A multisensor fusion approach to improve LAI time series
International audience; High-quality and gap-free satellite time series are required for reliable terrestrial monitoring. Moderate resolution sensors provide continuous observations at global scale for monitoring spatial and temporal variations of land surface characteristics. However, the full potential of remote sensing systems is often hampered by poor quality or missing data caused by clouds, aerosols, snow cover, algorithms and instrumentation problems. A multisensor fusion approach is here proposed to improve the spatio-temporal continuity, consistency and accuracy of current satellite products. It is based on the use of neural networks, gap filling and temporal smoothing techniques. …
Performances of neural networks for deriving LAI estimates from existing CYCLOPES and MODIS products
International audience; This paper evaluates the performances of a neural network approach to estimate LAI from CYCLOPES and MODIS nadir normalized reflectance and LAI products. A data base was generated from these products over the BELMANIP sites during the 2001-2003 period. Data were aggregated at 3 km x 3 km, resampled at 1/16 days temporal frequency and filtered to reject outliers. VEGETATION and MODIS reflectances show very consistent values in the red, near infrared and short wave infrared bands. Neural networks were trained over part of this data base for each of the 6 MODIS biome classes to retrieve both MODIS and CYCLOPES LAI products. Results show very good performances of neural …
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% …
Empirical and physical estimation of Canopy Water Content from CHRIS/PROBA data
20 páginas, 4 tablas, 7 figuras.
Accuracy assessment of fraction of vegetation cover and leaf area index estimates from pragmatic methods in a cropland area
The fraction of vegetation cover (FVC) and the leaf area index (LAI) are important parameters for many agronomic, ecological and meteorological applications. Several in-situ and remote sensing techniques for estimating FVC and LAI have been developed in recent years. In this paper, the uncertainty of in-situ FVC and LAI measurements was evaluated by comparing estimates from LAI-2000 and digital hemispherical photography (DHP). The accuracy achieved with a spectral mixture analysis algorithm and two vegetation indices-based methods was assessed using atmospherically corrected Landsat Thematic Mapper (TM) data over the Barrax cropland area where the European Space Agency (ESA) SENtinel-2 and …
Optimal modalities for radiative transfer-neural network estimation of canopy biophysical characteristics: Evaluation over an agricultural area with CHRIS/PROBA observations
International audience; Neural networks trained over radiative transfer simulations constitute the basis of several operational algorithms to estimate canopy biophysical variables from satellite reflectance measurements. However, only little attention was paid to the training process which has a major impact on retrieval performances. This study focused on the several modalities of the training process within neural network estimation of LAI, FCOVER and FAPAR biophysical variables. Performances were evaluated over both actual experimental observations and model simulations. The SAIL and PROSPECT radiative transfer models were used here to simulate the training and the synthetic test dataset…
Intercomparison and quality assessment of MERIS, MODIS and SEVIRI FAPAR products over the Iberian Peninsula
Abstract The fraction of absorbed photosynthetically active radiation (FAPAR) is a key variable in productivity and carbon cycle models. The variety of available FAPAR satellite products from different space agencies leads to the necessity of assessing the existing differences between them before using into models. Discrepancies of four FAPAR products derived from MODIS, SEVIRI and MERIS (TOAVEG and MGVI algorithms), covering the Iberian Peninsula from July 2006 to June 2007 are here analyzed. The assessment is based on an intercomparison involving the spatial and temporal consistency between products and a statistical analysis across land cover types. In general, significant differences ar…
Quantification of LAI interannual anomalies by adjusting climatological patterns
International audience; Scaling variations and shifts in the timing of seasonal phenology are central features of global change research. In this study, we propose a novel climatology fitting approach to quantify inter-annual anomalies in LAI seasonality. A consistent archive of daily LAI estimates was first derived from historical AVHRR satellite data for the 1981-2000 period over a globally representative sample of sites. The climatology values were then computed by averaging multi-year LAI profiles, gap filling and smoothing to eliminate possible high temporal frequency residual artifacts. The inter-annual variations in LAI were finally quantified by scaling and shifting the seasonal cli…
Prototyping of Land-SAF leaf area index algorithm with VEGETATION and MODIS data over Europe
Abstract The Satellite Application Facility on Land Surface Analysis (Land-SAF) aims to provide land surface variables for the meteorological and environmental science communities from EUMETSAT satellites. This study assesses the performance of a simplified (i.e. random distribution of vegetation is assumed) version of the Land-SAF algorithm for the estimation of Leaf Area Index (LAI) when prototyped with VEGETATION (processed in CYCLOPES program) and MODIS reflectances. The prototype estimates of LAI are evaluated both by comparison with validated CYCLOPES and MODIS LAI products derived from the same sensors and directly through comparison with ground-based estimates. Emphasis is given on …