Analysis of the Influence of Plot Size and LiDAR Density on Forest Structure Attribute Estimates

This paper assesses the combined effect of field plot size and LiDAR density on the estimation of four forest structure attributes: volume, total biomass, basal area and canopy cover. A total of 21 different plot sizes were considered, obtained by decreasing the field measured plot radius value from...

Descripción completa

Detalles Bibliográficos
Autores: Ruiz Fernández, Luis Ángel|||0000-0003-0073-7259, Hermosilla, T., Mauro, Francisco, Godino, Miguel
Tipo de recurso: artículo
Fecha de publicación:2014
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/61252
Acceso en línea:https://riunet.upv.es/handle/10251/61252
Access Level:acceso abierto
Palabra clave:Forest inventory
LiDAR
Plot size
Data density
Forest structure
Forest attributes
Remote sensing
INGENIERIA CARTOGRAFICA, GEODESIA Y FOTOGRAMETRIA
Descripción
Sumario:This paper assesses the combined effect of field plot size and LiDAR density on the estimation of four forest structure attributes: volume, total biomass, basal area and canopy cover. A total of 21 different plot sizes were considered, obtained by decreasing the field measured plot radius value from 25 to 5 m with regular intervals of 1 m. LiDAR data densities were simulated by randomly removing LiDAR pulses until reaching nine different density values. In order to avoid influence of the digital terrain model spatial resolution, eight different resolutions were considered (from 0.25 to 2 m grid size) and tested. A set of per-plot LiDAR metrics was extracted for each parameter combination. Prediction models of forest attributes were defined using forward stepwise ordinary least-square regressions. Results show that the highest R 2 values are reached by combining large plot sizes and high LiDAR data density values. However, plot size has a greater effect than LiDAR point density. In general, minimum plot areas of 500–600 m2 are needed for volume, biomass and basal area estimates, and of 300–400 m2 for canopy cover. Larger plot sizes do not significantly increase the accuracy of the models, but they increase the cost of fieldwork.