Publicação
FUNÇÃO ALOMÉTRICA DE BIOMASSA COM IMAGENS DE SATÉLITE DE ALTA RESOLUÇÃO ESPACIAL
| Resumo: | The aim of this study was to fit functions to estimate with data derived from high spatial resolution satellite images, the total biomass of Eucalyptus at local and regional scale. For this purpose, models were fit combining values of biomass estimated from forest inventory plots and vegetation indices based on Pléiades images. The function with which presented the best performance in the estimation of the total biomass, was the one that used as an independent variable the IV-SAVI, presenting a coefficient of determination (R2) of 64.6%, however without great difference for the NDVI and SR. The fit functions can be used in other regions for the same species, and similar climate and local characteristics. This approach can be used as a low cost tool to produce estimations of biomass at local and regional level. |
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| Autores principais: | Macedo, Fabrício |
| Outros Autores: | Sousa, Adélia; Gonçalves, Ana Cristina; Silva, Hélio; Rodrigues, Ricardo |
| Assunto: | Eucalipto Pleiades vegetation indices |
| Ano: | 2018 |
| País: | Portugal |
| Tipo de documento: | artigo |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade de Évora |
| Idioma: | português |
| Origem: | Repositório Científico da Universidade de Évora |
| Resumo: | The aim of this study was to fit functions to estimate with data derived from high spatial resolution satellite images, the total biomass of Eucalyptus at local and regional scale. For this purpose, models were fit combining values of biomass estimated from forest inventory plots and vegetation indices based on Pléiades images. The function with which presented the best performance in the estimation of the total biomass, was the one that used as an independent variable the IV-SAVI, presenting a coefficient of determination (R2) of 64.6%, however without great difference for the NDVI and SR. The fit functions can be used in other regions for the same species, and similar climate and local characteristics. This approach can be used as a low cost tool to produce estimations of biomass at local and regional level. |
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