Abstract. Steep, hardly accessible cliffs of rhyolite tuff in NE Hungary are prone to rockfalls, endangering visitors of a castle. Remote sensing techniques were employed to obtain data on terrain morphology and to provide slope geometry for assessing the stability of these rock walls. A RPAS (Remotely Piloted Aircraft System) was used to collect images which were processed by Pix4D mapper (structure from motion technology) to generate a point cloud and mesh. The georeferencing was made by Global Navigation Satellite System (GNSS) with the use of seven ground control points. The obtained digital surface model (DSM) was processed (vegetation removal) and the derived digital terrain model (DTM) allowed cross sections to be drawn and a joint system to be detected. Joint and discontinuity system was also verified by field measurements. On-site tests as well as laboratory tests provided additional engineering geological data for slope modelling. Stability of cliffs was assessed by 2-D FEM (finite element method). Global analyses of cross sections show that weak intercalating tuff layers may serve as potential slip surfaces. However, at present the greatest hazard is related to planar failure along ENE-WSW joints and to wedge failure. The paper demonstrates that RPAS is a rapid and useful tool for generating a reliable terrain model of hardly accessible cliff faces. It also emphasizes the efficiency of RPAS in rockfall hazard assessment in comparison with other remote sensing techniques such as terrestrial laser scanning (TLS).

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Scheimpflug imaging method is a useful tool to analyze the anterior segment parameters in FUS. Endothelial cell loss, as well as decreased percentage of endothelial hexagonal cells, is obtained by noncontact specular microscopy in patients with FUS.

ABSTRACT:The technological developments in remote sensing (RS) during the past decade has contributed to a significant increase in the size of data user community. For this reason data quality issues in remote sensing face a significant increase in importance, particularly in the era of Big Earth data. Dozens of available sensors, hundreds of sophisticated data processing techniques, countless software tools assist the processing of RS data and contributes to a major increase in applications and users. In the past decades, scientific and technological community of spatial data environment were focusing on the evaluation of data quality elements computed for point, line, area geometry of vector and raster data. Stakeholders of data production commonly use standardised parameters to characterise the quality of their datasets. Yet their efforts to estimate the quality did not reach the general end-user community running heterogeneous applications who assume that their spatial data is error-free and best fitted to the specification standards. The non-specialist, general user group has very limited knowledge how spatial data meets their needs. These parameters forming the external quality dimensions implies that the same data system can be of different quality to different users. The large collection of the observed information is uncertain in a level that can decry the reliability of the applications. Based on prior paper of the authors (in cooperation within the Remote Sensing Data Quality working group of ISPRS), which established a taxonomy on the dimensions of data quality in GIS and remote sensing domains, this paper is aiming at focusing on measures of uncertainty in remote sensing data lifecycle, focusing on land cover mapping issues. In the paper we try to introduce how quality of the various combination of data and procedures can be summarized and how services fit the users' needs. The present paper gives the theoretic overview of the issue, besides selected, practice-oriented approaches are evaluated too, finally widely-used dimension metrics like Root Mean Squared Error (RMSE) or confusion matrix are discussed. The authors present data quality features of well-defined and poorly defined object. The central part of the study is the land cover mapping, describing its accuracy management model, presented relevance and uncertainty measures of its influencing quality dimensions. In the paper theory is supported by a case study, where the remote sensing technology is used for supporting the area-based agricultural subsidies of the European Union, in Hungarian administration.

We could demonstrate close correlation between macular thickness and inflammation in anterior uveitic patients with spondyloarthropathy.

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Purpose To describe and correlate the degree of anterior segment inflammation with central retinal and choroidal thickness throughout the treatment period (in the course of follow-up) in the eyes affected with acute anterior uveitis in the patients with seronegative spondyloarthropathy (subgroup: ankylosing spondylitis). Methods Thirty eyes of 30 consecutive Caucasian patients with HLA-B27-associated acute anterior uveitis were included in this study. The flare, AC cell number, and central retinal/choroidal thickness were determined at each visit by optical coherence tomography and laser flare photometry. Treatment consisted of topical corticosteroids. Statistical analysis was performed by MathWorks Matlab software. Results In the follow-up period, central retinal thickness was increased in the first 9-10 days and then decreased until stabilization (after 5-6 weeks). The flare and AC cell number decreased rapidly at the beginning of the treatment, in the first 10 days, and thereafter, slower decrease could be observed until complete resolution of inflammation. Statistically significant, positive correlation was found between initial laser flare value and maximal central retinal thickness (r=0.881, p < 0.001). Positive correlation between flare and retinal thickening was observable throughout the treatment period. Central choroidal thickness was decreased also significantly during the follow-up (p < 0.001). Conclusions The retina and choroid may play a biomarker function in the anterior segment inflammation of the eye in the patients with seronegative spondyloarthropathy.

The state-of-the-art geodetic and remote sensing techniques can prove their potential through particular engineering applications. Besides the traditional surveying terrestrial laserscanning broadens its application field in civil engineering projects. The Department of Photogrammetry and Geoinformatics has long experience in the measurement methods, accuracy analysis and applications of terrestrial laserscanning. This paper deals with the potential of the technology through the examples of load test measurements of Danube bridges. Prior to the particular bridge surveying projects accuracy analysis has been carried out in laboratory measurements, the results validated the accuracy and reliability of the laserscanned data. The paper discusses the complex measurement procedure, the main steps of the data processing and results. Remote sensing can provide data about specific (e.g. with limited accessibility) areas of the structure that cannot be measured with traditional techniques during the short period of the load test measurements. The postprocessing includes comparison analysis using ground-based geodetic measurements (such as high precision leveling) as reference in defining displacements. By computing the accuracy measures of the terrestrial laserscanning the overall technology can be qualified and calibrated.