Wildfires can be beneficial for native vegetation. However, wildfires can impact property values, human safety, and ecosystem function. Resource managers require safe, easy to use, timely, and cost-effective methods for quantifying wildfire damage and regeneration. In this work, we demonstrate an approach using an unmanned aerial system (UAS) equipped with a MicaSense RedEdge multispectral sensor to classify and estimate wildfire damage in a coastal marsh. We collected approximately 7.2 km2 of five-band multispectral imagery after a wildfire event in February 2016, which was used to create a photogrammetry-based digital surface model (DSM) and orthomosaic for object-based classification analysis. Airborne light detection and ranging data were used to validate the accuracy of the DSM. Four-band airborne imagery from pre- and post-fire were used to estimate pre-fire health, post-fire damage, and track the vegetation recovery process. Immediate and long-term post-fire classifications, area, and volume of burned regions were produced to track the revegetation progress. The UAS-based classification produced from normalized difference vegetation index and DSM was compared to the Landsat-based Burned Area Reflectance Classification. Experimental results show the potential of using UAS and the presented approach compared to satellite-based mapping in terms of classification accuracies, turnaround time, and spatial and temporal resolutions.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Remote Sensing of Wildfire Using a Small Unmanned Aerial System: Post-Fire Mapping, Vegetation Recovery and Damage Analysis in Grand Bay, Mississippi/Alabama, USA


    Beteiligte:
    Sathishkumar Samiappan (Autor:in) / Lee Hathcock (Autor:in) / Gray Turnage (Autor:in) / Cary McCraine (Autor:in) / Jonathan Pitchford (Autor:in) / Robert Moorhead (Autor:in)


    Erscheinungsdatum :

    2019




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt




    Aerial remote sensing surveying and mapping unmanned aerial vehicle damping device

    SUN YAFEI / ZHANG JUANJUAN / ZHANG ZHIMIN et al. | Europäisches Patentamt | 2021

    Freier Zugriff

    Remote sensing engineering surveying and mapping unmanned aerial vehicle

    DING LEIXIANG / SUN YAFEI / ZHANG ZHIMIN et al. | Europäisches Patentamt | 2022

    Freier Zugriff

    Unmanned aerial vehicle for remote sensing surveying and mapping

    GAO PAN | Europäisches Patentamt | 2023

    Freier Zugriff

    Unmanned aerial vehicle remote sensing surveying and mapping device

    SU JIAYU / ZHOU HONGKAI / ZHANG XIAOYANG et al. | Europäisches Patentamt | 2024

    Freier Zugriff

    Remote sensing unmanned aerial vehicle

    LI CHUNYU / TAN ZHANMING / ZHANG YUAN et al. | Europäisches Patentamt | 2021

    Freier Zugriff