| Name: | Description: | Size: | Format: | |
|---|---|---|---|---|
| 9.58 MB | Adobe PDF |
Advisor(s)
Abstract(s)
Simulation of vegetation fires very often resorts to fire-behavior models that need fuel models as
input. The lack of fuel models is a common problem for researchers and fire managers because
its quality depends on the quality/availability of data. In this study we present a method that
combines expert- and research-based knowledge with several sources of data (e.g. satellite and
fieldwork) to produce customized fuel models maps. Fuel model classes are assigned to land cover
types to produce a basemap, which is then updated using empirical and user-defined rules. This
method produces a map of surface fuel models as detailed as possible. It is reproducible, and
its flexibility relies on juxtaposing independent spatial datasets, depending on their quality or
availability. This method is developed in a ModelBuilder/ArcGis toolbox named FUMOD that
integrates ten sub-models. FUMOD has been used to map the Portuguese annual fuel models
grids since 2019, supporting regional fire risk assessments and suppression decisions. Datasets,
models and supplementary files are available in a repository (https://github.com/anasa30/PT_
FuelModels).
Description
Keywords
land cover fire-atlas burned areas time since last fire spectral vegetation indexes fuel models expert-based knowledge flexible approach automatic updates
Pedagogical Context
Citation
A.C.L. Sá, A. Benali, B.A. Aparicio, C. Bruni, C. Mota, J.M.C. Pereira, P.M. Fernandes, A method to produce a flexible and customized fuel models dataset, MethodsX, Volume 10, 2023, 102218
Publisher
Elsevier