Assessment of fire severity and vegetation response using moderate-resolution imaging spectroradiometer: moderate resolution (MODIS) satellite images to assess vegetation response after a big fire event at the selected national parks around Sydney, Australia

Shahriar Rahman, Hsing-Chung Chang

    Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

    2 Citations (Scopus)

    Abstract

    Fire severity is the direct result of the combustion process and is related to the rate at which fuel is being consumed. Many studies have already been conducted to map fire severity using different burn severity indices and some of the research studies were based on field-based validation. A few studies have used the coarse and medium resolution satellite-based time series data to assess the fire severity and to assess the impacts on vegetation recovery. Therefore, this study is a remote sensing approach to map fire severity and to assess the vegetation regrowth after a big fire event (Black Christmas Bushfires) at the selected national parks in the outskirts of Sydney, Australia, using Moderate-resolution Imaging Spectroradiometer (MODIS) Data [from the year 2000 to 2016]. Two established fire severity indices, Normalised Burn Ratio (NBR) and differenced Normalised Burn Ratio (dNBR) were used to detect fire severity. Time series analysis of MODIS-derived vegetation indices [LAI (Leaf Area Index) and NDVI (Normalised Difference Vegetation Index)] was applied to understand the change in the phenological cycle after the fire events. Time-series analysis showed that MODIS-NDVI provides robust seasonality assessment than MODIS-LAI profile. The woodland area (Eucalypt Medium Woodland Forest) showed delayed vegetation recovery after the Big Christmas Bushfires.

    Original languageEnglish
    Title of host publication2017 Eleventh International Conference on Sensing Technology (ICST)
    Subtitle of host publicationproceedings
    Place of PublicationPiscataway, NJ
    PublisherInstitute of Electrical and Electronics Engineers (IEEE)
    Pages353-358
    Number of pages6
    ISBN (Electronic)9781509065264, 9781509065257
    ISBN (Print)9781509065271
    DOIs
    Publication statusPublished - 2017
    Event2017 Eleventh International Conference on Sensing Technology - Sydney, Australia
    Duration: 4 Dec 20176 Dec 2017
    Conference number: 11th

    Conference

    Conference2017 Eleventh International Conference on Sensing Technology
    Abbreviated titleICST
    Country/TerritoryAustralia
    CitySydney
    Period4/12/176/12/17

    Keywords

    • Black Christmas
    • DNBR
    • Fire Severity
    • NDVI
    • Vegetation Regrowth

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