Modeling diameter distributions in radiata pine plantations in Spain with existing countrywide LiDAR data

Abstract

& Key message We evaluated the use of low-density airborne laser scanning data to estimate diameter distributions in radiata pine plantations. The moment-based parameter recovery method was used to estimate the diameter distributions, considering LiDAR metrics as explanatory variables. The fitted models explained more than 77% of the observed variability. This approach can be replicated every 6 years (temporal cover planned for countrywide LiDAR flights in Spain). & Context The estimation of stand diameter distribution is informative for forest managers in terms of stand structure, forest growth model inputs, and economic timber value. In this sense, airborne LiDAR may represent an adequate source of information. & Aims The objective was to evaluate the use of low-density Spanish countrywide LiDAR data for estimating diameter distributions in Pinus radiata D. Don stands in NW Spain. & Methods The empirical distributions were obtained from 25 sample plots. We applied the moment-based parameter recovery method in combination with the Weibull function to estimate the diameter distributions, considering LiDAR metrics as explanatory variables. We evaluated the results by using the Kolmogorov-Smirnov (KS) test and a classification tree and random forest (RF) to relate the KS test result for each plot to stand-level variables.& Results The models used to estimate average (d m ) and quadratic (d g ) mean diameters from LiDAR metrics, required for recovery of the Weibull parameters, explained a high percentage of the observed variance (77 and 80%, respectively), with RMSE values of 3.626 and 3.422 cm for the same variables. However, the proportion of plots accepted by the KS was low. This poor performance may be due to the strictness of the KS test and/or by the characteristics of the LiDAR flight. & Conclusion The results justify the assessment of this approach over different species and forest types in regional or countrywide surveys.

Comparing Johnson’s SB and Weibull Functions to Model the Diameter Distribution of Forest Plantations through ALS Data

“…Nationwide data have been applied to many forest-oriented studies, showing promising results in, e.g., Finland [62,63], Sweden [64], and Denmark [65]. Likewise, the Spanish survey proved to be a consistent data source for different forest applications [34,[66][67][68][69][70]. However, nationwide ALS surveys are planned to reduce the flight costs so they present non-optimum scanning parameters for forest inventory, generally deriving low-density point clouds [71].…”

“…The altitude of most sites ranges 400-750 m and the slopes often exceed 15%. The forests are representative of P. radiata stands in NW of the Iberian Peninsula and are thus mainly characterized by high planting-density, low-intensity silvicultural treatments, and the presence of moderate shrub fuel loads (for more details see [34,35]).…”

Patterns of Density and Production in the Community Forests of the Sierra Madre Occidental, Mexico

“…The empirical diameter distribution is an important attribute of a forest community and widely used for characterizing forest structure [9]. The distribution of the tree diameter at breast height (dbh; cm), frequently used as an input for forest growth models, enables economic assessment of timber value and the development of management schedules [10]. Because of its flexibility and ability to describe a wide range of unimodal distributions, the Weibull function is a preferred model [11][12][13].…”

Estimación de la distribución vertical de combustibles finos del dosel de copas en masas de Pinus sylvestris empleando datos LiDAR de baja densidad

“…En España se encuentran disponibles en la actualidad datos LiDAR de baja resolución (0,5 primeros retornos m -2 ) para una buena parte de la superficie del territorio gracias a los vuelos del Plan Nacional de Ortofotografía Aérea (PNOA) y éstos ya han demostrado ser de gran utilidad en la estimación de variables de interés para la gestión forestal (p. ej. Alberdi et al, 2017;Arias-Rodil et al, 2018;Domingo et al, 2017Domingo et al, , 2018Domingo et al, , 2019Guerra-Hernández et al, 2016a,b;Jiménez et al, 2017;Lekuona Zazuo et al, 2017, Martín-García et al, 2017Montealegre et al, 2016;Sánchez Alberola et al, 2018) y el riesgo de incendios (González-Ferreiro et al, 2014Montealegre et al, 2014Montealegre et al, , 2017. El objetivo de este estudio es evaluar el potencial de estos datos LiDAR de baja resolución para modelizar la distribución vertical de combustibles del dosel de copas, empleando como datos de entrenamiento los datos de parcelas del Cuarto Inventario Forestal Nacional (IFN4) instaladas en rodales de Pinus sylvestris L. en Galicia (noroeste de España).…”