Analysis of Mediterranean Vegetation Fuel Type Changes Using Multitemporal LiDAR

Increasing fire size and severity over the last few decades requires new techniques to accurately assess canopy fuel conditions and change over larger areas. This article presents an analysis on vegetation changes by mapping fuel types (FT) based on conditional rules according to the Prometheus clas...

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Main Authors: Alba García-Cimarras, José Antonio Manzanera, Rubén Valbuena
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Forests
Subjects:
Online Access:https://www.mdpi.com/1999-4907/12/3/335
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author Alba García-Cimarras
José Antonio Manzanera
Rubén Valbuena
author_facet Alba García-Cimarras
José Antonio Manzanera
Rubén Valbuena
author_sort Alba García-Cimarras
collection DOAJ
description Increasing fire size and severity over the last few decades requires new techniques to accurately assess canopy fuel conditions and change over larger areas. This article presents an analysis on vegetation changes by mapping fuel types (FT) based on conditional rules according to the Prometheus classification system, which typifies the vertical profile of vegetation cover for fuel management and ecological purposes. Using multi-temporal LiDAR from the open-access Spanish national surveying program, we selected a 400 ha area of interest, which was surveyed in 2010 and 2016 with scan densities of 0.5 and 2 pulses·m<sup>−2</sup>, respectively. FTs were determined from the distribution of LiDAR heights over an area, using grids with a cell size of 20 × 20 m. To validate the classification method, we used a stratified random sampling without replacement of 15 cells per FT and made an independent visual assessment of FT. The overall accuracy obtained was 81.26% with a Kappa coefficient of 0.73. In addition, the relationships among different stand structures and ecological factors such as topographic aspect and forest vegetation cover types were analyzed. Our classification algorithm revealed that stands lacking understory vegetation usually appeared in shady slopes, which were mainly covered by beech stands, whereas sunny areas were preferentially covered by oak stands, where the understory reached greater height thanks to more light availability. Our analysis on FT changes during that 6 year time span revealed potentially hazardous transitions from cleared forests towards a vertical continuum of canopy fuels, where wildfire events would potentially reach tree crowns, especially in oak forests and southern slopes with higher sun exposure for lower fuel moistures and increased flammability. Accurate methods to characterize forest canopy fuels and change over time can help direct forest management activities to priority areas with greater fire hazard. Multi-date canopy fuel information indicated that while some forest types experienced a growth of the shrub layer, others presented an understory decrease. On the other hand, loss of understory was more frequently detected in beech stands; thus, those forests place lower risk of wildfire spread. Our approach was developed using low-density and publicly available datasets and was based on direct canopy fuel measurements from multi-return LiDAR data that can be accurately translated and mapped according to standard fuel type categories that are familiar to land managers.
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spelling doaj.art-89012bd01a86437bbe2984a8072146c52023-11-21T10:14:56ZengMDPI AGForests1999-49072021-03-0112333510.3390/f12030335Analysis of Mediterranean Vegetation Fuel Type Changes Using Multitemporal LiDARAlba García-Cimarras0José Antonio Manzanera1Rubén Valbuena2Research Group SILVANET, Universidad Politécnica de Madrid (UPM), ETSI Montes, Forestal y del Medio Natural, 28040 Madrid, SpainResearch Group SILVANET, Universidad Politécnica de Madrid (UPM), ETSI Montes, Forestal y del Medio Natural, 28040 Madrid, SpainThoday Building, School of Natural Sciences, Bangor University, Bangor LL57 2UW, UKIncreasing fire size and severity over the last few decades requires new techniques to accurately assess canopy fuel conditions and change over larger areas. This article presents an analysis on vegetation changes by mapping fuel types (FT) based on conditional rules according to the Prometheus classification system, which typifies the vertical profile of vegetation cover for fuel management and ecological purposes. Using multi-temporal LiDAR from the open-access Spanish national surveying program, we selected a 400 ha area of interest, which was surveyed in 2010 and 2016 with scan densities of 0.5 and 2 pulses·m<sup>−2</sup>, respectively. FTs were determined from the distribution of LiDAR heights over an area, using grids with a cell size of 20 × 20 m. To validate the classification method, we used a stratified random sampling without replacement of 15 cells per FT and made an independent visual assessment of FT. The overall accuracy obtained was 81.26% with a Kappa coefficient of 0.73. In addition, the relationships among different stand structures and ecological factors such as topographic aspect and forest vegetation cover types were analyzed. Our classification algorithm revealed that stands lacking understory vegetation usually appeared in shady slopes, which were mainly covered by beech stands, whereas sunny areas were preferentially covered by oak stands, where the understory reached greater height thanks to more light availability. Our analysis on FT changes during that 6 year time span revealed potentially hazardous transitions from cleared forests towards a vertical continuum of canopy fuels, where wildfire events would potentially reach tree crowns, especially in oak forests and southern slopes with higher sun exposure for lower fuel moistures and increased flammability. Accurate methods to characterize forest canopy fuels and change over time can help direct forest management activities to priority areas with greater fire hazard. Multi-date canopy fuel information indicated that while some forest types experienced a growth of the shrub layer, others presented an understory decrease. On the other hand, loss of understory was more frequently detected in beech stands; thus, those forests place lower risk of wildfire spread. Our approach was developed using low-density and publicly available datasets and was based on direct canopy fuel measurements from multi-return LiDAR data that can be accurately translated and mapped according to standard fuel type categories that are familiar to land managers.https://www.mdpi.com/1999-4907/12/3/335vegetation changefuel typefuel modelsPrometheus classification systemLiDAR
spellingShingle Alba García-Cimarras
José Antonio Manzanera
Rubén Valbuena
Analysis of Mediterranean Vegetation Fuel Type Changes Using Multitemporal LiDAR
Forests
vegetation change
fuel type
fuel models
Prometheus classification system
LiDAR
title Analysis of Mediterranean Vegetation Fuel Type Changes Using Multitemporal LiDAR
title_full Analysis of Mediterranean Vegetation Fuel Type Changes Using Multitemporal LiDAR
title_fullStr Analysis of Mediterranean Vegetation Fuel Type Changes Using Multitemporal LiDAR
title_full_unstemmed Analysis of Mediterranean Vegetation Fuel Type Changes Using Multitemporal LiDAR
title_short Analysis of Mediterranean Vegetation Fuel Type Changes Using Multitemporal LiDAR
title_sort analysis of mediterranean vegetation fuel type changes using multitemporal lidar
topic vegetation change
fuel type
fuel models
Prometheus classification system
LiDAR
url https://www.mdpi.com/1999-4907/12/3/335
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