Estimación de variables de combustible de copa y de masa, caracterizando el efecto de las claras en su estructura usando LiDAR aerotransportado

Abstract

Forest fires are a major threat in NW Spain. The importance and frequency of these events in the area suggests the need for fuel management programs to reduce the spread and severity of forest fires. Thinning treatments can contribute for fire risk reduction, because they cut off the horizontal continuity of forest fuels. Besides, it is necessary to conduct a fire risk management based on the knowledge of fuel allocation, since fire behaviour and fire spread study is dependent on the spatial factor. Therefore, mapping fuel for different silvicultural scenarios is essential. Modelling forest variables and forest structure parameters from LiDAR technology is the starting point for developing spatiallyexplicit maps. This is essential in the generation of fuel maps since field measurements of canopy fuel variables is not feasible. In the present study, we evaluated the potential of LiDAR technology to estimate canopy fuel variables and other stand variables, as well as to identify structural differences between silvicultural managed and unmanaged P. pinaster Ait. stands. Independent variables (LiDAR metrics) of greater explanatory significance were identified and regression analyses indicated strong relationships between those and field-derived variables (R 2 varied between 0.86 and 0.97). Significant differences were found in some LiDAR metrics when compared thinned and unthinned stands. Results showed that LiDAR technology allows to model canopy fuel and stand variables with high precision in this species, and provides useful information for identifying areas with and without silvicultural management.Key words: Pinus pinaster, Airborne Laser Scanning (ALS), fuel management, canopy fuel load, canopy bulk density, canopy base height. Estimación de variables de combustible de copa y de masa, caracterizando el efecto de las claras en su estructura usando LiDAR aerotransportadoResumen: Los incendios forestales suponen una gran amenaza en el NO de España. La importancia y frecuencia de estos eventos en la zona sugiere la necesidad de programas de gestión del combustible para reducir la propagación y severidad de los incendios. La realización de una selvicultura de claras puede contribuir a la reducción del riesgo de incendio, ya que ocasiona una ruptura de la continuidad horizontal del combustible forestal. Además, es necesario realizar una gestión del riesgo de incendio basada en el conocimiento de la localización del combustible sobre el

Improving silvicultural practices for Mediterranean forests through fire behaviour modelling using LiDAR-derived canopy fuel characteristics

“…The results obtained for Pinus pinaster forest must be treated with caution, given the very small sample size, although they provide some information about the variables that potentially explain the biomass components. The R 2 values obtained were similar to those obtained by Hevia et al (2016).…”

“…Several studies using either discrete return or full waveform data have demonstrated the LiDAR potential for estimating canopy fuel metrics (González-Olabarria et al 2012;Jakubowksi et al 2013;González-Ferreiro et al 2014;Hermosilla et al 2014;Hevia et al 2016). Typically, discrete systems derive LIDAR metrics related to canopy height and canopy closure, which subsequently are used as independent variables in regression models (Andersen et al 2005;Hall et al 2005;Erdody and Moskal 2010;Skowronski et al 2011;González-Ferreiro et al 2014).…”

Thinning- and tree-growth-caused changes in canopy cover and stand height and their estimation using low-density bitemporal airborne lidar measurements – a case study in hemi-boreal forests

“…The first-to-allechoes ratio in our dataset was slightly greater for the lower pulse repetition frequency compared to Naesset (2009), but that could be related to different scanners. CC ALS estimates from ALS point clouds were significantly influenced by commercial thinning, as found in other studies (Ellis et al, 2016;Hevia et al, 2016). In our study, the CC ALS decreased due to thinning by approximately 20% in leaf-on and leaf-off conditions.…”

“…Zhao et al (2018) demonstrated a strong correlation between the field-measured and lidar-based forest height growth and biomass increment predictions, and with the availability of high-density ALS data (>7 points per square metre, p m −2 ), change detection at the single-tree level could be realistic, provided with bi-temporal high-density ALS datasets. Hevia et al (2016) carried out thinning experiments with different intensities in four pure and even-aged maritime pine (Pinus pinaster Aiton) stands and found that canopy cover estimates were good indicators for thinning detection. Such reliable methods for mapping of disturbances and forest growth are necessary for national forest stock reporting, but can also enable pre-targeting of forest inventory fieldwork.…”

A Full-Waveform Airborne Laser Scanning Metric Extraction Tool for Forest Structure Modelling. Do Scan Angle and Radiometric Correction Matter?

“…On the other hand, discrete airborne laser scanning (ALS D ) can register larger areas, and it has been widely used to estimate some forest variables at stand-and individual-tree-level by tree segmentation approaches (e.g., [10,11]). Some of them are forest structure variables such as diameter at breast height (DBH) [12,13], basal area [14,15], stem volume [16,17], stem density [13][14][15], stand volume [18,19], fractional cover/gap fraction, and leaf area index (LAI) [20,21]; forest mass variables, such as biomass components [13,17,19]; and forest fuel variables, such as mean and dominant tree heights [18,22], canopy base height, canopy fuel load, and canopy bulk density [19,23]. Moreover, ALS D data have also been used in combination with multispectral or hyperspectral images to classify tree species [24,25] and fuel types [24,26,27].…”