66 datasets found
  1. d

    Geospatial Data from the Alpine Treeline Warming Experiment (ATWE) on Niwot...

    • search.dataone.org
    • data.ess-dive.lbl.gov
    • +1more
    Updated Jul 7, 2021
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    Fabian Zuest; Cristina Castanha; Nicole Lau; Lara M. Kueppers (2021). Geospatial Data from the Alpine Treeline Warming Experiment (ATWE) on Niwot Ridge, Colorado, USA [Dataset]. http://doi.org/10.15485/1804896
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    Dataset updated
    Jul 7, 2021
    Dataset provided by
    ESS-DIVE
    Authors
    Fabian Zuest; Cristina Castanha; Nicole Lau; Lara M. Kueppers
    Time period covered
    Jan 1, 2008 - Jan 1, 2012
    Area covered
    Description

    This is a collection of all GPS- and computer-generated geospatial data specific to the Alpine Treeline Warming Experiment (ATWE), located on Niwot Ridge, Colorado, USA. The experiment ran between 2008 and 2016, and consisted of three sites spread across an elevation gradient. Geospatial data for all three experimental sites and cone/seed collection locations are included in this package. ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Geospatial files include cone collection, experimental site, seed trap, and other GPS location/terrain data. File types include ESRI shapefiles, ESRI grid files or Arc/Info binary grids, TIFFs (.tif), and keyhole markup language (.kml) files. Trimble-imported data include plain text files (.txt), Trimble COR (CorelDRAW) files, and Trimble SSF (Standard Storage Format) files. Microsoft Excel (.xlsx) and comma-separated values (.csv) files corresponding to the attribute tables of many files within this package are also included. A complete list of files can be found in this document in the “Data File Organization” section in the included Data User's Guide. Maps are also included in this data package for reference and use. These maps are separated into two categories, 2021 maps and legacy maps, which were made in 2010. Each 2021 map has one copy in portable network graphics (.png) format, and the other in .pdf format. All legacy maps are in .pdf format. .png image files can be opened with any compatible programs, such as Preview (Mac OS) and Photos (Windows). All GIS files were imported into geopackages (.gpkg) using QGIS, and double-checked for compatibility and data/attribute integrity using ESRI ArcGIS Pro. Note that files packaged within geopackages will open in ArcGIS Pro with “main.” preceding each file name, and an extra column named “geom” defining geometry type in the attribute table. The contents of each geospatial file remain intact, unless otherwise stated in “niwot_geospatial_data_list_07012021.pdf/.xlsx”. This list of files can be found as an .xlsx and a .pdf in this archive. As an open-source file format, files within gpkgs (TIFF, shapefiles, ESRI grid or “Arc/Info Binary”) can be read using both QGIS and ArcGIS Pro, and any other geospatial softwares. Text and .csv files can be read using TextEdit/Notepad/any simple text-editing software; .csv’s can also be opened using Microsoft Excel and R. .kml files can be opened using Google Maps or Google Earth, and Trimble files are most compatible with Trimble’s GPS Pathfinder Office software. .xlsx files can be opened using Microsoft Excel. PDFs can be opened using Adobe Acrobat Reader, and any other compatible programs. A selection of original shapefiles within this archive were generated using ArcMap with associated FGDC-standardized metadata (xml file format). We are including these original files because they contain metadata only accessible using ESRI programs at this time, and so that the relationship between shapefiles and xml files is maintained. Individual xml files can be opened (without a GIS-specific program) using TextEdit or Notepad. Since ESRI’s compatibility with FGDC metadata has changed since the generation of these files, many shapefiles will require upgrading to be compatible with ESRI’s latest versions of geospatial software. These details are also noted in the “niwot_geospatial_data_list_07012021” file.

  2. Rangewide SNPL Window Survey Form 2.0

    • gis-fws.opendata.arcgis.com
    Updated Dec 3, 2024
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    U.S. Fish & Wildlife Service (2024). Rangewide SNPL Window Survey Form 2.0 [Dataset]. https://gis-fws.opendata.arcgis.com/maps/cfe52c047f584790bddcd6f69f0e528a
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    Dataset updated
    Dec 3, 2024
    Dataset provided by
    U.S. Fish and Wildlife Servicehttp://www.fws.gov/
    Authors
    U.S. Fish & Wildlife Service
    Area covered
    Earth
    Description

    This is a feature layer created from the Survey123 form to collect a baseline of data for the Western Snowy Plover during annual window surveys. This data is designed for use across the entire west coast portion of the species range, in collaboration with partners and cooperators. The form was created based on an initial version that was field tested in Recovery Unit 2. This form will similarly be tested across the range for it's field usability and data format creation. The intent is to continue to take feedback and improve the form for use across all recovery units.Western Snowy Plover (Charadrius nivosus nivosus; plover) Census and Monitoring Surveys – United States Fish and Wildlife Service (Service). This project focuses on electronic data collection (using Survey123) for Western Snowy Plover annual monitoring surveys in all Recovery Units (1-6) which covers coastal California, Oregon and Washington.The plover was listed as a federally threatened species under the Endangered Species Act in 1993. The U.S. Fish and Wildlife Service’s Western Snowy Plover Pacific Coast Population Recovery Plan was published in 2007. The 2007 Recovery Plan provides reasonable actions believed to be required to recover and/or protect plovers. The first action needed from the Recovery Plan is to monitor breeding and wintering populations and habitats of the Pacific coast population of the western snowy plover to determine progress of recovery actions to maximize survival and productivity. The census and monitoring surveys are critical data for determining if the recovery criteria have been met. Recovery criteria for delisting the plover includes: 1) An average of 3,000 breeding adults has been maintained for 10 years and 2) A yearly average productivity of at least one (1.0) fledged chick per male has been maintained in each recovery unit in the last 5 years prior to delisting. The survey effort is a collaboration between multiple FWS Field Offices, contracted partners, and official volunteers.For more information:Here is a direct link to the Data Management Plan for this project, the ServCat reference page, the Survey123 link, and a link to the relevant program page for Arcata Fish & Wildlife Office.

  3. USA Federal Lands

    • gis-calema.opendata.arcgis.com
    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • +1more
    Updated Jul 31, 2019
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    CA Governor's Office of Emergency Services (2019). USA Federal Lands [Dataset]. https://gis-calema.opendata.arcgis.com/datasets/usa-federal-lands
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    Dataset updated
    Jul 31, 2019
    Dataset provided by
    California Governor's Office of Emergency Services
    Authors
    CA Governor's Office of Emergency Services
    Area covered
    United States,
    Description

    In the United States, the federal government manages lands in significant parts of the country. These lands include 193 million acres managed by the US Forest Service in the nation's 154 National Forests and 20 National Grasslands, Bureau of Land Management lands that cover 247 million acres in Alaska and the Western United States, 150 million acres managed for wildlife conservation by the US Fish and Wildlife Service, 84 million acres of National Parks and other lands managed by the National Park Service and over 30 million acres managed by the Department of Defense. The Bureau of Reclamation manages a much smaller land base than the other agencies included in this layer but plays a critical role in managing the country's water resources.The agencies included in this layer are:Bureau of Land ManagementBureau of ReclamationDepartment of DefenseNational Park ServiceUS Fish and Wildlife ServiceUS Forest ServiceDataset SummaryPhenomenon Mapped: United States lands managed by six federal agencies Coordinate System: Web Mercator Auxiliary SphereExtent: 50 United States plus Puerto Rico, US Virgin Islands, Guam, American Samoa, and Northern Mariana Islands. The layer also includes National Monuments and Wildlife Refuges in the Pacific Ocean, Atlantic Ocean, and the Caribbean Sea.Visible Scale: The data is visible at all scales but draws best at scales greater than 1:2,000,000Source: BLM, DoD, USFS, USFWS, NPS, PADUS 2.1Publication Date: Various - Esri compiled and published this layer in May 2022. See individual agency views for data vintage.There are six layer views available that were created from this service. Each layer uses a filter to extract an individual agency from the service. For more information about the layer views or how to use them in your own project, follow these links:USA Bureau of Land Management LandsUSA Bureau of Reclamation LandsUSA Department of Defense LandsUSA National Park Service LandsUSA Fish and Wildlife Service LandsUSA Forest Service LandsWhat can you do with this Layer?This layer is suitable for both visualization and analysis across the ArcGIS system. This layer can be combined with your data and other layers from the ArcGIS Living Atlas of the World in ArcGIS Online and ArcGIS Pro to create powerful web maps that can be used alone or in a story map or other application.Because this layer is part of the ArcGIS Living Atlas of the World it is easy to add to your map:In ArcGIS Online, you can add this layer to a map by selecting Add then Browse Living Atlas Layers. A window will open. Type "federal lands" in the search box and browse to the layer. Select the layer then click Add to Map.In ArcGIS Pro, open a map and select Add Data from the Map Tab. Select Data at the top of the drop down menu. The Add Data dialog box will open on the left side of the box, expand Portal if necessary, then select Living Atlas. Type "federal lands" in the search box, browse to the layer then click OK.In both ArcGIS Online and Pro you can change the layer's symbology and view its attribute table. You can filter the layer to show subsets of the data using the filter button in Online or a definition query in Pro.The data can be exported to a file geodatabase, a shapefile or other format and downloaded using the Export Data button on the top right of this webpage.This layer can be used as an analytic input in both Online and Pro through the Perform Analysis window Online or as an input to a geoprocessing tool, model, or Python script in Pro.The ArcGIS Living Atlas of the World provides an easy way to explore many other beautiful and authoritative maps on hundreds of topics like this one.

  4. a

    STORMWATER

    • opendata.atlantaregional.com
    • 20200127-eastpointgis.hub.arcgis.com
    • +2more
    Updated Mar 25, 2019
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    City of East Point (2019). STORMWATER [Dataset]. https://opendata.atlantaregional.com/maps/eastpointgis::stormwater/about
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    Dataset updated
    Mar 25, 2019
    Dataset authored and provided by
    City of East Point
    Area covered
    Description

    On January 25, 2018 FEMA replaced this map with a new NFHL map with additional functionality which allows users to print official flood maps. On April 1, 2018 this map and NFHL link will no longer function. Please update your bookmark to https://hazards-fema.maps.arcgis.com/apps/webappviewer/index.html?id=8b0adb51996444d4879338b5529aa9cd. For more information on NFHL data availability, please visit the NFHL GIS Services page at https://hazards.fema.gov/femaportal/wps/portal/NFHLWMSAs of August 1, 2017 all FEMA systems will require the use of the “https” protocol, and “http” links will no longer function. This may impact NFHL web services. The FEMA GeoPlatform (including this map) will not be affected by this change. For more information on how NFHL GIS services will be impacted, please visit the NFHL GIS Services page at https://hazards.fema.gov/femaportal/wps/portal/NFHLWMS.An NFHL FIRMette print service is now available HERE. (For a video tutorial, click here.)OverviewThe National Flood Hazard Layer (NFHL) dataset represents the current effective flood data for the country, where maps have been modernized. It is a compilation of effective Flood Insurance Rate Map (FIRM) databases and Letters of Map Change (LOMCs). The NFHL is updated as studies go effective. For more information, visit FEMA's Map Service Center (MSC). Base Map ConsiderationsThe default base map is from a USGS service and conforms to FEMA's specification for horizontal accuracy. This base map from The National Map (TNM) consists of National Agriculture Imagery Program (NAIP) and high resolution orthoimagery (HRO) that combine the visual attributes of an aerial photograph with the spatial accuracy and reliability of a map. This map should be considered the best online resource to use for official National Flood Insurance Program (NFIP) purposes when determining locations in relation to regulatory flood hazard information. If a different base map is used with the NFHL, the accuracy specification may not be met and the resulting map should be used for general reference only, and not official NFIP purposes. Users can download a simplified base map from the USGS service via: https://viewer.nationalmap.gov/services/ For the specifics of FEMA’s policy on the use of digital flood hazard data for NFIP purposes see: http://www.fema.gov/library/viewRecord.do?id=3235Letter of Map Amendment (LOMA) pointsLOMA point locations are approximate. The location of the LOMA is referenced in the legal description of the letter itself. Click the LOMA point for a link to the letter (use the arrows at the top of the popup window to bring up the LOMA info, if needed).This LOMA database may include LOMAs that are no longer effective. To be certain a particular LOMA is currently valid, please check relevant documentation at https://msc.fema.gov/ . Relevant documents can be found for a particular community by choosing to "Search All Products", and finding the community by State and County. Documents include LOMAs found in the "Effective Products" and "LOMC" folders, as well as Revalidations (those LOMAs which are still considered to be effective after a map is revised).Updates3/27/2017 - Updated all references to https to prevent issues with mixed content.5/11/2016 - Added link to NFHL FIRMette Print Service. Updated LOMA and CBRS popup notes.2/20/2014 - Created a General Reference map for use when the USGS base map service is down. Renamed this map to "Official".Further InformationSpecific questions about FEMA flood maps can be directed to FEMAMapSpecialist@riskmapcds.comFor more flood map data, tool, and viewing options, visit the FEMA NFHL page. Information about connecting to web map services (REST, WMS, WFS) can be found here.Several fact sheets are available to help you learn more about FEMA’s NFHL utility: National Flood Hazard Layer (NFHL) GIS Services Users GuideNational Flood Hazard Layer (NFHL): New Products and Services for FEMA's Flood Hazard Map DataMoving to Digital Flood Hazard Information Standards for Flood Risk Analysis and MappingNFHL GIS Data: Perform Spatial Analyses and Make Custom Maps and Reports

  5. USA Bureau of Land Management Lands

    • colorado-river-portal.usgs.gov
    • crb-open-data-usgs.hub.arcgis.com
    • +3more
    Updated Feb 14, 2018
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    Esri (2018). USA Bureau of Land Management Lands [Dataset]. https://colorado-river-portal.usgs.gov/datasets/eb2c541a2ce24627a497e0f5887ff13d
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    Dataset updated
    Feb 14, 2018
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    One-eighth of the United States (247.3 million acres) is managed by the Bureau of Land Management. As part of the Department of the Interior, the agency oversees the 30 million acre National Landscape Conservation System, a collection of lands that includes 221 wilderness areas, 23 national monuments and 636 other protected areas. Bureau of Land Management Lands contain over 63,000 oil and gas wells and provide forage for over 18,000 grazing permit holders on 155 million acres of land. Dataset SummaryPhenomenon Mapped: United States lands managed by the Bureau of Land ManagementGeographic Extent: Contiguous United States and AlaskaData Coordinate System: WGS 1984Visible Scale: The data is visible at all scales but draws best at scales larger than 1:2,000,000.Source: BLM Surface Management Agency layer, Rasterized by Esri from features May 2025.Publication Date: December 2024This layer is a view of the USA Federal Lands layer. A filter has been used on this layer to eliminate non-Bureau of Land Management lands. For more information on layers for other agencies see the USA Federal Lands layer.What can you do with this layer?This layer is suitable for both visualization and analysis across the ArcGIS system. This layer can be combined with your data and other layers from the ArcGIS Living Atlas of the World in ArcGIS Online and ArcGIS Pro to create powerful web maps that can be used alone or in a story map or other application.Because this layer is part of the ArcGIS Living Atlas of the World it is easy to add to your map:In ArcGIS Online you can add this layer to a map by selecting Add then Browse Living Atlas Layers. A window will open. Type "bureau of land management" in the search box and browse to the layer. Select the layer then click Add to Map.In ArcGIS Pro open a map and select Add Data from the Map Tab. Select Data at the top of the drop down menu. The Add Data dialog box will open on the left side of the box expand Portal if necessary then select Living Atlas. Type "bureau of land management" in the search box, browse to the layer then click OK.In both ArcGIS Online and Pro you can change the layer's symbology and view its attribute table. You can filter the layer to show subsets of the data using the filter button in Online or a definition query in Pro.The data can be exported to a file geodatabase, a shape file or other format and downloaded using the Export Data button on the top right of this webpage.This layer can be used as an analytic input in both Online and Pro through the Perform Analysis window Online or as an input to a geoprocessing tool, model, or Python script in Pro.The ArcGIS Living Atlas of the World provides an easy way to explore many other beautiful and authoritative maps on hundreds of topics like this one.Questions?Please leave a comment below if you have a question about this layer, and we will get back to you as soon as possible.

  6. Attachment Viewer

    • noveladata.com
    Updated Jul 1, 2020
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    esri_en (2020). Attachment Viewer [Dataset]. https://www.noveladata.com/items/65dd2fa3369649529b2c5939333977a1
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    Dataset updated
    Jul 1, 2020
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    esri_en
    Description

    Use the Attachment Viewer template to provide an app for users to explore a layer's features and review attachments with the option to update attribute data. Present your images, videos, and PDF files collected using ArcGIS Field Maps or ArcGIS Survey123 workflows. Choose an attachment-focused layout to display individual images beside your map or a map-focused layout to highlight your map next to a gallery of images. Examples: Review photos collected during emergency response damage inspections. Display the results of field data collection and support downloading images for inclusion in a report. Present a map of land parcel along with associated documents stored as attachments. Data requirements The Attachment Viewer template requires a feature layer with attachments. It includes the capability to view attachments of a hosted feature service or an ArcGIS Server feature service (10.8 or later). Currently, the app can display JPEG, JPG, PNG, GIF, MP4, QuickTime (.mov), and PDF files in the viewer window. All other attachment types are displayed as a link. Key app capabilities App layout - Choose between an attachment-focused layout, which displays one attachment at a time in the main panel of the app with the map on the side, or a map-focused layout, which displays the map in the main panel of the app with a gallery of attachments. Feature selection - Allows users to select features in the map and view associated attachments. Review data - Enable tools to review and update existing records. Zoom, pan, download images - Allow users to interact with and download attachments. Language switcher - Provide translations for custom text and create a multilingual app. Home, Zoom controls, Legend, Layer List, Search Supportability This web app is designed responsively to be used in browsers on desktops, mobile phones, and tablets. We are committed to ongoing efforts towards making our apps as accessible as possible. Please feel free to leave a comment on how we can improve the accessibility of our apps for those who use assistive technologies.

  7. a

    Monthly Soil Moisture

    • afghanistan-uneplive.hub.arcgis.com
    • colorado-river-portal.usgs.gov
    • +6more
    Updated Jul 28, 2022
    + more versions
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    UN Environment, Early Warning &Data Analytics (2022). Monthly Soil Moisture [Dataset]. https://afghanistan-uneplive.hub.arcgis.com/datasets/monthly-soil-moisture
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    Dataset updated
    Jul 28, 2022
    Dataset authored and provided by
    UN Environment, Early Warning &Data Analytics
    Area covered
    Description

    Soils and soil moisture greatly influence the water cycle and have impacts on runoff, flooding and agriculture. Soil type and soil particle composition (sand, clay, silt) affect soil moisture and the ability of the soil to retain water. Soil moisture is also affected by levels of evaporation and plant transpiration, potentially leading to near dryness and eventual drought.Measuring and monitoring soil moisture can ensure the fitness of your crops and help predict or prepare for flash floods and drought. The GLDAS soil moisture data is useful for modeling these scenarios and others, but only at global scales. Dataset SummaryThe GLDAS Soil Moisture layer is a time-enabled image service that shows average monthly soil moisture from 2000 to the present at four different depth levels. It is calculated by NASA using the Noah land surface model, run at 0.25 degree spatial resolution using satellite and ground-based observational data from the Global Land Data Assimilation System (GLDAS-1). The model is run with 3-hourly time steps and aggregated into monthly averages. Review the complete list of model inputs, explore the output data (in GRIB format), and see the full Hydrology Catalog for all related data and information!What can you do with this layer?This layer is suitable for both visualization and analysis. It can be used in ArcGIS Online in web maps and applications and can be used in ArcGIS Desktop. The GLDAS soil moisture data is useful for modeling, but only at global scales. Time: This is a time-enabled layer. It shows the total evaporative loss during the map's time extent, or if time animation is disabled, a time range can be set using the layer's multidimensional settings. The map shows the sum of all months in the time extent. Minimum temporal resolution is one month; maximum is one year.Depth: This layer has four depth levels. By default they are summed, but you can view each using the multidimensional filter. You must disable time animation on the layer before using its multidimensional filter. It is also possible to toggle between depth layers using raster functions, accessed through the Image Display tab.Important: You must switch from the cartographic renderer to the analytic renderer in the processing template tab in the layer properties window before using this layer as an input to geoprocessing tools.This layer has query, identify, and export image services available. This layer is part of a larger collection of earth observation maps that you can use to perform a wide variety of mapping and analysis tasks.The Living Atlas of the World provides an easy way to explore the earth observation layers and many other beautiful and authoritative maps on hundreds of topics.Geonet is a good resource for learning more about earth observations layers and the Living Atlas of the World. Follow the Living Atlas on GeoNet.

  8. World Soils 250m Percent Clay

    • cacgeoportal.com
    Updated Oct 25, 2023
    + more versions
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    Esri (2023). World Soils 250m Percent Clay [Dataset]. https://www.cacgeoportal.com/maps/1bfc47d2a0d544bea70588f81aac8afb
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    Dataset updated
    Oct 25, 2023
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    Soil is the foundation of life on earth. More living things by weight live in the soil than upon it. It determines what crops we can grow, what structures we can build, what forests can take root.This layer contains the physical soil variable percent clay (clay).Within the subset of soil that is smaller than 2mm in size, also known as the fine earth portion, clay is defined as particles that are smaller than 0.002mm, making them only visible in an electron microscope. Clay soils contain low amounts of air, and water drains through them very slowly.This layer is a general, medium scale global predictive soil layer suitable for global mapping and decision support. In many places samples of soils do not exist so this map represents a prediction of what is most likely in that location. The predictions are made in six depth ranges by soilgrids.org, funded by ISRIC based in Wageningen, Netherlands.Each 250m pixel contains a value predicted for that area by soilgrids.org from best available data worldwide. Data for percent clay are provided at six depth ranges from the surface to 2 meters below the surface. Each variable and depth range may be accessed in the layer's multidimensional properties.Dataset SummaryPhenomenon Mapped: Proportion of clay particles (< 0.002 mm) in the fine earth fraction in g/100g (%)Cell Size: 250 metersPixel Type: 32 bit float, converted from online data that is 16 Bit Unsigned IntegerCoordinate System: Web Mercator Auxiliary Sphere, projected via nearest neighbor from goode's homolosine land (250m)Extent: World land area except AntarcticaVisible Scale: All scales are visibleNumber of Columns and Rows: 160300, 100498Source: Soilgrids.orgPublication Date: May 2020Data from the soilgrids.org mean predictions for clay were used to create this layer. You may access the percent clay in one of six depth ranges. To select one choose the depth variable in the multidimensional selector in your map client.Mean depth (cm)Actual depth range of data-2.50-5cm depth range-105-15cm depth range-22.515-30cm depth range-4530-60cm depth range-8060-100cm depth range-150100-200cm depth rangeWhat can you do with this Layer?This layer is suitable for both visualization and analysis across the ArcGIS system. This layer can be combined with your data and other layers from the ArcGIS Living Atlas of the World in ArcGIS Online and ArcGIS Pro to create powerful web maps that can be used alone or in a story map or other application.Because this layer is part of the ArcGIS Living Atlas of the World it is easy to add to your map: In ArcGIS Online, you can add this layer to a map by selecting Add then Browse Living Atlas Layers. A window will open. Type "world soils soilgrids" in the search box and browse to the layer. Select the layer then click Add to Map. In ArcGIS Pro, open a map and select Add Data from the Map Tab. Select Data at the top of the drop down menu. The Add Data dialog box will open on the left side of the box, expand Portal if necessary, then select Living Atlas. Type "world soils soilgrids" in the search box, browse to the layer then click OK.In ArcGIS Pro you can use the built-in raster functions or create your own to create custom extracts of the data. Imagery layers provide fast, powerful inputs to geoprocessing tools, models, or Python scripts in Pro.Online you can filter the layer to show subsets of the data using the filter button and the layer's built-in raster functions.This layer is part of the Living Atlas of the World that provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.More information about soilgrids layersAnswers to many questions may be found at soilgrids.org (ISRIC) frequently asked questions (faq) page about the data.To make this layer, Esri reprojected the expected value of ISRIC soil grids from soilgrids' source projection (goode's land WKID 54052) to web mercator projection, nearest neighbor, to facilitate online mapping. The resolution in web mercator projection is the same as the original projection, 250m. But keep in mind that the original dataset has been reprojected to make this web mercator version.This multidimensional soil collection serves the mean or expected value for each soil variable as calculated by soilgrids.org. For all other distributions of the soil variable, be sure to download the data directly from soilgrids.org. The data are available in VRT format and may be converted to other image formats within ArcGIS Pro.Accessing this layer's companion uncertainty layerBecause data quality varies worldwide, the uncertainty of the predicted value varies worldwide. A companion uncertainty layer exists for this layer which you can use to qualify the values you see in this map for analysis. Choose a variable and depth in the multidimensional settings of your map client to access the companion uncertainty layer.

  9. BSEE Data Center - Geographic Mapping Data in Digital Format

    • s.cnmilf.com
    • catalog.data.gov
    Updated Apr 4, 2025
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    Bureau of Safety and Environmental Enforcement (2025). BSEE Data Center - Geographic Mapping Data in Digital Format [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/bsee-data-center-geographic-mapping-data-in-digital-format
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    Dataset updated
    Apr 4, 2025
    Dataset provided by
    Bureau of Safety and Environmental Enforcementhttp://www.bsee.gov/
    Description

    The geographic data are built from the Technical Information Management System (TIMS). TIMS consists of two separate databases: an attribute database and a spatial database. The attribute information for offshore activities is stored in the TIMS database. The spatial database is a combination of the ARC/INFO and FINDER databases and contains all the coordinates and topology information for geographic features. The attribute and spatial databases are interconnected through the use of common data elements in both databases, thereby creating the spatial datasets. The data in the mapping files are made up of straight-line segments. If an arc existed in the original data, it has been replaced with a series of straight lines that approximate the arc. The Gulf of America OCS Region stores all its mapping data in longitude and latitude format. All coordinates are in NAD 27. Data can be obtained in three types of digital formats: INTERACTIVE MAP: The ArcGIS web maps are an interactive display of geographic information, containing a basemap, a set of data layers (many of which include interactive pop-up windows with information about the data), an extent, navigation tools to pan and zoom, and additional tools for geospatial analysis. SHP: A Shapefile is a digital vector (non-topological) storage format for storing geometric _location and associated attribute information. Shapefiles can support point, line, and area features with attributes held in a dBASE format file. GEODATABASE: An ArcGIS geodatabase is a collection of geographic datasets of various types held in a common file system folder, a Microsoft Access database, or a multiuser relational DBMS (such as Oracle, Microsoft SQL Server, PostgreSQL, Informix, or IBM DB2). The geodatabase is the native data structure for ArcGIS and is the primary data format used for editing and data management.

  10. a

    Soil Survey Geographic Database (SSURGO) Downloader

    • supply-chain-data-hub-nmcdc.hub.arcgis.com
    Updated Jun 17, 2022
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    New Mexico Community Data Collaborative (2022). Soil Survey Geographic Database (SSURGO) Downloader [Dataset]. https://supply-chain-data-hub-nmcdc.hub.arcgis.com/documents/305ef916da574a71877edb15c3f47f08
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    Dataset updated
    Jun 17, 2022
    Dataset authored and provided by
    New Mexico Community Data Collaborative
    Description

    The documentation below is in reference to this items placement in the NM Supply Chain Data Hub. The documentation is of use to understanding the source of this item, and how to reproduce it for updatesTitle: Soil Survey Geographic Database (SSURGO) DownloaderItem Type: Web Mapping Application URLSummary: Download ready-to-use project packages with over 170 attributes derived from the SSURGO (Soil Survey Geographic Database) dataset.Notes: Prepared by: Uploaded by EMcRae_NMCDCSource: https://nmcdc.maps.arcgis.com/home/item.html?id=cdc49bd63ea54dd2977f3f2853e07fff link to Esri web mapping applicationFeature Service: https://nmcdc.maps.arcgis.com/home/item.html?id=305ef916da574a71877edb15c3f47f08#overviewUID: 26Data Requested: Ag CensusMethod of Acquisition: Esri web mapDate Acquired: 6/16/22Priority rank as Identified in 2022 (scale of 1 being the highest priority, to 11 being the lowest priority): 8Tags: PENDINGDOCUMENTATION FROM DATA SOURCE URL: This application provides quick access to ready-to-use project packages filled with useful soil data derived from the SSURGO dataset.To use this application, navigate to your study area and click the map. A pop-up window will open. Click download and the project package will be copied to your computer. Double click the downloaded package to open it in ArcGIS Pro. Alt + click on the layer in the table of contents to zoom to the subbasin.Soil map units are the basic geographic unit of the Soil Survey Geographic Database (SSURGO). The SSURGO dataset is a compilation of soils information collected over the last century by the Natural Resources Conservation Service (NRCS). Map units delineate the extent of different soils. Data for each map unit contains descriptions of the soil’s components, productivity, unique properties, and suitability interpretations.Each soil type has a unique combination of physical, chemical, nutrient and moisture properties. Soil type has ramifications for engineering and construction activities, natural hazards such as landslides, agricultural productivity, the distribution of native plant and animal life and hydrologic and other physical processes. Soil types in the context of climate and terrain can be used as a general indicator of engineering constraints, agriculture suitability, biological productivity and the natural distribution of plants and animals.Dataset SummaryThe map packages were created from the October 2021 SSURGO snapshot. The dataset covers the 48 contiguous United States plus Hawaii and portions of Alaska. Map packages are available for Puerto Rico and the US Virgin Islands. A project package for US Island Territories and associated states of the Pacific Ocean can be downloaded by clicking one of the included areas in the map. The Pacific Project Package includes: Guam, the Marshall Islands, the Northern Marianas Islands, Palau, the Federated States of Micronesia, and American Samoa.Not all areas within SSURGO have completed soil surveys and many attributes have areas with no data. The soil data in the packages is also available as a feature layer in the ArcGIS Living Atlas of the World.AttributesKey fields from nine commonly used SSURGO tables were compiled to create the 173 attribute fields in this layer. Some fields were joined directly to the SSURGO Map Unit polygon feature class while others required summarization and other processing to create a 1:1 relationship between the attributes and polygons prior to joining the tables. Attributes of this layer are listed below in their order of occurrence in the attribute table and are organized by the SSURGO table they originated from and the processing methods used on them.Map Unit Polygon Feature Class Attribute TableThe fields in this table are from the attribute table of the Map Unit polygon feature class which provides the geographic extent of the map units.Area SymbolSpatial VersionMap Unit SymbolMap Unit TableThe fields in this table have a 1:1 relationship with the map unit polygons and were joined to the table using the Map Unit Key field.Map Unit NameMap Unit KindFarmland ClassInterpretive FocusIntensity of MappingIowa Corn Suitability RatingLegend TableThis table has 1:1 relationship with the Map Unit table and was joined using the Legend Key field.Project ScaleSurvey Area Catalog TableThe fields in this table have a 1:1 relationship with the polygons and were joined to the Map Unit table using the Survey Area Catalog Key and Legend Key fields.Survey Area VersionTabular VersionMap Unit Aggregated Attribute TableThe fields in this table have a 1:1 relationship with the map unit polygons and were joined to the Map Unit attribute table using the Map Unit Key field.Slope Gradient - Dominant ComponentSlope Gradient - Weighted AverageBedrock Depth - MinimumWater Table Depth - Annual MinimumWater Table Depth - April to June MinimumFlooding Frequency - Dominant ConditionFlooding Frequency - MaximumPonding Frequency - PresenceAvailable Water Storage 0-25 cm - Weighted AverageAvailable Water Storage 0-50 cm - Weighted AverageAvailable Water Storage 0-100 cm - Weighted AverageAvailable Water Storage 0-150 cm - Weighted AverageDrainage Class - Dominant ConditionDrainage Class - WettestHydrologic Group - Dominant ConditionIrrigated Capability Class - Dominant ConditionIrrigated Capability Class - Proportion of Map Unit with Dominant ConditionNon-Irrigated Capability Class - Dominant ConditionNon-Irrigated Capability Class - Proportion of Map Unit with Dominant ConditionRating for Buildings without Basements - Dominant ConditionRating for Buildings with Basements - Dominant ConditionRating for Buildings with Basements - Least LimitingRating for Buildings with Basements - Most LimitingRating for Septic Tank Absorption Fields - Dominant ConditionRating for Septic Tank Absorption Fields - Least LimitingRating for Septic Tank Absorption Fields - Most LimitingRating for Sewage Lagoons - Dominant ConditionRating for Sewage Lagoons - Dominant ComponentRating for Roads and Streets - Dominant ConditionRating for Sand Source - Dominant ConditionRating for Sand Source - Most ProbableRating for Paths and Trails - Dominant ConditionRating for Paths and Trails - Weighted AverageErosion Hazard of Forest Roads and Trails - Dominant ComponentHydric Classification - PresenceRating for Manure and Food Processing Waste - Weighted AverageComponent Table – Dominant ComponentMap units have one or more components. To create a 1:1 join component data must be summarized by map unit. For these fields a custom script was used to select the component with the highest value for the Component Percentage Representative Value field (comppct_r). Ties were broken with the Slope Representative Value field (slope_r). Components with lower average slope were selected as dominant. If both soil order and slope were tied, the first value in the table was selected.Component Percentage - Low ValueComponent Percentage - Representative ValueComponent Percentage - High ValueComponent NameComponent KindOther Criteria Used to Identify ComponentsCriteria Used to Identify Components at the Local LevelRunoff ClassSoil loss tolerance factorWind Erodibility IndexWind Erodibility GroupErosion ClassEarth Cover 1Earth Cover 2Hydric ConditionHydric RatingAspect Range - Counter Clockwise LimitAspect - Representative ValueAspect Range - Clockwise LimitGeomorphic DescriptionNon-Irrigated Capability SubclassNon-Irrigated Unit Capability ClassIrrigated Capability SubclassIrrigated Unit Capability ClassConservation Tree Shrub GroupGrain Wildlife HabitatGrass Wildlife HabitatHerbaceous Wildlife HabitatShrub Wildlife HabitatConifer Wildlife HabitatHardwood Wildlife HabitatWetland Wildlife HabitatShallow Water Wildlife HabitatRangeland Wildlife HabitatOpenland Wildlife HabitatWoodland Wildlife HabitatWetland Wildlife HabitatSoil Slip PotentialSusceptibility to Frost HeavingConcrete CorrosionSteel CorrosionTaxonomic ClassTaxonomic OrderTaxonomic SuborderGreat GroupSubgroupParticle SizeParticle Size ModCation Exchange Activity ClassCarbonate ReactionTemperature ClassMoist SubclassSoil Temperature RegimeEdition of Keys to Soil Taxonomy Used to Classify SoilCalifornia Storie IndexComponent KeyComponent Table – Weighted AverageMap units may have one or more soil components. To create a 1:1 join, data from the Component table must be summarized by map unit. For these fields a custom script was used to calculate an average value for each map unit weighted by the Component Percentage Representative Value field (comppct_r).Slope Gradient - Low ValueSlope Gradient - Representative ValueSlope Gradient - High ValueSlope Length USLE - Low ValueSlope Length USLE - Representative ValueSlope Length USLE - High ValueElevation - Low ValueElevation - Representative ValueElevation - High ValueAlbedo - Low ValueAlbedo - Representative ValueAlbedo - High ValueMean Annual Air Temperature - Low ValueMean Annual Air Temperature - Representative ValueMean Annual Air Temperature - High ValueMean Annual Precipitation - Low ValueMean Annual Precipitation - Representative ValueMean Annual Precipitation - High ValueRelative Effective Annual Precipitation - Low ValueRelative Effective Annual Precipitation - Representative ValueRelative Effective Annual Precipitation - High ValueDays between Last and First Frost - Low ValueDays between Last and First Frost - Representative ValueDays between Last and First Frost - High ValueRange Forage Annual Potential Production - Low ValueRange Forage Annual Potential Production - Representative ValueRange Forage Annual Potential Production - High ValueInitial Subsidence - Low ValueInitial Subsidence - Representative ValueInitial Subsidence - High ValueTotal Subsidence - Low ValueTotal Subsidence - Representative ValueTotal Subsidence - High ValueCrop Productivity IndexEsri SymbologyThis field was created to provide symbology based on the Taxonomic Order field (taxorder). Because some map units have a null value for soil order, a

  11. u

    USA National Park Service Lands

    • colorado-river-portal.usgs.gov
    • a-public-data-collection-for-nepa-sandbox.hub.arcgis.com
    • +2more
    Updated Feb 17, 2018
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    Esri (2018). USA National Park Service Lands [Dataset]. https://colorado-river-portal.usgs.gov/datasets/esri::usa-national-park-service-lands
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    Dataset updated
    Feb 17, 2018
    Dataset authored and provided by
    Esri
    Area covered
    Description

    The US National Park Service manages 84.4 million acres that include the United States" 63 national parks, many national monuments, and other conservation and historical properties. These lands range from the 13 million acre Wrangell-St. Elias National Park and Preserve in Alaska to the 0.02 acre Thaddeus Kosciuszko National Memorial in Pennsylvania.Dataset SummaryPhenomenon Mapped: Administrative boundaries of U.S. National Park Service landsGeographic Extent: 50 United States, District of Columbia, Puerto Rico, US Virgin Islands, Guam, American Samoa, and Northern Mariana IslandsData Coordinate System: WGS 1984Visible Scale: The data is visible at all scalesSource: NPS Administrative Boundaries of National Park System Units layerPublication Date: April, 2025This layer is a view of the USA Federal Lands layer. A filter has been used on this layer to eliminate non-Park Service lands. For more information on layers for other agencies see the USA Federal Lands layer.What can you do with this Layer?This layer is suitable for both visualization and analysis across the ArcGIS system. This layer can be combined with your data and other layers from the ArcGIS Living Atlas of the World in ArcGIS Online and ArcGIS Pro to create powerful web maps that can be used alone or in a story map or other application.Because this layer is part of the ArcGIS Living Atlas of the World it is easy to add to your map:In ArcGIS Online you can add this layer to a map by selecting Add then Browse Living Atlas Layers. A window will open. Type "national park service" in the search box and browse to the layer. Select the layer then click Add to Map.In ArcGIS Pro open a map and select Add Data from the Map Tab. Select Data at the top of the drop down menu. The Add Data dialog box will open on the left side of the box expand Portal if necessary then select Living Atlas. Type "national park service" in the search box, browse to the layer then click OK.In both ArcGIS Online and Pro you can change the layer's symbology and view its attribute table. You can filter the layer to show subsets of the data using the filter button in Online or a definition query in Pro.The data can be exported to a file geodatabase, a shape file or other format and downloaded using the Export Data button on the top right of this webpage.This layer can be used as an analytic input in both Online and Pro through the Perform Analysis window Online or as an input to a geoprocessing tool, model, or Python script in Pro.The ArcGIS Living Atlas of the World provides an easy way to explore many other beautiful and authoritative maps on hundreds of topics like this one.Questions?Please leave a comment below if you have a question about this layer, and we will get back to you as soon as possible.

  12. m

    Parcel Boundaries with Assessing Info - Martha's Vineyard

    • gis.data.mass.gov
    • data-dukescountygis.opendata.arcgis.com
    • +1more
    Updated Sep 28, 2021
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    Dukes County, MA GIS (2021). Parcel Boundaries with Assessing Info - Martha's Vineyard [Dataset]. https://gis.data.mass.gov/maps/Dukescountygis::parcel-boundaries-with-assessing-info-marthas-vineyard/about
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    Dataset updated
    Sep 28, 2021
    Dataset authored and provided by
    Dukes County, MA GIS
    Area covered
    Description

    These boundaries are for planning purposes only and are not survey grade. For the most up-to-date assessing info, please contact the Town's Assessor. The respective Fiscal Year of publication is provided in the parcel pop-up info window. Years may vary from town to town.The parcels from each town on Martha's Vineyard are included in this web map. The map must be zoomed in far enough before the parcels will display on the map. The data are served out from MassGIS. All parcel data comply with the MassGIS Level 3 Parcel Data Standard.Each Town in Dukes County hires their own parcel data consultant to maintain their GIS parcel file. In most cases, this is done once a year. At the time of data compilation, the town Assessor exports a standard info file from their database which gets associated with each digital parcel. The Town's consultant pulls the parcel bounds and assessing info table into a spatial geodatabase which is then forwarded to MassGIS. MassGIS completes a few additional data management tasks and then serves out the data through their ArcGIS OnLine organizational website.The Martha's Vineyard Commission (MVC) then pulls that parcel data feature class into this web map and sets a few things such as visibility zoom extents and how the data display in the pop-up. The MVC does not edit these data in any way.Building Info Note: If there are multiple buildings on a parcel, the building info provided is only for one building on the parcel. Which building (i.e. largest, smallest, newest, oldest) is unknown. Parcels with Multiple Owners (i.e. Condo): If there are multiple owners on one parcel, when clicking on the pop-up you'll see the option to cycle through several records worth of assessing info.Understanding the Attributes: See the MassGIS Level 3 Parcel Data website for details.

  13. a

    Australian Government Historical Aerial Photo Explorer

    • digital.atlas.gov.au
    Updated Mar 6, 2024
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    Digital Atlas of Australia (2024). Australian Government Historical Aerial Photo Explorer [Dataset]. https://digital.atlas.gov.au/datasets/australian-government-historical-aerial-photo-explorer
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    Dataset updated
    Mar 6, 2024
    Dataset authored and provided by
    Digital Atlas of Australia
    License

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

    Area covered
    Australia
    Description

    Before the advent of satellite imagery, aerial photography captured from planes offered a way to systematically document land information. The Australian Survey Corps and Royal Australian Air Force flew photography to produce topographic maps. Geoscience Australia’s predecessor organisations, such as the Australian Surveying and Land Information Group (AUSLIG), and the Division of National Mapping, also undertook aerial photography campaigns. Through these campaigns, every part of Australia and its external territories was imaged at some point, and often repeatedly. Our collection dates back to the 1920s, with coverage across our diverse country and neighbouring region. Discover historical aerial photos through a user-friendly interface that provides straightforward access to the digitised photos and metadata. Key featuresInteractive map: Zoom and pan in the interactive map to explore historical aerial photos. Photo details: Click on any photo point to obtain details of that photo, as well as a link to the full-resolution scanned frame or lower resolution preview image (if digitised). Flight line details: Click on any flight line to obtains details of that run, including frame numbers captured. User-friendly interface: Designed for users of all levels, this app provides a streamlined and intuitive experience for exploring historical aerial photos. CurrencyModification frequency: Data updated periodically, as more films are digitised.ContactGeoscience Australia, aerialphotography@ga.gov.auChangelogVersion 1.0.0 (25-07-2024) Map configured with the following layers:  Photo centres Flight lines Photo point cluster 4km, 6km, 8km, 10km, 12km, 14km hexagon aggregates. 250k AUSTopo map index 4 Mile military map index 1 Mile military map index ArcGIS Experience Builder app created using the following widgets/windows: Fixed window (splash screen) Point cluster legend Scanned/not scanned photo centre and flight line legend Links to HAP survey and GA aerial photography email address

    Fixed window (user guide) Configured with card and column widgets to display six views of instructions with accompanying screenshots

    Fixed window (about our historical aerial photo collection)

    Configured with card and column widgets to display information about the collection.

    Query Widget, configured to search photos

    Date search

    Digitisation status search (scanned, not scanned or both)

    Film type search (B&W, B&W infrared, colour, colour infrared, infrared, unknown)

    Film number search

    Spatial filter (current map extent, full map extent or drawn polygon/rectangle)

    Query Widget, configured to search flight lines

    Date search

    Digitisation status search (scanned, not scanned or both)

    Film number search

    Spatial filter (current map extent, full map extent or drawn polygon/rectangle)

    Add Data Widget

    Configured for users to add data from AGOL, Living Atlas, DAA curated collection, URLs and local drives.

    Coordinates Widget

    WGS 1984 Web Mercator Auxiliary Sphere

    Map Layers Widget

    Toggle on/off

    Basemap widget displaying the Basemap Gallery

    Configured to open on Dark Gray Canvas

    Address or place search bar

    Configured to use the HAP locator view which only returns relevant places or addresses.

  14. Heard Island Geology Map - compiled from data collected from 1929-2020

    • researchdata.edu.au
    • data.aad.gov.au
    Updated Apr 4, 2023
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    MCPHIE, JOCELYN; CAREY, REBECCA JANE; FOX, JODI; Fox, J., Carey, R.J., and McPhie, J.; FOX, JODI (2023). Heard Island Geology Map - compiled from data collected from 1929-2020 [Dataset]. https://researchdata.edu.au/heard-island-geology-1929-2020/3650737
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    Dataset updated
    Apr 4, 2023
    Dataset provided by
    Australian Antarctic Divisionhttps://www.antarctica.gov.au/
    Australian Antarctic Data Centre
    Authors
    MCPHIE, JOCELYN; CAREY, REBECCA JANE; FOX, JODI; Fox, J., Carey, R.J., and McPhie, J.; FOX, JODI
    License

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

    Time period covered
    Jan 1, 1929 - Oct 31, 2020
    Area covered
    Description

    ArcGIS geological map of Heard Island created using legacy field and sample data together with satellite imagery and published in Fox, Jodi M., et al. "Construction of an intraplate island volcano: The volcanic history of Heard Island." Bulletin of Volcanology 83.5 (2021): 37. The geological map was created in ArcMap 10.0 using satellite imagery, aerial photography, and historical maps and data. An initial map was generated by outlining geological features observed in the remote sensing images and the aerial photographs. This map was then cross-referenced with all available published and unpublished data to verify rock type, stratigraphic unit, and contact relationships. Where uncertainty in rock type or composition existed, the feature has been assigned to the stratigraphic unit without using a rock type label. In addition to published data, we collated and reviewed legacy unpublished maps, rock collections and unpublished data including hand-drawn sketches and notebooks.

    Criteria for allocation of rocks to formations were not changed from previous work (Barling 1990; Barling 1994; Lambeth 1948; Lambeth 1952; Stephenson 1964).

    Summary of the stratigraphy of Heard Island is as follows:

    1. Unconsolidated Deposits (Recent) - Moraines, beach pebble, gravel and sand deposits.
    2. Coastal Volcanic Cones (less than 15 ka) - Basaltic ash and scoria cones and associated small lavas.
    3. Newer Lavas (~750 ka- Present) - Comprises the Laurens Peninsula Group and the Big Ben Group.
    3a. Laurens Peninsula Group - Trachyte, tephrite, trachyandesite and basanite porphyritic lavas. Phenocrysts include clinopyroxene, olivine, plagioclase, kaersutite, magnetite, ilmenite and apatite. High TiO2 and P2O5 content.
    3b. Big Ben Group - Basalt-trachybasalt and basanite porphyritic lavas. Basalt-trachybasalt phenocryts include olivine, clinopyroxene, plagioclase and Fe-Ti oxides. Basanite phenocrysts and megacrysts include olivine and clinopyroxene
    4. Drygalski Formation (3.63-2.5 Ma) - Subhorizontal. Volcaniclastic breccia, conglomerate, sandstone and mudstone. Conglomerates are clast and matrix supported. Clasts are mainly basalt with minor trachyte, limestone and chert. Pillow lavas. Tillite. Microfossils include foraminifera and palynomorphs. Macrofossil - Austrochlamys heardensis
    5. Laurens Peninsula Limestone (Middle Eocene-Middle Oligocene) - Thin, white, grey and blue styolitic carbonate interbedded with thin, soft tuffaceous shales. Lense of chert. Microfossils include foraminifera, coccoliths and palynomorphs. Intruded by trachybasalt and dolerite dykes (5 cm-2 m thick) and dolerite and gabbro sills. Folded and tilted.

    For creation of the Heard Island geological map limestone and carbonate rocks were allocated to the Laurens Peninsula Limestones. Fresh, unaltered basalts were allocated to the Newer Lavas (Barling 1990). The Drygalski Formation includes all noncarbonate sedimentary rocks, clastic facies, and basalts between the Laurens Peninsula Limestones and the Newer Lavas (Barling 1990). Defining the boundary between the Drygalski Formation and the Newer Lavas is problematic, here we used the absence of chlorite as a criterion for allocating basalts to the Newer Lavas and the presence of basaltic pillows to allocate rocks to the Drygalski Formation consistent with Barling (1990). Although not ideal, these criteria were retained in the absence of more robust alternatives. Ridges of sediment in front of or adjacent to glaciers (current or since retreated) were mapped as moraines. Glacial retreat has been significant since the 1940s (~20 vol.% reduction), and locations where glaciers have been observed but have since retreated are relatively well known (Ruddell 2006). Ridges of unconsolidated sediment that have unclear relationships with glaciers and that could have been produced by aeolian and/or alluvial processes were mapped as unconsolidated sediment.

    Remote Sensing Resources Utilised:
    1. Mosaic of QuickBird satellite images of Heard Island (0.6m resolution) collected between 2006 and 2009 provided by the Australian Antarctic Division Data Centre (AADC).
    2. Satellite imagery from Google™ Earth. Images collected 1984-2016.
    3. Landsat 8 imagery from NASA via the USGS EarthExplorer online platform. Images collected 2013-2020.
    4. Analogue aerial photographs collected in 1987 and held at the AADC

    Published Resources Utilised
    1. Barling J (1990) The petrogenesis of the Newer Lavas on Heard Island unpublished thesis. Department of Earth Sciences, Monash University, Melbourne
    2. Barling J (1994) Origin and evolution of a high-Ti ocean island basalt suite; the Laurens Peninsula Series. Heard Island, Indian Ocean Mineralogical Magazine 58A:49–50
    3. Barling J, Goldstein SJ,Wheller GE, Nicholls IA (1988) Heard Island; an example of large isotopic variations on a small oceanic island. Chemical Geology 70:46–46
    4. Barling J, Goldstein SL, Nicholls IA (1994) Geochemistry of Heard Island (southern Indian Ocean); characterization of an enriched mantle component and implications for enrichment of the sub-Indian Ocean mantle, Journal of Petrology. 35:1017–1053
    5. Clarke I (1979) Petrogenesis of basic and ultrabasic lavas on Heard Island. J Geol Soc Aust 26:272–272
    6. Clarke I, McDougall I, Whitford DJ (1983) Volcanic evolution of Heard and McDonald islands, southern Indian Ocean. In: Oliver RL, James PR, Jago JB (eds) Antarctic earth science. Cambridge University, Cambridge, United Kingdom (GBR), pp 631–635
    7. Collerson KD, Regelous M, Frankland RA, Wendt JI, Wheller G, Anonymous (1998) 1997 eruption of McDonald Island (southern Indian Ocean); new trace element and Th-Sr-Pb-Nd isotopic constraints on Heard-McDonald island magmatism Abstracts. Geological Society of Australia 49:87
    8. Duncan RA, Quilty PG, Barling J, Fox JM (2016b) Geological development of Heard Island. Central Kerguelen Plateau. Aust J Earth Sci 63:81–89
    9. Fox JM (2014) Heard Island up-date LAVA news. Geological Society of Australia 25:6–7
    10. JonkersHA (2003) Late Cenozoic - recent pectinidae (mollusca: bivalvia) of the Southern Ocean and neighbouring regions. Monographs of marine Mollusca no.5. Backhuys Publishers BV, Leiden
    11. Kiernan K, McConnell A, Yates T (1998) Tube-fed pahoehoe lava-flow features of Azorella Peninsula, Heard Island, southern Indian Ocean. Polar Record 34:225–236
    12. Lambeth AJ (1952) A geological account of Heard Island. Journal and Proceedings of the Royal Society of New South Wales 86 Part 1:14–19
    13. Orth K, Carey RJ, Wright R (2013) Heard Island volcanic eruption. September-October, November 2012 LAVA News 24:3–4
    14. Patrick M (2013) Heard (Australia): Satellite imagery reveals lava flows in December 2012 Bulletin of the Global Volcanism Network 38:1
    15. Patrick MR, Smellie JL (2013) Synthesis: A spaceborne inventory of volcanic activity in Antarctica and southern oceans, 2000–10. Antarctic Science 25:475–500
    16. Quilty PG, Wheller G (2000) Heard Island and the McDonald Islands; a window into the Kerguelen Plateau. Papers and Proceedings of the Royal Society of Tasmania 133 Part 2:1–12
    17. Quilty PG, Shafik S, McMinn A, Brady H, Clarke I (1983) Microfossil evidence for the age and environment of deposition of sediments of Heard and McDonald Islands. In: Oliver RL, James PR, Jago JB (eds) Antarctic Earth Science. Cambridge University, Cambridge, pp 636–639
    18. Quilty PG, Murray-Wallace CV, Whitehead JM (2004) Austrochlamys heardensis (Fleming, 1957) (bivalvia, pectinidae) from Central Kerguelen plateau, Indian Ocean; palaeontology and possible tectonic significance. Antarctic Science 16:329–338. https://doi.org/10.1017/S0954102004002160
    19. Ruddell A (2006) An inventory of present glaciers on Heard Island and their historical variation. In: Green K, Woehler EJ (eds) Heard Island; Southern Ocean Sentinel. Surrey Beatty, Chipping Norton, New South Wales (AUS), pp 28–51
    20. Stephenson PJ (1964) Some geological observations on Heard Island. In: Adie RJ (ed) Antarctic Geology - Proceedings of the first international symposium on Antarctic geology. North-Holland Publishing Company, Amsterdam, pp 14–24
    21. Stephenson PJ (1972) Geochemistry of some Heard Island igneous rocks. In: Adie RJ (ed) Antarctic Geology and Geophysics. Scandinavian University Books, Oslo, pp 793–801
    22. Stephenson PJ, Barling J, Wheller G, Clarke I (2006) The geology and volcanic geomorphology of Heard Island. In: Green K, Woehler EJ (eds) Heard Island; Southern Ocean Sentinel. Surrey Beatty, Chipping Norton, Australia, pp 10–27
    23. Truswell EM, Quilty PG, McMinn A, MacPhail MK, Wheller GE (2005) Late Miocene vegetation and palaeoenvironments of the Drygalski Formation, Heard Island, Indian Ocean; evidence from palynology. Antarctic Science 17:427–442. https://doi.org/10.1017/S0954102005002865
    24. Tyrrell GW (1937) The petrology of Heard Island BANZARE reports 2part 3:27-56

    Unpublished Resources Utilised:

    1. H.O. Fletcher, 1929 Rock Collection Australian Museum, Sydney.
    2. A.J. Lambeth, 1948-1949 Rock collection, hand drawn outcrop sketches and maps, field notebooks, Australian Museum, Sydney
    3. P. Blaxland, 1948 Rock Collection Australian Museum, Sydney.
    4. G.C Compton, 1951 Personal letter outlining geological observations with sketches made during survey of Heard Island, Australian Museum Sydney.
    5. P.G. Law and T. Burstall, 1953 ANARE Interim Report 7 Heard Island, Australian Antarctic Museum Library.
    6. I. Clarke, 1982 Technical Report - Expedition to the Australian Territory of Heard Island and McDonald Island, Australian Antarctic Museum Library.
    7. R. Vining, 1983 A report of activities by the Heard Island Expedition 1983, Australian Antarctic Division Library, Kingston Tasmania
    8. H.R. Burton

  15. r

    1939 Imagery Collection: Download App

    • rigis.org
    Updated Sep 20, 2023
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    Environmental Data Center (2023). 1939 Imagery Collection: Download App [Dataset]. https://www.rigis.org/datasets/1939-imagery-collection-download-app
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    Dataset updated
    Sep 20, 2023
    Dataset authored and provided by
    Environmental Data Center
    Description

    1939 Digital Aerial Photography Contributor: Rhode Island Department of Administration, Statewide Planning Program This web app features scanned, georeferenced historical aerial photography collected in May of 1939. The scanned images are panchromatic (black and white) and have a spatial resolution of approximately 4 feet. While the original prints are archived by the Rhode Island Statewide Planning Program, the scanned images are available from the Rhode Island Geographic Information System (RIGIS) consortium.Using the point index and associated popup window, users can download these images individually or visit this page and download them all. These download in zipped MrSID format. Web services available:ArcGIS Online hosted tile layer ArcGIS map service (REST endpoint)Metadata

  16. USA Protected Areas - GAP Status 1-4 (Mature Support)

    • colorado-river-portal.usgs.gov
    • a-public-data-collection-for-nepa-sandbox.hub.arcgis.com
    • +1more
    Updated Feb 1, 2017
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    Esri (2017). USA Protected Areas - GAP Status 1-4 (Mature Support) [Dataset]. https://colorado-river-portal.usgs.gov/datasets/5929d41b496f4747ba6a7f588ca618a9
    Explore at:
    Dataset updated
    Feb 1, 2017
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    Important Note: This item is in mature support as of June 2024 and will be retired in December 2026. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version.The Protected Areas Database of the United States provides a comprehensive map of lands protected by government agencies and private land owners. This database combines federal lands with information on state and local government lands and conservation easements on private lands to create a powerful resource for land-use planning.Dataset SummaryPhenomenon Mapped: Areas mapped in the Protected Areas Data base of the United States (GAP Status 1-4)Units: MetersCell Size: 30.92208102 metersSource Type: ThematicPixel Type: 8-bit unsigned integerData Coordinate System: WGS 1984Mosaic Projection: Web Mercator Auxiliary SphereExtent: 50 United States plus Puerto Rico, the US Virgin Islands, Guam, Northern Mariana Islands and American Samoa.Source: USGS National Gap Analysis Program PAD-US version 3.0Publication Date: July 2022ArcGIS Server URL: https://landscape10.arcgis.com/arcgis/This layer displays lands mapped in Protected Areas Database of the United States version 3.0 created by the USGS National Gap Analysis Program. This layer displays all four GAP Status classes: GAP Status 1 - Areas managed for biodiversity where natural disturbances are allowed to proceedGAP Status 2 - Areas managed for biodiversity where natural disturbance is suppressedGAP Status 3 - Areas protected from land cover conversion but subject to extractive uses such as logging and miningGAP Status 4 - Areas with no known mandate for protectionThe source data for this layer are available here. A feature layer published from this dataset is also available. The polygon vector layer was converted to raster layers using the Polygon to Raster Tool using the National Elevation Dataset 1 arc second product as a snap raster.The service behind this layer was published with 8 functions allowing the user to select different views of the service. Other layers created from this service using functions include:USA Protected AreasUSA Protected from Land Cover ConversionUSA Unprotected AreasUSA Protected Areas - Gap Status 1USA Protected Areas - Gap Status 2USA Protected Areas - Gap Status 3USA Protected Areas - Gap Status 4What can you do with this Layer? This layer is suitable for both visualization and analysis across the ArcGIS system. This layer can be combined with your data and other layers from the ArcGIS Living Atlas of the World in ArcGIS Online and ArcGIS Pro to create powerful web maps that can be used alone or in a story map or other application.Because this layer is part of the ArcGIS Living Atlas of the World it is easy to add to your map:In ArcGIS Online, you can add this layer to a map by selecting Add then Browse Living Atlas Layers. A window will open. Type "Protected Areas" in the search box and browse to the layer. Select the layer then click Add to Map.In ArcGIS Pro, open a map and select Add Data from the Map Tab. Select Data at the top of the drop down menu. The Add Data dialog box will open on the left side of the box, expand Portal if necessary, then select Living Atlas. Type "Protected Areas" in the search box, browse to the layer then click OK.In ArcGIS Pro you can use the built-in raster functions to create custom extracts of the data. Imagery layers provide fast, powerful inputs to geoprocessing tools, models, or Python scripts in Pro.The ArcGIS Living Atlas of the World provides an easy way to explore many other beautiful and authoritative maps on hundreds of topics like this one.

  17. Monthly Precipitation

    • ai-climate-hackathon-global-community.hub.arcgis.com
    • colorado-river-portal.usgs.gov
    • +7more
    Updated Jun 24, 2015
    + more versions
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    Esri (2015). Monthly Precipitation [Dataset]. https://ai-climate-hackathon-global-community.hub.arcgis.com/maps/01fa55f171eb48a7ac9c460c0339e6c1
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    Dataset updated
    Jun 24, 2015
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    Precipitation is water released from clouds in the form of rain, sleet, snow, or hail. It is the primary source of recharge to the planet's fresh water supplies. This map contains a historical record showing the volume of precipitation that fell during each month from March 2000 to the present. Snow and hail are reported in terms of snow water equivalent - the amount of water that will be produced when they melt. Dataset SummaryThe GLDAS Precipitation layer is a time-enabled image service that shows average monthly precipitation from 2000 to the present, measured in millimeters. It is calculated by NASA using the Noah land surface model, run at 0.25 degree spatial resolution using satellite and ground-based observational data from the Global Land Data Assimilation System (GLDAS-1). The model is run with 3-hourly time steps and aggregated into monthly averages. Review the complete list of model inputs, explore the output data (in GRIB format), and see the full Hydrology Catalog for all related data and information!What can you do with this layer?This layer is suitable for both visualization and analysis. It can be used in ArcGIS Online in web maps and applications and can be used in ArcGIS for Desktop. It is useful for scientific modeling, but only at global scales.Time: This is a time-enabled layer. It shows the total evaporative loss during the map's time extent, or if time animation is disabled, a time range can be set using the layer's multidimensional settings. The map shows the sum of all months in the time extent. Minimum temporal resolution is one month; maximum is one year.Variables: This layer has two variables: rainfall and snowfall. By default the two are summed, but you can view either by itself using the multidimensional filter. You must disable time animation on the layer before using its multidimensional filter.Important: You must switch from the cartographic renderer to the analytic renderer in the processing template tab in the layer properties window before using this layer as an input to geoprocessing tools.This layer has query, identify, and export image services available.This layer is part of a larger collection of earth observation maps that you can use to perform a wide variety of mapping and analysis tasks.The Living Atlas of the World provides an easy way to explore the earth observation layers and many other beautiful and authoritative maps on hundreds of topics.Geonet is a good resource for learning more about earth observations layers and the Living Atlas of the World. Follow the Living Atlas on GeoNet.

  18. c

    Landforms

    • cacgeoportal.com
    Updated Mar 30, 2024
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    Central Asia and the Caucasus GeoPortal (2024). Landforms [Dataset]. https://www.cacgeoportal.com/maps/6a37e5e185d04f5184140cc53d86602a
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    Dataset updated
    Mar 30, 2024
    Dataset authored and provided by
    Central Asia and the Caucasus GeoPortal
    Area covered
    Description

    This layer is subset of World Ecological Facets Landform Classes Image Layer. Landforms are large recognizable features such as mountains, hills and plains; they are an important determinant of ecological character, habitat definition and terrain analysis. Landforms are important to the distribution of life in natural systems and are the basis for opportunities in built systems, and therefore landforms play a useful role in all natural science fields of study and planning disciplines.Dataset SummaryPhenomenon Mapped: LandformsUnits: MetersCell Size: 231.91560581932 metersSource Type: ThematicPixel Type: 8-bit unsigned integerData Coordinate System: WGS 1984Mosaic Projection: Web Mercator Auxiliary SphereExtent: GlobalSource: EsriPublication Date: May 2016ArcGIS Server URL: https://landscape7.arcgis.com/arcgis/In February 2017, Esri updated the World Landforms - Improved Hammond Method service with two display functions: Ecological Land Units landform classes and Ecological Facets landform classes. This layer represents Ecological Facets landform classes. You can view the Ecological Land Units landform classes by choosing Image Display, and changing the Renderer. This layer was produced using the Improved Hammond Landform Classification Algorithm produced by Esri in 2016. This algorithm published and described by Karagulle et al. 2017: Modeling global Hammond landform regions from 250-m elevation data in Transactions in GIS.The algorithm, which is based on the most recent work in this area by Morgan, J. & Lesh, A. 2005: Developing Landform Maps Using Esri’s Model Builder., Esri converted Morgan’s model into a Python script and revised it to work on global 250-meter resolution GMTED2010 elevation data. Hammond’s landform classification characterizes regions rather than identifying individual features, thus, this layer contains sixteen classes of landforms:Nearly flat plainsSmooth plains with some local reliefIrregular plains with moderate relief Irregular plains with low hillsScattered moderate hillsScattered high hillsScattered low mountainsScattered high mountainsModerate hillsHigh hills Tablelands with moderate reliefTablelands with considerable reliefTablelands with high relief Tablelands with very high relief Low mountainsHigh mountainsTo produce these classes, Esri staff first projected the 250-meter resolution GMTED elevation data to the World Equidistant Cylindrical coordinate system. Each cell in this dataset was assigned three characteristics: slope based on 3-km neighborhood, relief based on 6 km neighborhood, and profile based on 6-km neighborhood. The last step was to overlay the combination of these three characteristics with areas that are exclusively plains. Slope is the percentage of the 3-km neighborhood occupied by gentle slope. Hammond specified 8% as the threshold for gentle slope. Slope is used to define how flat or steep the terrain is. Slope was classified into one of four classes: Percent of neighborhood over 8% of slopeSlope Classes0 - 20%40021% -50%30051% - 80%200>81% 100Local Relief is the difference between the maximum and minimum elevation within in the 6-km neighborhood. Local relief is used to define terrain how rugged or the complexity of the terrain's texture. Relief was assigned one of six classes:Change in elevationRelief Class ID0 – 30 meters1031 meter – 90 meters2091 meter – 150 meters30151 meter – 300 meters40301 meter – 900 meters50>900 meters60The combination of slope and relief begin to define terrain as mountains, hills and plains. However, the difference between mountains or hills and tablelands cannot be distinguished using only these parameters. Profile is used to determine tableland areas. Profile identifies neighborhoods with upland and lowland areas, and calculates the percent area of gently sloping terrain within those upland and lowland areas. A 6-km circular neighborhood was used to calculate the profile parameter. Upland/lowland is determined by the difference between average local relief and elevation. In the 6-km neighborhood window, if the difference between maximum elevation and cell’s elevation is smaller than half of the local relief it’s an upland. If the difference between maximum elevation and cell’s elevation is larger than half of the local relief it’s a lowland. Profile was assigned one of five classes:Percent of neighborhood over 8% slope in upland or lowland areasProfile ClassLess than 50% gentle slope is in upland or lowland0More than 75% of gentle slope is in lowland150%-75% of gentle slope is in lowland250-75% of gentle slope is in upland3More than 75% of gentle slope is in upland4Early reviewers of the resulting classes noted one confusing outcome, which was that areas were classified as "plains with low mountains", or "plains with hills" were often mostly plains, and the hills or mountains were part of an adjacent set of exclusively identified hills or mountains. To address this areas that are exclusively plains were produced, and used to override these confusing areas. The hills and mountains within those areas were converted to their respective landform class.The combination of slope, relief and profile merged with the areas of plains, can be better understood using the following diagram, which uses the colors in this layer to show which classes are present and what parameter values produced them:What can you do with this layer?This layer is suitable for both visualization and analysis. It can be used in ArcGIS Online in web maps and applications and can be used in ArcGIS Desktop. This layer is part of a larger collection of landscape layers that you can use to perform a wide variety of mapping and analysis tasks.The Living Atlas of the World provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.Geonet is a good resource for learning more about landscape layers and the Living Atlas of the World. To get started see the Living Atlas Discussion Group.The Esri Insider Blog provides an introduction to the Ecophysiographic Mapping project.

  19. Monthly Runoff

    • africageoportal.com
    • iwmi.africageoportal.com
    • +1more
    Updated Jun 24, 2015
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    Esri (2015). Monthly Runoff [Dataset]. https://www.africageoportal.com/maps/4446d0e344b94734aeac07d998877357
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    Dataset updated
    Jun 24, 2015
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    When precipitation falls on the surface of the Earth, much of it is captured in storage (e.g. lakes, aquifers, soil moisture, snowpack, and vegetation). Precipitation that exceeds the storage capacity of the landscape becomes runoff, which flows into river systems. Overland flow is the most visible form of runoff, causing erosion and flash floods, but subsurface flow is the larger contributor in many watersheds. Subsurface flow can emerge on the surface through springs, or more commonly, seep into rivers and lakes through their banks. In urban areas, impervious land cover drastically increases the amount of surface runoff generated, which sweeps trash and urban debris into waterways and increases the likelihood and severity of flash floods. In agricultural areas, surface or subsurface runoff can carry excess salts and nutrients, especially nitrogen and phosphorus. This map contains a historical record showing the amount of runoff generated each month from March 2000 to present. It is reported in millimeters, so multiply by a surface area to calculate the total volume of runoff.Dataset SummaryThe GLDAS Runoff layer is a time-enabled image service that shows average monthly runoff from 2000 to the present measured in millimeters. It is calculated by NASA using the Noah land surface model, run at 0.25 degree spatial resolution using satellite and ground-based observational data from the Global Land Data Assimilation System (GLDAS-1). The model is run with 3-hourly time steps and aggregated into monthly averages. Review the complete list of model inputs, explore the output data (in GRIB format), and see the full Hydrology Catalog for all related data and information!What can you do with this layer?This layer is suitable for both visualization and analysis. It can be used in ArcGIS Online in web maps and applications and can be used in ArcGIS Desktop. t is useful for scientific modeling, but only at global scales.Time: This is a time-enabled layer. It shows the total runoff generated during the map's time extent, or if time animation is disabled, a time range can be set using the layer's multidimensional filter. The map shows the sum of all months in the time extent. Minimum temporal resolution is one month; maximum is one year.Variables: This layer has two variables: surface flow and subsurface flow. By default the two are summed, but you can view either by itself using the multidimensional filter. You must disable time animation on the layer before using its multidimensional filter.Important: You must switch from the cartographic renderer to the analytic renderer in the processing template tab in the layer properties window before using this layer as an input to geoprocessing tools.This layer has query, identify, and export image services available. This layer is part of a larger collection of earth observation maps that you can use to perform a wide variety of mapping and analysis tasks.The Living Atlas of the World provides an easy way to explore the earth observation layers and many other beautiful and authoritative maps on hundreds of topics.Geonet is a good resource for learning more about earth observations layers and the Living Atlas of the World. Follow the Living Atlas on GeoNet.

  20. NSW Bionet Vegetation Map Data Collection

    • data.wu.ac.at
    • data.nsw.gov.au
    • +1more
    pdf, zip
    Updated Sep 11, 2018
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    Office of Environment and Heritage (OEH) (2018). NSW Bionet Vegetation Map Data Collection [Dataset]. https://data.wu.ac.at/schema/data_nsw_gov_au/ZDYxM2EzZTMtNjNjNi00ZmIxLWJmYTgtYjA2OGI1YjE2MTgy
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    zip, pdfAvailable download formats
    Dataset updated
    Sep 11, 2018
    Dataset provided by
    Office of Environment & Heritagehttp://www.environment.nsw.gov.au/
    License

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

    Area covered
    New South Wales, d94c85d3c1dfe53dba4b1d4faefa52f71c29018b
    Description

    The BioNet Vegetation Map Data Collection is a catalogue of all available NSW vegetation type maps including Standardised products from the State vegetation Type Mapping Program, and non-standardised historic and contemporary maps. Each map stored in the catalogue is assigned a unique VIS (Vegetation Information System) identification number. This map catalogue contains: 1. geographical information system (GIS) data; 2. metadata, including technical reports; 3. images of cartographic map products; and 4. web map services, where available. For more information see http://www.environment.nsw.gov.au/research/VISmap.htm. There are over 680 native vegetation type maps available.

    All vegetation maps in this collection are available as individual data records in the SEED environmental data portal. For GIS data downloads for these individual vegetation maps go to the individual record in SEED. A combined map footprint layer can be downloaded here as a resource from this metadata record to assist GIS users in selecting maps. This footprint layer will eventually be removed once all individual vegetation maps in SEED have individual web map services created allowing them to be viewed in the SEED map viewer.

    The data collection includes State Vegetation Type Maps produced by the State Vegetation Type Mapping Program. For more detail on the Program see http://www.environment.nsw.gov.au/vegetation/state-vegetation-type-map.htm . You can search for maps produced under this Program by entering the search term "SVTM" in to the SEED search window.

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Fabian Zuest; Cristina Castanha; Nicole Lau; Lara M. Kueppers (2021). Geospatial Data from the Alpine Treeline Warming Experiment (ATWE) on Niwot Ridge, Colorado, USA [Dataset]. http://doi.org/10.15485/1804896

Geospatial Data from the Alpine Treeline Warming Experiment (ATWE) on Niwot Ridge, Colorado, USA

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Dataset updated
Jul 7, 2021
Dataset provided by
ESS-DIVE
Authors
Fabian Zuest; Cristina Castanha; Nicole Lau; Lara M. Kueppers
Time period covered
Jan 1, 2008 - Jan 1, 2012
Area covered
Description

This is a collection of all GPS- and computer-generated geospatial data specific to the Alpine Treeline Warming Experiment (ATWE), located on Niwot Ridge, Colorado, USA. The experiment ran between 2008 and 2016, and consisted of three sites spread across an elevation gradient. Geospatial data for all three experimental sites and cone/seed collection locations are included in this package. ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Geospatial files include cone collection, experimental site, seed trap, and other GPS location/terrain data. File types include ESRI shapefiles, ESRI grid files or Arc/Info binary grids, TIFFs (.tif), and keyhole markup language (.kml) files. Trimble-imported data include plain text files (.txt), Trimble COR (CorelDRAW) files, and Trimble SSF (Standard Storage Format) files. Microsoft Excel (.xlsx) and comma-separated values (.csv) files corresponding to the attribute tables of many files within this package are also included. A complete list of files can be found in this document in the “Data File Organization” section in the included Data User's Guide. Maps are also included in this data package for reference and use. These maps are separated into two categories, 2021 maps and legacy maps, which were made in 2010. Each 2021 map has one copy in portable network graphics (.png) format, and the other in .pdf format. All legacy maps are in .pdf format. .png image files can be opened with any compatible programs, such as Preview (Mac OS) and Photos (Windows). All GIS files were imported into geopackages (.gpkg) using QGIS, and double-checked for compatibility and data/attribute integrity using ESRI ArcGIS Pro. Note that files packaged within geopackages will open in ArcGIS Pro with “main.” preceding each file name, and an extra column named “geom” defining geometry type in the attribute table. The contents of each geospatial file remain intact, unless otherwise stated in “niwot_geospatial_data_list_07012021.pdf/.xlsx”. This list of files can be found as an .xlsx and a .pdf in this archive. As an open-source file format, files within gpkgs (TIFF, shapefiles, ESRI grid or “Arc/Info Binary”) can be read using both QGIS and ArcGIS Pro, and any other geospatial softwares. Text and .csv files can be read using TextEdit/Notepad/any simple text-editing software; .csv’s can also be opened using Microsoft Excel and R. .kml files can be opened using Google Maps or Google Earth, and Trimble files are most compatible with Trimble’s GPS Pathfinder Office software. .xlsx files can be opened using Microsoft Excel. PDFs can be opened using Adobe Acrobat Reader, and any other compatible programs. A selection of original shapefiles within this archive were generated using ArcMap with associated FGDC-standardized metadata (xml file format). We are including these original files because they contain metadata only accessible using ESRI programs at this time, and so that the relationship between shapefiles and xml files is maintained. Individual xml files can be opened (without a GIS-specific program) using TextEdit or Notepad. Since ESRI’s compatibility with FGDC metadata has changed since the generation of these files, many shapefiles will require upgrading to be compatible with ESRI’s latest versions of geospatial software. These details are also noted in the “niwot_geospatial_data_list_07012021” file.

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