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 density data from canopies of Eucalyptus spp., as collected in Capao 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 field data collection). Results indicate that stronger correlations were identified between crown dimensions and canopy height with near-infrared spectral band data (rho(s)4), 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 significant difference between models based on distinct data acquisition dates.

Estimativa do índice de área foliar e temperatura em uma área de eucalipto

It is known that the presence of large masses of vegetation is a factor that can influence the microclimate of a region. In this paper we analyzed the correlation between leaf area index (LAI) and land surface temperature (LST), both estimated from remote sensing images from Landsat-5 TM in an area of eucalyptus plantation, and these estimates were compared to the observed data. The correlation between LAI and LST was not significant (16%), which indicates that there is no necessarily a direct influence of vegetation in the local temperature. The comparison between estimated and observed data shows that the application of remote sensing techniques in the estimative of interested variables is efficient, because the estimatives followed consistently the observed values.