20 datasets found
  1. n

    Introduction to Survey 123

    • nccip.org
    • code-deegsnccu.hub.arcgis.com
    • +1more
    Updated May 24, 2022
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    North Carolina Central University (2022). Introduction to Survey 123 [Dataset]. https://www.nccip.org/datasets/introduction-to-survey-123
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    Dataset updated
    May 24, 2022
    Dataset authored and provided by
    North Carolina Central University
    Description

    Survey 123 is a simple way to collect data from people. Surveys allow us to ask questions, get answers, and make better decisions. You can create surveys with traditional survey questions, but a unique feature of Survey123 is that you can also ask questions where people can respond about specific places, such as where they have made an observation or places they value in your community. This location information can then be automatically included in maps that you can share with your community or the world through the web!Questions that are formulated in Survey 123 can come in various forms. Such as, single text, single choice, multiple choice questions, or numerical questions.

  2. a

    03.9 Survey123 for ArcGIS: Collect Field Data with Smart Forms

    • training-iowadot.opendata.arcgis.com
    • hub.arcgis.com
    Updated Feb 18, 2017
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    Iowa Department of Transportation (2017). 03.9 Survey123 for ArcGIS: Collect Field Data with Smart Forms [Dataset]. https://training-iowadot.opendata.arcgis.com/datasets/03-9-survey123-for-arcgis-collect-field-data-with-smart-forms
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    Dataset updated
    Feb 18, 2017
    Dataset authored and provided by
    Iowa Department of Transportation
    License

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

    Description

    Survey123 for ArcGIS is a simple and intuitive form-centric field data gathering solution. This seminar teaches you about Survey123. The presenters demonstrate how to create both simple and more sophisticated surveys, collect data over the web and in the field, analyze and view the survey results with Survey123's reporting capabilities, and how survey data is integrated with the ArcGIS platform.This seminar was developed to support the following:Survey123 for ArcGIS

  3. a

    03.1 Survey123 for ArcGIS: Ask Questions, Get the Facts, Make Decisions

    • training-iowadot.opendata.arcgis.com
    • hub.arcgis.com
    Updated Feb 18, 2017
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    Iowa Department of Transportation (2017). 03.1 Survey123 for ArcGIS: Ask Questions, Get the Facts, Make Decisions [Dataset]. https://training-iowadot.opendata.arcgis.com/datasets/03-1-survey123-for-arcgis-ask-questions-get-the-facts-make-decisions
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    Dataset updated
    Feb 18, 2017
    Dataset authored and provided by
    Iowa Department of Transportation
    License

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

    Description

    In this seminar, you will learn how to create, share, and analyze smart form-based surveys using a lightweight app called Survey123 for ArcGIS. You will discover a three-step approach to deploying surveys that simplify the data collection experience, facilitate easy data visualization and analysis, and support informed decision making.This seminar was developed to support the following:Survey123 for ArcGIS

  4. Georeferenced and cropped "Half Inch" (1:126,720) maps of Burma (colonial...

    • zenodo.org
    bin, jpeg, zip
    Updated Nov 24, 2024
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    Horst Held; Horst Held (2024). Georeferenced and cropped "Half Inch" (1:126,720) maps of Burma (colonial period) [Dataset]. http://doi.org/10.5281/zenodo.13346102
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    jpeg, bin, zipAvailable download formats
    Dataset updated
    Nov 24, 2024
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Horst Held; Horst Held
    License

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

    Description

    Georeferenced (to WGS1984) and cropped set of about 555 historic maps of Burma at a scale of 1 inch per two miles (1:126,720) covering most of the country. Those topographic maps, originally produced and published by the Great Trigonometrical Survey of India between 1878 and 1949, have been scanned and shared with the public as "Old Survey Of India Maps” Community under a CC BY 4.0 International Licence.

    Each of the map sheet scans was georeferenced using the Latitude-Longitude corner coordinates in Everest 1830 projection. Those map sheets were cropped, keeping only the map area - to allow a seamless mosaic without the mapframe overlapping adjacent map sheets when several map sheets are put together in a GIS. Those cropped map sheets were projected from Everest 1830 to WGS1984 (EPSG:4326) - standard GPS - projection to make them easier to use and combine with other GIS data.

    Many grid cells in this dataset are covered by 2 versions of map sheets - those with hill shade and only lat-lon grid and those without hill shade and featuring a LCC map grid.

    Those map sheets can be loaded directly in any GIS such as QGIS or ESRI ArcGIS.

    • The mm_HI_JBv2024_epsg4326 folder contains the cropped end georeferenced map sheets in jpg-format as well as accompagning georeference and metadata incl.
      • The mm_HI_JBv2024_epsg4326_kmlLinks contains a KML file for each map sheet facilitating their easy use in Google Earth byt linking them the georeferenced map sheet file located in the mm_HI_JBv2024_epsg4326 folder.
      • The mm_historicHI_EPSG4326.gdb contains three ESRI mosaic datasets to easily load all mapsheets, only mapheets with hillshading and lat-lon grid and only "regular" mapsheets without hillshading and LCC grid into ArcGIS
    • The mm_HI_JBv2024_scanMaps folder contains the uncropped original map scans (renamed though) in jpg-format.
    • The mm_historicTopoHI_JBv2024 is a masterlist cataloguing all map sheets for easier use and matching them with the original source files as shared via the "Old Survey Of India Maps” Community (e.g. to identify new mapsheets should new maps be released)

    All georeferenced map scans are based on maps shared as part of the "Old Survey Of India Maps” via Zenodo. Links to each file can be found in the above mentined excel file and most can be also accessed through the zenodo repository below.

    The file naming convention is to first give the number of the 4 degree x 4 degree block followed by the letter (A to P) of the sixteen 1 degree x 1 degree blocks in each 4 degree block eg. 38 D, and this is followed by the cardinal direction letters (NE, NW, SE, SW) to indicate the 30x30 minutes sized map position in the 1 degree block.

    This Number - Letter - Cardinal direction letter designation is followed by the year of the edition, followed by the map series type either HI-hs (hillshaded) or HI-reg (regular), followed by the map sheet title/name.

    The original files as shared as part of the "Old Survey Of India Maps” have been renamed to further standardize the file naming, sometimes correcting them and to make them unique in the case several editions of the same map sheet were available.

    Lineage: This version (1.01, Upload 2024-08-20) has some file attributes fixed.

  5. Georeferenced and cropped "63k Maps of Burma"

    • zenodo.org
    bin, jpeg, zip
    Updated Nov 24, 2024
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    Horst Held; Horst Held (2024). Georeferenced and cropped "63k Maps of Burma" [Dataset]. http://doi.org/10.5281/zenodo.11367062
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    bin, zip, jpegAvailable download formats
    Dataset updated
    Nov 24, 2024
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Horst Held; Horst Held
    License

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

    Description

    Georeferenced (to WGS1984) and cropped set of about 820 historic maps of Burma at a scale of 1 inch per mile (63,360) covering about 75% of the country. Those topographic maps, originally produced and published by the Great Trigonometrical Survey of India between 1899 and 1946, have been scanned and shared with the public as part of the "Old Survey Of India Maps” Community under a CC BY 4.0 International Licence. Many of these maps are reprints of earlier maps produced before the war. Most mapsheets are early editions (edition 1 or edition 2).

    Each of the 820 map sheet scans was georeferenced using the Latitude-Longitude corner coordinates in Everest 1830 projection. Those map sheets were cropped, keeping only the map area - to allow a seamless mosaic without the mapframe overlapping adjacent map sheets when several map sheets are put together in a GIS. Those cropped map sheets were projected from Everest 1830 to WGS1984 (EPSG4326) - standard GPS - projection to make them easier to use and combine with other GIS data.

    Those map sheets can be loaded directly in any GIS such as QGIS or ESRI ArcGIS as well as Google Earth.

    • The mm_OI_JBv2024 folder contains the cropped end georeferenced map sheets in jpg-format as well as accompagning georeference and metadata incl.
      • The mm_OI_JBv2024_kmlLinks contains kml files to easily load the mapsheets into Google Earth
      • The mm_historicOI_EPSG4326.gdb contains an ESRI mosaic dataset to easily load all mapsheets into ArcGIS
    • The mm_OI_JBv2024_scanMaps folder contains the uncropped original map scans (renamed though) in jpg-format.
    • The mm_topoOI_JBv7_masterlist.xlsx is a masterlist cataloguing all map sheets for easier use and matching them with the original source files as shared as part of the "Old Survey Of India Maps" (e.g. to identify new mapsheets should new maps be released)
    • The indexMaps folder contains small scale index maps to locate the map sheets using their map sheet Grid-Letter-nomenclature

    All georeferenced map scans are based on maps shared by John Brown via Zenodo

    The file naming convention is to first give the number of the 4 degree x 4 degree block followed by the letter (A to P) of the sixteen 1 degree x 1 degree blocks in each 4 degree block eg. 38 D, and this is followed by a number from 1 to 16 to indicate the number of the map in the 1 degree block.

    This Number Letter Number designation is followed by the map series type either OI (contains a LCC grid) or OILatLon (only has a Lat-Lon grid), followed by the edition and year of the edition, followed by the date of publication/print. If the information is not available an "X" (for edition) or "0000" (for an unknown year) is used. A best-guess approach was used if the edition and print year and version information was ambiguous.

    The files as shared via the "Old Survey Of India Maps" have been renamed to standardize the file naming, sometimes correcting them and to make them unique in the case several editions of the same map sheet were available.

    A topographical index produced by the Survey of India is provided to assist the viewer in selecting a particular map of interest.

  6. l

    Children with Easy Access to a Safe Place to Play

    • geohub.lacity.org
    • ph-lacounty.hub.arcgis.com
    • +2more
    Updated Dec 19, 2023
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    County of Los Angeles (2023). Children with Easy Access to a Safe Place to Play [Dataset]. https://geohub.lacity.org/datasets/lacounty::children-with-easy-access-to-a-safe-place-to-play
    Explore at:
    Dataset updated
    Dec 19, 2023
    Dataset authored and provided by
    County of Los Angeles
    Area covered
    Description

    Data for cities, communities, and City of Los Angeles Council Districts were generated using a small area estimation method which combined the survey data with population benchmark data (2022 population estimates for Los Angeles County) and neighborhood characteristics data (e.g., U.S. Census Bureau, 2017-2021 American Community Survey 5-Year Estimates). This indicator is based on caregiver report.Parks, playgrounds, and other safe places are vital community assets that provide spaces where children can engage in physical activity and build critical cognitive, social, and emotional skills through peer interactions and play. They also serve as spaces where all members of a community can gather and socialize, thereby promoting community cohesion.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.

  7. a

    begin photos

    • hub.arcgis.com
    • gis-fws.opendata.arcgis.com
    Updated Apr 9, 2024
    + more versions
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    U.S. Fish & Wildlife Service (2024). begin photos [Dataset]. https://hub.arcgis.com/maps/fws::begin-photos-1
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    Dataset updated
    Apr 9, 2024
    Dataset authored and provided by
    U.S. Fish & Wildlife Service
    Area covered
    Description

    The Golden-winged Warbler (GWWA) is a rapidly declining species of migratory songbird that is currently being considered for listing under the US Endangered Species Act. The golden-winged warbler relies on early successional habitat (old fields and young forest) which must be created and maintained to support breeding birds. In an effort to increase populations throughout the breeding range, creation and maintenance of habitat is essential. The Golden-winged Warbler Working Group is initiating a Habitat Management Challenge throughout the breeding range to encourage a variety of partners (state and federal agencies as well as non-profit organizations and private citizens) to contribute to this effort.This data hub will allow for easy access to upload new project surveys, update existing surveys, view the management StoryMap, and view current management progress!Contact - Lesley Bulluck - lpbulluck@vcu.edu and Randy Dettmers - randy_dettmers@fws.gov

  8. d

    Texas Well Header Data.

    • datadiscoverystudio.org
    zip
    Updated Apr 10, 2015
    + more versions
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    (2015). Texas Well Header Data. [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/98bd494f0d444aa3b75068e5f687b727/html
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    zipAvailable download formats
    Dataset updated
    Apr 10, 2015
    Description

    description: This dataset provides simple features that report basic information describing a simple or complex borehole. Published by the Arizona Geological Survey as a web feature service, a web map service, and as an ESRI service for the National Geothermal Data System. Wells with multiple well bores may have separate records (rows) for each well bore, each with a distinct HeaderURI (record identifier); in this case, the ParentWellURI should provide the HeaderURI representing the well. If multiple data items are associated with a single well header, the multiple values are concatenated in a single text field using '|' as a delimiter. Borehole type is factored into 4 facets-- commodity of interest, well function, well status, and production result.; abstract: This dataset provides simple features that report basic information describing a simple or complex borehole. Published by the Arizona Geological Survey as a web feature service, a web map service, and as an ESRI service for the National Geothermal Data System. Wells with multiple well bores may have separate records (rows) for each well bore, each with a distinct HeaderURI (record identifier); in this case, the ParentWellURI should provide the HeaderURI representing the well. If multiple data items are associated with a single well header, the multiple values are concatenated in a single text field using '|' as a delimiter. Borehole type is factored into 4 facets-- commodity of interest, well function, well status, and production result.

  9. GWWA survey 2023

    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • gis-fws.opendata.arcgis.com
    Updated Jan 18, 2024
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    U.S. Fish & Wildlife Service (2024). GWWA survey 2023 [Dataset]. https://arc-gis-hub-home-arcgishub.hub.arcgis.com/maps/fws::gwwa-survey-2023-1/explore
    Explore at:
    Dataset updated
    Jan 18, 2024
    Dataset provided by
    U.S. Fish and Wildlife Servicehttp://www.fws.gov/
    Authors
    U.S. Fish & Wildlife Service
    Area covered
    Earth
    Description

    The Golden-winged Warbler (GWWA) is a rapidly declining species of migratory songbird that is currently being considered for listing under the US Endangered Species Act. The golden-winged warbler relies on early successional habitat (old fields and young forest) which must be created and maintained to support breeding birds. In an effort to increase populations throughout the breeding range, creation and maintenance of habitat is essential. The Golden-winged Warbler Working Group is initiating a Habitat Management Challenge throughout the breeding range to encourage a variety of partners (state and federal agencies as well as non-profit organizations and private citizens) to contribute to this effort.This data hub will allow for easy access to upload new project surveys, update existing surveys, view the management StoryMap, and view current management progress!

  10. a

    USGS NHD and WBD from The National Map-Simple View

    • hub.arcgis.com
    • catalog-usgs.opendata.arcgis.com
    • +1more
    Updated Jul 19, 2013
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    U.S. Geological Survey (2013). USGS NHD and WBD from The National Map-Simple View [Dataset]. https://hub.arcgis.com/maps/7e1b29f7973e42edbf291f7d8f2afe43
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    Dataset updated
    Jul 19, 2013
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    U.S. Geological Survey
    Area covered
    Description

    This is a simple map that uses map services of the National Hydrography Dataset (NHD) and Watershed Boundaries Dataset (WBD) from The National Map (TNM). Additional layers of the current US Topo and older USA Topo service from Esri are included, but turned off by default. This map is useful as a simple viewer to see the content of the NHD and WBD. In the Search tool pulldown, the “nhd - Flowline - Large Scale” and “nhd - Waterbody - Large Scale” choices search based on ReachCode. The “wbd - 8-digit HU (Subbasin)” and “wbd - 12-digit HU (Subwatershed)” choices search based on the HU code (HUC).

  11. a

    United States of America Soil Survey Geographic Database (SSURGO) - Erosion...

    • supply-chain-data-hub-nmcdc.hub.arcgis.com
    • chi-phi-nmcdc.opendata.arcgis.com
    Updated Jul 26, 2022
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    New Mexico Community Data Collaborative (2022). United States of America Soil Survey Geographic Database (SSURGO) - Erosion Class, 2021 [Dataset]. https://supply-chain-data-hub-nmcdc.hub.arcgis.com/datasets/united-states-of-america-soil-survey-geographic-database-ssurgo-erosion-class-2021-1
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    Dataset updated
    Jul 26, 2022
    Dataset authored and provided by
    New Mexico Community Data Collaborative
    Area covered
    United States
    Description

    Erosion, the loss of soil due to the effects of water and wind, can lead to serious degradation of lands and the loss of agricultural productivity.This layer classifies the amount of soil loss in the top soil layers in 5 classes:None: Area of soil deposition.Class 1: In this map unit,1 to 25 percent of the original topsoil has been lost to erosion. Class 2: In this map unit, 1 to 25 percent of the original topsoil has been lost to erosion.Class 3: In this map unit, 75 to 99 percent of the original topsoil has been lost to erosion.Class 4: In this map unit, all of the original topsoil has been lost to erosionDataset SummaryPhenomenon Mapped: Top soil loss due to erosionUnits: ClassesCell Size: 30 metersSource Type: DiscretePixel Type: Unsigned integerData Coordinate System: USA Contiguous Albers Equal Area Conic USGS version (contiguous US, Puerto Rico, US Virgin Islands), WGS 1984 Albers (Alaska), Hawaii Albers Equal Area Conic (Hawaii), Western Pacific Albers Equal Area Conic (Guam, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American Samoa)Mosaic Projection: Web Mercator Auxiliary SphereExtent: Contiguous United States, Alaska, Hawaii, Puerto Rico, Guam, US Virgin Islands, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American SamoaSource: Natural Resources Conservation ServicePublication Date: December 2021ArcGIS Server URL: https://landscape11.arcgis.com/arcgis/Data from the gNATSGO database was used to create the layer for the contiguous United States, Alaska, Puerto Rico, and the U.S. Virgin Islands. The remaining areas were created with the gSSURGO database (Hawaii, Guam, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American Samoa).This layer is derived from the 30m (contiguous U.S.) and 10m rasters (all other regions) produced by the Natural Resources Conservation Service (NRCS). The value for runoff is derived from the gSSURGO component table field Erosion Class (erocl). The value in this layer is the dominant condition found within the map unit.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 "erosion class" 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 "erosion class" 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.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.

  12. Eklutna Spawning Survey results

    • gis-fws.opendata.arcgis.com
    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    Updated Sep 29, 2023
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    U.S. Fish & Wildlife Service (2023). Eklutna Spawning Survey results [Dataset]. https://gis-fws.opendata.arcgis.com/maps/b3e04b428d194538a8749a34ce685d92
    Explore at:
    Dataset updated
    Sep 29, 2023
    Dataset provided by
    U.S. Fish and Wildlife Servicehttp://www.fws.gov/
    Authors
    U.S. Fish & Wildlife Service
    Area covered
    Earth
    Description

    The Eklutna River is an anadromous river in South Central Alaska, whose salmon runs have provided important subsistence fishing for Native Alaskan's for millennia. US Fish and Wildlife Service and our partners at the Native Village of Eklutna are hoping to better document the locations of returning fish and the behaviors they are exhibiting during fall river surveys. Spawning behaviors, fish condition, and species are recorded along with a time and georeferenced point on the map. This survey will also help manage photos and data in a tidy structure. Making this query-able through ArcGIS Online will allow for easy data management and up to date sharing between USFWS and NVE. This template includes all XLSForm features supported in ArcGIS Survey123 and was created in Survey123 Connect.

  13. a

    United States of America Soil Survey Geographic Database (SSURGO) -...

    • chi-phi-nmcdc.opendata.arcgis.com
    Updated May 18, 2022
    + more versions
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    New Mexico Community Data Collaborative (2022). United States of America Soil Survey Geographic Database (SSURGO) - Erodibility Factor [Dataset]. https://chi-phi-nmcdc.opendata.arcgis.com/datasets/united-states-of-america-soil-survey-geographic-database-ssurgo-erodibility-factor
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    Dataset updated
    May 18, 2022
    Dataset authored and provided by
    New Mexico Community Data Collaborative
    Area covered
    Description

    Soil erodibility factor, also known as K factor, is one of the 5 inputs to the Universal Soil Loss Equation. Soil erodibility factor quantifies the susceptibility of soil particles to detachment and movement by water. For more information on how soil erodibilty factor is calculated see the National Soil Survey Handbook.The Universal Soil Loss Equation is a mathematical model commonly used to estimate soil erosion rates. Originally designed for the management and conservation of farmland soils, the USLE is now used for a variety of other projects such as managing non-point pollution and sediment load in streams. In the United States, the equation is frequently used by federal agencies. For example federal regulations require that the Department of Agriculture identify highly erodible land based on the Universal Soil Loss Equation and its derivative models.Dataset SummaryPhenomenon Mapped: Erodibility factorUnits: NoneCell Size: 30 metersSource Type: DiscretePixel Type: Unsigned integerData Coordinate System: USA Contiguous Albers Equal Area Conic USGS version (contiguous US, Puerto Rico, US Virgin Islands), WGS 1984 Albers (Alaska), Hawaii Albers Equal Area Conic (Hawaii), Western Pacific Albers Equal Area Conic (Guam, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American Samoa)Mosaic Projection: Web Mercator Auxiliary SphereExtent: Contiguous United States, Alaska, Hawaii, Puerto Rico, Guam, US Virgin Islands, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American SamoaSource: Natural Resources Conservation ServicePublication Date: December 2021ArcGIS Server URL: https://landscape11.arcgis.com/arcgis/Data from the gNATSGO database was used to create the layer for the contiguous United States, Alaska, Puerto Rico, and the U.S. Virgin Islands. The remaining areas were created with the gSSURGO database (Hawaii, Guam, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American Samoa).This layer is derived from the 30m (contiguous U.S.) and 10m rasters (all other regions) produced by the Natural Resources Conservation Service (NRCS). This field was calculated by selecting the least transmissive horizon of the dominant component for each mapunit. The values are in units of Micrometers per second (μm/s).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 "erodibility factor" 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 "erodibility factor" 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.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.

  14. a

    United States of America Soile Survey Geographic Database (SSURGO) -...

    • chi-phi-nmcdc.opendata.arcgis.com
    Updated May 19, 2022
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    New Mexico Community Data Collaborative (2022). United States of America Soile Survey Geographic Database (SSURGO) - Rangeland Production, 2021 [Dataset]. https://chi-phi-nmcdc.opendata.arcgis.com/maps/b4a7b7a4f7844bba93019732afc9c999
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    Dataset updated
    May 19, 2022
    Dataset authored and provided by
    New Mexico Community Data Collaborative
    Area covered
    Description

    Rangelands are regions dominated by grasses and shrubs including savannahs, grasslands, and deserts. Rangelands provide valuable forage for gazing and browsing animals. This layer quantifies annual range production in pounds/acre/year.A raw pixel value in this service represents the number of pounds of range forage expected per acre per year.Dataset SummaryPhenomenon Mapped: Range Forage ProductionUnits: pounds/acre/yearCell Size: 30 meterSource Type: DiscretePixel Type: Unsigned integerData Coordinate System: USA Contiguous Albers Equal Area Conic USGS version (contiguous US), WGS 1984 Albers (Alaska), Hawaii Albers Equal Area Conic (Hawaii)Mosaic Projection: Web Mercator Auxiliary SphereExtent: The western portion of the continental U.S., Florida, a small part of Alaska, and the Island of HawaiiSource: Natural Resources Conservation ServicePublication Date: December 2021ArcGIS Server URL: https://landscape11.arcgis.com/arcgis/Data from the gNATSGO database was used to create the layer for the contiguous United States, Alaska, Puerto Rico, and the U.S. Virgin Islands. The remaining areas were created with the gSSURGO database (Hawaii, Guam, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American Samoa).This layer is derived from the 30m (contiguous U.S.) and 10m rasters (all other regions) produced by the Natural Resources Conservation Service (NRCS). The value for range production is derived from the gSSURGO component table field Range Production - Representative Value (rsprod_r). The value in this layer is the average value for all components of each map unit weighted by component percent (comppct_r).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 "range production" 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 "range production" 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.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.

  15. a

    United States of America Soil Survey Geographic Database (SSURGO) - Farmland...

    • chi-phi-nmcdc.opendata.arcgis.com
    Updated May 19, 2022
    + more versions
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    New Mexico Community Data Collaborative (2022). United States of America Soil Survey Geographic Database (SSURGO) - Farmland Class [Dataset]. https://chi-phi-nmcdc.opendata.arcgis.com/datasets/united-states-of-america-soil-survey-geographic-database-ssurgo-farmland-class
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    Dataset updated
    May 19, 2022
    Dataset authored and provided by
    New Mexico Community Data Collaborative
    Area covered
    United States,
    Description

    The Farmland Protection Policy Act, part of the 1981 Farm Bill, is intended to limit federal activities that contribute to the unnecessary conversion of farmland to other uses. The law applies to construction projects funded by the federal government such as highways, airports, and dams, and to the management of federal lands. As part of the implementation of this law, the Natural Resources Conservation Service identifies high quality agricultural soils as prime farmland, unique farmland, and land of statewide or local importance. Each category may contain one or more limitations such as Prime Farmland if Irrigated. For a complete list of categories and definitions, see the National Soil Survey Handbook.All areas are prime farmlandFarmland of local importanceFarmland of statewide importanceFarmland of statewide importance, if drainedFarmland of statewide importance, if drained and either protected from flooding or not frequently flooded during the growing seasonFarmland of statewide importance, if irrigatedFarmland of statewide importance, if irrigated and drainedFarmland of statewide importance, if irrigated and either protected from flooding or not frequently flooded during the growing seasonFarmland of statewide importance, if irrigated and reclaimed of excess salts and sodiumFarmland of statewide importance, if irrigated and the product of I (soil erodibility) x C (climate factor) does not exceed 60Farmland of statewide importance, if protected from flooding or not frequently flooded during the growing seasonFarmland of statewide importance, if warm enoughFarmland of statewide importance, if warm enough, and either drained or either protected from flooding or not frequently flooded during the growing seasonFarmland of unique importanceNot prime farmlandPrime farmland if drainedPrime farmland if drained and either protected from flooding or not frequently flooded during the growing seasonPrime farmland if irrigatedPrime farmland if irrigated and drainedPrime farmland if irrigated and either protected from flooding or not frequently flooded during the growing seasonPrime farmland if irrigated and reclaimed of excess salts and sodiumPrime farmland if irrigated and the product of I (soil erodibility) x C (climate factor) does not exceed 60Prime farmland if protected from flooding or not frequently flooded during the growing seasonPrime farmland if subsoiled, completely removing the root inhibiting soil layerDataset SummaryPhenomenon Mapped: FarmlandUnits: ClassesCell Size: 30 metersSource Type: DiscretePixel Type: Unsigned integerData Coordinate System: USA Contiguous Albers Equal Area Conic USGS version (contiguous US, Puerto Rico, US Virgin Islands), WGS 1984 Albers (Alaska), Hawaii Albers Equal Area Conic (Hawaii), Western Pacific Albers Equal Area Conic (Guam, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American Samoa)Mosaic Projection: Web Mercator Auxiliary SphereExtent: Contiguous United States, Alaska, Hawaii, Puerto Rico, Guam, US Virgin Islands, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American SamoaSource: Natural Resources Conservation ServicePublication Date: December 2021ArcGIS Server URL: https://landscape11.arcgis.com/arcgis/Data from the gNATSGO database was used to create the layer for the contiguous United States, Alaska, Puerto Rico, and the U.S. Virgin Islands. The remaining areas were created with the gSSURGO database (Hawaii, Guam, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American Samoa).This layer is derived from the 30m (contiguous U.S.) and 10m rasters (all other regions) produced by the Natural Resources Conservation Service (NRCS). The value for farmland class is derived from the gSSURGO map unit table field Farm Class (farmlndcl).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 "farmland" 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 "farmland" 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.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.

  16. EklutnaSpawningSurvey

    • gis-fws.opendata.arcgis.com
    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    Updated Sep 30, 2023
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    U.S. Fish & Wildlife Service (2023). EklutnaSpawningSurvey [Dataset]. https://gis-fws.opendata.arcgis.com/datasets/eklutnaspawningsurvey
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    Dataset updated
    Sep 30, 2023
    Dataset provided by
    U.S. Fish and Wildlife Servicehttp://www.fws.gov/
    Authors
    U.S. Fish & Wildlife Service
    Area covered
    Earth
    Description

    The Eklutna River is an anadromous river in South Central Alaska, whose salmon runs have provided important subsistence fishing for Native Alaskan's for millennia. US Fish and Wildlife Service and our partners at the Native Village of Eklutna are hoping to better document the locations of returning fish and the behaviors they are exhibiting during fall river surveys. Spawning behaviors, fish condition, and species are recorded along with a time and georeferenced point on the map. This survey will also help manage photos and data in a tidy structure. Making this query-able through ArcGIS Online will allow for easy data management and up to date sharing between USFWS and NVE. This template includes all XLSForm features supported in ArcGIS Survey123 and was created in Survey123 Connect.

  17. GWWA Habitat Management Challenge (project information data)

    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • hub.arcgis.com
    • +1more
    Updated Jan 18, 2024
    + more versions
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    U.S. Fish & Wildlife Service (2024). GWWA Habitat Management Challenge (project information data) [Dataset]. https://arc-gis-hub-home-arcgishub.hub.arcgis.com/maps/fws::gwwa-habitat-management-challenge-project-information-data
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    Dataset updated
    Jan 18, 2024
    Dataset provided by
    U.S. Fish and Wildlife Servicehttp://www.fws.gov/
    Authors
    U.S. Fish & Wildlife Service
    Area covered
    Earth
    Description

    The Golden-winged Warbler (GWWA) is a rapidly declining species of migratory songbird that is currently being considered for listing under the US Endangered Species Act. The golden-winged warbler relies on early successional habitat (old fields and young forest) which must be created and maintained to support breeding birds. In an effort to increase populations throughout the breeding range, creation and maintenance of habitat is essential. The Golden-winged Warbler Working Group is initiating a Habitat Management Challenge throughout the breeding range to encourage a variety of partners (state and federal agencies as well as non-profit organizations and private citizens) to contribute to this effort.This data hub will allow for easy access to upload new project surveys, update existing surveys, view the management StoryMap, and view current management progress!

  18. a

    NLS Historic Maps API: Historical Maps of Great Britain

    • hub.arcgis.com
    • data.catchmentbasedapproach.org
    • +1more
    Updated Sep 19, 2017
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    klokantech (2017). NLS Historic Maps API: Historical Maps of Great Britain [Dataset]. https://hub.arcgis.com/maps/131be1ff1498429eacf806f939807f20
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    Dataset updated
    Sep 19, 2017
    Dataset authored and provided by
    klokantech
    License

    Attribution 3.0 (CC BY 3.0)https://creativecommons.org/licenses/by/3.0/
    License information was derived automatically

    Area covered
    Description

    National Library of Scotland Historic Maps APIHistorical Maps of Great Britain for use in mashups and ArcGIS Onlinehttps://nls.tileserver.com/https://maps.nls.uk/projects/api/index.htmlThis seamless historic map can be:embedded in your own websiteused for research purposesused as a backdrop for your own markers or geographic dataused to create derivative work (such as OpenStreetMap) from it.The mapping is based on out-of-copyright Ordnance Survey maps, dating from the 1920s to the 1940s.The map can be directly opened in a web browser by opening the Internet address: https://nls.tileserver.com/The map is ready for natural zooming and panning with finger pinching and dragging.How to embed the historic map in your websiteThe easiest way of embedding the historical map in your website is to copy < paste this HTML code into your website page. Simple embedding (try: hello.html):You can automatically position the historic map to open at a particular place or postal address by appending the name as a "q" parameter - for example: ?q=edinburgh Embedding with a zoom to a place (try: placename.html):You can automatically position the historic map to open at particular latitude and longitude coordinates: ?lat=51.5&lng=0&zoom=11. There are many ways of obtaining geographic coordinates. Embedding with a zoom to coordinates (try: coordinates.html):The map can also automatically detect the geographic location of the visitor to display the place where you are right now, with ?q=auto Embedding with a zoom to coordinates (try: auto.html):How to use the map in a mashupThe historic map can be used as a background map for your own data. You can place markers on top of it, or implement any functionality you want. We have prepared a simple to use JavaScript API to access to map from the popular APIs like Google Maps API, Microsoft Bing SDK or open-source OpenLayers or KHTML. To use our map in your mashups based on these tools you should include our API in your webpage: ... ...

  19. a

    United States of America Soile Survey Geographic Database (SSURGO) - Soil...

    • chi-phi-nmcdc.opendata.arcgis.com
    Updated May 19, 2022
    + more versions
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    New Mexico Community Data Collaborative (2022). United States of America Soile Survey Geographic Database (SSURGO) - Soil Hydrologic Group, 2021 [Dataset]. https://chi-phi-nmcdc.opendata.arcgis.com/maps/82e3a76807c04c08bdbf6bf321fa8c18
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    Dataset updated
    May 19, 2022
    Dataset authored and provided by
    New Mexico Community Data Collaborative
    Area covered
    Description

    When rain falls over land, a portion of it runs off into stream channels and storm water systems while the remainder infiltrates into the soil or returns to the atmosphere directly through evaporation.Physical properties of soil affect the rate that water is absorbed and the amount of runoff produced by a storm. Hydrologic soil group provides an index of the rate that water infiltrates a soil and is an input to rainfall-runoff models that are used to predict potential stream flow.For more information on using hydrologic soil group in hydrologic modeling see the publication Urban Hydrology for Small Watersheds (Natural Resources Conservation Service, United States Department of Agriculture, Technical Release–55).Dataset SummaryPhenomenon Mapped: Soil hydrologic groupUnits: ClassesCell Size: 30 metersSource Type: DiscretePixel Type: Unsigned integerData Coordinate System: USA Contiguous Albers Equal Area Conic USGS version (contiguous US, Puerto Rico, US Virgin Islands), WGS 1984 Albers (Alaska), Hawaii Albers Equal Area Conic (Hawaii), Western Pacific Albers Equal Area Conic (Guam, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American Samoa)Mosaic Projection: Web Mercator Auxiliary SphereExtent: Contiguous United States, Alaska, Hawaii, Puerto Rico, Guam, US Virgin Islands, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American SamoaSource: Natural Resources Conservation ServicePublication Date: December 2021ArcGIS Server URL: https://landscape11.arcgis.com/arcgis/Data from the gNATSGO database was used to create the layer for the contiguous United States, Alaska, Puerto Rico, and the U.S. Virgin Islands. The remaining areas were created with the gSSURGO database (Hawaii, Guam, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American Samoa).This layer is derived from the 30m (contiguous U.S.) and 10m rasters (all other regions) produced by the Natural Resources Conservation Service (NRCS). The value for hydrologic group is derived from the gSSURGO map unit aggregated attribute table field Hydrologic Group - Dominant Conditions (hydgrpdcd).The seven classes of hydrologic soil group followed by definitions:Group A - Group A soils consist of deep, well drained sands or gravelly sands with high infiltration and low runoff rates.Group B - Group B soils consist of deep well drained soils with a moderately fine to moderately coarse texture and a moderate rate of infiltration and runoff.Group C - Group C consists of soils with a layer that impedes the downward movement of water or fine textured soils and a slow rate of infiltration.Group D - Group D consists of soils with a very slow infiltration rate and high runoff potential. This group is composed of clays that have a high shrink-swell potential, soils with a high water table, soils that have a clay pan or clay layer at or near the surface, and soils that are shallow over nearly impervious material.Group A/D - Group A/D soils naturally have a very slow infiltration rate due to a high water table but will have high infiltration and low runoff rates if drained.Group B/D - Group B/D soils naturally have a very slow infiltration rate due to a high water table but will have a moderate rate of infiltration and runoff if drained.Group C/D - Group C/D soils naturally have a very slow infiltration rate due to a high water table but will have a slow rate of infiltration if drained.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 "soil hydrologic group" 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 "soil hydrologic group" 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.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.

  20. a

    Children with Good or Excellent Community Access to Fresh Fruits and...

    • data-lahub.opendata.arcgis.com
    • geohub.lacity.org
    • +2more
    Updated Dec 19, 2023
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    County of Los Angeles (2023). Children with Good or Excellent Community Access to Fresh Fruits and Vegetables [Dataset]. https://data-lahub.opendata.arcgis.com/maps/lacounty::children-with-good-or-excellent-community-access-to-fresh-fruits-and-vegetables
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    Dataset updated
    Dec 19, 2023
    Dataset authored and provided by
    County of Los Angeles
    Area covered
    Description

    Data for cities, communities, and City of Los Angeles Council Districts were generated using a small area estimation method which combined the survey data with population benchmark data (2022 population estimates for Los Angeles County) and neighborhood characteristics data (e.g., U.S. Census Bureau, 2017-2021 American Community Survey 5-Year Estimates).Easy community access to fresh fruits and vegetables is fundamental to promoting a healthy food environment.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.

  21. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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North Carolina Central University (2022). Introduction to Survey 123 [Dataset]. https://www.nccip.org/datasets/introduction-to-survey-123

Introduction to Survey 123

Explore at:
Dataset updated
May 24, 2022
Dataset authored and provided by
North Carolina Central University
Description

Survey 123 is a simple way to collect data from people. Surveys allow us to ask questions, get answers, and make better decisions. You can create surveys with traditional survey questions, but a unique feature of Survey123 is that you can also ask questions where people can respond about specific places, such as where they have made an observation or places they value in your community. This location information can then be automatically included in maps that you can share with your community or the world through the web!Questions that are formulated in Survey 123 can come in various forms. Such as, single text, single choice, multiple choice questions, or numerical questions.

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