A snow cover climatology for the Pyrenees from MODIS snow products

International audienceThe seasonal snow in the Pyrenees is critical for hydropower production, crop irrigation and tourism in France, Spain and Andorra. Complementary to in situ observations , satellite remote sensing is useful to monitor the effect of climate on the snow dynamics. The MODIS daily snow products (Terra/MOD10A1 and Aqua/MYD10A1) are widely used to generate snow cover climatologies, yet it is preferable to assess their accuracies prior to their use. Here, we use both in situ snow observations and remote sensing data to evaluate the MODIS snow products in the Pyrenees. First, we compare the MODIS products to in situ snow depth (SD) and snow water equivalent (SWE) measurements. We estimate the values of the SWE and SD best detection thresholds to 40 mm water equivalent (w.e.) and 150 mm, respectively , for both MOD10A1 and MYD10A1. κ coefficients are within 0.74 and 0.92 depending on the product and the variable for these thresholds. However, we also find a seasonal trend in the optimal SWE and SD thresholds, reflecting the hysteresis in the relationship between the depth of the snow-pack (or SWE) and its extent within a MODIS pixel. Then, a set of Landsat images is used to validate MOD10A1 and MYD10A1 for 157 dates between 2002 and 2010. The resulting accuracies are 97 % (κ = 0.85) for MOD10A1 and 96 % (κ = 0.81) for MYD10A1, which indicates a good agreement between both data sets. The effect of vegetation on the results is analyzed by filtering the forested areas using a land cover map. As expected, the accuracies decrease over the forests but the agreement remains acceptable (MOD10A1: 96 %, κ = 0.77; MYD10A1: 95 %, κ = 0.67). We conclude that MODIS snow products have a sufficient accuracy for hy-droclimate studies at the scale of the Pyrenees range. Using a gap-filling algorithm we generate a consistent snow cover climatology, which allows us to compute the mean monthly snow cover duration per elevation band and aspect classes. There is snow on the ground at least 50 % of the time above 1600 m between December and April. We finally analyze the snow patterns for the atypical winter 2011–2012. Snow cover duration anomalies reveal a deficient snowpack on the Span-ish side of the Pyrenees, which seems to have caused a drop in the national hydropower production

Can the original equations of a dynamical system be retrieved from observational time series?

International audienceThe aim of the present work is to investigate the possibility to retrieve the original sets of dynamical equations directly from observational time series when all the system variables are observed. Time series are generated from chosen dynamical systems, and the global modeling technique is applied to obtain optimal models of parsimonious structure from these time series. The obtained models are then compared to the original equations to investigate if the original equations can be retrieved. Twenty-seven systems are considered in the study. The Rossler system is first used to illustrate the procedure and then to test the robustness of the approach under various conditions, varying the initial conditions, time series length, dynamical regimes, subsampling (and resampling), measurement noise, and dynamical perturbations. The other 26 systems (four rational ones included) of various algebraic structures, sizes, and dimensions are then considered to investigate the generality of the approach

A Multi-Temporal and Multi-Spectral Method to Estimate Aerosol Optical Thickness over Land, for the Atmospheric Correction of FormoSat-2, LandSat, VENμS and Sentinel-2 Images

The correction of atmospheric effects is one of the preliminary steps required to make quantitative use of time series of high resolution images from optical remote sensing satellites. An accurate atmospheric correction requires good knowledge of the aerosol optical thickness (AOT) and of the aerosol type. As a first step, this study compares the performances of two kinds of AOT estimation methods applied to FormoSat-2 and LandSat time series of images: a multi-spectral method that assumes a constant relationship between surface reflectance measurements and a multi-temporal method that assumes that the surface reflectances are stable with time. In a second step, these methods are combined to obtain more accurate and robust estimates. The estimated AOTs are compared to in situ measurements on several sites of the AERONET (Aerosol Robotic Network). The methods, based on either spectral or temporal criteria, provide accuracies better than 0.07 in most cases, but show degraded accuracies in some special cases, such as the absence of vegetation for the spectral method or a very quick variation of landscape for the temporal method. The combination of both methods in a new spectro-temporal method increases the robustness of the results in all cases

A multi-temporal method for cloud detection, applied to FORMOSAT-2, VENµS, LANDSAT and SENTINEL-2 images

International audienceOver lands, the cloud detection on remote sensing images is not an easy task, because of the frequent difficulty to distinguish clouds from the underlying landscape, even at a high resolution. Up to now, most high resolution images have been distributed without an associated cloud mask. This situation should change in the near future, thanks to two new satellite missions that will provide optical images combining 3 features: high spatial resolution, high revisit frequency and constant viewing angles. The VENµS (French and Israeli cooperation) mission should be launched in 2012 and the European SENTINEL-2 mission in 2013. Fortunately, two existing satellite missions, FORMOSAT-2 and LANDSAT, enable to simulate the future data of these sensors. Multi-temporal imagery at constant viewing angles provides a new way to discriminate clouded and unclouded pixels, using the relative stability of the earth surface reflectances compared to the quick variations of the reflectance of pixels affected by clouds. In this study, we have used time series of images from FORMOSAT-2 and LANDSAT to develop and test a Multi-Temporal Cloud Detection (MTCD) method. This algorithm combines a detection of a sudden increase of reflectance in the blue wavelength on a pixel by pixel basis, and a test of the linear correlation of pixel neighborhoods taken from couples of images acquired successively. MTCD cloud masks are compared with cloud cover assessments obtained from FORMOSAT-2 and LANDSAT data catalogs. The results show that the MTCD method provides a better discrimination of clouded and unclouded pixels than the usual methods based on thresholds applied to reflectances or reflectance ratios. This method will be used within VENµS level 2 processing and will be proposed for SENTINEL-2 level 2 processing

Global modeling of aggregated and associated chaotic dynamics

International audienceSpatially distributed systems are rather difficult to investigate due to two distinct problems which can be sometimes combined. First, the spatial extension is taken into account by monitoring the system evolution at different locations. Second, the dynamics cannot always be continuously tracked in time, and segments of data – sometimes recorded at different places – are only available. When the dynamics underlying a single marker is under consideration – as for instance the normalized difference vegetation index which can be used for assessing the vegetation canopy of a given area – a global model can be obtained from a single scalar time series built by aggregating the available time series recorded at different places and/or associating the segments of data recorded at different times (and possibly at different locations). We investigated how these two data preprocessing – common in environmental studies – may affect the model dynamics by using a system of spatially distributed Rössler systems which are phase synchronized or not

Desert roughness retrieval using CYGNSS GNSS-R data

International audienceThe aim of this paper is to assess the potential use of data recorded by the Global Navigation Satellite System Reflectometry (GNSS-R) Cyclone Global Navigation Satellite System (CYGNSS) constellation to characterize desert surface roughness. The study is applied over the Sahara, the largest non-polar desert in the world. This is based on a spatio-temporal analysis of variations in Cyclone Global Navigation Satellite System (CYGNSS) data, expressed as changes in reflectivity. In general, the reflectivity of each type of land surface (reliefs, dunes, etc.) encountered at the studied site is found to have a high temporal stability. A grid of CYGNSS measurements has been developed, at the relatively fine resolution of 0.03° x 0.03°, and the resulting map of average reflectivity, computed over a 2.5-year period, illustrates the potential of CYGNSS data for the characterization of the main types of desert land surface (dunes, reliefs, etc.). A discussion of the relationship between aerodynamic or geometric roughness and CYGNSS reflectivity is proposed. A high correlation is observed between these roughness parameters and reflectivity. The behaviors of the GNSS-R reflectivity and the Advanced Land Observing Satellite-2 (ALOS-2) Synthetic Aperture Radar (SAR) backscattering coefficient are compared and found to be strongly correlated. An aerodynamic roughness (Z0) map of the Sahara is proposed, using four distinct classes of terrain roughness

Soil moisture retrieval using GNSS-R data

International audienceThe aim of this study is to propose an inversion algorithm for CYGNSS constellation data, which can be used for the monitoring of soil moisture. A change detection approach based on a 21-month CYGNSS data time series is proposed, and is processed to retrieve daily average reflectivity over a grid with a spatial resolution equal to 0.5° x 0.5°. Auxiliary data, including PROBA-V optical measurements and SRTM Digital Terrain Model products are used to account for the influence of vegetation and relief. The proposed estimates are validated at three different African sites (Merguellil, Tunisia; Basso Dallo, Niger; and Ouémé, Benin), using field moisture measurements acquired at 5 cm soil depth

Plate waste increases with the number of foods proposed: An exploratory experimental study in adolescents’ school canteens

International audienc