The design and calibration of a new hyperspectral Compact Laboratory Spectro-Goniometer (CLabSpeG) is presented. CLabSpeG effectively measures the bidirectional reflectance Factor (BRF) of a sample, using a halogen light source and an Analytical Spectral Devices (ASD) spectroradiometer. The apparatus collects 4356 reflectance data readings covering the spectrum from 350 nm to 2500 nm by independent positioning of the sensor, sample holder, and light source. It has an azimuth and zenith resolution of 30 and 15 degrees, respectively. CLabSpeG is used to collect BRF data and extract Bidirectional Reflectance Distribution Function (BRDF) data of non-isotropic vegetation elements such as bark, soil, and leaves. Accurate calibration has ensured robust geometric accuracy of the apparatus, correction for the conicality of the light source, while sufficient radiometric stability and repeatability between measurements are obtained. The bidirectional reflectance data collection is automated and remotely controlled and takes approximately two and half hours for a BRF measurement cycle over a full hemisphere with 125 cm radius and 2.4 minutes for a single BRF acquisition. A specific protocol for vegetative leaf collection and measurement was established in order to investigate the possibility to extract BRDF values from Fagus sylvatica L. leaves under laboratory conditions. Drying leaf effects induce a reflectance change during the BRF measurements due to the laboratory illumination source. Therefore, the full hemisphere could not be covered with one leaf. Instead 12 BRF measurements per leaf were acquired covering all azimuth positions for a single light source zenith position. Data are collected in radiance format and reflectance is calculated by dividing the leaf cycle measurement with a radiance cycle of a Spectralon reference panel, multiplied by a Spectralon reflectance correction factor and a factor to correct for the conical effect of the light source. BRF results of measured leaves are presented.

Abstract:The bidirectional reflectance parametric and semi-empirical Rahman-PintyVerstraete (RPV) model was inverted based on Bidirectional Reflectance Factor (BRF) measurements of 60 Fagus sylvatica L. leaves in the optical domain between 400 nm and 2,500 nm. This was accomplished using data retrieved from the Compact Laboratory Spectro-Goniometer (CLabSpeG) with an azimuth and zenith angular step of 30 and 15 degrees, respectively. Wavelength depended RPV parameters describing the leaf reflectance shape (rho0), the curve convexity (k) and the dominant forward scattering (Θ) were derived using the RPVinversion-2 software (Joint Research Centre) package with Correlation Coefficient values between modelled and measured data varying between 0.71 and 0.99 for all wavelengths, azimuth and zenith positions. The RPV model parameters were compared with a set of leaves not participating in the inversion procedure and presented Correlation Coefficient values ranging between 0.64 and 0.94 suggesting that RPV could be also used for simulating single canopy elements such as leaves.

Abstract:Multilayer canopy representations are the most common structural stand representations due to their simplicity. Implementation of recent advances in technology has allowed scientists to simulate geometrically explicit forest canopies. The effect of simplified representations of tree architecture (i.e., multilayer representations) of four Fagus sylvatica (L.) stands, each with different LAI, on the light absorption estimates was assessed in comparison with explicit 3D geometrical stands. The absorbed photosynthetic radiation at stand level was calculated. Subsequently, each geometrically explicit 3D stand was compared with three multilayer models representing horizontal, uniform, and planophile leaf angle distributions. The 3D stands were created either by in situ measured trees or by modelled trees generated with the AMAP plant growth software. The Physically Based Ray Tracer (PBRT) algorithm was used to simulate the irradiance absorbance of the detailed 3D architecture stands, while for the three multilayer representations, the probability of light interception was simulated by applying the Beer-Lambert's law. The irradiance inside the canopies was characterized as direct, diffuse and scattered irradiance. The irradiance absorbance of the stands was computed during OPEN ACCESSRemote Sens. 2009, 1 1010 eight angular sun configurations ranging from 10° (near nadir) up to 80° sun zenith angles. Furthermore, a leaf stratification (the number and angular distribution of leaves per LAI layer inside a canopy) analysis between the 3D stands and the multilayer representations was performed, indicating the amount of irradiance each leaf is absorbing along with the percentage of sunny and shadow leaves inside the canopy. The results reveal that a multilayer representation of a stand, using a multilayer modelling approach, greatly overestimated the absorbed irradiance in an open canopy, while it provided a better approximation in the case of a closed canopy. Moreover, the actual stratification of leaves differed significantly between a multilayer representation and a 3D architecture canopy of the same LAI. The deviations in irradiance absorbance were caused by canopy structure, clumping and positioning of leaves. Although it was found that the use of canopy simplifications for modelling purposes in closed canopies is demonstrated as a valid option, special care should be taken when considering forest stands irradiance simulation for sparse canopies and particularly on higher sun zenith angles where the surrounding trees strongly affect the absorbed irradiance and results can highly deviate from the multilayer assumptions.

A hyperspectral virtual forest scene of a Fagus sylvatica stand is presented. An off-the-shelf tree architectural software package (Bionatics) was used to generate a biologically accurate Fagus tree, while leaf BRDF data were acquired with the use of a hyperspectral Compact Laboratory Spectro-Goniometer (CLabSpeG). The goal behind the virtual forest scene is to create a Virtual Imaging System using measured BRDF data of vegetative material in order to improve existing canopy reflectance models. This imaging system is the first step towards the creation of a hyperspectral virtual laboratory that will be used to research and better understand earth solar interaction principles.

ABSTRACT:Innovation Technologies and Applications for Coastal Archaeological sites project (ITACA) aims to develop and test a management system for underwater archaeological sites in coastal regions. The discovering and monitoring service will use innovative satellite remote sensing techniques combined with image processing algorithms. The project will develop a set of applications integrated in a system pursuing the following objectives: Search and location of ancient ship wrecks;  Monitoring of ship wrecks, ruins and historical artefacts that are now submerged;  Integration of resulting search and monitoring data with on-site data into a management tool for underwater sites;  Demonstration of the system's suitability for a service. High resolution synthetic aperture radar (TerraSAR-X, Cosmo-SkyMed) and multispectral satellite data (WorldView) will be combined to derive the relative bathymetry of the bottom of the sea up to the depth of 50 meters. The resulting data fusion will be processed using shape detection algorithms specific for archaeological items. The new algorithms, the physical modelling and the computational capabilities will be integrated into the Web-GIS, together with data recorded from surface (2D and 3D modelling) and from underwater surveys. Additional specific archaeological layers will be included into the WebGIS to facilitate the object identification through shape detection techniques and mapping. The system will be verified and validated through an extensive onground (sea) campaign carried out with both cutting edge technologies (side-scan sonar, multi beam echo sounder) and traditional means (professional scuba divers) in two test sites in Italy and Greece. The project is leaded by Planetek Hellas E.P.E. and include ALMA Sistemi sas for the "shape detection" and dissemination tasks, DHI-GRAS and Kell Srl for multispectral and SAR bathymetry. The complete consortium is composed by eleven partners and the project Kick-Off has been held in January 2014. The present contribution aims to present the project research achievements and finding at the mid-term review.