22 datasets found
  1. World Imagery (for Export)

    • share-open-data-crawfordcountypa.opendata.arcgis.com
    Updated Oct 15, 2013
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    Esri (2013). World Imagery (for Export) [Dataset]. https://share-open-data-crawfordcountypa.opendata.arcgis.com/maps/226d23f076da478bba4589e7eae95952
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    Dataset updated
    Oct 15, 2013
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This layer is designed to support exporting small volumes of basemap tiles for offline use. The content of this layer is equivalent to World Imagery. World Imagery provides one meter or better satellite and aerial imagery in many parts of the world and lower resolution satellite imagery worldwide. See World Imagery for more details.The map service supporting this layer will enable you to export up to 150,000 tiles in a single request. For estimation purposes, this is large enough to support the export of:Large city (e.g. San Francisco) down to full level of detail at ~1:1,000 scale (Level 19)Medium size state or province (e.g. Colorado) down to scale of ~1:36,000 (Level 14)Medium to large country (e.g. Continental United States) down to scale of ~1:288,000 (Level 11)This layer is not intended to be used to display live map tiles for use in a web map or web mapping application. To display map tiles, please use World Imagery basemap.Service Information for DevelopersTo export tiles for World Imagery, you must use the instance of the World_Imagery service hosted on the tiledbasemaps.arcgis.com server referenced by this layer (see URL in Contents below), which has the Export Tiles operation enabled. This layer is intended to support export of basemap tiles for offline use in ArcGIS applications and other applications built with an ArcGIS Runtime SDK.

  2. OSM buildings noisy labels dataset

    • zenodo.org
    • explore.openaire.eu
    • +1more
    zip
    Updated Apr 27, 2022
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    Jonas Gütter; Jonas Gütter (2022). OSM buildings noisy labels dataset [Dataset]. http://doi.org/10.5281/zenodo.6477788
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    zipAvailable download formats
    Dataset updated
    Apr 27, 2022
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Jonas Gütter; Jonas Gütter
    License

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

    Description

    This dataset contains tile imagery from the OpenStreetMap project alongside label masks for buildings from OpenStreetMap. Besides the original clean label set, additional noisy label sets for random noise, removed and added buildings are provided.

    The purpose of this dataset is to provide training data for analysing the impact of noisy labels on the performance of models for semantic segmentation in Earth observation.

    The code for downloading and creating the datasets as well as for performing some preliminary analyses is also provided, however it is necessary to have access to a tile server where OpenStreetMap tiles can be downloaded in sufficient amounts.

    To reproduce the dataset and perform analysis on it, do the following:

    • unzip data.zip and code.zip
    • create the folder structure from data
    • Build and activate a python environment from environment.yml
    • Insert the url of a suitable tile server for OSM tiles in line 76 of utils.py
    • Execute download_OSM_dataset.py to download OSM image tiles alongside OSM labels
    • Execute create_noisy_labels.py for the OSM dataset to create noisy label sets
    • Divide the images and labels into train and test data. split_data.py can be used as a baseline for this, but pathnames have to be adjusted and the corresponding directories have to be created first.
    • Call train_model.py to train a model on the data. Specify the data size and the label set by giving command line arguments as shown in train_model.sh

  3. e

    S-57 ENC Hosted Tile Layer

    • national-government.esrij.com
    • maritime-portal-demo01.hub.arcgis.com
    • +3more
    Updated Nov 2, 2021
    + more versions
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    ejgovdata (2021). S-57 ENC Hosted Tile Layer [Dataset]. https://national-government.esrij.com/datasets/255b4cbfa7ba4499a6fe6be581b3ff06
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    Dataset updated
    Nov 2, 2021
    Dataset authored and provided by
    ejgovdata
    Area covered
    Description

    This tile service was created using the mcstpk.exe functionality from ArcGIS Maritime server extension. The tile package was created using publicly available S-57 ENC data downloaded from NOAA's ENC download site on May 6th, 2021.Level 0 - 18 was generated from these S-57 datasets and published to this service. Not all levels however have been published. Those that have been published are available for download.To learn more about this product visit ArcGIS Maritime.

  4. k

    Kentucky Elevation Data - DEM and DEM Tile Index

    • kyfromabove.ky.gov
    • hub.arcgis.com
    Updated Mar 29, 2013
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    KyGovMaps (2013). Kentucky Elevation Data - DEM and DEM Tile Index [Dataset]. https://kyfromabove.ky.gov/maps/785e6040154e4050bda80049fc12d4a6
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    Dataset updated
    Mar 29, 2013
    Dataset authored and provided by
    KyGovMaps
    License

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

    Area covered
    Description

    This web map leverages the KyFromAbove 5 foot Digital Elevation Model (DEM) ArcGIS Server Image Service and provides a 5K tiling grid with embedded links for downloading individual DEM tiles from Phase 1, Phase 2 and Phase3 collection periods. Each of the Phase1 DEM tiles are provided in an ERDAS Imagine (IMG) format and is zipped up with its associated metadata file in XML format. Phase2 and Phase3 DEM tiles are provided in a GeoTIFF format. The Phase1 data resource was derived from the ground class within KyFromAbove point cloud data and has a 5-foot point spacing. The Phase2 and Phase3 data was derived from the ground class within KyFromAbove point cloud data and has a 2-foot point spacing. DEM data specifications adopted by the KyFromAbove Technical Advisory Committee can be found here. More information regarding this data resource can be found on the KyFromAbove website.

  5. a

    SGIC SaskatchewanVectors Web Map Tiling Server

    • catalogue.arctic-sdi.org
    Updated Jun 10, 2022
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    (2022). SGIC SaskatchewanVectors Web Map Tiling Server [Dataset]. https://catalogue.arctic-sdi.org/geonetwork/srv/resources/datasets/f8d02285-96ff-48ff-be17-f8b32d910ff4
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    Dataset updated
    Jun 10, 2022
    Description

    The SGIC (Saskatchewan Geospatial Imagery Collaborative) web mapping tiling service provides access to high resolution orthophoto imagery as well as other referencing layers of the province of Saskatchewan, Canada, and is made available to the public and SGIC members through www.flysask2.ca. Portions of the province are acquired annually.

  6. v

    Virginia LiDAR Inventory Tile Grid

    • vgin.vdem.virginia.gov
    • vgin-vgin.hub.arcgis.com
    Updated Mar 31, 2022
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    Virginia Geographic Information Network (2022). Virginia LiDAR Inventory Tile Grid [Dataset]. https://vgin.vdem.virginia.gov/datasets/VGIN::virginia-lidar-inventory-tile-grid/explore?location=38.032118%2C-79.350100%2C7.26
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    Dataset updated
    Mar 31, 2022
    Dataset authored and provided by
    Virginia Geographic Information Network
    Area covered
    Description

    The Virginia LiDAR Inventory Web Mapping Application provides access to LiDAR point cloud and individual project metadata collected in the Commonwealth of Virginia according to the USGS 3DEP specification. Data is obtained from NOAA, USGS, and VGIN data portals. LiDAR Point Clouds are compressed for file storage and transfer. USGS and NOAA utilize the compressed .LAZ format. This dataset will provide the end user a necessary set of geographic extents that can be used with an ArcGIS Desktop or Pro session to select by location specific areas of download. The downloads can either be batch processed by the analysis with scripting and modeling or individual tiles can be downloaded. This is the tile data powering VGIN ArcGIS server services utilized in the VGIN LiDAR Download Application.

  7. C

    Calcium Sulphate Raised Access Floor Report

    • promarketreports.com
    doc, pdf, ppt
    Updated Mar 21, 2025
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    Pro Market Reports (2025). Calcium Sulphate Raised Access Floor Report [Dataset]. https://www.promarketreports.com/reports/calcium-sulphate-raised-access-floor-49059
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    pdf, ppt, docAvailable download formats
    Dataset updated
    Mar 21, 2025
    Dataset authored and provided by
    Pro Market Reports
    License

    https://www.promarketreports.com/privacy-policyhttps://www.promarketreports.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The global calcium sulphate raised access floor market is experiencing robust growth, driven by the increasing demand for flexible and adaptable workspace solutions across various sectors. The market size in 2025 is estimated at $1.5 billion USD, exhibiting a Compound Annual Growth Rate (CAGR) of 7% from 2025 to 2033. This growth is primarily fueled by the burgeoning data center and server room construction, coupled with the rising adoption of raised access floors in commercial office spaces for improved cable management and ease of maintenance. Technological advancements leading to more durable and aesthetically pleasing calcium sulphate floor tiles, alongside increasing awareness of their cost-effectiveness compared to alternative flooring solutions, are further bolstering market expansion. The steel-encased type segment dominates the market due to its superior strength and longevity, while server room applications represent a significant share of overall demand. However, challenges such as the relatively high initial investment cost and potential susceptibility to moisture damage could hinder market growth to some extent. The market's geographic landscape showcases diverse growth patterns. North America and Europe currently hold substantial market shares, driven by strong infrastructural development and high adoption rates in advanced economies. However, rapidly developing economies in Asia Pacific, particularly China and India, are poised to become significant growth drivers in the coming years due to expanding IT infrastructure and increasing investments in commercial real estate. Key players in the market, including Kingspan, CBI Europe, and Polygroup, are focusing on product innovation, strategic partnerships, and geographic expansion to strengthen their market positions and capitalize on the ongoing growth opportunities. Competition is intense, necessitating continuous improvements in product quality, design, and service offerings to maintain a competitive edge. This dynamic market landscape presents significant opportunities for both established players and emerging companies. This comprehensive report provides a detailed analysis of the global calcium sulphate raised access floor market, projecting robust growth exceeding $5 billion by 2030. It delves into market segmentation, key players, emerging trends, and challenges, offering invaluable insights for investors, manufacturers, and industry stakeholders. The report leverages extensive market research and data analysis, offering a granular understanding of this rapidly evolving sector. Keywords: Raised Access Floor, Calcium Sulphate, Data Center Flooring, Server Room Flooring, Commercial Flooring, Office Flooring, Access Floor Tiles, Steel Encased Access Floor, Finished Access Floor.

  8. g

    Esri ArcGIS Server View Service - Orthophoto CR (Web Mercator) | gimi9.com

    • gimi9.com
    Updated Dec 15, 2012
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    (2012). Esri ArcGIS Server View Service - Orthophoto CR (Web Mercator) | gimi9.com [Dataset]. https://gimi9.com/dataset/eu_cz-cuzk-ags-ortofoto-mercator
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    Dataset updated
    Dec 15, 2012
    License

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

    Description

    Esri ArcGIS Server View Service - Orthophoto CR (Web Mercator) is provided as a public view service for the Orthophoto of the Czech Republic data in Web Mercator coordinate system. The view service is provided using the Esri ArcGIS Server technology. To optimize the speed, the data are provided in form of pre-prepared map tiles. The service covers with orthophoto data complete applicable scale interval, i.e. also small scales. The Service is accessible by one of access interfaces – REST,SOAP,WMTS and WMS.

  9. g

    Recruitment Tile Motile Fauna data from the antFOCE (Antarctic Free Ocean...

    • gis.csiss.gmu.edu
    • catalogue-temperatereefbase.imas.utas.edu.au
    • +3more
    Updated Oct 11, 2020
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    (2020). Recruitment Tile Motile Fauna data from the antFOCE (Antarctic Free Ocean Carbon Enrichment) experiment at Casey Station [Dataset]. https://gis.csiss.gmu.edu/carbon/cwicport/DatasetViewer?catalog=fedeo_carbon_predefined&id=C1443630042-AU_AADC
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    Dataset updated
    Oct 11, 2020
    Area covered
    Description
    Title Recruitment Tile Motile Fauna data from the antFOCE (Antarctic Free Ocean Carbon Enrichment) experiment at Casey Station
    Description Refer to antFOCE report section 4.5.1 for deployment, sampling and analysis details. https://data.aad.gov.au/metadata/records/AAS_4127_antFOCE_Project4127 The download file contains an Excel workbook with one data spreadsheet and one of notes relevant to the data. The data are the total number of each motile organism collected from 2 recruitment tiles deployed in chambers or open plots during the antFOCE experiment. The 2 tiles were deployed together in a metal stand in either a horizontal or vertical orientation. Background The antFOCE experimental system was deployed in O’Brien Bay, approximately 5 kilometres south of Casey station, East Antarctica, in the austral summer of 2014/15. Surface and sub-surface (in water below the sea ice) infrastructure allowed controlled manipulation of seawater pH levels (reduced by 0.4 pH units below ambient) in 2 chambers placed on the sea floor over natural benthic communities. Two control chambers (no pH manipulation) and two open plots (no chambers, no pH manipulation) were also sampled to compare to the pH manipulated (acidified) treatment chambers. Details of the antFOCE experiment can be found in the report – “antFOCE 2014/15 – Experimental System, Deployment, Sampling and Analysis”. This report and a diagram indicating how the various antFOCE data sets relate to each other are available at: https://data.aad.gov.au/metadata/records/AAS_4127_antFOCE_Project4127
    Date
    Media Type ATOM | SRU
    Metadata ISO 19139 | ISO 19139-2
  10. Arctic DEM: Aspect Map (Mature Support)

    • opendata.rcmrd.org
    Updated Aug 30, 2016
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    Esri (2016). Arctic DEM: Aspect Map (Mature Support) [Dataset]. https://opendata.rcmrd.org/datasets/7b37bb89034743019e09b0fae5c83ee3
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    Dataset updated
    Aug 30, 2016
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    Important Note: This item is in mature support as of July 2024 and will retire in December 2025. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version.ArcticDEM is a National Geospatial-Intelligence Agency (NGA) and National Science Foundation (NSF) public-private initiative to automatically produce a high-resolution, high-quality Digital Surface Model (DSM) of the Arctic using sub-meter, stereoscopic satellite imagery collected by DigitalGlobe’s satellite constellation.The Arctic DEM layer is rendered here as Aspect Map. Using the server-side aspect function, this layer provides a colorized representation of aspect. The orientation of the downward sloping surface is indicated by different colors, rotating from green (North) to blue (East), to magenta (South) to orange (West).Geographic ExtentAll land area north of 60° north latitude, including all territory of Greenland, the entire state of Alaska, and the Kamchatka Peninsula of the Russian Federation.Map ProjectionThis layer is projected to WGS 1984 EPSG Alaska Polar Stereographic.The source data is projected to WGS 84 / NSIDC Sea Ice Polar Stereographic North.NOTE: By default, opening this layer in the Map Viewer will project the layer to Web Mercator. To display in the Alaska Polar projection, use Arctic DEM: Aspect Map Web MapSpatial Resolution2-meterAccuracyWithout ground control points absolute accuracy is approximately 4 meters in horizontal and vertical planes. Uniform ground control must be applied to achieve higher accuracy. Laser altimetry data from the NASA IceSAT spacecraft has been applied to the ArcticDEM mosaic files. Users may wish to use other sources for smaller areas, particularly on ArcticDEM strip files. Strip DEM files contain IceSAT altimetry offsets within the metadata, but have not had these values applied.The accuracy of these layers will vary as a function of location and data source. Please refer to the metadata available in the layers, and follow the links to the original sources for further details. An estimate of CE90 and LE90 are included as attributes.Pixel ValuesThis layer returns 8 bit color values representing a graphic visualization, not slope values.For access to numeric aspect values, use the Arctic DEM: Aspect Degree layer, which returns orientation values from 0 to 359 degrees.For elevation height values, please reference either Arctic DEM or Arctic DEM: Height Ellipsoidal.Data Dimensions and CompositionDEM Tiles are compiled from multiple strips that have been co-registered, blended, and feathered to reduce edge-matching artifacts. Tile sizes are standardized at 50 km x 50 km.Individual DEM strips are compiled from DigitalGlobe images. DEM strip dimensions will vary according to the sensor, off-nadir angle of collection, and the corresponding stereo-pair overlap. Most strips are between 16 km and 18 km in width, and 110 km and 120 km in length. Using this layerThis colorized aspect map is appropriate for visualizing the orientation of the surface at large map scales. This layer can be added to applications or maps to enhance contextual understanding.The 8 bit color values returned by this layer represent a graphic visualization, not slope values. For access to numeric aspect values, use the Arctic DEM: Aspect Degree layer, which returns orientation values from 0 to 359 degrees.This layer can be temporally filtered by acquisition date. This layer allows query, identify, and export image requests. The layer is restricted to a 4000 x 4000 pixel limit in a single request.For additional visual context and analysis, below is the full list of layers available as Raster Functions. These can be accessed from within the service or as individual AGOL items: Arctic DEM, Hillshade Gray, Aspect Degrees, Aspect Map, Contour 25, Hillshade Multidirectional, Slope Map, Slope Degrees, Contour Smoothed 25, Hillshade Elevation Tinted, Height Ellipsoidal Additional Data SpecificationsThe ArcticDEM product is a Digital Surface Model (DSM) which includes above ground features such as man-made structures and vegetation.The data has not been edited to remove processing anomalies. Pits, spikes, false landforms, and other DEM anomalies may exist in this dataset. Polygonal hydrographic features have not been flattened and the data has not been hydrologically enforced.Since the DEM’s are optically derived, clouds, fog, shadows, and other atmospheric obstructions can obscure the ground resulting in data gaps.Since the DEM strips have not been edge-matched, visible seams and deviations between adjacent strips may be observed.The data spans multiple years and seasons. A single season/year mosaic is not possible for large areas.Mosaic tiles are displayed by default. Strips can be selected and displayed via image filtering.For quick and easy access to this and additional elevation layers, see the Elevation Layers group in ArcGIS Online.For more information on the source data, see ArcticDEM.

  11. m

    Land Cover-Land Use (2016) Map Service

    • gis.data.mass.gov
    • hub.arcgis.com
    Updated May 24, 2019
    + more versions
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    MassGIS - Bureau of Geographic Information (2019). Land Cover-Land Use (2016) Map Service [Dataset]. https://gis.data.mass.gov/datasets/land-cover-land-use-2016-map-service
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    Dataset updated
    May 24, 2019
    Dataset authored and provided by
    MassGIS - Bureau of Geographic Information
    Area covered
    Description

    The statewide dataset contains a combination of land cover mapping from 2016 aerial imagery and land use derived from standardized assessor parcel information for Massachusetts. The data layer is the result of a cooperative project between MassGIS and the National Oceanic and Atmospheric Administration’s (NOAA) Office of Coastal Management (OCM). Funding was provided by the Mass. Executive Office of Energy and Environmental Affairs.

    This land cover/land use dataset does not conform to the classification schemes or polygon delineation of previous land use data from MassGIS (1951-1999; 2005).In this map service layer hosted at MassGIS' ArcGIS Server, all impervious polygons are symbolized by their generalized use code; all non-impervious land cover polygons are symbolized by their land cover category. The idea behind this method is to use both cover and use codes to provide a truer picture of how land is being used: parcel use codes may indicate allowed or assessed, not actual use; land cover alone (especially impervious) does not indicate actual use.

    See the full datalayer description for more details.This map service is best displayed at large (zoomed in) scales. Also available are a Feature Service and a Tile Service (cache). The tile cache will display very quickly in in ArcGIS Online, ArcGIS Desktop, and other applications that can consume tile services.

  12. e

    Esri ArcGIS Server View Service - Base maps of CR (Web Mercator)

    • data.europa.eu
    esri_map
    Updated May 17, 2013
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    (2013). Esri ArcGIS Server View Service - Base maps of CR (Web Mercator) [Dataset]. https://data.europa.eu/data/datasets/cz-cuzk-ags-zm_mercator?locale=es
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    esri_mapAvailable download formats
    Dataset updated
    May 17, 2013
    Description

    Esri ArcGIS Server View Service - Base maps of CR (Web Mercator) is provided as a public view service on the Base Maps of the Czech Republic data for scales 1:10,000, 1:25,000, 1:50,000, 1:100,000 and 1:200,000 in Web Mercator coordinate system. It is completed with maps of the Czech Republic at scales 1:500,000 and 1:1,000,000. The view service is provided using the Esri ArcGIS Server technology. To optimize the speed, the data are provided in form of pre-prepared map tiles. The Service is accessible by one of access interfaces – REST, SOAP, WMTS and WMS.

  13. Ontario Digital Terrain Model (Lidar-Derived)

    • geohub.lio.gov.on.ca
    • hub.arcgis.com
    • +1more
    Updated Aug 23, 2019
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    Ontario Ministry of Natural Resources and Forestry (2019). Ontario Digital Terrain Model (Lidar-Derived) [Dataset]. https://geohub.lio.gov.on.ca/maps/776819a7a0de42f3b75e40527cc36a0a
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    Dataset updated
    Aug 23, 2019
    Dataset provided by
    Ministry of Natural Resourceshttp://www.ontario.ca/page/ministry-natural-resources
    Authors
    Ontario Ministry of Natural Resources and Forestry
    License

    https://www.ontario.ca/page/open-government-licence-ontariohttps://www.ontario.ca/page/open-government-licence-ontario

    Area covered
    Description

    Zoom in on the map above and click your area of interest or use the Tile Index linked below to determine which package(s) you require for download. The DTM data is available in the form of 1-km by 1-km non-overlapping tiles grouped into packages for download.This dataset is a compilation of lidar data from multiple acquisition projects, as such specifications, parameters and sensors may vary by project. See the detailed User Guide linked below for additional information.

    You can monitor the availability and status of lidar projects on the Ontario Lidar Coverage map on the Ontario Elevation Mapping Program hub page.

    Now also available through a web service which exposes the data for visualization, geoprocessing and limited download. The service is best accessed through the ArcGIS REST API, either directly or by setting up an ArcGIS server connection using the REST endpoint URL. The service draws using the Web Mercator projection.

    For more information on what functionality is available and how to work with the service, read the Ontario Web Raster Services User Guide. If you have questions about how to use the service, email Geospatial Ontario (GEO) at geospatial@ontario.ca.

    Service Endpoints

    https://ws.geoservices.lrc.gov.on.ca/arcgis5/rest/services/Elevation/Ontario_DTM_LidarDerived/ImageServer https://intra.ws.geoservices.lrc.gov.on.ca/arcgis5/rest/services/Elevation/Ontario_DTM_LidarDerived/ImageServer (Government of Ontario Internal Users)

    Additional Documentation

    Ontario DTM (Lidar-Derived) - User Guide (DOCX)

    OMAFRA Lidar 2016-2018 -Cochrane-Additional Contractor Metadata (PDF) OMAFRA Lidar 2016-2018 -Peterborough-AdditionalContractorMetadata (PDF) OMAFRA Lidar 2016-2018 -Lake Erie-AdditionalContractorMetadata (PDF) CLOCA Lidar 2018 - Additional Contractor Metadata (PDF) South Nation Lidar 2018-19 - Additional Contractor Metadata (PDF) OMAFRA Lidar 2022 - Lake Huron - Additional Contractor Metadata (PDF) OMAFRA Lidar 2022 - Lake Simcoe - Additional Contractor Metadata (PDF) Huron-Georgian Lidar 2022-23 - Additional Contractor Metadata (Word) Kawartha Lakes Lidar 2023 - Additional Contractor Metadata (Word) Sault Ste Marie Lidar 2023-24 - Additional Contractor Metadata (Word) Thunder Bay Lidar 2023-24 - Additional Contractor Metadata (Word) Timmins Lidar 2024 - Additional Contractor Metadata (Word)

    Ontario DTM (Lidar-Derived) - Tile Index (SHP) Ontario Lidar Project Extents (SHP)

    OMAFRA Lidar DTM 2016-2018 -Cochrane- Breaklines (SHP) OMAFRA Lidar DTM 2016-2018 -Peterborough-Breaklines (SHP) OMAFRA Lidar DTM 2016-2018 -Lake Erie-Breaklines (SHP) CLOCA Lidar DTM 2018-Breaklines (SHP) South Nation Lidar DTM 2018-19-Breaklines (SHP) Ottawa-Gatineau Lidar DTM 2019-20 - Breaklines (SHP) OMAFRA Lidar DTM 2022 - Lake Huron - Breaklines (SHP) OMAFRA Lidar DTM 2022 - Lake Simcoe - Breaklines (SHP) Eastern Ontario Lidar DTM 2021-22 - Breaklines (SHP) Muskoka Lidar DTM 2018 - Breaklines CGVD2013 (SHP) / CGVD28 (SHP) Muskoka Lidar DTM 2021 - Breaklines CGVD2013 (SHP) / CGVD28 (SHP) Muskoka Lidar DTM 2023 - Breaklines CGVD2013 (SHP) / CGVD28 (SHP) DEDSFM Huron-Georgian Bay 2022-23 - Breaklines (SHP) DEDSFM Kawartha Lakes 2023 - Breaklines (SHP) DEDSFM Sault Ste Marie 2023-24- UTM16 - Breaklines (SHP) DEDSFM Sault Ste Marie 2023-24- UTM17 - Breaklines (SHP) DEDSFM Sudbury 2023-24 - Breaklines (SHP) DEDSFM Thunder Bay 2023-24 - Breaklines (SHP) DEDSFM Timmins 2024 - Breaklines (SHP)

    Product PackagesDownload links for the Ontario DTM (Lidar-Derived) (Word) Projects: LEAP 2009 GTA 2014-18 OMAFRA 2016-18 CLOCA 2018 South Nation CA 2018-19 Muskoka 2018-23 York-Lake Simcoe 2019 Ottawa River 2019-20 Ottawa-Gatineau 2019-20 Lake Nipissing 2020 Hamilton-Niagara 2021 Huron Shores 2021 Eastern Ontario 2021-22 OMAFRA Lake Huron 2022 OMAFRA Lake Simcoe 2022 Belleville 2022 Digital Elevation Data to Support Flood Mapping 2022-26

    Huron-Georgian Bay 2022-23 Kawartha Lakes 2023 Sault Ste Marie 2023-24 Sudbury 2023-24 Thunder Bay 2023-24 Timmins 2024

    Greater Toronto Area Lidar 2023

    Status On going: Data is continually being updated

    Maintenance and Update Frequency As needed: Data is updated as deemed necessary

    Contact Ontario Ministry of Natural Resources - Geospatial Ontario,geospatial@ontario.ca

  14. d

    SCR_Aerial_SantaRosaIslandSouth_10162012_KelpClass

    • opc.dataone.org
    • search.dataone.org
    Updated Jul 21, 2022
    + more versions
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    James Reed (2022). SCR_Aerial_SantaRosaIslandSouth_10162012_KelpClass [Dataset]. http://doi.org/10.25494/P6RS3G
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    Dataset updated
    Jul 21, 2022
    Dataset provided by
    California Ocean Protection Council Data Repository
    Authors
    James Reed
    Time period covered
    Jan 1, 2012 - Dec 30, 2012
    Area covered
    Description

    These raster and vector dataset were developed for the Sea Grant South Coast MPA Baseline Program as part of the project “Nearshore Substrate Mapping and Change Analysis using Historical and Concurrent Multispectral Imagery” (#R/MPA 30 10-049). The study region is the South Coast Region (SCR). Imagery was acquired on October 16, 2012 at a spatial resolution of 0.3 meters using a Microsoft UltraCam-X digital camera acquiring in the red, green, blue and near-infrared bands. Information on the UltraCam-X camera system and wavelengths for each ban can be found in the file "The Microsoft Vexcel UltraCam X.pdf" included in the Support folder on the image data delivery media and on the OceanSpaces.org server. This image mosaic product is a result of the resampling of the 0.3 meter data to 2 meter GSD. Details on this system and the data processing are below in the Lineage section of this document. Individual UCX image tiles were mosaicked into sections based on the islands covered and local coastal regions as well as the SCR MPA zones in order to generate this multispectral image product. These imagery were subsequently used to generate habitat classification thematic maps of the SCR's kelp beds from Point Conception to Imperial Beach, CA. The imagery files deliverd are in GeoTIFF format. More information on the classes resolved and processing methods are in the Lineage section of this document. This raster dataset contains a habitat classification of either offshore giant kelp beds along the California South Coast Region (SCR) from from Point Conception, CA down to Imperial beach, CA. This specific raster classification includes the South Point SMR and Skunk Point SMR. This dataset was originally uploaded to Oceanspaces (http://oceanspaces.org/) and the Knowledge Network for Biocomplexity (KNB, https://knb.ecoinformatics.org/data) in 2013 as part of the South Coast baseline monitoring program. In 2022 this dataset was moved to the California Ocean Protection Council Data Repository (https://opc.dataone.org/) by Mike Esgro (Michael.Esgro@resources.ca.gov) and Rani Gaddam (gaddam@ucsc.edu). At that time the GIS analysis products were added to the dataset. The long-term California MPA boundary and project info tables can be found as a separate dataset here: https://opc.dataone.org/view/doi:10.25494/P64S3W.

  15. d

    90 m DEM of Northern California, USA

    • datadiscoverystudio.org
    Updated Jun 27, 2018
    + more versions
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    (2018). 90 m DEM of Northern California, USA [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/90fec94daacf43f092f3bc36860a4357/html
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    Dataset updated
    Jun 27, 2018
    Area covered
    Description

    Link to the ScienceBase Item Summary page for the item described by this metadata record. Service Protocol: Link to the ScienceBase Item Summary page for the item described by this metadata record. Application Profile: Web Browser. Link Function: information

  16. Evaluation results of the glomeruli segmentation for each group and total.

    • plos.figshare.com
    xls
    Updated Jun 2, 2023
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    Manuel Stritt; Anna K. Stalder; Enrico Vezzali (2023). Evaluation results of the glomeruli segmentation for each group and total. [Dataset]. http://doi.org/10.1371/journal.pcbi.1007313.t001
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    xlsAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Manuel Stritt; Anna K. Stalder; Enrico Vezzali
    License

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

    Description

    Samples of each staining type are illustrated in Fig 6.

  17. a

    Legacy Shaded Relief from LiDAR (Tile Service)

    • hub.arcgis.com
    • geo-massdot.opendata.arcgis.com
    Updated Sep 15, 2021
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    MassGIS - Bureau of Geographic Information (2021). Legacy Shaded Relief from LiDAR (Tile Service) [Dataset]. https://hub.arcgis.com/maps/8418300d72be464189882fc41eaf796e
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    Dataset updated
    Sep 15, 2021
    Dataset authored and provided by
    MassGIS - Bureau of Geographic Information
    Area covered
    Description

    This shaded relief image was generated from the lidar-based bare-earth digital elevation model (DEM). A shaded relief image provides an illustration of variations in elevation using artificial shadows. Based on a specified position of the sun, areas that would be in sunlight are highlighted and areas that would be in shadow are shaded. In this instance, the position of the sun was assumed to be 45 degrees above the northwest horizon.The shaded relief image shows areas that are not in direct sunlight as shadowed. It does not show shadows that would be cast by topographic features onto the surrounding surface.Using ERDAS IMAGINE, a 3X3 neighborhood around each pixel in the DEM was analyzed, and a comparison was made between the sun's position and the angle that each pixel faces. The pixel was then assigned a value between -1 and +1 to represent the amount of light reflected. Negative numbers and zero values represent shadowed areas, and positive numbers represent sunny areas. In ArcGIS Desktop 10.7.1, the image was converted to a JPEG 2000 format with values from 0 (black) to 255 (white).See the MassGIS datalayer page to download the data as a JPEG 2000 image file.View this service in the Massachusetts Elevation Finder.MassGIS has also published a Lidar Shaded Relief image service from ArcGIS Server.

  18. Arctic DEM: Contour Smoothed 25

    • livingatlas-dcdev.opendata.arcgis.com
    Updated Aug 30, 2016
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    Esri (2016). Arctic DEM: Contour Smoothed 25 [Dataset]. https://livingatlas-dcdev.opendata.arcgis.com/datasets/6fedfbe38d9d4fc0a2b24b715d40017c
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    Dataset updated
    Aug 30, 2016
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    ArcticDEM is a National Geospatial-Intelligence Agency (NGA) and National Science Foundation (NSF) public-private initiative to automatically produce a high-resolution, high-quality Digital Surface Model (DSM) of the Arctic using sub-meter, stereoscopic satellite imagery collected by DigitalGlobe’s satellite constellation.The Arctic DEM layer is rendered here as Contour Smoothed 25. Using the server-side contour function, this layer dynamically generates contours based on the current viewing extents.For information on the Contour function see ContourRasterFunction.Geographic ExtentAll land area north of 60° north latitude, including all territory of Greenland, the entire state of Alaska, and the Kamchatka Peninsula of the Russian Federation.Map ProjectionThis layer is projected to WGS 1984 EPSG Alaska Polar Stereographic.The source data is projected to WGS 84 / NSIDC Sea Ice Polar Stereographic North.NOTE: By default, opening this layer in the Map Viewer will project the layer to Web Mercator. To display in the Alaska Polar projection, use Arctic DEM: Contour Smoothed 25 Web Map.Spatial Resolution2-meterAccuracyWithout ground control points absolute accuracy is approximately 4 meters in horizontal and vertical planes. Uniform ground control must be applied to achieve higher accuracy. Laser altimetry data from the NASA IceSAT spacecraft has been applied to the ArcticDEM mosaic files. Users may wish to use other sources for smaller areas, particularly on ArcticDEM strip files. Strip DEM files contain IceSAT altimetry offsets within the metadata, but have not had these values applied.The accuracy of these layers will vary as a function of location and data source. Please refer to the metadata available in the layers, and follow the links to the original sources for further details. An estimate of CE90 and LE90 are included as attributes.Height ValuesHeight values provided in meters.This layer provides height values as Orthometric height above the EGM2008 geoid.This product includes above ground features such as vegetation and man-made structures. There is no “bare earth” ArcticDEM terrain product.Data Dimensions and CompositionDEM Tiles are compiled from multiple strips that have been co-registered, blended, and feathered to reduce edge-matching artifacts. Tile sizes are standardized at 50 km x 50 km.Individual DEM strips are compiled from DigitalGlobe images. DEM strip dimensions will vary according to the sensor, off-nadir angle of collection, and the corresponding stereo-pair overlap. Most strips are between 16 km and 18 km in width, and 110 km and 120 km in length. Using this layerSmooth Contour 25 provides a quick indication of valleys and hills and steepness of slopes, at a range of map scales. This layer can be added to web applications or other maps to enhance contextual understanding.This layer can be temporally filtered by acquisition date. This layer allows query, identify, and export image requests. The layer is restricted to a 4000 x 4000 pixel limit in a single request.For additional visual context and analysis, below is the full list of layers available as Raster Functions. These can be accessed from within the service or as individual AGOL items: Arctic DEM, Hillshade Gray, Aspect Degrees, Aspect Map, Contour 25, Hillshade Multidirectional, Slope Map, Slope Degrees, Contour Smoothed 25, Hillshade Elevation Tinted, Height Ellipsoidal Additional Data SpecificationsThe ArcticDEM product is a Digital Surface Model (DSM) which includes above ground features such as man-made structures and vegetation.The data has not been edited to remove processing anomalies. Pits, spikes, false landforms, and other DEM anomalies may exist in this dataset. Polygonal hydrographic features have not been flattened and the data has not been hydrologically enforced.Since the DEM’s are optically derived, clouds, fog, shadows, and other atmospheric obstructions can obscure the ground resulting in data gaps.Since the DEM strips have not been edge-matched, visible seams and deviations between adjacent strips may be observed.The data spans multiple years and seasons. A single season/year mosaic is not possible for large areas.Mosaic tiles are displayed by default. Strips can be selected and displayed via image filtering.For quick and easy access to this and additional elevation layers, see the Elevation Layers group in ArcGIS Online.For more information on the source data, see ArcticDEM.

  19. d

    SCR_Aerial_SantaCatalinaIslandEast_10152012_KelpClass

    • dataone.org
    • search.dataone.org
    • +2more
    Updated Jul 15, 2022
    + more versions
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    James Reed (2022). SCR_Aerial_SantaCatalinaIslandEast_10152012_KelpClass [Dataset]. http://doi.org/10.25494/P6ZG6C
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    Dataset updated
    Jul 15, 2022
    Dataset provided by
    California Ocean Protection Council Data Repository
    Authors
    James Reed
    Time period covered
    Jan 1, 2012 - Dec 30, 2012
    Area covered
    Description

    These raster and vector dataset were developed for the Sea Grant South Coast MPA Baseline Program as part of the project “Nearshore Substrate Mapping and Change Analysis using Historical and Concurrent Multispectral Imagery” (#R/MPA 30 10-049). The study region is the South Coast Region (SCR). Imagery was acquired on October 15, 2012 at a spatial resolution of 0.3 meters using a Microsoft UltraCam-X digital camera acquiring in the red, green, blue and near-infrared bands. Information on the UltraCam-X camera system and wavelengths for each ban can be found in the file "The Microsoft Vexcel UltraCam X.pdf" included in the Support folder on the image data delivery media and on the OceanSpaces.org server. This image mosaic product is a result of the resampling of the 0.3 meter data to 2 meter GSD. Details on this system and the data processing are below in the Lineage section of this document. Individual UCX image tiles were mosaicked into sections based on the islands covered and local coastal regions as well as the SCR MPA zones in order to generate this multispectral image product. These imagery were subsequently used to generate habitat classification thematic maps of the SCR's kelp beds from Point Conception to Imperial Beach, CA. The imagery files deliverd are in GeoTIFF format. More information on the classes resolved and processing methods are in the Lineage section of this document. This raster dataset contains a habitat classification of either offshore giant kelp beds along the California South Coast Region (SCR) from from Point Conception, CA down to Imperial beach, CA. This specific raster classification includes the Lover's Cove SMCA and Casino Point SMCA. This dataset was originally uploaded to Oceanspaces (http://oceanspaces.org/) and the Knowledge Network for Biocomplexity (KNB, https://knb.ecoinformatics.org/data) in 2013 as part of the South Coast baseline monitoring program. In 2022 this dataset was moved to the California Ocean Protection Council Data Repository (https://opc.dataone.org/) by Mike Esgro (Michael.Esgro@resources.ca.gov) and Rani Gaddam (gaddam@ucsc.edu). At that time the GIS analysis products were added to the dataset. The long-term California MPA boundary and project info tables can be found as a separate dataset here: https://opc.dataone.org/view/doi:10.25494/P64S3W.

  20. MACHC Bathymetry Gap Analysis (non-U.S. portion)

    • fiu-srh-open-data-hub-fiugis.hub.arcgis.com
    • hub.arcgis.com
    • +1more
    Updated Mar 18, 2019
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    NOAA GeoPlatform (2019). MACHC Bathymetry Gap Analysis (non-U.S. portion) [Dataset]. https://fiu-srh-open-data-hub-fiugis.hub.arcgis.com/maps/5cfc8ca41b9540989da57adb637444c9
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    Dataset updated
    Mar 18, 2019
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    Authors
    NOAA GeoPlatform
    Area covered
    Description

    The Meso American - Caribbean Sea Hydrographic Commission (MACHC) Bathymetry Gap Analysis (non U.S. portion) is a map service providing visual access to the local sounding density derived from all modern bathymetric data holdings at NOAA's National Centers for Environmental Information (NCEI). This product is a complement to the United States Bathymetry Gap Analysis. It was designed to inform ocean and coastal mapping strategies within the waters of the International Hydrographic Organization’s MACHC region and contribute to the international Seabed 2030 initiative, which aims to map the entire ocean floor at 100 meter resolution by 2030.Underpinning the map service are three principal layers of bathymetry. Actual soundings of multibeam data (raw), single beam data (1960 or later), and crowdsourced bathymetry are included. All bathymetry layers used in the gap analysis are archived at NCEI.To effectively manage server resources, the analysis is partitioned across 78 tiles spanning the non-U.S. portions of the MACHC region. Each tile spans 6 degrees in longitude and 4 degrees in latitude. Within this framework, all modern depth soundings or coverage footprints are extracted from NCEI and associated with an approximately 100-m resolution grid of the area. MB_System, GDAL, GMT, and Esri ArcGIS software are used to prepare this analysis.To simplify the visual presentation and accommodate evolving views on the number of soundings needed for a single 100 m cell to be "mapped", the number of soundings for each grid tile are divided into categories of coverage. Sounding densities greater than 0 and less than 3 are reclassed to a value of 1 and displayed as a deep pink color. This value represents "minimally mapped" in this analysis. Sounding densities equal to 3 or greater are reclassed to a value of 3 and displayed as a deep purple color. This value represents "better mapped" in this analysis.Legend:

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Esri (2013). World Imagery (for Export) [Dataset]. https://share-open-data-crawfordcountypa.opendata.arcgis.com/maps/226d23f076da478bba4589e7eae95952
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World Imagery (for Export)

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7 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Oct 15, 2013
Dataset authored and provided by
Esrihttp://esri.com/
Area covered
Description

This layer is designed to support exporting small volumes of basemap tiles for offline use. The content of this layer is equivalent to World Imagery. World Imagery provides one meter or better satellite and aerial imagery in many parts of the world and lower resolution satellite imagery worldwide. See World Imagery for more details.The map service supporting this layer will enable you to export up to 150,000 tiles in a single request. For estimation purposes, this is large enough to support the export of:Large city (e.g. San Francisco) down to full level of detail at ~1:1,000 scale (Level 19)Medium size state or province (e.g. Colorado) down to scale of ~1:36,000 (Level 14)Medium to large country (e.g. Continental United States) down to scale of ~1:288,000 (Level 11)This layer is not intended to be used to display live map tiles for use in a web map or web mapping application. To display map tiles, please use World Imagery basemap.Service Information for DevelopersTo export tiles for World Imagery, you must use the instance of the World_Imagery service hosted on the tiledbasemaps.arcgis.com server referenced by this layer (see URL in Contents below), which has the Export Tiles operation enabled. This layer is intended to support export of basemap tiles for offline use in ArcGIS applications and other applications built with an ArcGIS Runtime SDK.

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