Estimativa de parâmetros florestais em área de cerrado a partir de imagens do sensor landsat 8

Abstract

The obtaining of data that characterize certain forest fragment comes up against the difficult of data processing, high costs and demanded time spent with forest inventories. The use of image Digital Processing Techniques (DPT) with remote sensing data to estimate forest variables can be useful and effective tool to complement the field inventory. This study aimed to evaluate the viability of the utilization the multispectral images from OLI Landsat 8 sensor through regression analysis with field data for estimation of forest parameters. For this, it was done an inventory in order to get the forest parameters: diameter at breast height (DBH); basal area (G); total height (Ht); number of trees (N) and timber volume (V). In DPT step, they were used the reflectance and the NDVI and SAVI vegetation index values from the pixels that cover the plots of the inventory and after it was conducted the correlation analysis among bands and forest parameters. Finally, they were made the adjustment of multiples linear regression models for spatialization data. The best results related to R²aj values for models of DBH; G; Ht; N; and V, were 0.57; 0.66; 0.16; 0.34 and 0.49, respectively. The results were allowed to conclude about the use potential of the methodology for the estimation of the following traits DBH, G and V with using NDVI and the bands related the green, red and SWI. Keywords: Remote sensing; forest inventory; reflectance; vegetation index