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

该提案的目标是利用智能手机和无人驾驶飞行器（UAV）的摄影测量来自动量化废物碎片。在飓风哈维和相关的飓风引发的洪水之后，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等城市地区。灾后碎片的管理是地方和联邦当局面临的一个重要问题：它占灾害管理费用的很大一部分，可产生数倍于受灾社区年废物产生率的废物，并由于对碎片的初步估计容易出错而导致支出增加。目前预测碎片体积的程序既不准确，效率也不高，因为它利用的是目视观察的定性数据。这项研究的结果将通过测量哈维飓风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，以应对未来继续影响墨西哥湾，美国，这个快速项目解决了缺乏后-灾难碎片体积数据集，通过自动智能手机摄影测量应用程序和无人机在德克萨斯州的博蒙和其他受影响地区收集短暂数据，并通过开源网络基础设施数据库提供数据。将通过探索使用智能手机自动量化废物碎片来量化碎片量。特别地，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再现和废物量的估计。这些估计将使用无人驾驶航空器摄影测量调查加以验证，而摄影测量调查又可以使用体积研究以及监测公司记录的其他现有碎片体积进行换算。如果成功，智能手机和无人机可以在未来的自然灾害中快速使用，以分析和描述数字图像，然后准确地量化废物碎片的数量。

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.