Staphylococcus lugdunensis Pacemaker-related Infection

We report the first known case of a device-related bloodstream infection involving Staphylococcus lugdunensis small-colony variants. Recurrent pacemaker-related bloodstream infection within a period of 10 months illustrates the poor clinical and microbiologic response even to prolonged antimicrobial drug therapy in a patient infected with this staphylococcal subpopulation

Population estimation in urban areas based on "mixed/cross" stereo models

In the project X3D4Pop we investigate if "mixed" satellite image pairs acquired on two different dates can be used to calculate meaningful building heights in urban areas. Based on These results, the dependency of urban population estimation models on the availability and quality of 3D data is tested. Study areas are Port-au-Prince and Salzburg. The 3D-models are validated against LiDAR-derived elevation models, population numbers are compared with rastered population data from Statistik Austria. The project explores first steps towards an urban population estimation Service by remote sensing, for the humanitarian community

Object-based 3D damage assessment using surface models derived from mixed-date stereo models

Damage assessment is a crucial aspect in different scientific but also publicly relevant fields. Especially in the humanitarian context the estimation is often time critical as conflict events, but also natural disasters urge a quick response. The presented approach analyzes the potential of cross-stereo satellite imagery, i.e. images from different dates of the same or even different satellite sensors, to allow the generation of pre- and post-event 3D information. The study area is located in the city of Mosul, Iraq. The concept of object-based analysis was applied for the 3D damage assessment. The classification outcomes are categorized in four different height classes. 73 % of the point reference data matches with the classification results of the damage assessment

Detection of Gully-Affected Areas by Applying Object-Based Image Analysis (OBIA) in the Region of Taroudannt, Morocco

This study aims at the detection of gully-affected areas by applying object-based image analysis in the region of Taroudannt, Morocco, which is highly affected by gully erosion while simultaneously  representing a major region of agro-industry with a high demand of arable land. As high-resolution optical satellite data are readily available from various sensors and with a much better temporal resolution than 3D terrain data, an area-wide mapping approach to extract gully-affected areas using only optical satellite imagery was developed. The methodology additionally incorporates expert knowledge and freely-available vector data in a cyclic object-based image analysis approach. This connects the two fields of geomorphology and remote sensing. The classification results show the successful implementation of the developed approach and allow conclusions on the current distribution of gullies. The results of the classification were checked against manually delineated reference data incorporating expert knowledge based on several field campaigns in the area, resulting in an overall classification accuracy of 62%. The error of omission accounts for 38% and the error of commission for 16%, respectively. Additionally, a manual assessment was carried out to assess the quality of the applied classification algorithm. The limited error of omission contributes with 23% to the overall error of omission and the limited error of commission contributes with 98% to the overall error of commission. This assessment improves the results and confirms the high quality of the developed approach for area-wide mapping of gully-affected areas in larger regions. In the field of landform mapping, the overall quality of the classification results is often assessed with more than one method to incorporate all aspects adequately

Processing of extremely high resolution LiDAR and RGB data: outcome of the 2015 IEEE GRSS data fusion contest—Part B: 3-D Contest

In this paper, we report the outcomes of the 2015 data fusion contest organized by the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society. As for previous years, the IADF TC organized a data fusion contest aiming at fostering new ideas and solutions for multisource studies. The 2015 edition of the contest proposed a multiresolution and multisensorial challenge involving extremely high resolution RGB images (with a ground sample distance of 5 cm) and a 3-D light detection and ranging point cloud (with a point cloud density of approximatively 65 pts/m2 ). The competition was framed in two parallel tracks, considering 2-D and 3-D products, respectively. In this Part B, we report the results obtained by the winners of the 3-D contest, which explored challenging tasks of road extraction and ISO containers identification, respectively. The 2-D part of the contest and a detailed presentation of the dataset are discussed in Part A

AGIT Journal für Angewandte Geoinformatik / Bevölkerungsabschätzung in Städten anhand von Stereo-Bildpaarungen, di e nicht am selben Tag aufgenommen wurden

Im Projekt X3D4Pop wird untersucht, inwiefern Bildpaare, die an unterschiedlichen Tagen aufgenommen wurden, geeignet sind, um daraus brauchbare Höheninformation von Gebäuden in Städten abzuleiten. Darauf aufbauend wird getestet, wie stark die Abschätzung der Bevölkerungszahl von der Verfügbarkeit von 3D-Daten abhängt. Testgebiete sind Salzburg und Port-au-Prince. Als Referenz dienen aus LiDAR-Daten abgeleitete Höhenmodelle sowie gerasterte Bevölkerungsdaten von Statistik Austria. Ziel ist, die Arbeitsabläufe eines Services zur urbanen Bevölkerungsabschätzung basierend auf Fernerkundungsdaten für humanitäre Organisationen zu entwickeln.In the project X3D4Pop we investigate if “mixed” satellite image pairs acquired on two different dates can be used to calculate meaningful building heights in urban areas. Based on These results, the dependency of urban population estimation models on the availability and quality of 3D data is tested. Study areas are Port-au-Prince and Salzburg. The 3D-models are validated against LiDAR-derived elevation models, population numbers are compared with rastered population data from Statistik Austria. The project explores first steps towards an urban population estimation Service by remote sensing, for the humanitarian community.(VLID)448205