Estimation of forest structure with the Vegetation Structure Perpendicular Index (VSPI) for dynamic fire spread simulations

Andrea Massetti, Christoph Rudiger, Marta Yebra, James Hilton

Research output: Chapter in Book/Report/Conference proceedingConference PaperOther

Abstract

Spatial fire spread models simulate the progression of a wildfire across the land under given meteorological conditions. As such, they can improve the fire-fighting real-time response and the rural planning of fire prone areas. However, fire-spread models require high-resolution information of vegetation, which is often difficult to acquire, as spatially variant growth, but also past fire occurrences impact on the spatial variability of the vegetation. Hence, forests often consist of a patchwork of vegetation in different growth stages, which is impossible to consistently map from the ground. In order to address this problem, the Vegetation Structure Perpendicular Index (VSPI) is introduced, here, which is a spatially and temporally continuous proxy for fuel structure derived from Landsat data. Forest age maps are derived by fitting post-fire VSPI time series to an exponential decay curve. The forest age maps derived from VSPI are then used as input into a rate-of-spread model to predict the fire spread of the 2003 Mt Cooke wildfire in Western Australia, as a proof-of-concept.

Original languageEnglish
Title of host publicationIGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages6704-6707
Number of pages4
ISBN (Electronic)9781538691540
DOIs
Publication statusPublished - Jul 2019
EventIEEE International Geoscience and Remote Sensing Symposium 2019 - Yokohama, Japan
Duration: 28 Jul 20192 Aug 2019
Conference number: 39th
https://igarss2019.org/ (Website)
https://ieeexplore.ieee.org/xpl/conhome/8891871/proceeding (Proceedings)

Conference

ConferenceIEEE International Geoscience and Remote Sensing Symposium 2019
Abbreviated titleIGARSS 2019
CountryJapan
CityYokohama
Period28/07/192/08/19
Internet address

Keywords

  • Landsat
  • Quantitative remote sensing
  • vegetation structure
  • wildfires

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