Estimación de variables forestales de pinus sylvestris l. en el contexto de un inventario forestal aplicando tecnología LiDAR aeroportada
[EN] The aim of this study is to estimate a number of forest structure parameters by using airborne LiDAR data (nominal density of 0.5 points m(-2)) in the context of a forest inventory. The estimated variables are: volume, tree density, basal area, dominant height, mean square diameter and abovegro...
| Autores: | , , , |
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| Tipo de documento: | artigo |
| Data de publicação: | 2018 |
| País: | España |
| Recursos: | Universitat Politècnica de València (UPV) |
| Repositório: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | espanhol |
| OAI Identifier: | oai:riunet.upv.es:10251/120644 |
| Acesso em linha: | https://riunet.upv.es/handle/10251/120644 |
| Access Level: | Acceso aberto |
| Palavra-chave: | LiDAR Inventario forestal Ordenación forestal Modelo Digital de Elevaciones Canopy Height Model INGENIERIA CARTOGRAFICA, GEODESIA Y FOTOGRAMETRIA INGENIERIA AGROFORESTAL |
| Resumo: | [EN] The aim of this study is to estimate a number of forest structure parameters by using airborne LiDAR data (nominal density of 0.5 points m(-2)) in the context of a forest inventory. The estimated variables are: volume, tree density, basal area, dominant height, mean square diameter and aboveground biomass for a stand of Pinus sylvestris L. located in Nogueruelas (Spain). The methodology used for the estimation of the variables is based on the ABA (Area Based Approach) method that involves deriving forest variables at the plot level from statistical distribution of heights extracted from LiDAR data. The best results were obtained for volume, basal area, dominant height, aboveground biomass and growth with adjusted R-2 values between 0.88 and 0.92. These results demonstrate the potential of LiDAR data for forest inventory applications. |
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