LadderFuelsR: A new automated tool for vertical fuel continuity analysis and crown base height detection using light detection and ranging
Widespread fuel accumulation in various strata is increasing the risk of high-severity, crown-fires. Knowing the vertical forest structure is a crucial factor for fire management planning.Light detection and ranging (LiDAR) sensors have successfully retrieved the main characteristics of the vertical...
| Autores: | , , , |
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| Formato: | artículo |
| Fecha de publicación: | 2024 |
| País: | España |
| Recursos: | Universidad de Castilla-La Mancha |
| Repositorio: | RUIdeRA. Repositorio Institucional de la UCLM |
| OAI Identifier: | oai:ruidera.uclm.es:10578/39582 |
| Acesso em linha: | https://doi.org/10.1111/2041-210X.14427 https://besjournals.onlinelibrary.wiley.com/doi/full/10.1111/2041-210X.14427 https://hdl.handle.net/10578/39582 |
| Access Level: | acceso abierto |
| Palavra-chave: | Crown base height Crown fire Fuel gaps Ladder fuels LiDAR |
| Resumo: | Widespread fuel accumulation in various strata is increasing the risk of high-severity, crown-fires. Knowing the vertical forest structure is a crucial factor for fire management planning.Light detection and ranging (LiDAR) sensors have successfully retrieved the main characteristics of the vertical structure of forests. However, detecting and vertically mapping the various fuel strata that can act as ladder fuels (i.e. fuel arrangements that will bring the fire from the surface to the canopy) is challenging and limits our ability to manage the most hazardous forests.Here we show how using LiDAR data and the LadderFuelsR package, developed in the R platform, can provide an automated tool for analysing the vertical fuel structure of a forest and to calculate crown base height (CBH) at tree-level, among other parameters. We include a suite of tools integrated into a sequential workflow for: (1) calculating the leaf area density (LAD) profiles of each segmented tree; (2) identifying gaps and the non-continuous fuel layers present; (3) estimating the vertical distance between fuel layers; and (4) retrieving their base height and depth. Additionally, other functions recalculate previous metrics after considering vertical distances greater than certain threshold and calculates the LAD percentage comprised in each fuel layer removing fuel layers below a specified value. Moreover, it calculates tree's CBH based on three criteria: maximum LAD, and both the largest and the last vertical distance between fuel layers. Additionally, when the LAD profiles showed only one fuel layer with CBH at the minimum base height, it identifies the tree's CBH by performing a segmented linear regression. Finally, a collection of plotting functions is developed to represent all previous metrics.This tool has been tested with different LiDAR sensors and thousands of trees in several Pinus pinaster forest areas in Central Spain, and its accuracy has been evaluated using field-based tree CBH in Pinus palustris Mills dominated forests in Florida (USA). This tool provides accurate information about the vertical structure of a forest, which can be used for prioritizing treatment areas to reduce fire hazard or identify high crown-fire risk areas. |
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