Estimativa e espacialização das variáveis biofísicas, utilizando dados de campo e de sensoriamento remoto em dois sítios de floresta tropical no estado do Amazonas, Brasil
Remote sensing (RS), geographic information system (GIS) and global positioning system (GPS) are important tools for different steps of forest inventories, including estimates of biomass. The size and complexity in the surveys of the Amazonia vegetation makes the development of these combinations de...
| Autor principal: | Celes, Carlos Henrique Souza |
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| Grau: | Dissertação |
| Idioma: | por |
| Publicado em: |
Instituto Nacional de Pesquisas da Amazônia - INPA
2020
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| Acesso em linha: |
https://repositorio.inpa.gov.br/handle/1/5054 http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4480966D1 |
| Resumo: |
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Remote sensing (RS), geographic information system (GIS) and global positioning system (GPS) are important tools for different steps of forest inventories, including estimates of biomass. The size and complexity in the surveys of the Amazonia vegetation makes the development of these combinations decisive for the estimation of biophysical variables. This work aimed to build a methodology for biophysical variables mapping using field data and remote sensing techniques. The field data were derived from continuous forest inventory system (IFC) of the forest management laboratory at the Amazonia Research National Institute (INPA-LMF). The remote sensing data were derived from TM sensor of the Landsat 5 satellite, and the surface digital elevation model (MDS) of the SRTM mission. The two areas chosen for this study were called forest sites (SF) in the municipalities of Barcelos and Maués in the state of Amazonas. In this work were used 58 and 76 plots respectively for estimate forests biophysical variables. Equations were fitted to estimate and distribute spatially the biophysical variables. Estimates indicated that the forest site Barcelos is smaller than the forest site in Maués. The best equation adjusted was to commercial volume at the forest site Maués. This one obtained a R2 equal 0.29 and estimate standard error of 22.12%. When equations are significant, the equation image was similar to the interpolation image. The regions with the largest difference in this case were in empty sample, that are distant regions of the plots. The advantage of the equations use is the manifestation of the forest spectral feature that explain the spatial variation of biophysical characteristics. |