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 language | English |
|---|---|
| Title of host publication | IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium |
| Publisher | IEEE, Institute of Electrical and Electronics Engineers |
| Pages | 6704-6707 |
| Number of pages | 4 |
| ISBN (Electronic) | 9781538691540 |
| DOIs | |
| Publication status | Published - Jul 2019 |
| Event | IEEE International Geoscience and Remote Sensing Symposium 2019 - Yokohama, Japan Duration: 28 Jul 2019 → 2 Aug 2019 Conference number: 39th https://igarss2019.org/ (Website) https://ieeexplore.ieee.org/xpl/conhome/8891871/proceeding (Proceedings) |
Conference
| Conference | IEEE International Geoscience and Remote Sensing Symposium 2019 |
|---|---|
| Abbreviated title | IGARSS 2019 |
| Country/Territory | Japan |
| City | Yokohama |
| Period | 28/07/19 → 2/08/19 |
| Internet address |
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UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 15 Life on Land
Keywords
- Landsat
- Quantitative remote sensing
- vegetation structure
- wildfires
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