Comparison between backscattered TerraSAR signals and simulations from the radar backscattering models IEM, Oh, and Dubois

The objective of this paper is to evaluate on bare soils the surface backscattering models IEM, Oh, and Dubois in X-band. This analysis uses a large database of TerraSAR-X images and in situ measurements (soil moisture and surface roughness). Oh's model correctly simulates the radar signal for HH and VV polarizations whereas the simulations performed with the Dubois model show a poor correlation between TerraSAR data and model. The backscattering Integral Equation Model (IEM) model simulates correctly the backscattering coefficient only for rms1.5 cm in using Gaussian function. However, the results are not satisfactory for a use of IEM in the inversion of TerraSAR data. A semi-empirical calibration of IEM was done in X-band. Good agreement was found between the TerraSAR data and the simulations using the calibrated version of the IEM

Basal ganglia dysfunction in OCD: subthalamic neuronal activity correlates with symptoms severity and predicts high-frequency stimulation efficacy

Functional and connectivity changes in corticostriatal systems have been reported in the brains of patients with obsessive–compulsive disorder (OCD); however, the relationship between basal ganglia activity and OCD severity has never been adequately established. We recently showed that deep brain stimulation of the subthalamic nucleus (STN), a central basal ganglia nucleus, improves OCD. Here, single-unit subthalamic neuronal activity was analysed in 12 OCD patients, in relation to the severity of obsessions and compulsions and response to STN stimulation, and compared with that obtained in 12 patients with Parkinson's disease (PD). STN neurons in OCD patients had lower discharge frequency than those in PD patients, with a similar proportion of burst-type activity (69 vs 67%). Oscillatory activity was present in 46 and 68% of neurons in OCD and PD patients, respectively, predominantly in the low-frequency band (1–8 Hz). In OCD patients, the bursty and oscillatory subthalamic neuronal activity was mainly located in the associative–limbic part. Both OCD severity and clinical improvement following STN stimulation were related to the STN neuronal activity. In patients with the most severe OCD, STN neurons exhibited bursts with shorter duration and interburst interval, but higher intraburst frequency, and more oscillations in the low-frequency bands. In patients with best clinical outcome with STN stimulation, STN neurons displayed higher mean discharge, burst and intraburst frequencies, and lower interburst interval. These findings are consistent with the hypothesis of a dysfunction in the associative–limbic subdivision of the basal ganglia circuitry in OCD's pathophysiology

The pathophysiology of restricted repetitive behavior

Restricted, repetitive behaviors (RRBs) are heterogeneous ranging from stereotypic body movements to rituals to restricted interests. RRBs are most strongly associated with autism but occur in a number of other clinical disorders as well as in typical development. There does not seem to be a category of RRB that is unique or specific to autism and RRB does not seem to be robustly correlated with specific cognitive, sensory or motor abnormalities in autism. Despite its clinical significance, little is known about the pathophysiology of RRB. Both clinical and animal models studies link repetitive behaviors to genetic mutations and a number of specific genetic syndromes have RRBs as part of the clinical phenotype. Genetic risk factors may interact with experiential factors resulting in the extremes in repetitive behavior phenotypic expression that characterize autism. Few studies of individuals with autism have correlated MRI findings and RRBs and no attempt has been made to associate RRB and post-mortem tissue findings. Available clinical and animal models data indicate functional and structural alterations in cortical-basal ganglia circuitry in the expression of RRB, however. Our own studies point to reduced activity of the indirect basal ganglia pathway being associated with high levels of repetitive behavior in an animal model. These findings, if generalizable, suggest specific therapeutic targets. These, and perhaps other, perturbations to cortical basal ganglia circuitry are mediated by specific molecular mechanisms (e.g., altered gene expression) that result in long-term, experience-dependent neuroadaptations that initiate and maintain repetitive behavior. A great deal more research is needed to uncover such mechanisms. Work in areas such as substance abuse, OCD, Tourette syndrome, Parkinson’s disease, and dementias promise to provide findings critical for identifying neurobiological mechanisms relevant to RRB in autism. Moreover, basic research in areas such as birdsong, habit formation, and procedural learning may provide additional, much needed clues. Understanding the pathophysioloy of repetitive behavior will be critical to identifying novel therapeutic targets and strategies for individuals with autism

Semi-Empirical Calibration of the Integral Equation Model for Co-Polarized L-Band Backscattering

The objective of this paper is to extend the semi-empirical calibration of the backscattering Integral Equation Model (IEM) initially proposed for Synthetic Aperture Radar (SAR) data at C- and X-bands to SAR data at L-band. A large dataset of radar signal and in situ measurements (soil moisture and surface roughness) over bare soil surfaces were used. This dataset was collected over numerous agricultural study sites in France, Luxembourg, Belgium, Germany and Italy using various SAR sensors (AIRSAR, SIR-C, JERS-1, PALSAR-1, ESAR). Results showed slightly better simulations with exponential autocorrelation function than with Gaussian function and with HH than with VV. Using the exponential autocorrelation function, the mean difference between experimental data and Integral Equation Model (IEM) simulations is +0.4 dB in HH and −1.2 dB in VV with a Root Mean Square Error (RMSE) about 3.5 dB. In order to improve the modeling results of the IEM for a better use in the inversion of SAR data, a semi-empirical calibration of the IEM was performed at L-band in replacing the correlation length derived from field experiments by a fitting parameter. Better agreement was observed between the backscattering coefficient provided by the SAR and that simulated by the calibrated version of the IEM (RMSE about 2.2 dB)

Monitoring loss of tropical forest cover from Sentinel-1 time-series: A CuSum-based approach

International audienceThe forest decline in tropical areas is one of the largest global environmental threats as the growth of both global population and its needs have put an increasing pressure on these ecosystems. Efforts are ongoing to reduce tropical deforestation rates. Earth observations are increasingly used to monitor deforestation over the whole equatorial area. Change detection methods are mainly applied to satellite optical images which face limitations in humid tropical areas. For instance, due to frequent cloud cover in the tropics, there are often long delays in the detection of deforestation events. Recently, detection methods applied to Synthetic Aperture Radar (SAR) have been developed to address the limitations related to cloud cover. In this study, we present an application of a recently developed change detection method for monitoring forest cover loss from SAR time-series data in tropical zone. The method is based on the Cumulative Sum algorithm (CuSum) combined with a bootstrap analysis. The method was applied to time-series of Sentinel-1 ground range detected (GRD) dual polarization (VV, VH) images forming a dataset of 60 images to monitor forest cover loss in a legal forest concession of the Democratic Republic of Congo during the 2018-2020 period. A cross-threshold recombination was then conducted on the computed maps. Evaluated against reference forest cut maps, an overall accuracy up to 91% and a precision up to 75% in forest clear cut detection was obtained. Our results show that more than 60% of forest disturbances were detected before the PlanetScope-based estimated date of cut, which may suggest the capacity of our method to detect forest degradation

Mapping surface soil moisture over the Gourma mesoscale site (Mali) by using ENVISAT ASAR data

The potentialities of ENVISAT ASAR (Advanced Synthetic Aperture Radar) multi-angle data for mapping surface soil moisture (SSM) in Sahelian rangelands are investigated at medium scale (30 000 km(2)). The Wide Swath data are selected to take advantage of their high temporal repetitivity (about 8 days at the considered scale) associated to a moderate spatial resolution (150m). In the continuity of previous studies conducted at a local scale in the same region, SSM maps are here processed over the whole AMMA Gourma mesoscale site at 1 km resolution scale. Overall, the generated maps are found to be in good agreement with field data, EPSAT-SG (Estimation des Pluies par SATellite - Second Generation) rainfall estimates and ERS (European Remote Sensing) Wind Scatterometer (WSC) SSM products. The present study shows that the spatial pattern of SSM can be realistically estimated at a kilometric scale. The resulting SSM maps are expected to provide valuable information for initialisation of land surface models and the estimation of the spatial distribution of radiative fluxes. Particularly, SSM maps could help to desaggregate low-resolution products such as those derived from WSC data

Soil Moisture Estimation and Analysis in Western Africa Based on ERS Scatterometer

International audienceThe present paper presents a new methodology for the estimation of surface soil moisture over Western Africa, based on data provided by the European Remote sensing Wind SCatterometer (WSC) instrument, in which an empirical model is used to estimate volumetric soil moisture. This approach takes into account the effects of vegetation and soil roughness in the soil moisture estimation process. The proposed estimations have been validated using different methods, and a good degree of coherence has been observed between satellite estimations and ground truth measurements. Comparison with the multi-model analysis product provided by the Global Soil Wetness Project, Phase 2 (GSWP-2) indicates that their estimations are well correlated

Soil Moisture Estimation and Analysis in Western Africa Based on ERS Scatterometer

International audienceThe present paper presents a new methodology for the estimation of surface soil moisture over Western Africa, based on data provided by the European Remote sensing Wind SCatterometer (WSC) instrument, in which an empirical model is used to estimate volumetric soil moisture. This approach takes into account the effects of vegetation and soil roughness in the soil moisture estimation process. The proposed estimations have been validated using different methods, and a good degree of coherence has been observed between satellite estimations and ground truth measurements. Comparison with the multi-model analysis product provided by the Global Soil Wetness Project, Phase 2 (GSWP-2) indicates that their estimations are well correlated