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Título
What is the most suitable height range of ALS point cloud and LiDAR metric for understorey analysis? A study case in a mixed deciduous forest, Pokupsko basin, Croatia
Autor
Año del Documento
2022
Editorial
MDPI
Descripción
Producción Científica
Documento Fuente
Remote Sensing, 2022, Vol. 14, Nº. 9, 2095
Zusammenfassung
Understorey evaluation is essential in wildlife habitat management, biomass storage and wildfire suppression, among other areas. The lack of a standardised methodology in the field measurements, and in their subsequent analysis, forces researchers to look for procedures that effectively extract understorey data to make management decisions corresponding to actual stand conditions. In this sense, when analysing the understorey characteristics from LiDAR data, it is very usual to ask: “what value should we set the understorey height range to?” It is also usual to answer by setting a numeric value on the basis of previous research. Against that background, this research aims to identify the optimal height to canopy base (HCB) filter–LiDAR metric relationship for estimating understorey height (UH) and understorey cover (UC) using LiDAR data in the Pokupsko Basin lowland forest complex (Croatia). First, several HCB values per plot were obtained from field data (measured HCBi—HCBM-i, where i ϵ (minimum, maximum, mean, percentiles)), and then they were modelled based on LiDAR metrics (estimated HCBi—HCBE-i). These thresholds, measured and estimated HCBi per plot, were used as point cloud filters to estimate understorey parameters directly on the point cloud located under the canopy layer. In this way, it was possible to predict the UH with errors (RMSE) between 0.90 and 2.50 m and the UC with errors (RMSE) between 8.8 and 18.6 in cover percentage. Finally, the sensitivity analysis showed the HCB filter (the upper threshold to select the understorey LiDAR points) is the most important factor affecting the UH estimates, while this factor and the LiDAR metric are the most important factors affecting the UC estimates.
Materias (normalizadas)
Understorey
Forests and forestry
Bosques y silvicultura
Arbustos
Deciduous forest
Forest fires - Prevention and control
Bosques - Incendios - Prevención y control
Forest ecology
Ecología forestal
Forest management
Bosques - Gestión
Sustainable development
Desarrollo sostenible
Croatia
Materias Unesco
3106 Ciencia Forestal
3106.08 Silvicultura
ISSN
2072-4292
Revisión por pares
SI
Patrocinador
Ministerio de Economía, Industria y Competitividad - (grant DI-16-08446)
Comisión Europea - (grant H2020-EO-2017; 776045)
Fundación Científica de Croacia - (project IP-2016-06-7686)
Comisión Europea - (grant H2020-EO-2017; 776045)
Fundación Científica de Croacia - (project IP-2016-06-7686)
Version del Editor
Propietario de los Derechos
© 2022 The Authors
Idioma
eng
Tipo de versión
info:eu-repo/semantics/publishedVersion
Derechos
openAccess
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