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Advisor(s)
Abstract(s)
The estimation of vegetation parameters, such as above-ground biomass, with high accuracy
using remote sensing data, represents a promising approach. The present study develops
models to estimate and map above-ground biomass of Mediterranean Quercus rotundifolia
stands using one QuickBird satellite image in pan-sharpened mode, with four multispectral
bands (blue, green, red and near infrared) and a spatial resolution of 0.70 m. The satellite
image was orthorectified, geometrically and radiometrically corrected. Object-oriented classi fication methods and multi-resolution segmentation were used to derive a vegetation mask
per forest species. Data from forest inventory (24 plots) and vegetation indices (NDVI, EVI, SR
and SAVI) derived from high spatial resolution satellite images were used for an area of
133 km2
, in southern Portugal. The statistical analysis included correlation, variance analysis
and linear regression. The linear regression models fitted included the arithmetic mean and
the median values of the vegetation indices per inventory plot as explanatory variables. The
overall results of the fitted models show a trend of better performance for those with the
median value of the vegetation index as the explanatory variable. The best fitted model
(R2 = 75.3) was associated with the Simple Ratio (SR) median value as an explanatory variable.
A Quercus rotundifolia above-ground biomass map was produced.
Description
Keywords
Above-ground biomass High spatial resolution Vegetation indices Linear regression . Escola Superior de Tecnologias e Gestão
Citation
Macedo, F. L., Sousa, A. M., Gonçalves, A. C., Marques da Silva, J. R., Mesquita, P. A., & Rodrigues, R. A. (2018). Above-ground biomass estimation for Quercus rotundifolia using vegetation indices derived from high spatial resolution satellite images. European Journal of Remote Sensing, 51(1), 932-944.
Publisher
Taylor and Francis