Transportation systems are vulnerable to hurricanes and yet their recovery plays a critical role in returning a community to its pre-hurricane state. Vegetative debris is among the most significant causes of disruptions on transportation infrastructure. Therefore, identifying the driving factors of hurricane-caused debris generation can help clear roadways faster and improve the recovery time of infrastructure systems. Previous studies on hurricane debris assessment are generally based on field data collection, which is expensive, time consuming, and dangerous. With the availability and convenience of remote sensing powered by the simple yet accurate estimations on the vigor of vegetation or density of manufactured features, spectral indices can change the way that emergency planners prepare for and perform vegetative debris removal operations. Thus, this study proposes a data fusion framework combining multispectral satellite imagery and various vector data to evaluate post-hurricane vegetative debris with an exploratory analysis in small geographical units. Actual debris removal data were obtained from the City of Tallahassee, Florida after Hurricane Michael (2018) and aggregated into U.S. Census Block Groups along with four groups of datasets representing vegetation, storm surge, land use, and socioeconomics. Findings suggest that vegetation and other land characteristics are more determinant factors on debris generation, and Modified Soil-Adjusted Vegetation Index (MSAVI2) outperforms other vegetation indices for hurricane debris assessment. The proposed framework can help better identify equipment stack locations and temporary debris collection centers while providing resilience enhancements with a focus on the transportation infrastructure.


    Access

    Download

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Post-Hurricane Vegetative Debris Assessment Using Spectral Indices Derived from Satellite Imagery


    Additional title:

    Transportation Research Record


    Contributors:


    Publication date :

    2021-08-08




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Use and Assessment of Multi-Spectral Satellite Imagery in NWS Operational Forecasting Environments

    Molthan, Andrew / Fuell, Kevin / Stano, Geoffrey et al. | NTRS | 2015



    Satellite views of Hurricane Camille

    Shenk, William E. / Rodgers, Edward B. | TIBKAT | 1974


    Mesoscale Sea Surface Currents Derived from Multi-Sensor Satellite Imagery

    Gade, M. / Fiedler, G. / Dreschler-Fischer, L. et al. | British Library Conference Proceedings | 2007