Die Festung Ehrenbreitstein ist der ideale Standort zur Beobachtung des Zusammenflusses von Rhein und Mosel am Deutschen Eck in Koblenz. Aus ca. 100 m Höhe über dem Wasserspiegel liefert die WebCam der Bundesanstalt der Gewässerkunde jede Minute ein aktuelles Bild der Situation. Oftmals sind deutliche Unterschiede in der Färbung des Wassers sichtbar, besonders bei sich ändernden Wasserständen in den beiden Flüssen. Grund für die unterschiedliche Farbe sind die wechselnden Schwebstoffanteile. Auch der Wasserstand lässt sich mit einem Blick erkennen. Ab einem Wasserstand von ca. sieben Metern am Pegel Koblenz/Rhein wird der Platz vor dem Reiterstandbild Kaiser Wilhelms I allmählich überflutet. Dieser Service wird ermöglicht mit freundlicher Unterstützung der Verwaltungen von Burgen, Schlösser, Altertümer Rheinland-Pfalz und dem Landesmuseum Koblenz.
Das Projekt "WebSnow: Integration of Webcam data for deriving Snow cover and snow depth from Sentinel-1, Sentinel-2 and Pléiades data" wird/wurde gefördert durch: Österreichische Forschungsförderungsgesellschaft mbH (FFG). Es wird/wurde ausgeführt durch: Technische Universität Wien, Department für Geodäsie und Geoinformation (E120).The variability in snow cover have huge impact on climate, on a variety of ecosystems, and on socio-economic aspects of human life. Snowfall and persistence of snow cover are strongly dependent on atmospheric temperature and precipitation, thus likely to change in complex ways in a changing climate. In the Alpine region, snow cover variability is a high socio-economic aspect not only as local water resource and storage, but also as climate-related hazard and winter tourism. To quantify the effect of climate change on snow variation and the annual and inter-annual snow dynamics required by local stakeholders, a continuous reliable measurement of the temporal and spatial variability of snow cover is needed. For monitoring snow cover variability, the most important parameters are the amount and duration of seasonal snow cover and snow depth from where the amount of water stored within the snowpack can be derived.
The available techniques and sampling strategies employed to quantify snow cover and depth have all strengths and limitations. To monitor the extent of wet snow areas during the melting season Synthetic Aperture Radar satellite data are currently used in the Alps. At dry snow conditions, the snow cover extent for complex alpine terrain can be retrieved from high-resolution optical satellite imagery. However, the fundamental challenges of satellite data remain in terms of data availability, spatial resolution and cloud cover. Furthermore, quantifying large scale snow depth from satellite platform remains on open issue. In this respect, snow depth is currently estimated at local and regional scale by mean of photogrammetric techniques from manned and unmanned aerial platforms. However, snow is a challenging surface for photogrammetric techniques due to its relatively uniform surface with limited identifiable features. An alternative to airborne technologies to derive snow cover and depth is terrestrial photography. Currently this technique is used on study areas under control conditions such as camera information are known, and often linked to meteorological stations equipped with snow depth sensors or snow stakes in the field of view of the camera. Only recently, outdoor webcam images are considered as potential data source for deriving snow cover, thanks to their high spatio-temporal resolution and availability.
WebSnow focuses on improving snow cover maps and snow depth estimates using a large network (accessible via Bergfex) of webcam images available at different elevation zone from ski resort and mountain areas. The overall goal of the project is to develop a methodology and study the feasibility of using webcam images for (i) validating and improving snow cover maps from high resolution Sentinel-1 & -2 data and for (ii) deriving snow depth from Pléiades images at higher temporal resolutions and larger areas than what is feasible using UAV and aerial images. (abridged text)
Das Projekt "Development and evaluation of a webcam based luminometer for the luminescent bacteria test" wird/wurde ausgeführt durch: Technische Hochschule Ulm, University of Applied Sciences Labor Biotechnologie, Fakultät Mechatronik und Medizintechnik.Vibrio fischeri is a luminescent marine bacterium whose luminous intensity depends on the toxicity of its surroundings. By comparing light intensity before and after a certain contact time with a water sample, these bacteria can be used to detect various environmental toxins including unknown ones. A sample is considered nontoxic when the inhibition is less then 20 percent after 30min contact. In Germany, the luminescent bacteria inhibition test described in DIN EN ISO 11348 (Part 1) is a compulsory test for waste waters of industrial origin. Commercial Luminometers use Photomultiplier tubes for detection. PMTs are highly sensitive measurement devices hence the price of commercial instruments can be up to 15,000€ (including VAT). Our group has some experience with detection of low (fluorescent) light intensities by CCD cameras and webcams. In a preceding student research project we were able to prove that selected webcams are sensitive enough to detect luminescence by Vibrio fischeri in the low concentrations used in commercially available test kits. We now have developed a simple but sensitive Luminometer based on a low priced modified (black and white CCD chip and long exposure) webcam. The inhibition of various bacteria concentrations was compared to a commercial device as well as tests with actual samples. The webcam takes a picture of the light emitting test sample. The software then calculates the average luminescence of a pre defined region of interest. An additional feature is a LED for measurement of optical density which is needed to produce bacteria suspensions with standard concentrations.