J. Meliá

A directional spectral mixture analysis method: application to multiangular airborne measurements

This study aims at developing an operational approach-namely, directional spectral mixture analysis (DISMA)-for retrieving vegetation parameters like fractional vegetation cover (FVC) and leaf area index (LAI) from multispectral and multiangular data. The approach attempts to highlight the consistency of one-dimensional models and linear mixture approaches. DISMA combines spectral signatures of soil and vegetation components with an analytical approximation of the radiative transfer equation, giving rise to a fast invertible bidirectional reflectance distribution function (BRDF) model of discontinuous canopies. Both the forward model and its inversion using a simple technique based on lookup tables method are tested using airborne POLDER and HyMap data corresponding to cropland. The method has proven fast enough to image vegetation properties over large areas, providing accurate and stable maps of FVC and LAI. The retrievals of LAI correspond well with ground-based measurements of specific crops, with root mean square error differences of 0.5-0.6 and a r/sup 2/ of the linear fitting around 0.92. Though the accuracy assessment of retrieved parameters may be sensitive to the BRDF sampling, the results of model inversion remain consistent when varying the angular and spectral configurations. A model intercomparison exercise has been carried out using different models, either purely descriptive or based on radiative transfer modeling, indicating that this general approach is both sound and consistent. Thus, DISMA appears to be a useful tool for exploiting the synergistic spectral and angular potential of the new sensors.

Direct validation of FVC, LAI and FAPAR VEGETATION/SPOT derived products using LSA SAF methodology

The aim of this work is to perform a direct validation of fraction of vegetation cover (FVC), leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FAPAR) resulting products from applying the LSA SAF methodology to VEGETATION BRDF data. LSA SAF adapted algorithms were tested in adequate test sites comprising different continental biomes covering a wide range of FVC, LAI and FAPAR values. Results seem to indicate the competitiveness of LSA SAF proposed methodology to retrieve remotely sensed biophysical parameters. A noticeable good agreement regarding the ground measurements was found. The overall accuracy (RAISE) is around 20% for FVC and FAPAR and around 15% for LAI.

Procedure for the regional scale mapping of FVC and LAI over land degradated areas in the DeSurvey project

The aim of this work is to analyze the consistency of the FVC and LAI regional scale mapping products derived from new generation of sensor systems, SPOT/VEGETATION and MSG/SEVIRI, for vegetation monitoring, especially over hot spot areas affected by land degradation processes. The FVC has been developed from a probabilistic Spectral Mixture Analysis (SMA) using as input the nadir-zenith normalized TOC reflectance coefficient (k0) for the different spectral channels. In this sense, using k0 as input accounts for the different acquisition geometry in the data. FVC is subsequently used to estimate LAI using the Roujean and Lacaze semi-empirical relationship. The results have demonstrated the competitiveness of the FVC and LAI derived products regarding similar satellite products at local scales and the suitability of using them to reproduce the temporal variability over dryland condition areas.

Prototyping algorithm for retrieving FAPAR using MSG data in the context of the LSA SAF project

This paper describes the prototyping algorithm developed for retrieving the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) using MSG data in the framework of satellite application facility on land surface analysis (LSA SAF). The prototyping relies on the Roujean and Breon (1995) method, which is based on simulations of visible and near infrared reflectance values in an optimal geometry. A relationship is found between a vegetation index and daily FAPAR The algorithm has been applied to one year of MSG BRDF data since August 2005, using a temporal frequency of 5-days, and then validated against a set of operational satellite FAPAR products such as MODIS, MERIS, SeaWiFS and CYCLOPES, as well as with ground-truth information. MSG FAPAR products present a reliable spatial and temporal distribution of retrievals. The inter-comparison of the MSG FAPAR product with different operational products shows the large existing differences among FAPAR products. However, the best consistency is found between MSG and MERIS (only July 2006 was evaluated) or between MSG and CYCLOPES (available only for 2003). At a pixel level, the RMS over selected validation sites is lower than 0.1 between MSG and MERIS or MSG and CYCLOPES products, which demonstrates the competitiveness of the proposed prototype.

Prototyping algorithm for retrieving vegetation parameters from the MSG and EPS EUMETSAT platforms

EUMETSAT has developed a network of Satellite Application Facilities (SAF) for the future Application Ground Segments for the new generation Meteosat Second Generation (MSG) and European Polar System (EPS) platforms. Our main concern in LSA SAF is to develop an operational algorithm for retrieving vegetation parameters. In particular, fractional vegetation cover (FVC) and leaf area index (LAI), which are key parameters in the description of both land-surface processes and land-atmosphere interactions. The LSA SAF vegetation products will be provided over the full MSG disk at 3-km spatial resolution with a temporal resolution of 10-days. The use of BRDF models assures that these products will be corrected of the surface anisotropy effects. The algorithm is based on the complementary use of variable and multiple endmember spectral mixture analysis (DISMA), according with the available directional sampling. Land cover map, soil type databases and the clumping index are auxiliary information in the prototype. The prototyping algorithm has been tested using both airborne POLDER data over croplands, and the POLDEr on ADEOS BRDF database. A first version of the prototype for the MSG developed on synthetic MSG data is already implemented in the LSA SAF system. In this paper, the prototyping algorithm designed to retrieve the LSA SAF vegetation products and its validation on the above mentioned data sets are presented.

Reflectance anisotropy analysis of homogeneous canopies using laboratory and HyMap airborne data

The BRDF (Bidirectional Reflectance Distribution Function) of vegetation canopies exhibits an anisotropic behaviour that is related to illumination and viewing geometries. However, some other aspects such as the optical properties and the structural parameters of the targets should be taken into account for an adequate explanation of the bidirectional phenomenon. The present investigation examines the anisotropic behaviour of the homogeneous canopies reflectance from laboratory data as a function of viewing geometry, structural parameters and optical properties of the samples in order to obtain relevant information to improve biophysical parameters retrieval and discrimination of vegetation canopies from optical spectral data. Airborne data acquired in Daisex-99 campaign over Barrax test site (Albacete/Spain) with the HyMap instrument are also included. The HyMap concept is able to record hot spot effect, and moreover, the different flight tracks carried out in Daisex-99 allow us to complete anisotropic behaviour shown in laboratory experience, where illumination was fixed, with airborne data acquired under different solar zenith angle. Results confirm initial hypothesis that anisotropy reflectance is related to structural parameters of the vegetation and show anisotropic behaviour usefulness to study vegetation canopies increasing data dimensionality, varying both illumination and view angles. The anisotropy factor, ANIF, has resulted a simple relationship to provide us with relevant information about vegetation canopies structure. Keywords- Vegetation Canopies, Anisotropy, Reflectance, Hot Spot, Hymap.

Global mapping of vegetation parameters from SEVIRI/MSG data

In this work we present an innovative method for retrieving vegetation variables whilst at the same time making optimal use of the new generation satellite sensors. The approach is aimed to the generation of vegetation products exploding the angular capabilities provided by the MSG/SEVIRI and EPS/AVHRR within the LSA SAF Project. The products include leaf area index (LAI) and fractional vegetation cover (FVC). The algorithm is based on the complementary use of Variable Multiple Endmember Spectral Mixture Analysis (VMESMA) and the inversion of a light-canopy interaction model, namely DISMA (DIrectional Spectral Mixture Analysis), which combines the geometric optics of large scale canopy structure with principles of radiative transfer for volume scattering within individual crowns. Unlike VMESMA, DISMA fully accounts for additional information on directional anisotropy. The prototype has been implemented in the LSA SAF system and tested using SEVIRI synthetic data. The algorithm validation includes feasibility analyses, sensitivity assessments as well as evaluation of the prototype on SEVIRI synthetic data. The study contributes to assess the uncertainties with SEVIRI based vegetation products.

Tracking seasonal drought effects on ecosystem light use efficiency in a mediterranean forest using climatic and remote sensing data

Daily values of light use efficiency (LUE) of a Mediterranean forest throughout five years have been analyzed in terms of different spectral indices obtained from MODIS products and which are informative on the water stress conditions. Although correlations between LUE and the different indices are rather high, the inter-annual variation of LUE due to the summer water stress is not well identified in most of them. In particular, the PRI (photochemical reflectance index) inter-annual variation has been found to be mostly attributable to concurrent variations in sun and view zenith angles. For the study area and at MODIS spatial resolution, the different indices are informative on changes in pigments and canopy structure related to the vegetation response to prolonged water stress.

Methodology to validate MSG vegetation products: part II. Geostatistical approaches for upscaling field data to high-resolution satellite scales

This paper is the second part of two-part set which proposes a methodology in order to validate the LSA SAF vegetation products (LAI/FVC/fAPAR) derived from SEVIRI/MSG. The main objective of this methodology refers to assessing the uncertainty of SEVIRI/MSG products by analytical comparison to in situ measurements. The scaling problem is solved in this work by considering high-resolution maps in order to make the direct comparison between ground truth and coarse-resolution products. A detail description of the measurement acquisition and estimates was presented in a first document whereas the estimation of the high-resolution biophysical maps from this in situ data set is undertaken in this paper. This work attempts to evaluate the capabilities of a geostatistical approach in the estimation of high-resolution LAI/FVC/fAPAR maps. The geostatistical approach is based on collocated cokriging, which allows to derive high-resolution maps from in situ measurements over a small area (5x5 km2), centred at Barrax test site. This technique takes into account the spatial dependence of the data, the neighbouring information, densely sampled auxiliary information and the variance estimation as opposed to empirical functions. The method has shown to be appropriate for the spatial extension of in situ measurements. An important contribution of this work is the analysis of the uncertainties associated to the method which provides an appreciation of the varying precision of the cokriged estimates due to the irregular disposition of informative points by means of the estimated variance. On the other hand, a flag image is also provided by using the convex hull tool in order to account for possible uncertainties in previous steps to the final cokriging output.