Above ground biomass functions with vegetation indices for multiple use systems of two evergreen oaks

Remote sensing is a promising approach for above ground biomass estimation, as forest parameters can be obtained indirectly. The analysis in space and time is quite straight forward due to the flexibility of the method to determine forest crown parameters with remote sensing. It can be used to evaluate and monitoring for example the development of a forest area in time and the impact of disturbances, such as silvicultural practices or deforestation. The vegetation indices, which condense data in a quantitative numeric manner, have been used to estimate several forest parameters, such as the volume, basal area and above ground biomass. The objective of this study was the development of allometric functions to estimate above ground biomass using vegetation indices as independent variables. The vegetation indices used were the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Simple Ratio (SR) and Soil-Adjusted Vegetation Index (SAVI). QuickBird satellite data, with 0.70 m of spatial resolution, was orthorectified, geometrically and atmospheric corrected, and the digital number were converted to top of atmosphere reflectance (ToA). Forest inventory data and published allometric functions at tree level were used to estimate above ground biomass per plot. Linear functions were fitted for the monospecies and multispecies stands of two evergreen oaks (Quercus suber and Quercus rotundifolia) in multiple use systems, montados. The allometric above ground biomass functions were fitted considering the mean and the median of each vegetation index per grid as independent variable. Species composition as a dummy variable was also considered as an independent variable. The linear functions with better performance are those with mean NDVI or mean SR as independent variable. Noteworthy is that the two better functions for monospecies cork oak stands have median NDVI or median SR as independent variable. When species composition dummy variables are included in the function (with stepwise regression) the best model has median NDVI as independent variable. The vegetation indices with the worse model performance were EVI and SAVI.

ABOVE-GROUND BIOMASS ESTIMATION OF OPUNTIA FICUS-INDICA (L.) MILL. FOR FORAGE CROP IN A MEDITERRANEAN ENVIRONMENT BY USING NON-DESTRUCTIVE METHODS

In marginal lands Opuntia ficus-indica (OFI) could be used as an alternative fruit and forage crop. The plant vigour and the biomass production were evaluated in Portuguese germplasm (15 individuals from 16 ecotypes) by non-destructive methods, 2 years following planting in a marginal soil and dryland conditions. Two Italian cultivars (Gialla and Bianca) were included in the study for comparison purposes. The biomass production and the plant vigour were estimated by measuring the cladodes number and area, and the fresh (FW) and dry weight (DW) per plant. We selected linear models by using the biometric data from 60 cladodes to predict the cladode area, the FW and the DW per plant. Among ecotypes, significant differences were found in the studied biomass-related parameters and several homogeneous groups were established. Four Portuguese ecotypes had higher biomass production than the others, 3.20 Mg ha−1 on average, a value not significantly different to the improved ‘Gialla’ cultivar, which averaged 3.87 Mg ha−1. Those ecotypes could be used to start a breeding program and to deploy material for animal feeding and fruit production.