LiDAR technology applied to vegetation quantification and qualification

• Ano de defesa: 2014
• Autor(a) principal: Görgens, Eric Bastos
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Biblioteca Digitais de Teses e Dissertações da USP
• Palavras-chave em Português: ALS; Estimação de volume; Laser; LiDAR metrics; Métricas LiDAR; Perfil vertical; Vertical profile; Volume estimation
• Link de acesso: http://www.teses.usp.br/teses/disponiveis/11/11150/tde-10042015-112503/

The methodology to quantify vegetation from airborne laser scanning (or LiDAR - Light Detection And Ranging) is somehow consolidated, but some concerns are still in the checklist of the scientific community. This thesis aims to bring some of those concerns and try to contribute with some results and insights. Four aspects were studied along this thesis. In the first study, the effect of threshold heights (minimum height and height break) in the quality of the set of metrics was investigated aiming the volume estimation of a eucalyptus plantation. The results indicate that higher threshold height may return a better set of metrics. The impact of threshold height was more evident in young stands and for canopy density metrics. In the second study, the stability of the LiDAR metrics between different LiDAR surveys over the same area was analyzed. This study demonstrated how the selection of stable metrics contributed to generate reliable models between different data sets. According to our results, the height metrics provided the greatest stability when used in the models, specifically the higher percentiles (>50%) and the mode. The third study was designed to evaluate the use of machine learning tools to estimate wood volume of eucalyptus plantations from LiDAR metrics. Rather than being limited to a subset of LiDAR metrics in attempting explain as much variability in a dependent variable as possible, artificial intelligence tools explored the complete metrics set when looking for patterns between LiDAR metrics and stand volume. The fourth and last study has focused upon several highly important forest typologies, and shown that it is possible to differentiate the typologies through their vertical profiles as derived from airborne laser surveys. The size of the sampling cell does have an influence on the behavior observed in analyses of spatial dependence. Each typology has its own specific characteristics, which will need to be taken into consideration in projects targeting monitoring, inventory construction, and mapping based upon airborne laser surveys. The determination of a converged vertical profile could be achieved with data representing 10 % of the area for all typologies, while for some typologies 2 % coverage was sufficient.