In case of an emergency, all dams are required to have a map of areas that would be inundated in the event of a dam failure. This dataset is a digital version of those areas within Kern County to be used for planning purposes.Use limitations Summary: This disclaimer statement requires the data recipient to receive the data "as is" with no warranty, and to hold all data providers not liable for any losses or damages caused by use of the data. The statement also requires the data recipient to not distribute any portion of the data without a copy of this disclaimer statement. Whereas the Kern Geographic Information Network (Kern GEONET) and its members and other agencies have developed digital geographic data herein referred to as "the Data." Whereas the entity or entities acquiring a copy the Data are herein referred to as "the Recipient." Whereas the Kern Geographic Information Network and its members, Kern Council of Governments and its member agencies, and other agencies that have developed and contributed the Data which is being transmitted to the Recipient by these agencies are herein referred to as "the Data Providers."

I. Disclaimer of Liability and Warranties A. The Recipient understands and agrees that it is possible that errors and omissions will occur in data input or programming done by the Data Providers to provide the data in the form desired. The Recipient further understands and agrees that it is probable that errors and omissions will occur in record keeping processes, especially when large numbers of records are developed and maintained, and that data may not meet the Recipient's standards as to accuracy or completeness. Notwithstanding, the Recipient agrees to take the data "as is", fully expecting that there may be errors and omissions associated with the data. B. The Recipient further understands and agrees that the Data Providers make absolutely no warranty whatsoever, whether expressed or implied, as to the accuracy, thoroughness, value, quality, validity, merchantability, suitability, condition or fitness for a particular purpose of the data or any programming used to obtain the data, nor as to whether the data are error-free, up-to-date, complete or based upon accurate or meaningful facts. C. The Recipient further understands and agrees that it will forever waive any and all rights, claims, causes of action or other recourse that it might otherwise have against the Data Providers for any injuries or damages of any type, whether direct, indirect, incidental, consequential or otherwise, resulting from any error or omission in the data or in any programming used to obtain the data, or in any manner arising out of or related to this agreement or the data provided hereunder. The Recipient agrees that the Data Providers shall not be liable to the Recipient for any liability, claim, loss, damage, injury or expense of any kind caused or alleged to be caused, directly or indirectly, by the inadequacy of data obtained from the Data Providers, by any deficiency of the Data Providers or the Recipient systems, by any delay or failure to provide any service, or by any other interruption, disruption or loss of the Recipient operations. II. Indemnification A. The Recipient agrees that it will provide no copy or partial copy of any data to any other party, including consultants under contract with The Recipient, without disclosing that the copy or partial copy was obtained from the Data Providers and without attaching the Disclaimer of Liability and Warranties paragraph. B. The Recipient hereby agrees to defend, save, hold harmless and indemnify the Data Providers and signatories to its data sharing agreements and its/their officers, employees and agents against claims by anyone for any loss, injury, damage, risk, cause of action, or liability of any type (including legal fees) incurred by the Recipient or any other person, relating to or arising out of the subject matter of this agreement, or which may be alleged to have been caused, either directly or indirectly, by the acts, conduct, omissions, negligence or lack of good faith of the Data Providers, their officers, agents or employees.

This point feature class represents high water marks captured by Baltimore County DPWT - Surveys section in November of 2003 following hurricane Isabel. Elevation values are in NAVD88. Most points have a PDF picture attachment available showing the location of the point surveyed.

This data is part of the series of maps that covers the whole of Australia at a scale of 1:250 000 (1cm on a map represents 2.5km on the ground) and comprises 513 maps. This is the largest scale at which published topographic maps cover the entire continent. Data is downloadable in various distribution formats.

This is a feature class outlining Palm Oil Plantations in Ucayali Province in Peru. A small team of faculty and student researchers hand digitized polygons delineating palm oil plantations in Ucayali, Peru in support of SERVIR Amazonia goals. GIS experts used high-resolution (< 1 m) optical observations to identify areas of oil palm presence across different conditions (young vs. mature, industrial vs. small-scale). This hand-digitized oil palm presence map will serve as a calibration / validation dataset for an automated classification model using remote sensing observations. This task presented numerous challenges, namely the availability of cloud-free, high resolution imagery. Polygons were digitized from numerous imagery datasets including mosaiced basemap imagery from Maxar and Planet Scope. Whenever the high resolution Maxar imagery was available, it was used. In some cases, we were unable to procure imagery in the time frame. We provide a training document describing our methodology and process in QGIS, an open source geospatial software package so other researchers could repeat our methods at later times or different geographic extents. The major variables in our study were the spatial extents of the palm oil plantations, whether they were open or closed canopy, and the imagery data source

These data were automated to provide an accurate high-resolution historical shoreline of Elizabeth River, Virginia suitable as a geographic information system (GIS) data layer. These data are derived from shoreline maps that were produced by the NOAA National Ocean Service including its predecessor agencies which were based on an office interpretation of imagery and/or field survey. The NGS attribution scheme 'Coastal Cartographic Object Attribute Source Table (C-COAST)' was developed to conform the attribution of various sources of shoreline data into one attribution catalog. C-COAST is not a recognized standard, but was influenced by the International Hydrographic Organization's S-57 Object-Attribute standard so the data would be more accurately translated into S-57. This resource is a member of https://inport.nmfs.noaa.gov/inport/item/39808

The Elizabeth River Trail (ERT) is a biking and pedestrian trail in the City of Norfolk that has transformed several former railroad rights-of-ways, connected predominantly by off-road and some on-road trails, into an urban trail. The trail provides recreational and educational opportunities as well as an alternate mode of transportation from the Norfolk Naval Base, located in the northern portion of the city, into downtown Norfolk. The nine-mile Elizabeth River Trail, which runs from Norfolk State University following the Elizabeth River northward to Terminal Boulevard, began with an abandoned railroad spur being transformed into a walking and bicycle trail. The Atlantic City Spur section of the trail neighbors the Midtown Tunnel and adjacent Plum Point Park. The Trail can be accessed at various points along the Elizabeth River to include the Waterside Festival Marketplace, the end of Southampton Avenue near the public health building, or at Claremont Avenue near Raleigh Avenue in West Ghent. The trail offers scenic views of the Elizabeth River and interpretive markers tell the history of the area and environment. For more information and a map of the complete trail visit norfolk.gov/bike.
References:
http://www.downtownnorfolk.org/enjoy/attractions?location_id=617
http://www.norfolk.gov/index.aspx?NID=746
https://mapsengine.google.com/map/viewer?mid=zC9qX0Q5IPQc.kRgK85wcXA6E

These data provide an accurate high-resolution shoreline compiled from imagery of Port of Brownsville/Port Isabel, TX . This vector shoreline data is based on an office interpretation of imagery that may be suitable as a geographic information system (GIS) data layer. This metadata describes information for both the line and point shapefiles. The NGS attribution scheme 'Coastal Cartographic Object Attribute Source Table (C-COAST)' was developed to conform the attribution of various sources of shoreline data into one attribution catalog. C-COAST is not a recognized standard, but was influenced by the International Hydrographic Organization's S-57 Object-Attribute standard so the data would be more accurately translated into S-57. This resource is a member of https://inport.nmfs.noaa.gov/inport/item/39808

Seagrass beds are critical wetlands components of shallow marine ecosystems along the Massachusetts coastline. Seagrass beds provide food and cover for a great variety of commercially and recreationally important fauna and their prey. The leaf canopy of the seagrass bed calms the water, filters suspended matter and together with extensive roots and rhizomes, stabilizes sediment. Seagrasses are often referred to as "Submerged Aquatic Vegetation" or SAV. This distinguishes them from algae, which are not classified as plants by biologists (rather they are often placed in the kingdom protista), and distinguishes them from the "emergent" saltwater plants found in salt marshes.

In Massachusetts, the dominant SAV is Zostera marina or eelgrass. The other species found in the embayments of the Massachusetts coast is Ruppia maritima, commonly called “widgeon grass,” which is present in areas of less salinity along Cape Cod and Buzzards Bay. Widgeon grass, found in the upper reaches of embayments, has a thread-like morphology that makes it difficult to identify using remotely sensed data. It can only be identified and located by on-site survey.

The Massachusetts Department of Environmental Protection (MassDEP) began a program to map the state's SAV resources in the early 1990s and since 1995 the MassDEP Eelgrass Mapping Project has produced multiple surveys of SAV along the Massachusetts coastline, as listed here:

PhaseProject YearsProject Area11995Entire MA Coast22001Coast-wide MA Coast except Elizabeth Islands (Gosnold) and Mount Hope Bay32006/07Selected embayments, coast-wide including Elizabeth Islands42010-20132010 - South Shore of Cape Cod: Woods Hole to Chatham, selected embayments, Pleasant Bay;2012 - North Shore, Boston Harbor, South Shore to Provincetown;2013 - Buzzards Bay, Elizabeth Islands, Martha's Vineyard and Nantucket52015-20172015 - South Shore of Cape Cod, Pleasant Bay, Nantucket;2016 - North Shore, Boston Harbor, South Shore to Canal;2017 - Buzzards Bay, North Shore of Cape Cod, Elizabeth Islands and Martha's Vineyard62019-20232019 - South Shore of Cape Cod, Pleasant Bay, North Shore of Nantucket2020 - Martha’s Vineyard, Buzzards Bay and Elizabeth Islands 2021 - Cape Cod Bay (Provincetown through Duxbury) 2022 - South Shore, Boston Harbor, North Shore (Marshfield through Rockport)2023 - Cape Ann to the New Hampshire border (Essex through Newburyport)

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Also see the map service.

These data were automated to provide an accurate high-resolution historical shoreline of Padre Island to Port Isabel, TX suitable as a geographic information system (GIS) data layer. These data are derived from shoreline maps that were produced by the NOAA National Ocean Service including its predecessor agencies which were based on an office interpretation of imagery and/or field survey. The NGS attribution scheme 'Coastal Cartographic Object Attribute Source Table (C-COAST)' was developed to conform the attribution of various sources of shoreline data into one attribution catalog. C-COAST is not a recognized standard, but was influenced by the International Hydrographic Organization's S-57 Object-Attribute standard so the data would be more accurately translated into S-57. This resource is a member of https://inport.nmfs.noaa.gov/inport/item/39808

These data provide an accurate high-resolution shoreline compiled from imagery of PORT OF BROWNSVILLE/PORT ISABEL, TX . This vector shoreline data is based on an office interpretation of imagery that may be suitable as a geographic information system (GIS) data layer. This metadata describes information for both the line and point shapefiles. The NGS attribution scheme 'Coastal Cartographic Object Attribute Source Table (C-COAST)' was developed to conform the attribution of various sources of shoreline data into one attribution catalog. C-COAST is not a recognized standard, but was influenced by the International Hydrographic Organization's S-57 Object-Attribute standard so the data would be more accurately translated into S-57. This resource is a member of https://www.fisheries.noaa.gov/inport/item/39808

The Galapagos coastal area is the most studied of the Galapagos Marine Reserve (GMR) and also the most vulnerable to impacts since it is where the greatest part of human activities takes place (fishing, tourism, leisure, etc.). Edgar et al. (2004) analysed shallow subtidal rocky reef coastal biodiversity data (fish and macro-invertebrate communities) collected in 2000-2001 in order to derive regional biogeography areas. Sampling units consisted of 50 m x 10 m line transects for fish and 50 m x 2 m line transects for macro-invertebrate species (sea cucumbers, sea urchins, octopus, lobsters, large gastropods, etc.) at various depths between - 2 and - 20 m and distributed along the coastal subtidal area of 50 islands and islets of the Galapagos. A multivariate analysis of the data resulted in the identification of three major biogeographical regions: the Far-northern islands of Darwin and Wolf; the Central-south-eastern islands, including the east coast of Isabela; and the Western region, comprising Fernandina and the west coast of Isabela. The Central-south-eastern region could be further divided in two, namely the Northern region, including the islands of Pinta, Marchena and Genovesa; and the Central-south-eastern region, including the islands of Santiago, Rábida, Pinzón, Santa Cruz, Baltra, Santa Fe, San Cristóbal, Floreana, Española and the eastern side of Isabela. Another region could be further identified in the Western region, the Elizabeth region, covering an area comprising the Bolivar channel and Urbina and Elizabeth bays down to Punta Moreno in Isabela and Punta Mangle in Fernandina. Edgar et al.'s study is one of the most cited marine studies in the Galapagos. However, the authors only included a small scale map and a written description of the bioregions geographical limits within the GMR but did not include a detailed paper or digital map. Here, I provide an interpretation of the bioregions identified in Edgar et al.'s study based on the figure and the descriptions included in it. The resulting data set is a GIS layer in ArcGIS shapefile format, EPSG 32715 (WGS 1984/UTM Zone 15S) and a Google Earth layer in KMZ format of the GMR shallow subtidal rocky reef bioregions based on fish and macro-invertebrate data. The layers include attribute information on bioregion name and area (in square km). This dataset will be of most utility to those attempting to use Edgar et al.'s Galapagos bioregions in their analyses since it provides for a consistent use of bioregion boundaries. Reference: Edgar, G. J., Banks, S., Fariña, J. M., Calvopiña, M., and Martínez, C. (2004, doi:10.1111/j.1365-2699.2004.01055.x). This publication is contribution number 2294DS of the Charles Darwin Foundation for the Galapagos Islands.

These data provide an accurate high-resolution shoreline compiled from imagery of BROWNSVILLE SHIP CHANNEL, PORT ISABEL TO BROWNSVILLE, TX . This vector shoreline data is based on an office interpretation of imagery that may be suitable as a geographic information system (GIS) data layer. This metadata describes information for both the line and point shapefiles. The NGS attribution scheme 'Coastal Cartographic Object Attribute Source Table (C-COAST)' was developed to conform the attribution of various sources of shoreline data into one attribution catalog. C-COAST is not a recognized standard, but was influenced by the International Hydrographic Organization's S-57 Object-Attribute standard so the data would be more accurately translated into S-57. This resource is a member of https://res1wwwd-o-tfisheriesd-o-tnoaad-o-tgov.vcapture.xyz/inport/item/39808

These data were automated to provide an accurate high-resolution historical shoreline of Elizabeth, NJ suitable as a geographic information system (GIS) data layer. These data are derived from shoreline maps that were produced by the NOAA National Ocean Service including its predecessor agencies which were based on an office interpretation of imagery and/or field survey. The NGS attribution scheme 'Coastal Cartographic Object Attribute Source Table (C-COAST)' was developed to conform the attribution of various sources of shoreline data into one attribution catalog. C-COAST is not a recognized standard, but was influenced by the International Hydrographic Organization's S-57 Object-Attribute standard so the data would be more accurately translated into S-57. This resource is a member of https://res1inportd-o-tnmfsd-o-tnoaad-o-tgov.vcapture.xyz/inport/item/39808

These data provide an accurate high-resolution shoreline compiled from imagery of Willoughby Bay to Norfolk Harbor Reach and Elizabeth River to Port Norfolk, VA . This vector shoreline data is based on an office interpretation of imagery that may be suitable as a geographic information system (GIS) data layer. This metadata describes information for both the line and point shapefiles. The NGS attribution scheme 'Coastal Cartographic Object Attribute Source Table (C-COAST)' was developed to conform the attribution of various sources of shoreline data into one attribution catalog. C-COAST is not a recognized standard, but was influenced by the International Hydrographic Organization's S-57 Object-Attribute standard so the data would be more accurately translated into S-57. This resource is a member of https://www.fisheries.noaa.gov/inport/item/39808

These data provide an accurate high-resolution shoreline compiled from imagery of Gilmerton Bridge, Elizabeth River, VA . This vector shoreline data is based on an office interpretation of imagery that may be suitable as a geographic information system (GIS) data layer. This metadata describes information for both the line and point shapefiles. The NGS attribution scheme 'Coastal Cartographic...

This dataset contains polyline features representing the alignment of the Elizabeth River Trail. The polyline is broken into segments based on changes in surface type.Data collected, compiled, and maintained by the City of Norfolk, Department of Recreation, Parks, and Open Space.Any and all data sets are for graphical representations only and should not be used for legal purposes. Any determination of topography or contours, or any depiction of physical improvements, property lines or boundaries is for general information only and shall not be used for the design, modification, or construction of improvement to real property or for flood plain determination.

These data were automated to provide an accurate high-resolution historical shoreline of Vicinity of Elizabeth River, NC suitable as a geographic information system (GIS) data layer. These data are derived from shoreline maps that were produced by the NOAA National Ocean Service including its predecessor agencies which were based on an office interpretation of imagery and/or field survey. The NGS attribution scheme 'Coastal Cartographic Object Attribute Source Table (C-COAST)' was developed to conform the attribution of various sources of shoreline data into one attribution catalog. C-COAST is not a recognized standard, but was influenced by the International Hydrographic Organization's S-57 Object-Attribute standard so the data would be more accurately translated into S-57. This resource is a member of https://inport.nmfs.noaa.gov/inport/item/39808

Locations of TfL Rail stationsUpdate Frequency: As requiredLast Updated: Not knownData Owner/Key Contact: London UndergroundSpatial Data Source: Shapefiles provided by London UndergroundMastermap Alignment: N/A

Address Points dataset current as of 2008. Elizabeth City Address Points.

Zoning districts of Elizabeth, ColoradoNOTE: This is NOT an authoritative dataset.