV)的摄影测量来自动化废物碎片的量化。在飓风哈维和相关的降雨引发的洪水之后，将产生大量的废物和碎片，特别是在德克萨斯州的休斯顿和博蒙特等城市地区。灾后碎片管理是地方和联邦当局面临的一个重要问题：它贡献了灾害管理费用的很大一部分，可产生数倍于受影响社区的年垃圾产生率，并由于容易出错的初始碎片估计而导致支出增加。目前预测碎片数量的程序不准确且效率低下，因为它使用的是目视观测的定性数据。这项研究的结果将通过测量飓风哈维产生的碎片来改进洪水碎片估计模型的校准。这将有助于决策工具，最终将导致更快、更具成本效益的碎片管理操作，以应对未来的降雨、热带风暴和飓风引发的洪水事件，这些事件将继续影响墨西哥湾、美国和世界其他地方。这个快速项目解决了缺乏灾后碎片体积数据集的问题，方法是通过自动智能手机摄影测量应用程序和德克萨斯州其他受影响地区的无人机收集短暂数据，并通过开源网络基础设施数据库提供数据。碎片体积将通过探索使用智能手机自动量化废物碎片来进行量化。特别是，由监视器、居民或当地政府机构捕获的智能手机图像可以被处理和缩放，以开发3D再现和垃圾数量的估计。这些估计将使用无人驾驶飞行器(无人机)摄影测量来验证，然后可以使用体积研究以及监测公司记录的其他可用碎片体积进行转换。如果成功，智能手机和无人机可以在未来的自然灾害中迅速使用，以分析和表征数字图像，然后准确地量化垃圾碎片的数量。

The goal of this proposal is to leverage photogrammetry from smart phones and unmanned aerial vehicles (UAVs) to automate the quantification of waste debris. In the aftermath of Hurricane Harvey and associated rainfall-induced flooding, a significant volume of waste and debris will be generated, especially in urban areas such as Houston and Beaumont, Texas. The management of post-disaster debris is an important issue faced by local and federal authorities: it contributes a significant portion of disaster management costs, can generate several times the annual waste generation rates of the affected community, and leads to higher expenditures due to error prone initial debris estimations. The current process to predict debris volume is inaccurate and inefficient, as it utilizes qualitative data from visual observation. The results of this study will improve the calibration of the flood debris estimation models by measuring debris generation due to Hurricane Harvey. This will aid in decision-making tools that ultimately will result in faster and more cost-effective debris management operations for future rainfall, tropical storm, and hurricane-induced flood events that continue to impact the Gulf, the US, and elsewhere around the world.This RAPID project addresses the lack of post-disaster debris volume dataset by collecting ephemeral data through an automated smartphone photogrammetric app and UAV in Beaumont and other affected regions in Texas, and making the data available through open-source cyber-infrastructure databases. Debris volumes will be quantified by exploring the use of smartphones to automate the quantification of waste debris. In particular, smart phone images captured by the monitor, resident, or local government agency can be processed and scaled to develop a 3-D rendition and an estimate of waste volumes. These estimations will be validated using an unmanned aerial vehicle (UAV) photogrammetry surveys and which in turn can be converted using volumetric studies as well as other available debris volumes documented by monitoring companies. If successful, smartphones and UAVs can be quickly used in future natural disasters to analyze and characterize the digital images and then accurately quantify waste debris volumes.