Detalhes bibliográficos
Ano de defesa: |
2016 |
Autor(a) principal: |
Oliveira, Julianne de Castro |
Orientador(a): |
Não Informado pela instituição |
Banca de defesa: |
Não Informado pela instituição |
Tipo de documento: |
Tese
|
Tipo de acesso: |
Acesso aberto |
Idioma: |
eng |
Instituição de defesa: |
Biblioteca Digitais de Teses e Dissertações da USP
|
Programa de Pós-Graduação: |
Não Informado pela instituição
|
Departamento: |
Não Informado pela instituição
|
País: |
Não Informado pela instituição
|
Palavras-chave em Português: |
|
Link de acesso: |
http://www.teses.usp.br/teses/disponiveis/11/11150/tde-28092016-130547/
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Resumo: |
Radiative transfer models (RTM) have been successfully used to simulate the effect of forest structural and biochemical characteristics, such as tree sizes and shapes, leaf area index (LAI), leaf angle distribution (LAD), on the canopy radiative budget. One particular use of RTM is the analysis of the reflected light by the canopy, which can be measured by remote sensing techniques. RTM allows a physically based interpretation of the reflectance quantity measured by satellite and can help disentangling the multiple source of variation of the reflectance signal. The DART model - Discrete Anisotropic Radiative Transfer - is one of the most complex three-dimensional RTM, since it uses an accurate mathematical approach of physical processes and a great realism of the landscapes under simulation. Its main simulation outputs are the reflectance of the scene (e.g. a forest stand) at particular spectral wavelength from bottom and top of the atmosphere, the simulation of satellite images, and the simulation of localized radiative budget. Despite the DART potential in analyzing biophysical parameters from remote sensing data, few studies report its application in forest plantations in Brazil, which can have a large number of important field measurements to parameterize the model. The main objective of this project is to evaluate if the DART RTM can help understand the satellite-measured canopy reflectance of Eucalyptus plantations and in particular if DART RTM can improve LAI estimation rather than use only empirical models, as spectral vegetation indices. DART model was parameterized using extensive in situ data obtained from a clonal test, part of the EucFlux project. The specific objectives were: i) parameterize the DART model at different growth stages and for different clonal materials of Eucalyptus plantations and compare simulated reflectance with high resolution satellite images acquired on the same site; ii) analyze the relationship between the Leaf Area Index (LAI) and Spectral Vegetation Indices (SVI) based on empirical relationships, and then use the DART model; iii) analyze the advantage and drawbacks of using a generic relationship or a clone-specific relationship between LAI and SVI, and find other criteria for grouping the genotypes in the same. In Chapter 2, we demonstrated the good performance of DART to simulate canopy reflectance of Eucalyptus forest plantations. The simulated reflectance was similar to those measured by very high resolution images from satellite, despite some discrepancies found in the near infrared region. Then, in Chapter 3, we showed that empirical relationships between LAI and SVI were able to give a reasonable precision for generic relationships; however, genotype-scale relationships gave even better results. The same methodology applied on a DART simulated dataset lead to the same conclusions. An intermediate possibility of grouping the genotypes regarding their litter or leaf optical properties gave intermediate performance. We finally concluded about the superiority of NDVI to estimate LAI using a genotype-specific calibration. Overall, DART simulated datasets created in this work enable to calibrate different LAI -SVI relationships in terms of genotypes, sensors and acquisition characteristics. |