Estimating Fuel Loads and Structural Characteristics of Shrub Communities by Using Terrestrial Laser Scanning

• Main Authors: Cecilia Alonso-Rego, Stéfano Arellano-Pérez, Carlos Cabo, Celestino Ordoñez, Juan Gabriel Álvarez-González, Ramón Alberto Díaz-Varela, Ana Daría Ruiz-González
• Format: Article
• Language: English
• Published: MDPI AG 2020-11-01
• Series: Remote Sensing
• Subjects: live/dead fuel fractions; shrub cover; shrub height; litter depth; simultaneous fitting; fuel load additivity
• Online Access: https://www.mdpi.com/2072-4292/12/22/3704

Forest fuel loads and structural characteristics strongly affect fire behavior, regulating the rate of spread, fireline intensity, and flame length. Accurate fuel characterization, including disaggregation of the fuel load by size classes, is therefore essential to obtain reliable predictions from fire behavior simulators and to support decision-making in fuel management and fire hazard prediction. A total of 55 sample plots of four of the main non-tree covered shrub communities in NW Spain were non-destructively sampled to estimate litter depth and shrub cover and height for species. Fuel loads were estimated from species-specific equations. Moreover, a single terrestrial laser scanning (TLS) scan was collected in each sample plot and features related to the vertical and horizontal distribution of the cloud points were calculated. Two alternative approaches for estimating size-disaggregated fuel loads and live/dead fractions from TLS data were compared: (i) a two-steps indirect estimation approach (IE) based on fitting three equations to estimate shrub height and cover and litter depth from TLS data and then use those estimates as inputs of the existing species-specific fuel load equations by size fractions based on these three variables; and (ii) a direct estimation approach (DE), consisting of fitting seven equations, one for each fuel fraction, to relate the fuel load estimates to TLS data. Overall, the direct approach produced more balanced goodness-of-fit statistics for the seven fractions considered jointly, suggesting that it performed better than the indirect approach, with equations explaining more than 80% of the observed variability for all species and fractions, except the litter loads.