422 research outputs found

    Remote Sensing of Soil

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    Remote sensing has shown a high potential in soil characteristics retrieving in the last three decades. Different methodologies have been proposed for the estimation of soil parameters, based on different remote sensing sensors and techniques (passive and active)

    Use of TerraSAR-X data to retrieve soil moisture over bare soil agricultural fields

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    The retrieval of the bare soil moisture content from TerraSAR-X data is discussed using empirical approaches. Two cases were evaluated: 1) one image at low or high incidence angle and 2) two images, one at low incidence and one at high incidence. This study shows by using three databases collected between 2008 and 2010 over two study sites in France (Orgeval and Villamblain) that TerraSAR-X is a good remote sensing tool for the retrieving of surface soilmoisture with accuracy of about 3% (rmse).Moreover, the accuracy of the soil moisture estimate does not improve when two incidence angles (26◦–28◦ or 50◦–52◦) are used instead of only one. When compared with the result obtained with a high incidence angle (50◦–52◦), the use of low incidence angle (26◦–28◦) does not enable a significant improvement in estimating soil moisture (about 1%)

    Control of Vibrations due to Moving Loads on Suspension Bridges

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    The flexibility and low damping of the long span suspended cables in suspension bridges makes them prone to vibrations due to wind and moving loads which affect the dynamic responses of the suspended cables and the bridge deck. This paper investigates the control of vibrations of a suspension bridge due to a vertical load moving on the bridge deck with a constant speed. A vertical cable between the bridge deck and the suspended cables is used to install a hydraulic actuator able to generate an active control force on the bridge deck. Two control schemes are proposed to generate the control force needed to reduce the vertical vibrations in the suspended cables and in the bridge deck. The proposed controllers, whose design is based on Lyapunov theory, guarantee the asymptotic stability of the system. The MATLAB software is used to simulate the performance of the controlled system. The simulation results indicate that the proposed controllers work well. In addition, the performance of the system with the proposed controllers is compared to the performance of the system controlled with a velocity feedback controller

    Desert roughness retrieval using CYGNSS GNSS-R data

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    The 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 (G). 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 G 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 coeffcient 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

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

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    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

    Warm and fertile sub-humid conditions enhance litterfall to sustain high soil respiration fluxes in a mediterranean cork oak forest

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    Soil respiration is a major component of the global carbon budget and Mediterranean ecosystems have usually been studied in locations with shallow soils, mild temperatures, and a prolonged dry season. This study investigates seasonal soil respiration rates and underlying mechanisms under wetter, warmer, and more fertile conditions in a Mediterranean cork oak forest of Northern Tunisia (Africa), acknowledged as one of the most productive forests in the Mediterranean basin. We applied a soil respiration model based on soil temperature and relative water content and investigated how ecosystem functioning under these favorable conditions affected soil carbon storage through carbon inputs to the soil litter. Annual soil respiration rates varied between 1774 gC m(-2) year(-1) and 2227 gC m(-2) year(-1), which is on the highest range of observations under Mediterranean climate conditions. We attributed this high soil carbon flux as a response to favorable temperatures and soil water content, but this could be sustained only by a small carbon allocation to roots (root/shoot ratio = 0.31-0.41) leading to a large allocation to leaves with a multiannual leaf production, enhanced annual twig elongation (11.5-28.5 cm) with a reduced leaf life span (<1 year) maintaining a low LAI (1.68-1.88) and generating a high litterfall (386-636 gC m(-2) year(-1)). Thus, the favorable climatic and edaphic conditions experienced by these Mediterranean cork oak forests drove high soil respiration fluxes which balanced the high carbon assimilation leading to a relatively small overall contribution (10.96-14.79 kgC m(-2)) to soil carbon storage

    Smooth motion profile for trajectory planning of a flexible manipulator

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    © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksThis paper deals with the problem of trajectory generation with a motion law in joint space for a flexible singlelink manipulator. To this aim, we propose a smooth motion profile based on polynomial function for a flexible manipulator. This motion law is tested with a dynamic model of the manipulator that is controlled using a model-free approach so that the robot can follow the desired trajectory.Peer ReviewedPostprint (author's final draft

    Analysis of TerraSAR-X data and their sensitivity to soil surface parameters over bare agricultural fields

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    International audienceCette recherche a pour objectif de mettre en évidence la contribution des capteurs haute résolution pour une meilleure caractérisation de la surface du sol et pour analyser les effets de la polarisation et de l'angle d'incidence radar. L'objectif de cet article est d'analyser la sensibilité des données haute résolution Terrassar-X sur des sols sans couverture végétale et d'étudier la variabilité spatiale. Les relations entre le coefficient de rétrodiffusion et les paramètres du sol seront étudiés grâce aux images (TerraSAR, Ikonos, SPOT) ainsi que grâce aux mesures de terrain recueillies pendant plusieurs campagnes de terrain en hiver et printemps 2008-2009. Ce travail a été mené sur le bassin de l'Orgeval (France). / Our research aims to show the contribution of high resolution spatial sensors for a better characterization of soil surface, and to analyze polarization effects and radar incidence angle. The objective of this paper is to analyze the sensitivity of very high resolution TerraSAR-X radar data taken over bare soils, and to study the spatial variability. The relationship between backscattering coefficient and soil's parameters (moisture, surface roughness, and texture) will be examined by means of satellite images (TerraSAR, Ikonos, SPOT), as well as ground truth measurements, recorded during several field campaigns in the winter and spring of 2008 and 2009. This study is carried out on Orgeval catchment (France)

    A potential use for the C-band polarimetric SAR parameters to characterise the soil surface over bare agriculture fields

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    The objective of this study was to analyze the potential of the C-band polarimetric SAR parameters for the soil surface characterization of bare agricultural soils. RADARSAT-2 data and simulations using the Integral Equation Model (IEM) were analyzed to evaluate the polarimetric SAR parameters' sensitivities to the soil moisture and surface roughness. The results showed that the polarimetric parameters in the C-band were not very relevant to the characterization of the soil surface over bare agricultural areas. Low dynamics were often observed between the polarimetric parameters and both the soil moisture content and the soil surface roughness. These low dynamics do not allow for the accurate estimation of the soil parameters, but they could augment the standard inversion approaches to improve the estimation of these soil parameters. The polarimetric parameter alpha_1 could be used to detect very moist soils (>30%), while the anisotropy could be used to separate the smooth soils
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