LEAF AREA INDEX AND CANOPY OPENNESS ESTIMATION USING HIGH SPATIAL RESOLUTION IMAGE QUICKBIRD

The aim of this paper was to evaluate and propose a high spatial resolution image analysis method, for public managers, regarding to monitoring and observation of degraded areas recuperation success. The specific objectives were: i) to obtain leaf area index (LAI) and canopy openness data in field, ii) to calculate the relation between LAI and canopy openness data sampled in field, iii) to estimate canopy openness using the Quickbird high resolution image, iv) to use data sampled in field to obtain LAI values by image, and v) to analyze the residuals between data sampled in field and that obtained by image, of twelve species monitored in the Ecological and Multiple Use Olhos D'agua Park, Brazil. The estimates of canopy openness and leaf area index of twelve Cerrado species using high resolution images were effective, as for the tolerable error of the adjustments obtained (6.9%) from the models, as for the image's practicality: it attends a larger area and larger timescale, and is efficient to evaluate the execution of revegetation projects.