RAPID: Investigating Illegal Dumping During the Course of Debris Collection Operations Following Hurricane Ian

RAPID：调查伊恩飓风后碎片收集作业过程中的非法倾倒行为

• 批准号: 2305113
• 负责人: Juyeong Choi
• 金额: $ 7.5万
• 依托单位: Florida State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-11-15 至 2024-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2305113&HistoricalAwards=false
• 关键词: RAPID; Investigating; Illegal; Dumping; During

Hurricane Ian made landfall as a catastrophic Category 4 hurricane on September 28, 2022, in the southwestern region of Florida. It generated substantial amounts of debris, exceeding the capacity of local waste management systems. Delayed collection of debris from public property and rights-of-way incurs public health and safety concerns. Since affected communities use their own limited resources for debris removal before the reimbursement by FEMA, it is critical to accurately estimate and keep track of the uncollected debris throughout recovery. While various tools are available to estimate the initial amount of disaster debris, current approaches do not update the estimates as a debris collection process proceeds over time. Further, illegal dumping - the disposal of ineligible debris at public sites without legal permission - often causes such initial estimates to become obsolete and complicates debris logistics planning and reimbursement management. This Grant for Rapid Response Research (RAPID) project aims to collect ephemeral data on uncollected debris on public roadways during the course of debris collection operations in order to investigate illegal debris disposal and its social and environmental impacts. This project will (i) conduct a sequential survey of affected public roadways with unmanned aerial vehicles and a LiDAR scanner to capture the amount of illegally dumped waste over time, (ii) link illegally dumped debris to its relevant collection trajectories through collaboration with debris contractors, and (iii) perform online surveys to understand the social and environmental impacts of uncollected debris, debris disposal methods, and community settings. The volume of debris at different points in time will be quantified through machine learning algorithms with aerial imagery and 3-D point cloud data resulting from the sequential survey. The volume of illegally disposed debris on each roadway section will then be estimated by comparing the debris volumes at subsequent times along with the volume of debris collected by haulers over the elapsed time.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

飓风伊恩于2022年9月28日以灾难性的四级飓风强度在佛罗里达西南部地区登陆。它产生了大量的碎片，超过了当地废物管理系统的能力。拖延收集公共财产和通行权的碎片会引起公众健康和安全问题。由于受影响社区在联邦应急管理局偿还之前使用自己有限的资源清除碎片，因此在整个恢复过程中准确估计和跟踪未收集的碎片至关重要。虽然有各种工具可用于估计灾害碎片的初始数量，但目前的方法并不随着碎片收集过程的进行而更新估计数。此外，非法倾倒----即未经法律的许可在公共场所处置不合格的碎片----往往使这种初步估计变得过时，并使碎片后勤规划和补偿管理复杂化。这一快速反应研究赠款项目旨在收集垃圾收集作业期间公共道路上未收集垃圾的短暂数据，以调查非法垃圾处置及其社会和环境影响。该项目将（i）使用无人驾驶飞行器和激光雷达扫描仪对受影响的公共道路进行连续调查，以记录一段时间内非法倾倒的废物数量，（ii）通过与碎片承包商合作，将非法倾倒的碎片与其相关收集轨迹联系起来，（iii）进行在线调查，以了解未收集碎片的社会和环境影响，碎片处理方法，和社区设置。将通过机器学习算法，利用航空图像和连续调查产生的三维点云数据，对不同时间点的碎片量进行量化。然后，通过将随后沿着的碎片量与运输车在过去的时间内收集的碎片量进行比较，估计每个路段上非法处理的碎片量。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。