基于卫星图像的龙卷风后道路碎片检测:综合GIS和图像处理方法

IF 3.8 Q2 ENVIRONMENTAL SCIENCES
Richard Boadu Antwi, Prince Lartey Lawson, Eren Erman Ozguven, Ren Moses
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引用次数: 0

摘要

美国东南部经常经历龙卷风,需要州和联邦机构的快速反应和恢复努力。关于龙卷风造成破坏的程度和严重程度的准确信息,特别是碎片的数量和位置,对这些工作至关重要。因此,本研究的重点是佛罗里达州莱昂县的龙卷风后碎片评估,该县于2024年5月遭受了两次EF-2和EF-1龙卷风袭击。利用Planetscope卫星和地理信息系统(GIS)的卫星图像,对龙卷风碎片的影响进行了宏观评估,特别是对道路和受影响社区的影响。拟议的方法包括评估整个县及其人口在龙卷风后的总体碎片影响,并详细分析碎片对道路的影响及其对可达性的影响。利用卫星影像的光谱指数,特别是归一化植被指数(NDVI)来推导评估参数。通过比较龙卷风前后图像的NDVI值,我们分析了道路沿线植被和碎片堆积的变化,从而可能导致道路封闭。这种综合方法为加强龙卷风易发地区的灾害响应和恢复行动提供了关键的见解。结果表明,在县域人口最多的中南部地区存在大量的植被碎片。该地区的路段也记录了最高的碎片量,这对于需要了解受严重影响位置的机构来说是一个关键信息。将结果与地面真实损坏数据进行比较,记录的准确性为74%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Post-tornado roadway debris detection from satellite images: An integrated GIS and image processing approach
Southeastern United States frequently experience tornadoes, necessitating rapid response and recovery efforts by state and federal agencies. Accurate information about the extent and severity of tornado-induced damage, especially debris volume and locations, is crucial for these efforts. This study, therefore, focuses on post-tornado debris assessment in Leon County, Florida, which was hit by two EF-2 and an EF-1 tornadoes in May 2024. Using satellite imagery from the Planetscope satellite and Geographic Information Systems (GIS), a macro-level evaluation of tornado debris impact was conducted, particularly on roadways and impacted communities. The proposed approach includes an evaluation of the overall post-tornado debris impact across the entire county and its population, and a detailed analysis of debris impact on roadways and its effect on accessibility. Spectral indices from satellite images, specifically the Normalized Difference Vegetation Index (NDVI), were utilized to derive assessment parameters. By comparing NDVI values from pre- and post-tornado images, we analyzed changes in vegetation and debris accumulation along roadway segments leading to possible roadway closures. This integrated method provides critical insights for enhancing disaster response and recovery operations in tornado-prone regions. Findings indicate that high volumes of vegetative debris were present in the south-central parts of the county, which is occupied by the highest population of county residents. The roadway segments in this region also recorded highest debris volumes, which is a critical information for agencies that need to know highly impacted locations. Comparing the results to ground truth damage data, the accuracy recorded was 74%.
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来源期刊
CiteScore
8.00
自引率
8.50%
发文量
204
审稿时长
65 days
期刊介绍: The journal ''Remote Sensing Applications: Society and Environment'' (RSASE) focuses on remote sensing studies that address specific topics with an emphasis on environmental and societal issues - regional / local studies with global significance. Subjects are encouraged to have an interdisciplinary approach and include, but are not limited by: " -Global and climate change studies addressing the impact of increasing concentrations of greenhouse gases, CO2 emission, carbon balance and carbon mitigation, energy system on social and environmental systems -Ecological and environmental issues including biodiversity, ecosystem dynamics, land degradation, atmospheric and water pollution, urban footprint, ecosystem management and natural hazards (e.g. earthquakes, typhoons, floods, landslides) -Natural resource studies including land-use in general, biomass estimation, forests, agricultural land, plantation, soils, coral reefs, wetland and water resources -Agriculture, food production systems and food security outcomes -Socio-economic issues including urban systems, urban growth, public health, epidemics, land-use transition and land use conflicts -Oceanography and coastal zone studies, including sea level rise projections, coastlines changes and the ocean-land interface -Regional challenges for remote sensing application techniques, monitoring and analysis, such as cloud screening and atmospheric correction for tropical regions -Interdisciplinary studies combining remote sensing, household survey data, field measurements and models to address environmental, societal and sustainability issues -Quantitative and qualitative analysis that documents the impact of using remote sensing studies in social, political, environmental or economic systems
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