Cette carte montre les valeurs médianes de turbidité maximale mensuelle (en unités de turbidité néphélémétrique) pour les installations de traitement de l’eau selon la région de drainage. La turbidité est définie par le manque de limpidité de l’eau causé par des particules en suspension dans l’eau. Les données permettant de mesurer les valeurs de turbidité maximale mensuelle des sources d’eau de surface ont été recueillies dans le cadre de l’Enquête sur les usines de traitement de l’eau potable pour les installations ayant déclaré des données sur la turbidité pendant au moins 10 mois. Ces installations ont approvisionné 24 millions de personnes et ont produit 4 091 millions de mètres cubes d’eau potable provenant de sources d’eau de surface en 2013. La turbidité des sources d’eau a été surveillée de façon continue par 42 % de ces usines de traitement de l’eau potable en 2013, et au moins une fois par jour par 34 % des usines. La surveillance était moins fréquente dans les autres installations.

Dieser Dienst stellt aktuelle Wettervorhersageinformation für das Bundesland Sachsen und angrenzende Gebiete bereit. Die Daten werden durch das numerische Vorhersagemodell WRF-EMS (The Weather Research and Forecast Environmental Modeling System) im Labor Geoinformatik der Hochschule für Technik und Wirtschaft Dresden alle 6 Stunden neu berechnet. Es werden für eine Vorhersagedauer von 48 Stunden Wetterkarten für die folgenden Parameter veröffentlicht: - Temperatur in 2 m Höhe - Niederschlagsmenge - Windgeschwindigkeit in 10 m Höhe und Windrichtung - Relative Luftfeuchte - Wolkenbedeckung - Schneefall (Menge) - Luftdruck auf Meeresniveau. Zur Berechnung der Vorhersagedaten werden globale meteorologische Modelldaten des amerikanischen Wetterdienstes (NOAA) sowie Oberflächendaten des Geologischen Dienstes der USA (USGS) verwendet. Zusätzlich werden stationsbezogene Vorhersagedaten als Piktogramme des norwegischen Wetterdienstes yr.no bereitgestellt. Über eine Sachdatenabfrage können zusätzlich Meteogramme abgefragt werden.

Administrative boundaries from National Land Survey of Iceland database called IS 50V

This dataset combines the work of several different projects to create a seamless data set for the contiguous United States. Data from four regional Gap Analysis Projects and the LANDFIRE project were combined to make this dataset. In the Northwestern United States (Idaho, Oregon, Montana, Washington and Wyoming) data in this map came from the Northwest Gap Analysis Project. In the Southwestern United States (Colorado, Arizona, Nevada, New Mexico, and Utah) data used in this map came from the Southwest Gap Analysis Project. The data for Alabama, Florida, Georgia, Kentucky, North Carolina, South Carolina, Mississippi, Tennessee, and Virginia came from the Southeast Gap Analysis Project and the California data was generated by the updated California Gap land cover project. In areas of the county (central U.S., Northeast) that have not yet been covered by a regional Gap Analysis Project, data from the Landfire project was used. In 2009 Landfire data was combined by the Landscope project into one uniform coverage. This compiled data was the data pulled into this project. Similarities in the methods used by these projects made possible the combining of the data they derived into one seamless coverage. They all used multi-season satellite imagery (Landsat ETM+) from 1999-2001 in conjunction with digital elevation model (DEM) derived datasets (e.g. elevation, landform) to model natural and semi-natural vegetation. Vegetation classes were drawn from NatureServe's Ecological System Classification (Comer et al. 2003). Additionally, all of the projects included land use classes that were employed to describe areas where natural vegetation has been altered. In many areas of the country these classes were derived from the National Land Cover Dataset (NLCD). For the majority of classes and, in most areas of the country, a decision tree classifier was used to discriminate ecological system types. In some areas of the country, more manual techniques were used to discriminate small patch systems and systems not distinguishable through topography. The digital land cover dataset may be used for various purposes with user's discretion. Specifically, this dataset was created for regional terrestrial biodiversity assessment. These data are not intended to be used at scales larger than 1:100,000.

This is a description of your Web Map Server.

WMS

A compliant implementation of WMS plus most of the SLD extension (dynamic styling). Can also generate PDF, SVG, KML, GeoRSS

WMS

WMS