38 datasets found
  1. Engineering Projects

    • data-bc-er.opendata.arcgis.com
    • hub.arcgis.com
    • +2more
    Updated Aug 30, 2016
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    BC_Energy_Regulator (2016). Engineering Projects [Dataset]. https://data-bc-er.opendata.arcgis.com/datasets/81a48eb254e840b0b5c4e79efa6e3646
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    Dataset updated
    Aug 30, 2016
    Dataset provided by
    Oil and Gas Commission
    Authors
    BC_Energy_Regulator
    Area covered
    Description

    BC Energy Regulator Engineering Project approvals may be issued, upon application, under the authority of Section 100 of the Drilling and Production Regulation or Section 97 of the Petroleum and Natural Gas Act, depending on project type. Projects grant the applicant operating latitude, under specific conditions, for the purpose of extracting oil and/or natural gas in the most efficient way that will result in maximization of resource recovery and benefit to the Crown, balanced with surface impact and socio-economic factors. Examples are ?Good Engineering Practice?, allowing increased well density in a poor quality reservoir, or ?Pressure Maintenance Water Flood? to allow injection of water into an oil pool to increase total oil recovery. Spatial data for approved projects are included. Data is updated nightly.

  2. ArcGIS Training in Nepal

    • kaggle.com
    zip
    Updated Sep 22, 2024
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    Tek Bahadur Kshetri (2024). ArcGIS Training in Nepal [Dataset]. https://www.kaggle.com/datasets/tekbahadurkshetri/arcgis-training-in-nepal
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    zip(571304278 bytes)Available download formats
    Dataset updated
    Sep 22, 2024
    Authors
    Tek Bahadur Kshetri
    Area covered
    Nepal
    Description

    The Civil Engineering Students Society organized an 'ArcGIS Online Training for Beginners.' Geographical Information System (GIS) technology provides the tools for creating, managing, analyzing, and visualizing data associated with developing and managing infrastructure.

    It also allowed civil engineers to manage and share data, turning it into easily understood reports and visualizations that could be analyzed and communicated to others. Additionally, it helped civil engineers in spatial analysis, data management, urban development, town planning, and site analysis.

    It is equally important for beginner geospatial students.

  3. m

    Data from: Data for GIS-based spatial vulnerability analysis in the area of...

    • data.mendeley.com
    Updated Mar 21, 2025
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    Amirehsan Charlang Bakhtyari (2025). Data for GIS-based spatial vulnerability analysis in the area of Alessandria in Italy in case of road network disruption [Dataset]. http://doi.org/10.17632/sg7267bcs6.2
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    Dataset updated
    Mar 21, 2025
    Authors
    Amirehsan Charlang Bakhtyari
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Alessandria, Italy
    Description

    The input file contains supply data (based on data from geoportal of piedmont and OSM data) and flood map (based on data from geoportal of piedmont) for the Alessandria area in Italy, detailing both basic and disrupted flood scenarios to be analyzed in GIS software. It includes information on closed bridges during flood events. The output file presents the analysis results for both the basic and disrupted scenarios.

  4. Urban Road Network Data

    • figshare.com
    • resodate.org
    zip
    Updated May 30, 2023
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    Urban Road Networks (2023). Urban Road Network Data [Dataset]. http://doi.org/10.6084/m9.figshare.2061897.v1
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    zipAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Urban Road Networks
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Tool and data set of road networks for 80 of the most populated urban areas in the world. The data consist of a graph edge list for each city and two corresponding GIS shapefiles (i.e., links and nodes).Make your own data with our ArcGIS, QGIS, and python tools available at: http://csun.uic.edu/codes/GISF2E.htmlPlease cite: Karduni,A., Kermanshah, A., and Derrible, S., 2016, "A protocol to convert spatial polyline data to network formats and applications to world urban road networks", Scientific Data, 3:160046, Available at http://www.nature.com/articles/sdata201646

  5. i17 Delta Levees Stationing

    • gis.data.cnra.ca.gov
    • data.ca.gov
    • +4more
    Updated Feb 8, 2023
    + more versions
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    Carlos.Lewis@water.ca.gov_DWR (2023). i17 Delta Levees Stationing [Dataset]. https://gis.data.cnra.ca.gov/datasets/cd210fba6c3249a1987b14e6ea4d0b97
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    Dataset updated
    Feb 8, 2023
    Dataset provided by
    California Department of Water Resourceshttp://www.water.ca.gov/
    Authors
    Carlos.Lewis@water.ca.gov_DWR
    Area covered
    Description

    Levee stations, usually in feet but in some cases miles, snapped to 2017 Delta levee centerlines (derived from the 2017 Delta LiDAR). Base source for station locations are surveyed field markers on the levees or distance-derived CAD files, in either case as supplied by local maintaining agency's engineers. DWR collected station location data and snapped the stations into the levee centerline file from 2012. After updated levee centerlines were created, the existing points were snapped to the new lines. So there is some small difference between the supplied station locations, previous station locations and these station locations. In some cases, multiple series of stations exist for a district, generally associated with distinct waterways. Also, district levees may be demarked in feet or in miles. The label fields are simply cartographic support, the label data are identical in all cases, but are provided to support fast labeling at more infrequent intervals as needed. Stationing is not as simple as it may seem. In some cases, multiple sets of stationing exist for a district's levees (see Sherman Island for example). What this dataset intends to represent is the current stationing used by District engineers for that District on levee maintenance and improvement projects. As changes are made to the stationing, and the new stationing data become available to the Levee Program, they will be added to this database. Some islands also have separate groups of stations for various parts of the district. This version is current as of 03/24/2020. Source of the original levee stationing is DWR Delta Levees Program, compiled from data provided by internal files, from CSU Chico State, MBK Engineers, KSN Engineers, Siegfried Engineers, Malani & Associates, Green Mountain Engineers, and DCC Engineers. Processing work done by CA DWR, Division of Engineering, Geodetic Branch, Geospatial Data Support Section, specifically by Arina Ushakova (Research Data Analyst I), and initial QC by Joel Dudas (Senior Engineer, Water Resources).

  6. a

    Centerline

    • data-cosm.hub.arcgis.com
    • data.nola.gov
    • +2more
    Updated Oct 22, 2020
    + more versions
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    City of San Marcos (2020). Centerline [Dataset]. https://data-cosm.hub.arcgis.com/datasets/centerline
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    Dataset updated
    Oct 22, 2020
    Dataset authored and provided by
    City of San Marcos
    Area covered
    Description

    Road segments representing centerlines of all roadways or carriageways in a local government. Typically, this information is compiled from orthoimagery or other aerial photography sources. This representation of the road centerlines support address geocoding and mapping. It also serves as a source for public works and other agencies that are responsible for the active management of the road network. (From ESRI Local Government Model "RoadCenterline" Feature)**This dataset was significantly revised in August of 2014 to correct for street segments that were not properly split at intersections. There may be issues with using data based off of the original centerline file. ** The column Speed Limit was updated in November 2014 by the Transportation Intern and is believed to be accurate** The column One Way was updated in November of 2014 by core GIS and is believed to be accurate.[MAXIMOID] A unique id field used in a work order management software called Maximo by IBM. Maximo uses GIS CL data to assign locations to work orders using this field. This field is maintained by the Transportation GIS specialists and is auto incremented when new streets are digitized. For example, if the latest digitized street segment MAXIMOID = 999, the next digitized line will receive MAXIMOID = 1000, and so on. STREET NAMING IS BROKEN INTO THREE FIELDS FOR GEOCODING:PREFIX This field is attributed if a street name has a prefix such as W, N, E, or S.NAME Domain with all street names. The name of the street without prefix or suffix.ROAD_TYPE (Text,4) Describes the type of road aka suffix, if applicable. CAPCOG Addressing Guidelines Sec 504 U. states, “Every road shall have corresponding standard street suffix…” standard street suffix abbreviations comply with USPS Pub 28 Appendix C Street Abbreviations. Examples include, but are not limited to, Rd, Dr, St, Trl, Ln, Gln, Lp, CT. LEFT_LOW The minimum numeric address on the left side of the CL segment. Left side of CL is defined as the left side of the line segment in the From-To direction. For example, if a line has addresses starting at 101 and ending at 201 on its left side, this column will be attributed 101.LEFT_HIGH The largest numeric address on the left side of the CL segment. Left side of CL is defined as the left side of the line segment in the From-To direction. For example, if a line has addresses starting at 101 and ending at 201 on its left side, this column will be attributed 201.LOW The minimum numeric address on the RIGHT side of the CL segment. Right side of CL is defined as the right side of the line segment in the From-To direction. For example, if a line has addresses starting at 100 and ending at 200 on its right side, this column will be attributed 100.HIGHThe maximum numeric address on the RIGHT side of the CL segment. Right side of CL is defined as the right side of the line segment in the From-To direction. For example, if a line has addresses starting at 100 and ending at 200 on its right side, this column will be attributed 200.ALIAS Alternative names for roads if known. This field is useful for geocode re-matching. CLASSThe functional classification of the centerline. For example, Minor (Minor Arterial), Major (Major Arterial). THIS FIELD IS NOT CONSISTENTLY FILLED OUT, NEEDS AN AUDIT. FULLSTREET The full name of the street concatenating the [PREFIX], [NAME], and [SUFFIX] fields. For example, "W San Antonio St."ROWWIDTH Width of right-of-way along the CL segment. Data entry from Plat by Planning GIS Or from Engineering PICPs/ CIPs.NUMLANES Number of striped vehicular driving lanes, including turn lanes if present along majority of segment. Does not inlcude bicycle lanes. LANEMILES Describes the total length of lanes for that segment in miles. It is manually field calculated as follows (( [ShapeLength] / 5280) * [NUMLANES]) and maintained by Transportation GIS.SPEEDLIMIT Speed limit of CL segment if known. If not, assume 30 mph for local and minor arterial streets. If speed limit changes are enacted by city council they will be recorded in the Traffic Register dataset, and this field will be updating accordingly. Initial data entry made by CIP/Planning GIS and maintained by Transportation GIS.[YRBUILT] replaced by [DateBuilt] See below. Will be deleted. 4/21/2017LASTYRRECON (Text,10) Is the last four-digit year a major reconstruction occurred. Most streets have not been reconstructed since orignal construction, and will have values. The Transportation GIS Specialist will update this field. OWNER Describes the governing body or private entity that owns/maintains the CL. It is possible that some streets are owned by other entities but maintained by CoSM. Possible attributes include, CoSM, Hays Owned/City Maintained, TxDOT Owned/City Maintained, TxDOT, one of four counties (Hays, Caldwell, Guadalupe, and Comal), TxState, and Private.ST_FROM Centerline segments are split at their intersections with other CL segments. This field names the nearest cross-street in the From- direction. Should be edited when new CL segments that cause splits are added. ST_TO Centerline segments are split at their intersections with other CL segments. This field names the nearest cross-street in the To- direction. Should be edited when new CL segments that cause splits are added. PAV_WID Pavement width of street in feet from back-of-curb to back-of-curb. This data is entered from as-built by CIP GIS. In January 2017 Transportation Dept. field staff surveyed all streets and measured width from face-of-curb to face-of-curb where curb was present, and edge of pavement to edge of pavement where it was not. This data was used to field calculate pavement width where we had values. A value of 1 foot was added to the field calculation if curb and gutter or stand up curb were present (the face-of-curb to back-of-curb is 6 in, multiple that by 2 to find 1 foot). If no curb was present, the value enter in by the field staff was directly copied over. If values were already present, and entered from asbuilt, they were left alone. ONEWAY Field describes direction of travel along CL in relation to digitized direction. If a street allows bi-directional travel it is attributed "B", a street that is one-way in the From_To direction is attributed "F", a street that is one-way in the To_From direction is attributed "T", and a street that does not allow travel in any direction is attibuted "N". ROADLEVEL Field will be aliased to [MINUTES] and be used to calculate travel time along CL segments in minutes using shape length and [SPEEDLIMIT]. Field calculate using the following expression: [MINUTES] = ( ([SHAPE_LENGTH] / 5280) / ( [SPEEDLIMIT] / 60 ))ROWSTATUS Values include "Open" or "Closed". Describes whether a right-of-way is open or closed. If a street is constructed within ROW it is "Open". If a street has not yet been constructed, and there is ROW, it is "Cosed". UPDATE: This feature class only has CL geometries for "Open" rights-of-way. This field should be deleted or re-purposed. ASBUILT field used to hyper link as-built documents detailing construction of the CL. Field was added in Dec. 2016. DateBuilt Date field used to record month and year a road was constructed from Asbuilt. Data was collected previously without month information. Data without a known month is entered as "1/1/YYYY". When month and year are known enter as "M/1/YYYY". Month and Year from asbuilt. Added by Engineering/CIP. ACCEPTED Date field used to record the month, day, and year that a roadway was officially accepted by the City of San Marcos. Engineering signs off on acceptance letters and stores these documents. This field was added in May of 2018. Due to a lack of data, the date built field was copied into this field for older roadways. Going forward, all new roadways will have this date. . This field will typically be populated well after a road has been drawn into GIS. Entered by Engineering/CIP. ****In an effort to make summarizing the data more efficient in Operations Dashboard, a generic date of "1/1/1900" was assigned to all COSM owned or maintained roads that had NULL values. These were roads that either have not been accepted yet, or roads that were expcepted a long time ago and their accepted date is not known. WARRANTY_EXP Date field used to record the expiration date of a newly accepted roadway. Typically this is one year from acceptance date, but can be greater. This field was added in May of 2018, so only roadways that have been excepted since and older roadways with valid warranty dates within this time frame have been populated.

  7. a

    TCID Water Righted Areas

    • data-ndwr.hub.arcgis.com
    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    Updated Aug 11, 2022
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    Nevada Division of Water Resources (2022). TCID Water Righted Areas [Dataset]. https://data-ndwr.hub.arcgis.com/maps/NDWR::tcid-water-righted-areas
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    Dataset updated
    Aug 11, 2022
    Dataset authored and provided by
    Nevada Division of Water Resources
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    Description

    This feature class is updated every business day using Python scripts and the TCID databases. Please disregard the "Date Updated" field as it does not keep in sync with DWR's internal enterprise geodatabase updates. This dataset is the result of the place of use for water rights after permit changes are approved by the State Engineer. The dataset covers surface water rights in the Fernley and Fallon areas of Nevada. Contracts and permits depict exactly where permit owners can water and how much they are permitted to water. Farm units depict the boundary where permit owners can irrigate their approved volume of water (acre-feet). Permit numbers with a ‘v’ as a suffix identify water rights that were established before contracts came into effect (Pre-Contract).This dataset is used to determine the water acreage permitted in an area to show if the appropriated amount of water is used. It also shows how much water the owner of a water right is using and where they are allowed to use that water.Representation:This dataset can be represented by the Permit Type field.Permit – an approved change of decreed water rights submitted for review by the State Engineer.Pre-Contract – a vested water right established prior to July 2nd, 1902.Contract – a certificate of water rights issued by the Bureau of Reclamation (BOR) after July 2nd, 1902 and prior to 1926.Farm Unit – is a defined boundary where a set quantity of water can be used.Date of Creation – 2015This dataset is updated whenever there is a change to a water right within the Newlands Mapping Project. The water right place of use change is plotted to add or remove acreage from an existing water right.

  8. d

    Polygon Data | Marina Polygon Dataset for US & Canada | GIS Maps &...

    • datarade.ai
    Updated Mar 23, 2023
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    Xtract (2023). Polygon Data | Marina Polygon Dataset for US & Canada | GIS Maps & Geospatial Insights [Dataset]. https://datarade.ai/data-products/xtract-io-geometry-data-marinas-in-us-and-canada-xtract
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    .json, .csv, .xls, .txtAvailable download formats
    Dataset updated
    Mar 23, 2023
    Dataset authored and provided by
    Xtract
    Area covered
    Canada, United States
    Description

    This specialized location dataset delivers detailed information about marina establishments. Maritime industry professionals, coastal planners, and tourism researchers can leverage precise location insights to understand maritime infrastructure, analyze recreational boating landscapes, and develop targeted strategies.

    How Do We Create Polygons?

    -All our polygons are manually crafted using advanced GIS tools like QGIS, ArcGIS, and similar applications. This involves leveraging aerial imagery, satellite data, and street-level views to ensure precision. -Beyond visual data, our expert GIS data engineers integrate venue layout/elevation plans sourced from official company websites to construct highly detailed polygons. This meticulous process ensures maximum accuracy and consistency. -We verify our polygons through multiple quality assurance checks, focusing on accuracy, relevance, and completeness.

    What's More?

    -Custom Polygon Creation: Our team can build polygons for any location or category based on your requirements. Whether it’s a new retail chain, transportation hub, or niche point of interest, we’ve got you covered. -Enhanced Customization: In addition to polygons, we capture critical details such as entry and exit points, parking areas, and adjacent pathways, adding greater context to your geospatial data. -Flexible Data Delivery Formats: We provide datasets in industry-standard GIS formats like WKT, GeoJSON, Shapefile, and GDB, making them compatible with various systems and tools. -Regular Data Updates: Stay ahead with our customizable refresh schedules, ensuring your polygon data is always up-to-date for evolving business needs.

    Unlock the Power of POI and Geospatial Data

    With our robust polygon datasets and point-of-interest data, you can: -Perform detailed market and location analyses to identify growth opportunities. -Pinpoint the ideal locations for your next store or business expansion. -Decode consumer behavior patterns using geospatial insights. -Execute location-based marketing campaigns for better ROI. -Gain an edge over competitors by leveraging geofencing and spatial intelligence.

    Why Choose LocationsXYZ?

    LocationsXYZ is trusted by leading brands to unlock actionable business insights with our accurate and comprehensive spatial data solutions. Join our growing network of successful clients who have scaled their operations with precise polygon and POI datasets. Request your free sample today and explore how we can help accelerate your business growth.

  9. i12 Delta Hydrology

    • gis.data.ca.gov
    • data.ca.gov
    • +5more
    Updated Jun 19, 2023
    + more versions
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    Joel.Dudas@water.ca.gov_DWR (2023). i12 Delta Hydrology [Dataset]. https://gis.data.ca.gov/datasets/4d1ddb65e64f456b85536f42368d1c28
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    Dataset updated
    Jun 19, 2023
    Dataset provided by
    California Department of Water Resourceshttp://www.water.ca.gov/
    Authors
    Joel.Dudas@water.ca.gov_DWR
    Area covered
    Description

    This point dataset represents the location of gaging stations in the Sacramento-San Joaquin Delta and Suisun Marsh that have historic and statistical hydrologic data, specifically various river stage data. Stages are given in NAVD88, units feet. Specific stages are given for peak stages, 100-year stages produced under 2 separate US Army Corps of Engineers hydrology reports from 1976 and 1992, the year of previous peak stages cited by the 1976 and 1992 reports, and approximate typical tidal values as approximately estimated based on long term data records. This 2023 version of this datset replaces the prior 2020 version, and should be used as a complete replacement. The underlying analyses did not change, but the USACE peak observed stage field names from the prior version were corrected and supplemental USACE 50- and 100-year stages were added accordingly. In addition, the vertical datum conversion used at specific gages was added. The vertical datum conversion is based on DWR survey and North Central Regional Office information that is maintained for each gage station. The stage data was compiled by Karen Tolentino, engineer with Delta Levees, and by Joel Dudas, Senior Engineer in DWR's Division of Engineering, based on a wide variety of sources, including the HYDSTRA database, various historic bulletins, raw data, station histories, and other information provided by DWR's North Central Region Office, USGS, and other misc sources. They also adjusted all data to approximate NAVD88-related stages. Observed data periods of record varied widely by station, but go back as far as 1905. All peak values were derived from start of records until up to May, 2017.The associated data are considered DWR enterprise GIS data, which meet all appropriate requirements of the DWR Spatial Data Standards, specifically the DWR Spatial Data Standard version 3.5, dated April 12, 2023. DWR makes no warranties or guarantees —either expressed or implied — as to the completeness, accuracy, or correctness of the data. DWR neither accepts nor assumes liability arising from or for any incorrect, incomplete, or misleading subject data. Comments, problems, improvements, updates, or suggestions should be forwarded to GIS@water.ca.gov.

  10. USACE GIS Open Data Portal

    • data.cnra.ca.gov
    Updated Jul 18, 2020
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    United States Army Corps of Engineers (2020). USACE GIS Open Data Portal [Dataset]. https://data.cnra.ca.gov/dataset/usace-gis-open-data-portal
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    Dataset updated
    Jul 18, 2020
    Dataset authored and provided by
    United States Army Corps of Engineershttp://www.usace.army.mil/
    Description

    The U.S. Army Corps of Engineers Geospatial Open Data provides shared and trusted USACE geospatial data, services and applications for use by our partner agencies and the public.

  11. n

    High-Resolution QuickBird Imagery and Related GIS Layers for Barrow, Alaska,...

    • cmr.earthdata.nasa.gov
    • datasets.ai
    • +3more
    not provided
    Updated Oct 7, 2025
    + more versions
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    (2025). High-Resolution QuickBird Imagery and Related GIS Layers for Barrow, Alaska, USA, Version 1 [Dataset]. https://cmr.earthdata.nasa.gov/search/concepts/C1386246127-NSIDCV0.html
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    not providedAvailable download formats
    Dataset updated
    Oct 7, 2025
    Time period covered
    Aug 1, 2002 - Aug 2, 2002
    Area covered
    Description

    This data set contains high-resolution QuickBird imagery and geospatial data for the entire Barrow QuickBird image area (156.15° W - 157.07° W, 71.15° N - 71.41° N) and Barrow B4 Quadrangle (156.29° W - 156.89° W, 71.25° N - 71.40° N), for use in Geographic Information Systems (GIS) and remote sensing software. The original QuickBird data sets were acquired by DigitalGlobe from 1 to 2 August 2002, and consist of orthorectified satellite imagery. Federal Geographic Data Committee (FGDC)-compliant metadata for all value-added data sets are provided in text, HTML, and XML formats.

    Accessory layers include: 1:250,000- and 1:63,360-scale USGS Digital Raster Graphic (DRG) mosaic images (GeoTIFF format); 1:250,000- and 1:63,360-scale USGS quadrangle index maps (ESRI Shapefile format); an index map for the 62 QuickBird tiles (ESRI Shapefile format); and a simple polygon layer of the extent of the Barrow QuickBird image area and the Barrow B4 quadrangle area (ESRI Shapefile format).

    Unmodified QuickBird data comprise 62 data tiles in Universal Transverse Mercator (UTM) Zone 4 in GeoTIFF format. Standard release files describing the QuickBird data are included, along with the DigitalGlobe license agreement and product handbooks.

    The baseline geospatial data support education, outreach, and multi-disciplinary research of environmental change in Barrow, which is an area of focused scientific interest. Data are provided on four DVDs. This product is available only to investigators funded specifically from the National Science Foundation (NSF), Office of Polar Programs (OPP), Arctic Sciences Section. An NSF OPP award number must be provided when ordering this data. Contact NSIDC User Services at nsidc@nsidc.org to order the data, and include an NSF OPP award number in the email.

  12. OSE Points of Diversion

    • geospatialdata-ose.opendata.arcgis.com
    • hub.arcgis.com
    Updated Oct 23, 2025
    + more versions
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    New Mexico Office of the State Engineer (2025). OSE Points of Diversion [Dataset]. https://geospatialdata-ose.opendata.arcgis.com/datasets/ose-points-of-diversion/data
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    Dataset updated
    Oct 23, 2025
    Dataset authored and provided by
    New Mexico Office of the State Engineerhttps://www.ose.state.nm.us/
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    This dataset has a data dictionary that can be downloaded here.The NM Office of the State Engineer (OSE) "Point of Diversions" (POD) layer includes well locations, surface declarations, or surface permits. These data were extracted from the OSE W.A.T.E.R.S. (Water Administration Technical Engineering Resource System) database and geo-located (mapped). These data have varying degrees of accuracy and have not been validated. This message is to alert users of this data to various changes regarding how this POD data is generated and maintained by the NM Office of the State Engineer. In addition, all attribute fields are fully described in the metadata, including descriptions of field codes. Please read the metadata accompanying this GIS data layer for further information. Any questions regarding this GIS data should be directed NM OSE Information Technology Systems Bureau GIS at the contact information given below.Stephen N. HayesNMOSE ITSB GIS Data Manager(505) 827-6321PO Box 25102Santa Fe, NM 87504stephen.hayes@ose.nm.gov

  13. m

    A new geophysical and geospatial dataset from the Quaternary basin of Norcia...

    • data.mendeley.com
    Updated May 18, 2020
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    Maurizio Ercoli (2020). A new geophysical and geospatial dataset from the Quaternary basin of Norcia (central Italy) [Dataset]. http://doi.org/10.17632/78pwtzstz6.1
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    Dataset updated
    May 18, 2020
    Authors
    Maurizio Ercoli
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Norcia
    Description

    We provide the entire dataset of the paper "Dataset of seismic ambient vibrations from the Quaternary Norcia basin (central Italy)" submitted to "Data in Brief" journal, including geophysical and geospatial data.

    The dataset was used and analysed in the article:

    Di Giulio, G., Ercoli, M., Vassallo, M., Porreca, M. (2020). Investigation of the Norcia basin (Central Italy) through ambient vibration measurements and geological surveys, Engineering Geology, 267, 105501, https://doi.org/10.1016/j.enggeo.2020.105501

    The geophysical dataset was collected in the Norcia basin in Central Italy, area struck by a long earthquake sequence during the 2016-2017, including five main-shocks with Mw>5.0.

    The Mw 6.5 mainshock occurred on 30 October 2016 close to the town of Norcia. Different degrees of damages were observed during this seismic crisis, with a variable seismic shaking controlled, among many factors, by important 1D and 2D variation of Quaternary fluvio-lacustrine sediments infilling the basin.

    Following this seismic sequence, we registered seismic vibration measurements, mainly single-seismic station noise data. We aimed to determine the distribution of resonant frequency (f0) of the basin and, though a join analysis with the available geological information, to infer the subsurface basin architecture.

    A total of 60 sites were measured to cover the entire extension in the basin. We deployed seismometers along three transects of a total length of 21 km, mostly along the main structural directions of the basin (i.e. NNW-SSE and NE-SW).

    Two 2D arrays of seismic stations with a elicoidal-shaped geometry, and a set of MASW active data were also acquired in the northern sector of the basin, in order to better constrain the seismic velocity of the sedimentary infilling.

    In comparison to the data used in the paper Di Giulio et al. (2020), seven additional records have been here recovered across the basin (i.e. N54-N60).

    We also provide geospatial ancillary data, both as a complete open-source Geographical Information Systems (GIS) project and as a set of single GeoPackage (.gpkg) and Keyhole Markup Language (.kml) files.

    The dataset can be used for different purposes: specific researches on the Norcia basin, comparative studies on similar areas around the world, development of new data modeling/analysis software.

  14. u

    Barrow Area Remote Sensing - BAID Be Research Sites

    • data.ucar.edu
    • dataone.org
    • +2more
    archive
    Updated Aug 1, 2025
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    Craig E. Tweedie (2025). Barrow Area Remote Sensing - BAID Be Research Sites [Dataset]. https://data.ucar.edu/dataset/barrow-area-remote-sensing-baid-be-research-sites
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    archiveAvailable download formats
    Dataset updated
    Aug 1, 2025
    Authors
    Craig E. Tweedie
    Time period covered
    Jan 1, 2005 - Nov 13, 2009
    Area covered
    Description

    This dataset contains GIS shape files in a single zip file. Data are remote sensing sites of the Barrow Area Information Database (BAID).

  15. d

    Protected Areas Database of the United States (PAD-US)

    • search.dataone.org
    • data.wu.ac.at
    Updated Oct 26, 2017
    + more versions
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    US Geological Survey (USGS) Gap Analysis Program (GAP) (2017). Protected Areas Database of the United States (PAD-US) [Dataset]. https://search.dataone.org/view/0459986b-9a0e-41d9-9997-cad0fbea9c4e
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    Dataset updated
    Oct 26, 2017
    Dataset provided by
    USGS Science Data Catalog
    Authors
    US Geological Survey (USGS) Gap Analysis Program (GAP)
    Time period covered
    Jan 1, 2005 - Jan 1, 2016
    Area covered
    Variables measured
    Shape, Access, Des_Nm, Des_Tp, Loc_Ds, Loc_Nm, Agg_Src, GAPCdDt, GAP_Sts, GIS_Src, and 20 more
    Description

    The USGS Protected Areas Database of the United States (PAD-US) is the nation's inventory of protected areas, including public open space and voluntarily provided, private protected areas, identified as an A-16 National Geospatial Data Asset in the Cadastral Theme (http://www.fgdc.gov/ngda-reports/NGDA_Datasets.html). PAD-US is an ongoing project with several published versions of a spatial database of areas dedicated to the preservation of biological diversity, and other natural, recreational or cultural uses, managed for these purposes through legal or other effective means. The geodatabase maps and describes public open space and other protected areas. Most areas are public lands owned in fee; however, long-term easements, leases, and agreements or administrative designations documented in agency management plans may be included. The PAD-US database strives to be a complete “best available” inventory of protected areas (lands and waters) including data provided by managing agencies and organizations. The dataset is built in collaboration with several partners and data providers (http://gapanalysis.usgs.gov/padus/stewards/). See Supplemental Information Section of this metadata record for more information on partnerships and links to major partner organizations. As this dataset is a compilation of many data sets; data completeness, accuracy, and scale may vary. Federal and state data are generally complete, while local government and private protected area coverage is about 50% complete, and depends on data management capacity in the state. For completeness estimates by state: http://www.protectedlands.net/partners. As the federal and state data are reasonably complete; focus is shifting to completing the inventory of local gov and voluntarily provided, private protected areas. The PAD-US geodatabase contains over twenty-five attributes and four feature classes to support data management, queries, web mapping services and analyses: Marine Protected Areas (MPA), Fee, Easements and Combined. The data contained in the MPA Feature class are provided directly by the National Oceanic and Atmospheric Administration (NOAA) Marine Protected Areas Center (MPA, http://marineprotectedareas.noaa.gov ) tracking the National Marine Protected Areas System. The Easements feature class contains data provided directly from the National Conservation Easement Database (NCED, http://conservationeasement.us ) The MPA and Easement feature classes contain some attributes unique to the sole source databases tracking them (e.g. Easement Holder Name from NCED, Protection Level from NOAA MPA Inventory). The "Combined" feature class integrates all fee, easement and MPA features as the best available national inventory of protected areas in the standard PAD-US framework. In addition to geographic boundaries, PAD-US describes the protection mechanism category (e.g. fee, easement, designation, other), owner and managing agency, designation type, unit name, area, public access and state name in a suite of standardized fields. An informative set of references (i.e. Aggregator Source, GIS Source, GIS Source Date) and "local" or source data fields provide a transparent link between standardized PAD-US fields and information from authoritative data sources. The areas in PAD-US are also assigned conservation measures that assess management intent to permanently protect biological diversity: the nationally relevant "GAP Status Code" and global "IUCN Category" standard. A wealth of attributes facilitates a wide variety of data analyses and creates a context for data to be used at local, regional, state, national and international scales. More information about specific updates and changes to this PAD-US version can be found in the Data Quality Information section of this metadata record as well as on the PAD-US website, http://gapanalysis.usgs.gov/padus/data/history/.) Due to the completeness and complexity of these data, it is highly recommended to review the Supplemental Information Section of the metadata record as well as the Data Use Constraints, to better understand data partnerships as well as see tips and ideas of appropriate uses of the data and how to parse out the data that you are looking for. For more information regarding the PAD-US dataset please visit, http://gapanalysis.usgs.gov/padus/. To find more data resources as well as view example analysis performed using PAD-US data visit, http://gapanalysis.usgs.gov/padus/resources/. The PAD-US dataset and data standard are compiled and maintained by the USGS Gap Analysis Program, http://gapanalysis.usgs.gov/ . For more information about data standards and how the data are aggregated please review the “Standards and Methods Manual for PAD-US,” http://gapanalysis.usgs.gov/padus/data/standards/ .

  16. H

    Maui 2019 DTM

    • opendata.hawaii.gov
    • geoportal.hawaii.gov
    • +2more
    Updated Sep 5, 2025
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    Office of Planning (2025). Maui 2019 DTM [Dataset]. https://opendata.hawaii.gov/dataset/maui-2019-dtm
    Explore at:
    html, arcgis geoservices rest apiAvailable download formats
    Dataset updated
    Sep 5, 2025
    Dataset provided by
    Hawaii Statewide GIS Program
    Authors
    Office of Planning
    Area covered
    Maui
    Description

    Digital Terrain Model (bare earth) of parts of Maui and Molokai. Partial coverage Vexcel, Inc. LIDAR of Maui and Molokai were purchased by County of Maui to assist with three-dimensional modeling of structures in areas of higher development. 1'/px, LIDAR-derived, bare earth DEM/elevation raster of parts of Maui and Molokai – specifically, Central Molokai, Kahului, Kihei, Lahaina and Pukalani. XY units: feet, Z units: meters. Use Limitations: 1.Disclaimer - This dataset is being placed in the public domain. Any use is allowed except for re-sale. Neither Vexcel, Inc., the County of Maui, nor the State of Hawaii make any guarantees, expressed or implied, regarding its accuracy or fitness of use. Users should verify XYZ values through a licensed surveyor for any engineering application. This data should only be used as a guide, vs. a statement of fact regarding real-world conditions. 2.Vertical Datum - The originator of this LIDAR dataset, Vexcel Inc. of Boulder, Colorado referenced Z values to the North American Vertical Datum of 1988 (NAVD88). NAVD88 is not recognized as a valid vertical reference for the state of Hawaii. Currently Hawaii has no official (de jure or de facto) vertical datum, and NOAA's National Geodetic Survey (NGS) recommends that elevations be referenced to the nearest NOAA tidal gauge. A legacy LIDAR dataset produced in 2013 by the United States Army Corps of Engineers (USACE) used NAD83(PA11) as its vertical reference. In theory this approach should result in better accuracy for the Z dimension as PA11 is a Pacific plate-centric datum. In comparing flat areas containing neither structures or vegetation, it was found that the Vexcel values sit approximately 4 feet above the USACE dataset. The vertical datum issue was brought to the attention of Vexcel, Inc. Vexcel used the 2013 USACE LIDAR as vertical control to correct their LIDAR data. The (corrected) .las data is shared as it was delivered. As stated above, the use of this data transfers all risks and assumption of responsibility to the user. For more information see https://files.hawaii.gov/dbedt/op/gis/data/Maui_2019_DTM.html or contact County of Maui at GISMonitor@co.maui.hi.us or Hawaii Statewide GIS Program at gis@hawaii.gov.

  17. OSE Points of Diversion

    • catalog.newmexicowaterdata.org
    csv, html, xlsx, zip
    Updated Jun 24, 2025
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    New Mexico Office of the State Engineer & Interstate Stream Commission (2025). OSE Points of Diversion [Dataset]. https://catalog.newmexicowaterdata.org/dataset/ose-points-of-diversion
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    html, xlsx(84245), csv(150535724), zip(30911308)Available download formats
    Dataset updated
    Jun 24, 2025
    Dataset provided by
    New Mexico Office of the State Engineerhttps://www.ose.state.nm.us/
    License

    Open Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
    License information was derived automatically

    Description

    The NM Office of the State Engineer (OSE) "Point of Diversions" (POD) layer includes well locations, surface declarations, or surface permits updated on a monthly basis. These data were extracted from the OSE W.A.T.E.R.S. (Water Administration Technical Engineering Resource System) database and geo-located (mapped). These data have varying degrees of accuracy and have not been validated. Data included in this dataset only includes PODs that have coordinates located within the State of New Mexico. This message is to alert users of this data to various changes regarding how this POD data is generated and maintained by the NM Office of the State Engineer. In addition, all attribute fields are fully described in the metadata, including descriptions of field codes. Please read the metadata accompanying this GIS data layer for further information. Any questions regarding this GIS data should be directed NM OSE Information Technology Systems Bureau GIS at the contact information given below.

  18. h

    Maui 2019 elevation (terrain)

    • geoportal.hawaii.gov
    • opendata.hawaii.gov
    • +3more
    Updated Aug 11, 2021
    + more versions
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    Hawaii Statewide GIS Program (2021). Maui 2019 elevation (terrain) [Dataset]. https://geoportal.hawaii.gov/maps/ad6906de458e46528e0c352321015788
    Explore at:
    Dataset updated
    Aug 11, 2021
    Dataset authored and provided by
    Hawaii Statewide GIS Program
    Area covered
    Description

    Digital Terrain Model (bare earth) of parts of Maui and Molokai. Partial coverage Vexcel, Inc. LIDAR of Maui and Molokai were purchased by County of Maui to assist with three-dimensional modeling of structures in areas of higher development. 1'/px, LIDAR-derived, bare earth DEM/elevation raster of parts of Maui and Molokai – specifically, Central Molokai, Kahului, Kihei, Lahaina and Pukalani. XY units: feet, Z units: meters. Use Limitations: 1.Disclaimer - This dataset is being placed in the public domain. Any use is allowed except for re-sale. Neither Vexcel, Inc., the County of Maui, nor the State of Hawaii make any guarantees, expressed or implied, regarding its accuracy or fitness of use. Users should verify XYZ values through a licensed surveyor for any engineering application. This data should only be used as a guide, vs. a statement of fact regarding real-world conditions. 2.Vertical Datum - The originator of this LIDAR dataset, Vexcel Inc. of Boulder, Colorado referenced Z values to the North American Vertical Datum of 1988 (NAVD88). NAVD88 is not recognized as a valid vertical reference for the state of Hawaii. Currently Hawaii has no official (de jure or de facto) vertical datum, and NOAA's National Geodetic Survey (NGS) recommends that elevations be referenced to the nearest NOAA tidal gauge. A legacy LIDAR dataset produced in 2013 by the United States Army Corps of Engineers (USACE) used NAD83(PA11) as its vertical reference. In theory this approach should result in better accuracy for the Z dimension as PA11 is a Pacific plate-centric datum. In comparing flat areas containing neither structures or vegetation, it was found that the Vexcel values sit approximately 4 feet above the USACE dataset. The vertical datum issue was brought to the attention of Vexcel, Inc. Vexcel used the 2013 USACE LIDAR as vertical control to correct their LIDAR data. The (corrected) .las data is shared as it was delivered. As stated above, the use of this data transfers all risks and assumption of responsibility to the user. For more information see https://files.hawaii.gov/dbedt/op/gis/data/Maui_2019_DTM.html or contact County of Maui at GISMonitor@co.maui.hi.us or Hawaii Statewide GIS Program at gis@hawaii.gov.

  19. Data from: Database of Geographic Information: Topographic Map of Central...

    • search.dataone.org
    • portal.edirepository.org
    Updated Oct 4, 2013
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    Alexander Buyantuyev (2013). Database of Geographic Information: Topographic Map of Central Arizona [Dataset]. https://search.dataone.org/view/knb-lter-cap.220.9
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    Dataset updated
    Oct 4, 2013
    Dataset provided by
    Long Term Ecological Research Networkhttp://www.lternet.edu/
    Authors
    Alexander Buyantuyev
    Time period covered
    Jan 1, 1954 - Jan 1, 1984
    Area covered
    Description

    This dataset has been created to meet the needs of the research community of Arizona State University. Apart from purely vizualization purposes (i.e. displaying the data on various maps) it can potentially be used for spatial modeling. The data consist of engineering-quality contours, also known as isolines, created from the NED 10-meter Digital Elevation Model subset to the extent somewhat exceeding Cetral Arizona - Phoenix LTER. Contours ( lines connecting points of equal height above sea level) are drawn at 15 meter intervals with the base set at 145 m of elevation. Contours are an exact interpretation of the grid surface model and may sometimes appear blocky looking, may cross, appear to intersect, or form an unclosed branching line. All these are valid engineering-quality interpretations of the elevation surface that cartographers typically modify (smooth) for aesthetic purposes.

  20. a

    Wells NM RG

    • geospatialcentroid-csurams.hub.arcgis.com
    Updated May 20, 2020
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    Colorado State University (2020). Wells NM RG [Dataset]. https://geospatialcentroid-csurams.hub.arcgis.com/items/d306b602cbba481fb522619ff9a4235f
    Explore at:
    Dataset updated
    May 20, 2020
    Dataset authored and provided by
    Colorado State University
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    New Mexico water wells within the Rio Grande River Basin. THIS OSE PODS DATASET IS ACCOMPANIED BY A SEPARATELY DOWNLOADED DATA DICTIONARY (METADATA). (http://www.ose.state.nm.us/GIS/PODS/nmose_WATERS_PODs_data_dictionary_v8.xlsx) The NM Office of the State Engineer (OSE) "Point of Diversions" (POD) layer includes well locations, surface declarations, or surface permits updated on a monthly basis. These data were extracted from the OSE W.A.T.E.R.S. (Water Administration Technical Engineering Resource System) database and geo-located (mapped). These data have varying degrees of accuracy and have not been validated. Data included in this dataset only includes PODs that have coordinates located within the State of New Mexico. This message is to alert users of this data to various changes regarding how this POD data is generated and maintained by the NM Office of the State Engineer. In addition, all attribute fields are fully described in the metadata, including descriptions of field codes. Please read the metadata accompanying this GIS data layer for further information. Any questions regarding this GIS data should be directed NM OSE Information Technology Systems Bureau GIS at the contact information given below.

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BC_Energy_Regulator (2016). Engineering Projects [Dataset]. https://data-bc-er.opendata.arcgis.com/datasets/81a48eb254e840b0b5c4e79efa6e3646
Organization logo

Engineering Projects

Explore at:
Dataset updated
Aug 30, 2016
Dataset provided by
Oil and Gas Commission
Authors
BC_Energy_Regulator
Area covered
Description

BC Energy Regulator Engineering Project approvals may be issued, upon application, under the authority of Section 100 of the Drilling and Production Regulation or Section 97 of the Petroleum and Natural Gas Act, depending on project type. Projects grant the applicant operating latitude, under specific conditions, for the purpose of extracting oil and/or natural gas in the most efficient way that will result in maximization of resource recovery and benefit to the Crown, balanced with surface impact and socio-economic factors. Examples are ?Good Engineering Practice?, allowing increased well density in a poor quality reservoir, or ?Pressure Maintenance Water Flood? to allow injection of water into an oil pool to increase total oil recovery. Spatial data for approved projects are included. Data is updated nightly.

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