Airborne hyperspectral images collected over San Rossore Natural Park (Pisa, Italy) by the Multispectral Infrared and Visible Imaging Spectrometer (MIVIS) on June 21st, 2000 were analyzed in order to assess the best indices for forest LAI estimation. Hemispherical photography was used for ground truth measurements, simultaneously with the overflights, in hardwood and conifer stands characterized by a LAI ranging between 1.2 and 4.5. All band combinations expressed as simple ratios and normalized indices (a total of 89 single bands, and 7832 and 3916 indices, respectively) were linearly correlated to LAI in order to detect the best correlations. Determination coefficients were analyzed by means of a graphical matrix to highlight relevant spectral regions. Normalized indices composed by the red chlorophyll absorption wavelength (680 nm) and the wavelengths after the green reflectance peak (580-640 nm) in the orange region were strongly correlated to LAI. Best results were obtained with the newly proposed Orange Slope Vegetation Index [OSVI=(ρ 620 -ρ 680 )/(ρ 620+ ρ 680 ), R 2 =0.88, RMSE=0.5). The index performed better than the normalized difference vegetation index (NDVI=(ρ 780 -ρ 680 )/(ρ 780+ ρ 680 ), R 2 =0.47) Using SAIL radiative transfer model 1 , canopy reflectance at different viewing angles and a wide range of LAI was simulated in order to verify the sensitivity of OSVI and NDVI. For LAI between 0.25 and 8 both indices resulted stable for viewing zenith angles between -60° and +60°. OSVI, being saturated with values greater than 4, could be used to estimate a wider range of LAI than NDVI. Application of GeoSail model 2 resulted in a good agreement between simulated and measured OSVI.

A large part of arid areas in tropical and sub-tropical regions are dominated by sparse xerophytic vegetation, which are essential for providing products and services for local populations. While a large number of researches already exist for the derivation of wall-to-wall estimations of above ground biomass (AGB) with remotely sensed data, only a few of them are based on the direct use of non-photogrammetric aerial photography. In this contribution we present an experiment carried out in a study area located in the Santiago Island in the Cape Verde archipelago where a National Forest Inventory (NFI) was recently carried out together with a new acquisition of a visible high-resolution aerial orthophotography. We contrasted two approaches: single-tree, based on the automatic delineation of tree canopies; and area-based, on the basis of an automatic image classification. Using 184 field plots collected for the NFI we created parametric models to predict AGB on the basis of the crown projection area (CPA) estimated from the two approaches. Both the methods produced similar root mean square errors (RMSE) at pixel level 45% for the single-tree and 42% for the area-based. However, the latest was able to better predict the AGB along all the variable range, limiting the saturation problem which is evident when the CPA tends to reach the full coverage of the field plots. These findings demonstrate that in regions dominated by sparse vegetation, a simple aerial orthophoto can be used to successfully create AGB wall-to-wall predictions. The level of these estimations' uncertainty permits the derivation of small area estimations useful for supporting a more correct implementation of sustainable management practices of wood resources.

On June 21st, 2000 the Multispectral Infrared and Visible Imaging Spectrometer (MIVIS) and the Visible Infrared Spectrometer have been mounted on a Casa 212 aircraft in order to compare the two sensors for environmental monitoring. This study relates the hyperspectral data collected over San Rossore Reserve (Pisa, Italy) by the two airborne imaging spectrometers to ground measurements of forest structure and biochemical status. The images were acquired on a total of 122 channels with a spectral resolution of up to 2.5 nm and a spatial resolution of 2.5 and 5 meters for overflights at 1500 and 3000 m, respectively. After correction for atmospheric effects, a good agreement was found between the spectra acquired by the two imaging spectrometers and at the two altitudes. An extensive field measurement campaign was carried out contextually to the flight to provide a ground truth for the airborne data. Measurements focused on 11 stands of various age, comprising both natural hardwoods and pine plantations (Pinus pinea and P. pinaster). Biophysical (stand density, basal area, height, green canopy depth and leaf area index, together with specific leaf area) and biochemical parameters (leaf water content, foliar nitrogen, carotenoids and chlorophyll concentration) were measured for each stand. Vegetation indices (VI) taken from the literature were computed from airborne reflectances and related to each parameter. Very good relationships were found between vegetation indices and biochemical compounds. Biochemical concentrations (g g -1 ) were better correlated to VIs than biochemical contents (g m -2 ). Pearson coefficients higher than 0.9 were found for chlorophyll, carotenoids and nitrogen concentration and for carbon-to-nitrogen ratio, whilst tissue carbon and water content had R 2 higher than 0.8.