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Abstract: The extraordinary meteorological conditions of summer 2003 provide a singular case of study of the response of vegetation to drought under conditions that are similar to what is expected by some scenarios to be a normal summer by the latter decades of the 21st century. After collecting climatic and meteorological information to produce monthly fields of mean temperature, precipitation and precipitation deficit (as the difference between precipitation and potential evapo-transpiration), we have analyzed a monthly series of fields of normalized difference vegetation index (NDVI). Our results indicate strongly negative anomalies of satellite NDVI: a 25% of the area covered by herbaceous vegetation had a relative anomaly of NDVI in August lower than −17%, while the equivalent value for deciduous forests was −11%. Geographically, the most affected area was located to the SE of a diagonal line crossing France from SW to NE. As low values of NDVI in August indicate early leaf withering, some deciduous forests experienced a serious reduction of the number of valid days for photosynthesis. [Copyright &y& Elsevier]

Abstract: In this study we investigated the perspective offered by coupling a simple vegetation growth model and ground-based remotely-sensed data for the monitoring of wheat production. A simple model was developed to simulate the time courses of green leaf area index (GLAI), dry above-ground phytomass (DAM) and grain yield (GY). A comprehensive sensitivity analysis has allowed addressing the problem of model calibration, distinguishing three categories of parameters: (1) those, well known, derived from the present or previous wheat experiments; (2) those, phenological, which have been identified for the wheat variety under study; (3) those, related to farmer practices, which has been adjusted field by field. The approach was tested against field data collected on irrigated winter wheat in the semi-arid Marrakech plain. This data set includes estimates of GLAI with additional DAM and GY measurements. The model provides excellent simulations of both GLAI and DAM time courses. GY space variations are correctly predicted, but with a general underestimation on the validation fields. Despite this limitation, the approach offers the advantage of being quite simple, without requiring any data on agricultural practices (sowing, irrigation and fertilisation). This makes it very attractive for operational application at a regional scale. This perspective is discussed in the conclusion. [Copyright &y& Elsevier]

Since April 1998, the VEGETATION/SPOT-4 sensor has acquired global observations at kilometer scale in four optical spectral bands on a daily basis. Its large field of view results in a strong dependency of surface reflectances on the Sun–target–sensor geometry. Our objective is to define a method to remove this anisotropy during the processing of 10-day syntheses derived from data acquired at every VEGETATION orbit pass. This article investigates the concepts that were developed for AVHRR/NOAA, POLDER/ADEOS, and MODIS/TERRA. The investigation is based on the statistical analysis of 18,000 simulated time series of red and near infrared reflectances, close to the ones acquired on various land classes by the VEGETATION sensor under different geometric, cloudiness, and atmospheric conditions. Conclusions are reached on the successive key stages that are required for the removal of surface reflectance anisotropy during the processing of syntheses. Firstly, we suggest to separate the time window devoted to the retrieval of Bidirectional Reflectance Distribution Functions (BRDFs) from a second one (shorter) that is used for combining the most recent observations. Secondly, we verify the robustness of the Roujean''s BRDF model through various angular sampling, land classes, cloudiness, and atmospheric noise. Thirdly, we improve the stability of the formula that normalises reflectances at nadir views. Fourthly, we show that a simple averaging is relevant to combine the observations after normalisation. The comparison with the common Maximum Value Compositing (MVC) method shows that the normalisation of directional effects greatly improves both consistency and accuracy in time series of surface reflectances. Despite the use of two time windows that allows to increase the efficiency of BRDF retrieval, anisotropy removal is still not possible in many cloudy regions of the world. The associated Part II article exposes a method that is fully operational on a 10-day basis under high cloudiness conditions. [Copyright &y& Elsevier]

This article shows the capacity do derive depth using the sub metric Pleiades satellite mission (Airbus/CNES) in persistent mode, which allows acquiring a sequence of images (12 images) at a regional scale (~100 km2). To derive depths, a spatiotemporal cross-correlation method for estimating wave velocity and inverse bathymetry is presented and applied to the 12-image sequence. A good agreement is found with in-situ bathymetry measurements obtained during the COMBI 2017 Capbreton experiment (correlation of 0.8, RMSE = 1.4 m). Depth estimate saturation is found for depths >35 m, mainly in a deep canyon just off the coast located in front of the entrance to Capbreton harbour. The image sequence is used to study the sensitivity of the number of images. The results show that the accuracy increases with the number of images in the sequence and with a fine resolution. Despite their noisy nature, newly available time-updated satellite bathymetries can be used to understand coastal evolution at several scales and improve risk mitigation strategies through modelling. • Pleiades satellite enables sequence capturing of metric resolution at regional scale. • New spatio-temporal cross-correlation technique used to estimate bathymetry. • Accuracy improves with the number of images used and finer resolution. [ABSTRACT FROM AUTHOR]

Abstract: An approach based on Independent Component Analysis (ICA) has been applied on a combination of monthly GRACE satellite solutions computed from official providers (CSR, JPL and GFZ), to separate useful geophysical signals from important striping undulations. We pre-filtered the raw GRACE Level-2 solutions using Gaussian filters of 300, 400, 500-km of radius to verify the non-Gaussianity condition which is necessary to apply the ICA. This linear inverse approach ensures to separate components of the observed gravity field which are statistically independent. The most energetic component found by ICA corresponds mainly to the contribution of continental water mass change. Series of ICA-estimated global maps of continental water storage have been produced over 08/2002–07/2009. Our ICA estimates were compared with the solutions obtained using other post-processing of GRACE Level-2 data, such as destriping and Gaussian filtering, at global and basin scales. Besides, they have been validated with in situ measurements in the Murray–Darling Basin. Our computed ICA grids are consistent with the different approaches. Moreover, the ICA-derived time series of water masses showed less north–south spurious gravity signals and improved filtering of unrealistic hydrological features at the basin-scale compared with solutions obtained using other filtering methods. [ABSTRACT FROM AUTHOR]

Since April 1998, the VEGETATION/SPOT-4 sensor has provided global reflectances on a daily basis. Its large field-of-view makes the observations strongly dependent on the Sun-target-sensor geometry. This paper presents the “BiDirectional Compositing” (BDC) method we designed for the VEGETATION operational line to normalise directional effects in 10-day global syntheses. For each spectral band and each pixel, BDC results every 10 days in one nadir view datum derived from the observations acquired at every orbit pass. BDC is based on two main ideas. Firstly, the length of the time window devoted to Bidirectional Reflectance Distribution Functions (BRDFs) retrieval is conceived as a variable in such a way that a constant number of cloud-free data is always available to fit the BRDF model. Secondly, BRDF retrieval is separated from data normalisation and compositing, which operates only on 10-day windows before the date of syntheses in order to keep the reflectances level of the most recent observations. As a reliable BRDF is always available from VEGETATION data, BDC is fully productive at a 10-day step. It allows to use one single method to derive global syntheses, which can be easily adapted for any large field-of-view optical sensor. Using VEGETATION data sets acquired on four regions of the world, we finally compare 10-day syntheses obtained by BDC to the ones derived with two versions of Maximum Value Compositing (MVC) differing by the performance in detection of clouds and aerosols. The seasonal and spatial coherence of reflectances and Normalised Difference Vegetation Index (NDVI) are much larger on BDC than on MVC syntheses, both at a regional and pixel (km2) scale. Compared to the version of MVC that is presently used in the VEGETATION operational line, BDC smoothes 10-day fluctuations of reflectances and NDVI time series by a factor 2.8 on average. [Copyright &y& Elsevier]