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Moradi A.,CNRS Paris Institute of Global Physics | Metivier L.,Institute National Of Linformation Geographique Et Forestiere Ign | de Viron O.,CNRS Paris Institute of Global Physics | de Viron O.,CNRS Coastal and Marine Environment Laboratory | And 2 more authors.
International Journal of Remote Sensing | Year: 2014

Moderate-Resolution Imaging Spectroradiometer (MODIS) optical and infrared data are used to monitor changes in the Caspian Sea coastline. The information extracted from MODIS images is converted into total water volume and mean lake level by combining a digital elevation model (DEM) with remote-sensing data. The elevation estimates were enhanced by reprocessing the MODIS data at the sub-pixel scale. The water volume variations estimated from MODIS data along with DEM are compared to other estimations derived from altimetry data sets, and show fair agreement. © 2014, © 2014 Taylor & Francis. Source


Lisein J.,University of Liege | Lisein J.,University Paris Est Creteil | Bonnet S.,University of Liege | Lejeune P.,University of Liege | And 2 more authors.
Revue Francaise de Photogrammetrie et de Teledetection | Year: 2014

Recent development of small unmanned aerial systems opens the door for their use in forest mapping, as both the spatial and temporal resolution of drone imagery better suit local-scale investigation than traditional remote sensing tools. An original photogrammetric workflow, based on the open source toolbox MICMAC, was set up to model the forest canopy surface from low-altitude aerial images. In combination with a LiDAR digital terrain model, the elevation of vegetation was determined after a fine co-registration of the photogrammetric canopy surface model. The investigation of different images matching strategies is performed within MICMAC and their performance in modelling the outer canopy is compared. Although photogrammetric reconstruction do not account for small peaks and gaps in the canopy surface, our results have shown the potential of drones to accurately estimate canopy height in broadleaf stands, confirming thus the feasibility of modeling height growth from UAV images time series. Source


Willis P.,Institute National Of Linformation Geographique Et Forestiere Ign | Willis P.,CNRS Paris Institute of Global Physics | Bock O.,CNRS Pascal Institute | Bar-Sever Y.E.,Jet Propulsion Laboratory
International Association of Geodesy Symposia | Year: 2014

We reprocessed DORIS for all of 2010, using the latest model and strategy improvements to estimate Zenith Tropospheric Delays (ZTDs), as well as tropospheric horizontal gradients for about 60 ground stations. These results were compared to recent GPS-based estimates obtained at the Jet Propulsion Laboratory (JPL). After discussing some of the data processing options and current limitations of the DORIS data, we showthat the DORIS-GPS comparisons possess a high degree of correlation (average being 0.97), and that total zenith delay estimates from the two techniques agree at the 3 mm level on average with 8.6 mm total RMS, with better results being obtained when a 5° elevation cutoff angle is used for DORIS. While these DORIS results cannot be used for real-time weather prediction, they could contribute to scientific investigations for climatology, thanks to the homogenous tracking network of the DORIS system, as well as the long-term history of the observation time series. © Springer-Verlag Berlin Heidelberg 2014. Source


Saunier J.,Institute National Of Linformation Geographique Et Forestiere Ign | Auriol A.,French National Center for Space Studies | Tourain C.,French National Center for Space Studies
Advances in Space Research | Year: 2016

The DORIS system measures distances between phase centers of onboard and ground antennas to determine the position of the satellites in their orbits. To this end, the ground antenna phase center position must be known in a terrestrial reference frame. Its position is linked and defined with respect to the antenna reference point (ARP), a conventional physical point for which coordinates are assigned. Although the determination of the ARP position with respect to ground markers can be achieved by traditional surveys, the connection with the actual measurement point (phase center) is far more difficult to determine. This is the main concern explored in this paper. Regardless of the need for a good antenna characterization, CNES and IGN jointly worked to establish a first error budget of the ground antenna position. With this aim in view, each component was clearly identified and studied separately. We distinguished between errors from manufacturing and from site surveying and, on the other hand, errors affecting horizontal and vertical position. The knowledge of the antenna geometry and the guarantee of a good reproducibility in the manufacturing process are essential. Based on these requirements, we have defined new manufacturing specifications to create a new antenna type: Starec type C. Compared to the previous antenna (Starec type B), the standard uncertainty of the 2. GHz phase center position in the vertical direction has been reduced from 5. mm to 1. mm. Following this work, we provide for the new Starec antenna (type C) total uncertainties involved in the ground antenna positioning in a local reference frame: 2. mm in the horizontal plane, 2.5. mm for the vertical component and 3.2. mm in three-dimensional combination. We also propose for DORIS new definitions of conventional points and a new method to determine ground antennas position that were not possible before this manufacturing specifications change. © 2016 COSPAR. Source


Lisein J.,University of Liege | Lisein J.,University Paris Est Creteil | Bonnet S.,University of Liege | Lejeune P.,University of Liege | And 2 more authors.
Revue Francaise de Photogrammetrie et de Teledetection | Year: 2014

Recent development of small unmanned aerial systems opens the door for their use in forest mapping, as both the spatial and temporal resolution of drone imagery better suit local-scale investigation than traditional remote sensing tools. An original photogrammetric workflow, based on the open source toolbox MICMAC, was set up to model the forest canopy surface from low-altitude aerial images. In combination with a LiDAR digital terrain model, the elevation of vegetation was determined after a fine co-registration of the photogrammetric canopy surface model. The investigation of different images matching strategies is performed within MICMAC and their performance in modelling the outer canopy is compared. Although photogrammetric reconstruction do not account for small peaks and gaps in the canopy surface, our results have shown the potential of drones to accurately estimate canopy height in broadleaf stands, confirming thus the feasibility of modeling height growth from UAV images time series. Source

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