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A dynamic and evidence-based approach to mapping burn potential
by
Ruscalleda-Alvarez, Jaume
, van Dongen, Richard
, Gosper, Carl R.
in
Australia
/ climate
/ Climate variability
/ Deserts
/ Ecosystem management
/ fire history
/ Landsat
/ Landsat satellites
/ Mapping
/ Native peoples
/ Prescribed fire
/ Recovery
/ Remote sensing
/ risk
/ Satellite imagery
/ Variability
/ Vegetation
/ wildfires
2023
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A dynamic and evidence-based approach to mapping burn potential
by
Ruscalleda-Alvarez, Jaume
, van Dongen, Richard
, Gosper, Carl R.
in
Australia
/ climate
/ Climate variability
/ Deserts
/ Ecosystem management
/ fire history
/ Landsat
/ Landsat satellites
/ Mapping
/ Native peoples
/ Prescribed fire
/ Recovery
/ Remote sensing
/ risk
/ Satellite imagery
/ Variability
/ Vegetation
/ wildfires
2023
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While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
A dynamic and evidence-based approach to mapping burn potential
by
Ruscalleda-Alvarez, Jaume
, van Dongen, Richard
, Gosper, Carl R.
in
Australia
/ climate
/ Climate variability
/ Deserts
/ Ecosystem management
/ fire history
/ Landsat
/ Landsat satellites
/ Mapping
/ Native peoples
/ Prescribed fire
/ Recovery
/ Remote sensing
/ risk
/ Satellite imagery
/ Variability
/ Vegetation
/ wildfires
2023
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A dynamic and evidence-based approach to mapping burn potential
Journal Article
A dynamic and evidence-based approach to mapping burn potential
2023
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Overview
Background: Fire management is a crucial part of managing ecosystems. The years since last burn (YSLB) metric is commonly used in fire planning to predict when an area might be suitable to burn; however, this metric fails to account for variable recovery due to climate variability.Aim: The aim of this study was to develop a predictor of when an area may be able to ‘carry’ fire based on observed patterns of vegetation recovery and fire occurrence that is responsive to climate variability.Methods: Fire history maps and Landsat satellite imagery within the Great Victoria Desert of Australia were used to map vegetation recovery following fire. Burn potential models were then created by calculating the distributions of YSLB and vegetation recovery values for areas that subsequently burnt.Key result: A burn potential model based on vegetation recovery is a better predictor of when an area is likely to burn than a model based on YSLB.Conclusions: A burn potential model based on vegetation recovery provides an evidence-based and dynamic assessment of whether an area is likely to burn.Implications: This approach provides a model that is responsive to climate variability that can assist fire managers in burn planning and assessing fire risk.
Publisher
CSIRO
Subject
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