Traffic carrying flammable, corrosive, poisonous, and radioactive materials continues to increase in proportion with the growth in their production and consumption. The sustained risk of accidental releases of such hazardous materials poses serious threats to public safety. Early detection of spills will potentially save lives, protect the environment, and thwart the need for expensive cleanup campaigns. Ground patrols and terrestrial sensing equipment cannot scale cost-effectively to cover the entire transportation network. Remote sensing with existing airborne and spaceborne platforms has the capacity to monitor vast areas regularly but often lacks the spatial resolution necessary for high accuracy detections. The emergence of unmanned aircraft systems with lightweight hyperspectral image sensors enables a resolution agile approach that can adapt both spatial and spectral resolutions in real time. Equipment operators can exploit such a capability to enhance the resolution of potential target materials detected within a larger field-of-view to verify their identification or to perform further inspections. However, the complexity of algorithms available to classify hyperspectral scenes limits the potential for real-time target detection to support rapid decision making. This research introduces and benchmarks the performance of a low-complexity method of hyperspectral image classification. The hybrid supervised–unsupervised technique approaches the performance of prevailing methods that are at least 30-fold more computationally complex.


    Access

    Download

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Resolution Agile Remote Sensing for Detection of Hazardous Material Spills


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:


    Publication date :

    2016-01-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    Remote Sensing of Oil Spills

    Fingas, M. / Brown, C. | British Library Online Contents | 1997


    Laser radar for remote detection of oil spills

    Sato, T. / Suzuki, Y. / Kashiwagi, H. et al. | Tema Archive | 1978


    Remote Sensing for Risk Analysis of Oil Spills in the Arctic Ocean

    Johansson, A.M. / Eriksson, L.E.B. / Hassellov, I.-M. et al. | British Library Conference Proceedings | 2013


    Light agile remote sensing satellite platform configuration

    WANG XIAOFENG / XU SHENXIN / ZHANG RUBIAN et al. | European Patent Office | 2024

    Free access