As of March 2025, there were a reported 5,426 data centers in the United States, the most of any country worldwide. A further 529 were located in Germany, while 523 were located in the United Kingdom. What is a data center? A data center is a network of computing and storage resources that enables the delivery of shared software applications and data. These facilities can house large amounts of critical and important data, and therefore are vital to the daily functions of companies and consumers alike. As a result, whether it is a cloud, colocation, or managed service, data center real estate will have increasing importance worldwide. Hyperscale data centers In the past, data centers were highly controlled physical infrastructures, but the cloud has since changed that model. A cloud data service is a remote version of a data center – located somewhere away from a company's physical premises. Cloud IT infrastructure spending has grown and is forecast to rise further in the coming years. The evolution of technology, along with the rapid growth in demand for data across the globe, is largely driven by the leading hyperscale data center providers.

The hyperscale data center industry is experiencing robust growth, projected to reach a market size of $101.23 billion in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 5.29% from 2025 to 2033. This expansion is fueled by several key drivers. The exponential increase in data generated by cloud computing, the Internet of Things (IoT), and big data analytics necessitates massive data storage and processing capabilities, driving demand for hyperscale data centers. Furthermore, the increasing adoption of artificial intelligence (AI), machine learning (ML), and high-performance computing (HPC) applications further intensifies this demand. The shift towards digital transformation across various industries, coupled with the growing need for enhanced network connectivity and low latency, is also contributing significantly to market growth. Hyperscale colocation facilities are gaining traction, offering businesses a scalable and cost-effective alternative to self-build data centers. Competition among major players, including IBM, Hewlett Packard Enterprise, Alphabet, Cisco, Microsoft, Amazon Web Services, Huawei, Quanta Computer, Alibaba, Facebook, and Nvidia, is fierce, driving innovation and efficiency improvements within the sector. Geographical distribution reveals a strong presence in North America and Europe, driven by mature digital economies and robust IT infrastructure. However, the Asia-Pacific region is witnessing rapid growth, particularly in countries like India and China, fueled by increasing digitalization and government initiatives to support the development of digital infrastructure. Despite the positive growth trajectory, challenges remain. These include the high initial capital investment required for building and maintaining hyperscale data centers, the escalating energy consumption, and the growing concerns regarding data security and privacy. Addressing these challenges will be crucial for sustainable and responsible growth in the hyperscale data center market throughout the forecast period. The industry is likely to see further consolidation and strategic partnerships as companies seek to leverage economies of scale and expand their market reach. Recent developments include: November 2022 - Big Data Exchange (BDx), PT Indosat Tbk (Indosat Ooredoo Hutchison), and PT Aplikanusa Lintasarta announced their plan to build a 100MW data center complex on 12 acres of land. This new data center campus, CGK5, will be located in Karawang, West Java, east of Jakarta, and will be part of the company's third availability zone. The BDx Indonesia joint venture is a key component of the BDx platform, and the construction of CGK5 is BDx's 11th data center in the Asia-Pacific region. With more than USD 1 billion in committed investment funding, BDx's strong development trajectory across Asia allows scaled innovation in the most challenging markets., June 2022 - Equinix Inc., one of the leading global digital infrastructure companies, and PGIM Real Estate, the real estate investment and financing arm of PGIM, Prudential financial's global asset management business, announced the opening of the xScale data center in Sydney, named SY9x. This achievement followed the completion of the parties' USD 575 million joint venture., May 2022 - NTT Ltd in India announced the launch of its new hyperscale data center facility in Navi Mumbai, beginning with the NAV1A data center. This increases NTT's data center presence in the nation to 12 facilities, covering more than 2.5 million sq ft (232,258 m2) and 220 MW of facility power, solidifying its position as India's market leader in this segment., March 2022 - Yondr Group, one of the global leaders in developer, owner-operator, and service provider of data centers announced its expansion into the Malaysian market with a planned 200MW hyperscale campus to be developed on 72.8 acres of land acquired from TPM Technopark Sdn Bhd, a wholly owned subsidiary of Johor Corporation. Yondr's hyper-scale campus will be built in phases and have a total capacity of 200MW when completed, with the first phase anticipated to be completed in 2024. With at least 600MW of capacity, black fiber connectivity, and scalable utilities and infrastructure.. Key drivers for this market are: Growing Demand for Cloud Computing and Other High Performance Technologies. Potential restraints include: High Costs and Operational Concerns, Concerns related to Geoprivacy and Confidential Data. Notable trends are: Growing Demand for Cloud Computing and Other Hight Performance Technologies Driving the Market.

The U.S. Geological Survey and the University of Massachusetts at Amherst (UMass Amherst), in cooperation with the Massachusetts Department of Environmental Protection (MassDEP), began a series of studies in 2019 to develop a web-based statewide hydraulic modeling tool to provide preliminary culvert designs to support stream crossing replacement projects in Massachusetts. This Web Map Service (WMS) has been developed to query data from the hydraulic models at select stream crossing locations using the StreamStats web application for Massachusetts. The WMS contains stream crossing point locations with hydrology and hydraulic data tables and associated watershed polygons. These stream crossing locations were derived from the North Atlantic Aquatic Connectivity Collaborative data center (NAACC Data Center). Preliminary culvert designs for three-sided box, conspan arch, and a pipe culvert have been modeled using the U.S. Army Corps of Engineer’s Hydrologic Engineering Center’s River Analysis System (HEC-RAS) software with cross-sectional and channel geometry data derived from high-resolution light detection and ranging (lidar) Digital Elevation Models (DEM). The WMS layer provides the ability to generate reports in the StreamStats web application for Massachusetts at the stream crossing locations for site _location information, preliminary culvert designs, flood flows, bankfull channel geometry, aquatic habitat and stream connectivity restoration potential, basin characteristics, and other select information.

This project is a cooperative effort among the National Ocean Service, National Centers for Coastal Ocean Science, Center for Coastal Monitoring and Assessment; U.S. Geological Survey; National Park Service; and the National Geophysical Data Center to produce benthic habitat maps and georeferenced imagery for Puerto Rico and the U.S. Virgin Islands. This project was conducted in support of the U.S. Coral Reef Task Force. These point data were generated while conducting ground validation during map preparation.

Find a NYC Department of Small Business Services NYC Business Solutions Center, Workforce1 Career Center, or Employment Works Center. Click here to view a map- https://maps.nyc.gov/sbs/

The Navigation Data Center had several objectives in developing the U.S. Waterway Data. These objectives support the concept of a National Spatial Data Provide public access to national waterway data. Foster interagency and intra-agency cooperation through data sharing. Provide a mechanism to integrate waterway data (U.S. Army Corps of Engineers Port/Facility and U.S. Coast Guard Accident Data, for example) Provide a basis for intermodal analysis. Assist standardization of waterway entity definitions (Ports/Facilities, Locks, etc.). Provide public access to the National Waterway Network, which can be used as a basemap to support graphical overlays and analysis with other spatial data (waterway and modal network/facility databases, for example). Provide reliable data to support future waterway and intermodal applications. Source of Data The data included in these files are based upon the Annual Summary of Lock Statistics published by the U.S. Army Corps of Engineers/CEIWR, Navigation Data Center. The data are collected at each Corps owned and/or operated Lock by Corps personnel and towing industry vessel operators. This data was collected from the US Army Corps of Engineers and distributed on the National Transportation Atlas Database (NTAD).

© The U.S. Army Corps of Engineers/CEIWR, Navigation Data Center This layer is sourced from maps.bts.dot.gov.

Monthly summary statistics are based on data from the Lock Performance Monitoring System (LPMS). The LPMS was developed to collect a 100% sample of data on the locks that are owned and/or operated by the US Army Corps of Engineers. Each record contains data summarized monthly by lock chamber, and direction (upbound and number and types of vessels and lockages (recreation, commercial, tows, other), cuts, hardware operations, delay and processing times, number of tows and all vessels delayed, total tons, commodity tonnages, and number of barges. The data are by waterway and by calendar year. The waterway files contain 5 years of data for one waterway. The calendar year files contain 1 year of data for all waterways.

The Navigation Data Center had several objectives in developing the U.S. Waterway Data. These objectives support the concept of a National Spatial Data Provide public access to national waterway data. Foster interagency and intra-agency cooperation through data sharing. Provide a mechanism to integrate waterway data (U.S. Army Corps of Engineers Port/Facility and U.S. Coast Guard Accident Data, for example) Provide a basis for intermodal analysis. Assist standardization of waterway entity definitions (Ports/Facilities, Locks, etc.). Provide public access to the National Waterway Network, which can be used as a basemap to support graphical overlays and analysis with other spatial data (waterway and modal network/facility databases, for example). Provide reliable data to support future waterway and intermodal applications. Source of Data The data included in these files are based upon the Annual Summary of Lock Statistics published by the U.S. Army Corps of Engineers/CEIWR, Navigation Data Center. The data are collected at each Corps owned and/or operated Lock by Corps personnel and towing industry vessel operators. This data was collected from the US Army Corps of Engineers and distributed on the National Transportation Atlas Database (NTAD).

© The U.S. Army Corps of Engineers/CEIWR, Navigation Data Center

NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the National Tsunami Hazard Mitigation Program's (NTHMP) efforts to improve community preparedness and hazard mitigation. These integrated bathymetric-topographic DEMs are used to support tsunami and coastal inundation mapping. Bathymetric, topographic, and shoreline data used in DEM compilation are obtained from various sources, including NGDC, the U.S. National Ocean Service (NOS), the U.S. Geological Survey (USGS), the U.S. Army Corps of Engineers (USACE), the Federal Emergency Management Agency (FEMA), and other federal, state, and local government agencies, academic institutions, and private companies. DEMs are referenced to various vertical and horizontal datums depending on the specific modeling requirements of each State. For specific datum information on each DEM, refer to the appropriate DEM documentation. Cell sizes also vary depending on the specification required by modelers in each State, but typically range from 8/15 arc-second (~16 meters) to 8 arc-seconds (~240 meters).The DEM Global Mosaic is an image service providing access to bathymetric/topographic digital elevation models stewarded at NOAA's National Centers for Environmental Information (NCEI), along with the global GEBCO_2014 grid: http://www.gebco.net/data_and_products/gridded_bathymetry_data. NCEI builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. They can be used for modeling of coastal processes (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness. This service is a general-purpose global, seamless bathymetry/topography mosaic. It combines DEMs from a variety of near sea-level vertical datums, such as mean high water (MHW), mean sea level (MSL), and North American Vertical Datum of 1988 (NAVD88). Elevation values have been rounded to the nearest meter, with DEM cell sizes going down to 1 arc-second. Higher-resolution DEMs, with greater elevation precision, are available in the companion NAVD88: http://noaa.maps.arcgis.com/home/item.html?id=e9ba2e7afb7d46cd878b34aa3bfce042 and MHW: http://noaa.maps.arcgis.com/home/item.html?id=3bc7611c1d904a5eaf90ecbec88fa799 mosaics. By default, the DEMs are drawn in order of cell size, with higher-resolution grids displayed on top of lower-resolution grids. If overlapping DEMs have the same resolution, the newer one is shown. Please see NCEI's corresponding DEM Footprints map service: http://noaa.maps.arcgis.com/home/item.html?id=d41f39c8a6684c54b62c8f1ab731d5ad for polygon footprints and more information about the individual DEMs used to create this composite view. In this visualization, the elevations/depths are displayed using this color ramp: http://gis.ngdc.noaa.gov/viewers/images/dem_color_scale.png.A map service showing the location and coverage of land and seafloor digital elevation models (DEMs) available from NOAA's National Centers for Environmental Information (NCEI). NCEI builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. They can be used for modeling of coastal processes (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness. Layers available in the map service: Layers 1-4: DEMs by Category (includes various DEMs, both hosted at NCEI, and elsewhere on the web); Layers 6-11: NCEI DEM Projects (DEMs hosted at NCEI, color-coded by project); Layer 12: All NCEI Bathymetry DEMs (All bathymetry or bathy-topo DEMs hosted at NCEI).

There are a variety of resources available via The National Map homepage, such as static maps, interactive map viewers, and geospatial data. Some of these maps and apps include, the National Map Viewer, the 3D Elevation Program, the National Hydrography Dataset and Hydrography Viewer, the Historical Topographic Map and the US Topo. Via The National Map, historical topographic maps are available to search and download via a variety of options. The 3D Elevation Program (3DEP) provides information about, and access to elevation data meeting the 3DEP guidelines. Users can also access and view the National Hydrography Dataset via the Hydrography viewer; this is similar to the National Map Viewer, however the basemap is based on HUC watersheds. Using the National Map Viewer, users can search for, access and download current 7.5 minute US Topos for the entire country; users can also explore and view other data for their area of interest. Below, find links to the different The National Map resources that were described above. The National Map also provides access to other data and viewers, such as the National Land Cover Database, and The National Map Corps.

This comprehensive retail point-of-interest (POI) dataset provides a detailed map of retail establishments across the United States and Canada. Retail strategists, market researchers, and business developers can leverage precise store location data to analyze market distribution, identify emerging trends, and develop targeted expansion strategies.

Point of Interest (POI) data, also known as places data, provides the exact location of buildings, stores, or specific places. It has become essential for businesses to make smarter, geography-driven decisions in today's competitive retail landscape of location intelligence.

LocationsXYZ, the POI data product from Xtract.io, offers a comprehensive retail store data database of 6 million locations across the US, UK, and Canada, spanning 11 diverse industries, including: -Retail store locations -Restaurants -Healthcare -Automotive -Public utilities (e.g., ATMs, park-and-ride locations) -Shopping centers and malls, and more

Why Choose LocationsXYZ for Your Retail POI Data Needs? At LocationsXYZ, we: -Deliver POI data with 95% accuracy for reliable store location data -Refresh POIs every 30, 60, or 90 days to ensure the most recent retail location information -Create on-demand POI datasets tailored to your specific retail data requirements -Handcraft boundaries (geofences) for shopping center locations to enhance accuracy -Provide retail POI data and polygon data in multiple file formats

Unlock the Power of Retail Location Intelligence With our point-of-interest data for retail stores, you can: -Perform thorough market analyses using comprehensive store location data -Identify the best locations for new retail stores -Gain insights into consumer behavior and shopping patterns -Achieve an edge with competitive intelligence in retail markets

LocationsXYZ has empowered businesses with geospatial insights and retail location data, helping them scale and make informed decisions. Join our growing list of satisfied customers and unlock your business's potential with our cutting-edge retail POI data and shopping center location intelligence.

This data set comprises the Environmental Sensitivity Index (ESI) maps for the shoreline of San Francisco Bay. ESI data characterize estuarine environments and wildlife by their sensitivity to spilled oil. The ESI data include information for three main components: shoreline habitats; sensitive biological resources; and human-use resources. This atlas was developed to be utilized within desktop GIS systems and contains GIS files and related D-base files. Associated files include MOSS (Multiple Overlay Statistical System) export files, .PDF maps, and detailed user guides and metadata. A later version of these data was released in March 2007 and is filed under NODC accession number 0036884.

NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the National Tsunami Hazard Mitigation Program's (NTHMP) efforts to improve community preparedness and hazard mitigation. These integrated bathymetric-topographic DEMs are used to support tsunami and coastal inundation mapping. Bathymetric, topographic, and shoreline data used in DEM compilation are obtained from various sources, including NGDC, the U.S. National Ocean Service (NOS), the U.S. Geological Survey (USGS), the U.S. Army Corps of Engineers (USACE), the Federal Emergency Management Agency (FEMA), and other federal, state, and local government agencies, academic institutions, and private companies. DEMs are referenced to various vertical and horizontal datums depending on the specific modeling requirements of each State. For specific datum information on each DEM, refer to the appropriate DEM documentation. Cell sizes also vary depending on the specification required by modelers in each State, but typically range from 8/15 arc-second (~16 meters) to 8 arc-seconds (~240 meters).This is an ArcGIS image service showing color shaded relief visualizations of high-resolution digital elevation models (DEMs) of U.S. coastal regions. NOAA's National Geophysical Data Center (NGDC) builds and distributes high-resolution coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. They can be used for modeling of coastal processes (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness. DEMs included in this visualization: High-resolution DEMs of select U.S. coastal communities and surrounding areas. Most are at a resolution of 1/3 to 1 arc-second (approx 10-30 m); U.S. Coastal Relief Model: A 3 arc-second (approx 90 m) comprehensive view of the conterminous U.S. coastal zone, Puerto Rico, and Hawaii; Southern Alaska Coastal Relief Model: A 24 arc-second (approx. 500 m) model of Southern Alaska, spanning the Bering Sea, Aleutian Islands, and Gulf of Alaska. This map service can be used as a basemap. It has a transparent background, so it can also be shown as a layer on top of a different basemap. Please see NGDC's corresponding DEM Footprints map service for polygon footprints and more information about the individual DEMs used to create this composite view.A map service showing the location and coverage of land and seafloor digital elevation models (DEMs) available from NOAA's National Geophysical Data Center. NOAA's National Geophysical Data Center (NGDC) builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. They can be used for modeling of coastal processes (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness. Layers available in the map service: Layers 1-4: DEMs by Category (includes various DEMs, both hosted at NGDC, and elsewhere on the web); Layers 6-11: NGDC DEM Projects (DEMs hosted at NGDC, color-coded by project); Layer 12: All NGDC Bathymetry DEMs (All bathymetry or bathy-topo DEMs hosted at NGDC).

The USGS Transportation downloadable data from The National Map (TNM) is based on TIGER/Line data provided through U.S. Census Bureau and supplemented with HERE road data to create tile cache base maps. Some of the TIGER/Line data includes limited corrections done by USGS. Transportation data consists of roads, railroads, trails, airports, and other features associated with the transport of people or commerce. The data include the name or route designator, classification, and location. Transportation data support general mapping and geographic information system technology analysis for applications such as traffic safety, congestion mitigation, disaster planning, and emergency response. The National Map transportation data is commonly combined with other data themes, such as boundaries, elevation, hydrography, and structure ...

however, they are responsible for its appropriate application. Digital data files are periodically updated. Files are dated and users are responsible for obtaining the latest revisions of the data. Although these data have been processed successfully on a computer system at the U.S. Geological Survey, no warranty expressed or implied is made by the agency regarding the utility of the data on any other system, nor shall the act of distribution constitute any such warranty. A copy of this map is presented on the CAPS Version 1.0 CD-ROM, June 1998.

Contains physical information on commercial facilities at the principal U.S. Coastal, Great Lakes and Inland Ports. The data consists of listings of port area's waterfront facilities, including information on berthing, cranes, transit sheds, grain elevators, marine repair plants, fleeting areas, and docking and storage facilities. Collection of data is performed on a rotational basis to ensure on-site accuracy at each facility.

© The National Waterway Network was created on behalf of the Office of the Asistant Secretary for Research and Technology's Bureau of Transportation Statistics, the U.S. Army Corps of Engineers, the U.S. Bureau of Census, and the U.S. Coast Guard by Vanderbilt University and Oak Ridge National Laboratory. Additional agencies with input into network development include Volpe National Transportation Systems Center, Maritime Administration, Military Traffic Management Command, Tennessee Valley Authority, U.S. Environmental Protection Agency, and the Federal Railroad Administration. This layer is sourced from maps.bts.dot.gov.

The Navigation Data Center had several objectives in developing the U.S. Waterway Data. These objectives support the concept of a National Spatial Data Provide public access to national waterway data. Foster interagency and intra-agency cooperation through data sharing. Provide a mechanism to integrate waterway data (U.S. Army Corps of Engineers Port/Facility and U.S. Coast Guard Accident Data, for example) Provide a basis for intermodal analysis. Assist standardization of waterway entity definitions (Ports/Facilities, Locks, etc.). Provide public access to the National Waterway Network, which can be used as a basemap to support graphical overlays and analysis with other spatial data (waterway and modal network/facility databases, for example). Provide reliable data to support future waterway and intermodal applications.

© The National Waterway Network was created on behalf of the Office of the Asistant Secretary for Research and Technology's Bureau of Transportation Statistics, the U.S. Army Corps of Engineers, the U.S. Bureau of Census, and the U.S. Coast Guard by Vanderbilt University and Oak Ridge National Laboratory. Additional agencies with input into network development include Volpe National Transportation Systems Center, Maritime Administration, Military Traffic Management Command, Tennessee Valley Authority, U.S. Environmental Protection Agency, and the Federal Railroad Administration.

This data set provides soil maps for the United States (US) (including Alaska), Canada, Mexico, and a part of Guatemala. The map information content includes maximum soil depth and eight soil attributes including sand, silt, and clay content, gravel content, organic carbon content, pH, cation exchange capacity, and bulk density for the topsoil layer (0-30 cm) and the subsoil layer (30-100 cm). The spatial resolution is 0.25 degree. The Unified North American Soil Map (UNASM) combined information from the state-of-the-art US General Soil Map (STATSGO2) and Soil Landscape of Canada (SLCs) databases. The area not covered by these data sets was filled by using the Harmonized World Soil Database version 1.21 (HWSD1.21). The Northern Circumpolar Soil Carbon (NCSCD) database was used to provide more accurate and up-to-date soil organic carbon information for the high-latitude permafrost region and was combined with soil organic carbon content derived from the UNASM (Liu et al., 2013). The UNASM data were utilized in the North American Carbon Program (NACP) Multi-Scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) as model input driver data (Huntzinger et al., 2013). The driver data were used by 22 terrestrial biosphere models to run baseline and sensitivity simulations. The compilation of these data was facilitated by the NACP Modeling and Synthesis Thematic Data Center (MAST-DC). MAST-DC was a component of the NACP (www.nacarbon.org) designed to support NACP by providing data products and data management services needed for modeling and synthesis activities.

NOAA's National Geophysical Data Center (NGDC) created a bathymetric digital elevation model (DEM) for the Mariana Trench and adjacent seafloor in the Western Pacific Ocean. Bathymetric data used in DEM compilation were obtained from various sources, including internation, federal and academic partners. The DEM is referenced to the horizontal datum of World Geodetic System 1984 (WGS 84) and the vertical datum of sea level. Grid spacings for the Mariana Trench DEM is 6 arc-seconds (~180 meters). Please note that while positive elevations (elevations greater than 0 meters) are present in the DEM over 'dry' land (i.e. islands such as Guam and the Northern Mariana Islands), they should be ignored as the focus of DEM development was solely in the bathymetric realm.This is an ArcGIS image service showing color shaded relief visualizations of high-resolution digital elevation models (DEMs) of U.S. coastal regions. NOAA's National Geophysical Data Center (NGDC) builds and distributes high-resolution coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. They can be used for modeling of coastal processes (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness. DEMs included in this visualization: High-resolution DEMs of select U.S. coastal communities and surrounding areas. Most are at a resolution of 1/3 to 1 arc-second (approx 10-30 m); U.S. Coastal Relief Model: A 3 arc-second (approx 90 m) comprehensive view of the conterminous U.S. coastal zone, Puerto Rico, and Hawaii; Southern Alaska Coastal Relief Model: A 24 arc-second (approx. 500 m) model of Southern Alaska, spanning the Bering Sea, Aleutian Islands, and Gulf of Alaska. This map service can be used as a basemap. It has a transparent background, so it can also be shown as a layer on top of a different basemap. Please see NGDC's corresponding DEM Footprints map service for polygon footprints and more information about the individual DEMs used to create this composite view.A map service showing the location and coverage of land and seafloor digital elevation models (DEMs) available from NOAA's National Geophysical Data Center. NOAA's National Geophysical Data Center (NGDC) builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. They can be used for modeling of coastal processes (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness. Layers available in the map service: Layers 1-4: DEMs by Category (includes various DEMs, both hosted at NGDC, and elsewhere on the web); Layers 6-11: NGDC DEM Projects (DEMs hosted at NGDC, color-coded by project); Layer 12: All NGDC Bathymetry DEMs (All bathymetry or bathy-topo DEMs hosted at NGDC).

Global Surface Summary of the Day is derived from The Integrated Surface Hourly (ISH) dataset. The ISH dataset includes global data obtained from the USAF Climatology Center, located in the Federal Climate Complex with NCDC. The latest daily summary data are normally available 1-2 days after the date-time of the observations used in the daily summaries. The online data files begin with 1929 and are at the time of this writing at the Version 8 software level. Over 9000 stations' data are typically available. The daily elements included in the dataset (as available from each station) are: Mean temperature (.1 Fahrenheit) Mean dew point (.1 Fahrenheit) Mean sea level pressure (.1 mb) Mean station pressure (.1 mb) Mean visibility (.1 miles) Mean wind speed (.1 knots) Maximum sustained wind speed (.1 knots) Maximum wind gust (.1 knots) Maximum temperature (.1 Fahrenheit) Minimum temperature (.1 Fahrenheit) Precipitation amount (.01 inches) Snow depth (.1 inches) Indicator for occurrence of: Fog, Rain or Drizzle, Snow or Ice Pellets, Hail, Thunder, Tornado/Funnel Cloud Global summary of day data for 18 surface meteorological elements are derived from the synoptic/hourly observations contained in USAF DATSAV3 Surface data and Federal Climate Complex Integrated Surface Hourly (ISH). Historical data are generally available for 1929 to the present, with data from 1973 to the present being the most complete. For some periods, one or more countries' data may not be available due to data restrictions or communications problems. In deriving the summary of day data, a minimum of 4 observations for the day must be present (allows for stations which report 4 synoptic observations/day). Since the data are converted to constant units (e.g, knots), slight rounding error from the originally reported values may occur (e.g, 9.9 instead of 10.0). The mean daily values described below are based on the hours of operation for the station. For some stations/countries, the visibility will sometimes 'cluster' around a value (such as 10 miles) due to the practice of not reporting visibilities greater than certain distances. The daily extremes and totals--maximum wind gust, precipitation amount, and snow depth--will only appear if the station reports the data sufficiently to provide a valid value. Therefore, these three elements will appear less frequently than other values. Also, these elements are derived from the stations' reports during the day, and may comprise a 24-hour period which includes a portion of the previous day. The data are reported and summarized based on Greenwich Mean Time (GMT, 0000Z - 2359Z) since the original synoptic/hourly data are reported and based on GMT.

This dataset show the point locations of High Frequency (HF) radar systems across the US. HF radars measure the speed and direction of ocean surface currents in near real time. These radars can measure currents over a large region of the coastal ocean, from a few kilometers offshore up to 200 km, and can operate under any weather conditions. They are located near the water’s edge, and need not be situated atop a high point of land. Dozens of institutions own and operate HF radars within the United States, and many are coordinated through the US Integrated Ocean Observing System. Ocean surface current data from these radars are shared on national servers by the National Data Buoy Center and Scripps Institution of Oceanography. If specific information regarding a local radar system is needed, please contact Dr. Jack Harlan, Project Manager for the HF Radar Ocean Remote Sensing, US IOOS Program Office.

© US Integrated Ocean Observing System This layer is a component of Physical Oceanographic and Marine Habitat.

MarineCadastre.gov themed service for public consumption featuring layers related to the Physical and Oceanographic and Marine Habitat themes. This map service presents spatial information about MarineCadastre.gov services across the United States and Territories in the Web Mercator projection. The service was developed by the National Oceanic and Atmospheric Administration (NOAA), but may contain data and information from a variety of data sources, including non-NOAA data. NOAA provides the information “as-is” and shall incur no responsibility or liability as to the completeness or accuracy of this information. NOAA assumes no responsibility arising from the use of this information. The NOAA Office for Coastal Management will make every effort to provide continual access to this service but it may need to be taken down during routine IT maintenance or in case of an emergency. If you plan to ingest this service into your own application and would like to be informed about planned and unplanned service outages or changes to existing services, please register for our Data Services Newsletter (http://coast.noaa.gov/digitalcoast/publications/subscribe). For additional information, please contact the NOAA Office for Coastal Management (coastal.info@noaa.gov).

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Abstract: This data set provides a structural feature map of the Ronne Ice Shelf in Antarctica (also known as the Filchner-Ronne Ice Shelf). The map was developed as part of a project to study fracture propagation in the Ronne Ice Shelf, with special focus on the Evans Ice Stream. Features were digitized from the MODIS Mosaic of Antartica (MOA), a composite of individual Moderate Resolution Imaging Spectradiometer (MODIS) images taken between 20 November 2003 and 29 February 2004, with an effective resolution of 125 m. The data set includes estimates of the shelf boundary, including ice stream grounding zones, outlets of glaciers feeding the shelf, extents of islands and ice rises, and the location of the shelf front, and features observed within the shelf, including suture zones between ice streams, streaklines, fractures (crevasses and rifts), and fold-like features. Individual features can be extracted as a group of points and grouping is used to facilitate identification and plotting. Data files are available via FTP in ASCII text (.txt) format. One image file, in Portable Document Format (.pdf), shows the data included in the dataset, plotted using MATLAB. The data set also provides a MATLAB script which can be used to plot the data.