OpenStreetMap is a free editable map of the whole world. It is made by people like you.
OpenStreetMap allows you to view, edit and use geographical data in a collaborative way from anywhere on Earth
Vielversprechend aber nicht vollständig
Der NiedersachsenViewer ist ein Werkzeug zur Visualisierung von Geodaten. Er ermöglicht die individuelle Kartenzusammenstellung durch Kombination der angebotenen Ebenen und das Hinzufügen von Inhalten externer Anbieter. Das Abfragen von Attributen zu den Karten wird unterstützt.
Der FOSSGIS e.V. ist ein eingetragener und gemeinnütziger Verein. Unser Ziel ist die Förderung und Verbreitung freier Geographischer Informationssysteme (GIS) im Sinne Freier Software und Freier Geodaten.
I joined the EVASION team in september 2006 in order to work on real time rendering of natural landscapes as a whole. I'm interested in the animation and realistic rendering of terrain, atmosphere, ocean, vegetation, rivers, clouds, etc. I'm looking for real-time and scalable algorithms allowing users to navigate freely anywhere in very large landscapes (up to whole planets), from ground to space, without visible transitions.
free geographical database of over eight million geographical names and consists of 6.3 million unique features available for download and accessible through a number of webservices
government-funded and approved agencies such as the Ordnance Survey and UK Hydrographic Office and Highways Agency collect data using our funds should make that data available for free
E. Valle, H. Qasim, und I. Celino. Proceedings of 1st International Workshop on Pervasive Web Mapping, Geoprocessing and Services (WebMGS 2010), (2010)
A. Frank, und R. Barrera. Design and Implementation of Large Spatial Databases, Volume 409 von Lecture Notes in Computer Science, Springer Berlin Heidelberg, (1989)
A. Geronimus, J. Bound, und L. Neidert. Journal of the American Statistical Association, 91 (434):
529--537(Juni 1996)Investigators of social differentials in health outcomes commonly augment incomplete microdata by appending socioeconomic characteristics of residential areas (such as median income in a zip code) to proxy for individual characteristics. But little empirical attention has been paid to how well this aggregate information serves as a proxy for the individual characteristics of interest. We build on recent work addressing the biases inherent in proxies and consider two health-related examples within a statistical framework that illuminates the nature and sources of biases. Data from the Panel Study of Income Dynamics and the National Maternal and Infant Health Survey are linked to census data. We assess the validity of using the aggregate census information as a proxy for individual information when estimating main effects and when controlling for potential confounding between socioeconomic and sociodemographic factors in measures of general health status and infant mortality. We find a general, but not universal, tendency for aggregate proxies to exaggerate the effects of micro-level variables and to do more poorly than micro-level variables at controlling for confounding. The magnitude and direction of these biases vary across samples, however. Our statistical framework and empirical findings suggest the difficulties in and limits to interpreting proxies derived from aggregate census data as if they were micro-level variables. The statistical framework that we outline for our study of health outcomes should be generally applicable to other situations where researchers have merged aggregate data with microdata samples..