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We have investigated calibration variations in the Rameau water vapor Raman lidar. This lidar system was developed by the Institut National de l'Information Géographique et Forestière (IGN) together with the Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS). It aims at calibrating Global Navigation Satellite System (GNSS) measurements for tropospheric wet delays and sounding the water vapor variability in the lower troposphere. The Rameau system demonstrated good capacity in retrieving water vapor mixing ratio (WVMR) profiles accurately in several campaigns. However, systematic shortterm and long-term variations in the lidar calibration factor pointed to persistent instabilities. A careful testing of each subsystem independently revealed that these instabilities are mainly induced by mode fluctuations in the optic fiber used to couple the telescope to the detection subsystem and by the spatial nonuniformity of the photomultiplier photocathodes. Laboratory tests that replicate and quantify these instability sources are presented. A redesign of the detection subsystem is presented, which, combined with careful alignment procedures, is shown to significantly reduce the instabilities. Outdoor measurements were performed over a period of 5 months to check the stability of the modified lidar system. The calibration changes in the detection subsystem were monitored with lidar profile measurements using a common nitrogen filter in both Raman channels. A short-term stability of 2-3% and a long-term drift of 2-3% per month are demonstrated. Compared to the earlier Development of Methodologies forWater Vapour Measurement (DEMEVAP) campaign, this is a 3-fold improvement in the long-term stability of the detection subsystem. The overall water vapor calibration factors were determined and monitored with capacitive humidity sensor measurements and with GPS zenith wet delay (ZWD) data. The changes in the water vapor calibration factors are shown to be fairly consistent with the changes in the nitrogen calibration factors. The nitrogen calibration results can be used to correct the overall calibration factors without the need for additional water vapor measurements to within 1% per month. [ABSTRACT FROM AUTHOR]

In classical photogrammetric processing pipeline, the automatic tie point extraction plays a key role in the quality of achieved results. The image tie points are crucial to pose estimation and have a significant influence on the precision of calculated orientation parameters. Therefore, both relative and absolute orientations of the 3D model can be affected. By improving the precision of image tie point measurement, one can enhance the quality of image orientation. The quality of image tie points is under the influence of several factors such as the multiplicity, the measurement precision and the distribution in 2D images as well as in 3D scenes. In complex acquisition scenarios such as indoor applications and oblique aerial images, tie point extraction is limited while only image information can be exploited. Hence, we propose here a method which improves the precision of pose estimation in complex scenarios by adding a second iteration to the classical processing pipeline. The result of a first iteration is used as a priori information to guide the extraction of new tie points with better quality. Evaluated with multiple case studies, the proposed method shows its validity and its high potiential for precision improvement. [ABSTRACT FROM AUTHOR]

A detailed investigation of calibration variation sources in the instrumental part of the detection-fibered, water vapor Raman lidar, Rameau, is presented. This lidar has been developed by the Institut National de l'Information Géographique et Forestière (IGN) together with the Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS) and aims at calibrating GNSS wet delay signals and thus at improving vertical positioning. Several measurements campaigns enabled to validate the capacity of the instrument to retrieve high accuracy water vapor measurements. However, in order to insure a good stability, regular calibrations were necessary and led us to seek for instability sources in each sub-system of the instrument. The calibration variations are shown to be induced by fiber mode fluctuations and spatial non-uniformity of the photomultiplier photocathodes, and are responsible for significant calibration coefficient drifts. Such drifts are incompatible with both the long term stability required for applications such as climatology and the absolute accuracy needed for wet path delay correction of GNSS signals. We show by means of experimental tests that variation sources can be mitigated by means of an optimization and re-design of the optical detection system, a careful alignment procedure, and the operational monitoring of the system with dedicated measurements. In order to validate the modifications of the system and the new procedure, measurements were repeated over a period of 5 months. The detection subsystem stability was monitored from lidar profiles measured with a unique nitrogen filter used for detecting the signal in the two measurement channels. Compared to the previous campaign (Development of Methodologies for Water Vapor Measurement, Demevap), we observe an improvement in the stability of the system based on the nitrogen measurements which showed a drift of less than 3 & % per month and a standard deviation of about 3 & % during the campaign. The water vapor calibration coefficients were determined from capacitive humidity sensor measurements and from GPS zenith wet delays measurements. They show a similar small drift of 3 & % per month and a standard deviation of ~ & 6 & %. Thanks to the N2 measurements, the drift can be completely removed. Lower standard deviation can be achieved by increasing the Signal to Noise Ratio and/or spatial and temporal integration window. [ABSTRACT FROM AUTHOR]