STRUCTURAL CHARACTERIZATION OF CANOPIES OF Eucalyptus spp. USING RADIOMETRIC DATA FROM TM/Landsat 5

Empirical approaches and, more recently, physical approaches, have grounded the establishment of logical connections between radiometric variables derived from remote data and biophysical variables derived from vegetation cover. This study was aimed at evaluating correlations of dendrometric and den...

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Detalles Bibliográficos
Autores: Pacheco, Ludmila Roque Ferraz, Ponzoni, Flávio Jorge, Santos, Sandra Benfica dos, Andrades Filho, Clódis de Oliveira, Mello, Márcio Pupin, Campos, Rogério Costa
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2016
País:Brasil
Institución:Universidade Federal de Lavras (UFLA)
Repositorio:Cerne (Online)
Idioma:inglés
OAI Identifier:oai:cerne.ufla.br:article/804
Acceso en línea:https://cerne.ufla.br/site/index.php/CERNE/article/view/804
Access Level:acceso abierto
Palabra clave:Spectral characterization
estimate of biophysical data
canopy refl ectance.
Descripción
Sumario:Empirical approaches and, more recently, physical approaches, have grounded the establishment of logical connections between radiometric variables derived from remote data and biophysical variables derived from vegetation cover. This study was aimed at evaluating correlations of dendrometric and density data from canopies of Eucalyptus spp., as collected in Capão Bonito forest unit, with radiometric data from imagery acquired by the TM/Landsat-5 sensor on two orbital passages over the study site (dates close to fi eld data collection). Results indicate that stronger correlations were identifi ed between crown dimensions and canopy height with near-infrared spectral band data (ρs4), irrespective of the satellite passage date. Estimates of spatial distribution of dendrometric data and canopy density (D) using spectral characterization were consistent with the spatial distribution of tree ages during the study period. Statistical tests were applied to evaluate performance disparities of empirical models depending on which date data were acquired. Results indicated a signifi cant difference between models based on distinct data acquisition dates.