67 datasets found
  1. Duplicate Value Calculator_ArcMap ESRI

    • kaggle.com
    zip
    Updated Sep 21, 2022
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    Raj Kumar Pandey (2022). Duplicate Value Calculator_ArcMap ESRI [Dataset]. https://www.kaggle.com/datasets/rajkumarpandey02/duplicate-value-calculator-arcmap
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    zip(49216 bytes)Available download formats
    Dataset updated
    Sep 21, 2022
    Authors
    Raj Kumar Pandey
    License

    http://opendatacommons.org/licenses/dbcl/1.0/http://opendatacommons.org/licenses/dbcl/1.0/

    Description

    A custom Python Tool Box exclusively for ESRI ArcMap Application. This toolbox contains two tools: 1. Duplicate Value Calculator : - to search duplicate values in a specified Attribute Field of Table /FeautureClass and populate user defined text for such records in another specified Attribute Field of same Table/FeatureClass. If no Attribute Field is selected to populate text, a default Attribute Field will be added with Name as "DUPLICATE_{Name of Field for Search Duplicate values}".

    Further, User can imply SQL Expression to limit the records to be searched as per requirement.

    Caution : This Tool modifies the SCHEMA of selected Table/FeatureClass if no Attribute Field is selected to populate text for duplicate values. So preconsider to choose both Attribute Fields - One for Duplicate Search and other for Text against duplicate value if You are concerned about to add new field to Your Table/FeatureClass.

    1. Delete Rows : - to delete Rows from input Table/FeatureClass. Put an SQL Expression for records filter, otherwise all rows will be deleted.
  2. a

    National Hydrography Data Set

    • gis-foleyal.hub.arcgis.com
    Updated Feb 15, 2025
    + more versions
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    City of Foley, AL (2025). National Hydrography Data Set [Dataset]. https://gis-foleyal.hub.arcgis.com/maps/43212cf0ef1f438aa0848e83526c791d
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    Dataset updated
    Feb 15, 2025
    Dataset authored and provided by
    City of Foley, AL
    Area covered
    Description

    The National Hydrography Dataset Plus (NHDplus) maps the lakes, ponds, streams, rivers and other surface waters of the United States. Created by the US EPA Office of Water and the US Geological Survey, the NHDPlus provides mean annual and monthly flow estimates for rivers and streams. Additional attributes provide connections between features facilitating complicated analyses. For more information on the NHDPlus dataset see the NHDPlus v2 User Guide.Dataset SummaryPhenomenon Mapped: Surface waters and related features of the United States and associated territories not including Alaska.Coordinate System: Web Mercator Auxiliary Sphere Extent: The United States not including Alaska, Puerto Rico, Guam, US Virgin Islands, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American Samoa Visible Scale: Visible at all scales but layer draws best at scales larger than 1:1,000,000Resolution/Tolerance: 1 meter/2 meters Number of Features: 3,035,617 flowlines, 473,936 waterbodies, 16,658 sinksFeature Request Limit: 5,000Source: EPA and USGSPublication Date: March 13, 2019ArcGIS Server URL: https://services.arcgis.com/P3ePLMYs2RVChkJx/arcgis/rest/services/NHDPlusV21/FeatureServerPrior to publication, the NHDPlus network and non-network flowline feature classes were combined into a single flowline layer. Similarly, the NHDPlus Area and Waterbody feature classes were merged under a single schema.Attribute fields were added to the flowline and waterbody layers to simplify symbology and enhance the layer's pop-ups. Fields added include Pop-up Title, Pop-up Subtitle, On or Off Network (flowlines only), Esri Symbology (waterbodies only), and Feature Code Description. All other attributes are from the original NHDPlus dataset. No data values -9999 and -9998 were converted to Null values for many of the flowline fields.What can you do with this Feature Layer?Feature layers work throughout the ArcGIS system. Generally your work flow with feature layers will begin in ArcGIS Online or ArcGIS Pro. Below are just a few of the things you can do with a feature service in Online and Pro.ArcGIS OnlineAdd this layer to a map in the map viewer. The layer is limited to scales of approximately 1:1,000,000 or larger but a vector tile layer created from the same data can be used at smaller scales to produce a webmap that displays across the full range of scales. The layer or a map containing it can be used in an application. Change the layer’s transparency and set its visibility rangeOpen the layer’s attribute table and make selections. Selections made in the map or table are reflected in the other. Center on selection allows you to zoom to features selected in the map or table and show selected records allows you to view the selected records in the table.Apply filters. For example you can set a filter to show larger streams and rivers using the mean annual flow attribute or the stream order attribute. Change the layer’s style and symbologyAdd labels and set their propertiesCustomize the pop-upUse as an input to the ArcGIS Online analysis tools. This layer works well as a reference layer with the trace downstream and watershed tools. The buffer tool can be used to draw protective boundaries around streams and the extract data tool can be used to create copies of portions of the data.ArcGIS ProAdd this layer to a 2d or 3d map. Use as an input to geoprocessing. For example, copy features allows you to select then export portions of the data to a new feature class. Change the symbology and the attribute field used to symbolize the dataOpen table and make interactive selections with the mapModify the pop-upsApply Definition Queries to create sub-sets of the layerThis layer is part of the ArcGIS 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.

  3. a

    Southern California Critical Habitat

    • maps-cadoc.opendata.arcgis.com
    Updated Nov 19, 2019
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    ArcGIS Pro Tutorials (2019). Southern California Critical Habitat [Dataset]. https://maps-cadoc.opendata.arcgis.com/maps/arcgisdoc::southern-california-critical-habitat
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    Dataset updated
    Nov 19, 2019
    Dataset authored and provided by
    ArcGIS Pro Tutorials
    Area covered
    Description

    This data has been clipped from the USA Critical Habitat layer on ArcGIS Living Atlas of the World. It is intended for Esri tutorial purposes only and may not reflect the current state of critical habitat. Use the USA Critical Habitat layer for authoritative data.In the United States, species in danger of extinction are protected by the Endangered Species Act. As part of these protections, the US Fish and Wildlife Service can designate critical habitat. Activities that are carried out, authorized, or funded by the federal government that are likely to adversely modify or destroy critical habitat are generally prohibited by the Endangered Species Act.Because the Endangered Species Act prohibits federal actions that degrade critical habitat, limitations may be placed on land management and other projects. Proposed federal actions that may adversely modify or destroy critical habitat require that the agency or private entity proposing the action consult with the appropriate regulatory agency (US Fish and Wildlife Service or the National Oceanic and Atmospheric Administration).The consultation and permitting process often relies heavily on GIS to organize, analyze, and display key information. This layer provides the information necessary to begin a landscape assessment of the distribution of critical habitat.Dataset SummaryPhenomenon Mapped: Critical Habitat for Threatened and Endangered species. Coordinate System: Web Mercator Auxiliary SphereExtent: 50 United States plus Puerto Rico, the US Virgin Islands, Guam, and the Northern Mariana IslandsVisible Scale: The data is visible at all scales but draws best at scales larger than 1: 2,000,000Source: U.S. Fish and Wildlife ServicePublication Date: June 14, 2019This layer displays critical habitat data (June 14, 2019) from the U.S. Fish and Wildlife Service (USFWS). The service contains 2 layers, lines and polygons, which correspond to the two shape files included in the original data. The source data for this layer are available here. Esri modified the attributes of these data to facilitate their use. A Species Type field was added and populated denoting the taxonomic group of each species and a field was added to link to the USFWS species profile for each species. The scientific and common name fields were edited to standardize capitalization and remove special characters. Several fields that did not contain data were removed. Attributes included in this layer are: Common NameScientific NameSpecies TypeSpecies CodePopulation CodeCritical Habitat Status - Final or ProposedFederal Register Publication Citation - The pop-ups for this field are pre-configured to link to the Federal Register search page for this value.Federal Register Publication DateListing Status - Threatened, Endangered, Proposed Threatened, or Proposed EndangeredLink to USFWS Species ProfileWhat 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 feature service is symbolized on the status of the critical habitat for each species. In ArcGIS Online you can change symbology.The data can also be filtered. For example selecting common name as the field and northern spotted owl as the value in the filter will return a map displaying only northern spotted owl critical habitat.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 the description page.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.

  4. a

    CHAFFEE PARCELS (Def Query Applied)

    • citizen-problem-reporter-chaffeecountygis.hub.arcgis.com
    Updated Jul 16, 2025
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    Chaffee County, Colorado (2025). CHAFFEE PARCELS (Def Query Applied) [Dataset]. https://citizen-problem-reporter-chaffeecountygis.hub.arcgis.com/datasets/chaffee-parcels-def-query-applied
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    Dataset updated
    Jul 16, 2025
    Dataset authored and provided by
    Chaffee County, Colorado
    Area covered
    Description

    Metadata creation by Eric Lubell (GIS Coordinator) on 7/15/24. Current GIS Coordinator is taking over from a retired employee who curated the data for 25 years, with a varied degree of attention to detail. This is a small, rural County, and we apologize in advance for any errors.MAP - this is the last 3 digits of the parcel number and needs to be updated whenever a parcel number is changed. This field should not be null.LOT - this is typically from the plat and may or may not exist. This field, historically, has many values other than the LOT stored in it. This field has not been reliably populated and is assumed to have many errors that will eventually be fixed. No ETA on accuracy QAQC. This field can be null.BLK - current GIS Coordinator still not entirely sure what this field represents. This field can be null.SUB - this field is supposed to represent the subdivision that the parcel is contained within. This field has not been reliably populated and is assumed to have many errors that will eventually be fixed. No ETA on accuracy QAQC. This field can not be null.MAPLOC - this is a combination of data. The first 4 digits should represent the State of Colorado's Assessment Mapping and Parcel Identification ID. The next 2 digits are the PLSS Section number. I'm not exactly sure what any additional digits represent but is is common to have additional digits. It is also common to only have 4 digits and, as always, QAQC is needed and an ETA is unknown.ORDER_ - C stands for Calculated (Aliquot parts w/o survey infromation) and S stands for Survey. This field can be null and I suspect there are many errors, not really sure if it should be kept at all. REMOVED 6/16/25 after backup.MR - this is for Mineral Rights. 600s are for improvements on leased land, 700s are mineral rights, 800s are mining claims. MRO is mineral rights only. This field can be null and I suspect there are many errors, not really sure if it should be kept at all.PI - this is for Partial Interest. This field can be null and I suspect there are many errors, not really sure if it should be kept at all. REMOVED 6/16/25 after backup.MapType - clearly something related to PLSS data but I suspect this field is highly inaccurate. This field can be null and I suspect there are many errors, not really sure if it should be kept at all. REMOVED 6/16/25 after backup.ORDERNO - this field is no longer relevant and will be deleted. DELETED 8/1/24.STREETNO - the street number of the address. Some parcels have yet to be assigned an address, so this field can be null.PREDIRECTION - the direction of the address, for example W for West before something like Main Street. This field can be null.STREETNAME - the street name of the address. This field can be null but should probably be filled in more than it is.STREETTYPE - the street type, drive, circle, etc. This field can be null.UNITTYPE - field used to identify the type of unit, currently only building, common elements, hangar, lot, or unit. UNITTYPE and LOT seem to have been used interchangeably, so some QAQC needs to happen. This is primarily for multi family housing. This field can be null.UNITNAME - the number or letter assigned to the unit. This field can be null.PROPERTYCITY - the city or township where the parcel is situated. Unincorporated indicates it is on County land. This field should not be null.EXEMPT - this field identifies exempt parcels: BV is Buena Vista, CC is Chaffee County, CO is State of Colorado, OT is Other (think churches), PS is Poncha Springs, SA is Salida, SA/CC is Salida and Chaffee County, SD is School District, US is the Federal Government, DPT = Department of Property Taxation. These are tax exempt properties. This field can be null.BUSINESSNAME - no clue as to the accuracy of this data but an attempt at identifying the business that exists on the parcel. It should probably be removed from the parcel data and only remain in the exports from RealWare. This field can be null.ADDRES - the full address concatenated from the other address related fields. This field should not be null.TaxDist - the tax district of the parcel. With the exception of parcels that split a tax district, this field should be accurate as of 7/14/24. This field should not be null.AREA - this is where the area was captured from the plat map. However, it was not filled in consistently. It will be replaced with the next 4 fields for better accuracy. This field should not be null.Plat_Acres - if there is an acres value on the plat, it should be recorded here. This field can be null.GIS_Acres - calculated with geodesic value on all parcels and used as a QAQC on the plat acres (if applicable). This field should not be null.Plat_SqFt - if there is a square footage value on the plat, it should be recorded here. This field can be null.GIS_SqFt - calculated with geodesic value on all parcels and used as a QAQC on the plat square footage (if applicable). This field should not be null.NOTE_01 - field added by current GIS Coordinator to capture notes not applicable to other fields. This field was used in some cases to capture previously entered data that wasn't entered into the correct place. This field can be null.NOTE_02 - second field added by current GIS Coordinator to capture notes not applicable to other fields. This field was used in some cases to capture previously entered data that wasn't entered into the correct place. This field can be null.Added "ReceptNum" on 9/20/24 to record the reception number from the Recorder's Office.PROCESSING NOTES: Over the last six months, the current GIS Coordinator has spent significant amounts of time and effort to clean this layer up. Starting on 7/14/24, additional QA/QC and processing notes will be recorded here:7/18/24 - used Select by Attributes to identify 75 parcels where the MAP value did NOT match the last three digits of the Parcel and fixed them accordingly. PARCEL LIKE '%' || CAST(MAP AS VARCHAR(3)). This was the field calculator expression to fix the issue: !PARCEL![-3:]8/1/24 - added and attributed the Fire District and Tax District fields. Also exported the Owner table from ListBuilder so I could populate the STATUS field and the GIS_TYPE field.8/8/24 - added in the redacted accounts (Status = Redacted) so that I can be sure NOT to deliver the ownership data for these parcels in data requests. The query STATUS LIKE '%Redacted%' will identify them all.8/8/24 - Ran the Condo Search in RW and updated the GIS_TYPE field accordingly. My initial accounting of Condos in GIS came up with 554 parcels but the RW export showed 689 so much more accurate.

  5. Sinks

    • oregonwaterdata.org
    • dangermondpreserve-tnc.hub.arcgis.com
    • +2more
    Updated Mar 16, 2023
    + more versions
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    Esri (2023). Sinks [Dataset]. https://www.oregonwaterdata.org/maps/esri::sinks-2
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    Dataset updated
    Mar 16, 2023
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    The National Hydrography Dataset Plus High Resolution (NHDplus High Resolution) maps the lakes, ponds, streams, rivers and other surface waters of the United States. Created by the US Geological Survey, NHDPlus High Resolution provides mean annual flow and velocity estimates for rivers and streams. Additional attributes provide connections between features facilitating complicated analyses.For more information on the NHDPlus High Resolution dataset see the User’s Guide for the National Hydrography Dataset Plus (NHDPlus) High Resolution.Dataset SummaryPhenomenon Mapped: Surface waters and related features of the United States and associated territoriesGeographic Extent: The Contiguous United States, Hawaii, portions of Alaska, Puerto Rico, Guam, US Virgin Islands, Northern Marianas Islands, and American SamoaProjection: Web Mercator Auxiliary Sphere Visible Scale: Visible at all scales but layer draws best at scales larger than 1:1,000,000Source: USGSUpdate Frequency: AnnualPublication Date: July 2022This layer was symbolized in the ArcGIS Map Viewer and while the features will draw in the Classic Map Viewer the advanced symbology will not. Prior to publication, the network and non-network flowline feature classes were combined into a single flowline layer. Similarly, the Area and Waterbody feature classes were merged under a single schema.Attribute fields were added to the flowline and waterbody layers to simplify symbology and enhance the layer's pop-ups. Fields added include Pop-up Title, Pop-up Subtitle, Esri Symbology (waterbodies only), and Feature Code Description. All other attributes are from the original dataset. No data values -9999 and -9998 were converted to Null values.What can you do with this layer?Feature layers work throughout the ArcGIS system. Generally your work flow with feature layers will begin in ArcGIS Online or ArcGIS Pro. Below are just a few of the things you can do with a feature service in Online and Pro.ArcGIS OnlineAdd this layer to a map in the map viewer. The layer or a map containing it can be used in an application. Change the layer’s transparency and set its visibility rangeOpen the layer’s attribute table and make selections. Selections made in the map or table are reflected in the other. Center on selection allows you to zoom to features selected in the map or table and show selected records allows you to view the selected records in the table.Apply filters. For example you can set a filter to show larger streams and rivers using the mean annual flow attribute or the stream order attribute.Change the layer’s style and symbologyAdd labels and set their propertiesCustomize the pop-upUse as an input to the ArcGIS Online analysis tools. This layer works well as a reference layer with the trace downstream and watershed tools. The buffer tool can be used to draw protective boundaries around streams and the extract data tool can be used to create copies of portions of the data.ArcGIS ProAdd this layer to a 2d or 3d map.Use as an input to geoprocessing. For example, copy features allows you to select then export portions of the data to a new feature class.Change the symbology and the attribute field used to symbolize the dataOpen table and make interactive selections with the mapModify the pop-upsApply Definition Queries to create sub-sets of the layerThis layer is part of the ArcGIS 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.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. l

    Los Angeles Storm Drain System

    • data.lacounty.gov
    • geohub.lacity.org
    • +2more
    Updated Jun 7, 2021
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    County of Los Angeles (2021). Los Angeles Storm Drain System [Dataset]. https://data.lacounty.gov/datasets/los-angeles-storm-drain-system
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    Dataset updated
    Jun 7, 2021
    Dataset authored and provided by
    County of Los Angeles
    Area covered
    Los Angeles
    Description

    The Los Angeles County Storm Drain System is a geometric network model representing the storm drain infrastructure within Los Angeles County. The long term goal of this network is to seamlessly integrate the countywide drainage infrastructure, regardless of ownership or jurisdiction. Current uses by the Department of Public Works (DPW) include asset inventory, operational maintenance, and compliance with environmental regulations.

    GIS DATA DOWNLOADS: (More information is in the table below)

    File geodatabase: A limited set of feature classes comprise the majority of this geometric network. These nine feature classes are available in one file geodatabase (.gdb). ArcMap versions compatible with the .gdb are 10.1 and later. Read-only access is provided by the open-source software QGIS. Instructions on opening a .gdb file are available here, and a QGIS plugin can be downloaded here.

    Acronyms and Definitions (pdf) are provided to better understand terms used.

    ONLINE VIEWING: Use your PC’s browser to search for drains by street address or drain name and download engineering drawings. The Web Viewer link is: https://dpw.lacounty.gov/fcd/stormdrain/

    MOBILE GIS: This storm drain system can also be viewed on mobile devices as well as your PC via ArcGIS Online. (As-built plans are not available with this mobile option.)

    More About these Downloads All data added or updated by Public Works is contained in nine feature classes, with definitions listed below. The file geodatabase (.gdb) download contains these eleven feature classes without network connectivity. Feature classes include attributes with unabbreviated field names and domains.

    ArcMap versions compatible with the .gdb are 10.1 and later.

    Feature Class Download Description

    CatchBasin In .gdb Catch basins collect urban runoff from gutters

    Culvert In .gdb A relatively short conduit that conveys storm water runoff underneath a road or embankment. Typical materials include reinforced concrete pipe (RCP) and corrugated metal pipe (CMP). Typical shapes are circular, rectangular, elliptical, or arched.

    ForceMain In .gdb Force mains carry stormwater uphill from pump stations into gravity mains and open channels.

    GravityMain In .gdb Underground pipes and channels.

    LateralLine In .gdb Laterals connect catch basins to underground gravity mains or open channels.

    MaintenanceHole In .gdb The top opening to an underground gravity main used for inspection and maintenance.

    NaturalDrainage In .gdb Streams and rivers that flow through natural creek beds

    OpenChannel In .gdb Concrete lined stormwater channels.

    PumpStation In .gdb Where terrain causes accumulation, lift stations are used to pump stormwater to where it can once again flow towards the ocean

    Data Field Descriptions

    Most of the feature classes in this storm drain geometric network share the same GIS table schema. Only the most critical attributes are listed here per LACFCD operations.

    Attribute Description

    ASBDATE The date the design plans were approved “as-built” or accepted as “final records”.

    CROSS_SECTIN_SHAPE The cross-sectional shape of the pipe or channel. Examples include round, square, trapezoidal, arch, etc.

    DIAMETER_HEIGHT The diameter of a round pipe or the height of an underground box or open channel.

    DWGNO Drain Plan Drawing Number per LACFCD Nomenclature

    EQNUM Asset No. assigned by the Department of Public Works’ (in Maximo Database).

    MAINTAINED_BY Identifies, to the best of LAFCD’s knowledge, the agency responsible for maintaining the structure.

    MOD_DATE Date the GIS features were last modified.

    NAME Name of the individual drainage infrastructure.

    OWNER Agency that owns the drainage infrastructure in question.

    Q_DESIGN The peak storm water runoff used for the design of the drainage infrastructure.

    SOFT_BOTTOM For open channels, indicates whether the channel invert is in its natural state (not lined).

    SUBTYPE Most feature classes in this drainage geometric nature contain multiple subtypes.

    UPDATED_BY The person who last updated the GIS feature.

    WIDTH Width of a channel in feet.

  7. d

    Data from: Landslide Inventories across the United States (ver. 3.0,...

    • catalog.data.gov
    • s.cnmilf.com
    Updated Nov 12, 2025
    + more versions
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    U.S. Geological Survey (2025). Landslide Inventories across the United States (ver. 3.0, February 2025) [Dataset]. https://catalog.data.gov/dataset/landslide-inventories-across-the-united-states-ver-3-0-february-2025
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    Dataset updated
    Nov 12, 2025
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    United States
    Description

    Abstract Landslides are damaging and deadly, and they occur in every U.S. state. However, our current ability to understand landslide hazards at the national scale is limited, in part because spatial data on landslide occurrence across the U.S. varies greatly in quality, accessibility, and extent. Landslide inventories are typically collected and maintained by different agencies and institutions, usually within specific jurisdictional boundaries, and often with varied objectives and information attributes or even in disparate formats. The purpose of this data release is to provide an openly accessible, centralized map of existing information about landslide occurrence across the entire U.S. This data release is an update of previous versions 1 (Jones and others, 2019) and 2 (Belair and others, 2022). Changes relative to version 2 are summarized in us_ls_v3_changes.txt. It provides an integrated database of the landslides from these inventories (refer to US_Landslide_v3_gpkg) with a selection of uniform attributes, including links to the original digital inventory files (whenever available) (“Inv_URL”). The data release includes digital inventories created by both USGS and non-USGS authors. The original inventory is denoted by an abbreviation in the “Inventory” attribute. The full citation for each abbreviation can be found in us_ls_v3_references.csv. The date of the landslide event is included as a minimum and maximum (“Date_Min” and “Date_Max”) to accommodate events that happen within a range of dates. The date value is inherently difficult to interpret or discern due to the nature of landsliding, where some landslides move for long periods of time or move intermittently, and some areas can exhibit multiple landslide events. To preserve the constituent inventories as much as possible, we include all entries even if they are not considered landslides, such as “gullies” or “avalanche chutes.” We include a landslide type attribute when that information is available (“LS_Type”). The landslide classification system used in the original inventories is not always known or stated in the metadata, but many mapping entities use the schema from Cruden and Varnes (1996) or the updated schema from Hungr and others (2014). Given the wide range of landslide information sources in this data compilation, we provide an attribute to assess the relative confidence in the characterization of the location and extent of each landslide (entry) (“Confidence”). The confidence level reflects the resolution and quality of input data, as well as the method used for identification and mapping. This confidence does not reflect a formal accuracy assessment of field attributes. Relative to the previous data releases (version 1 and 2), this update (v3) includes more inventories, updated confidence rules, a new landslide type attribute, a new unique identifier (“USGS_ID”), new machine-readable date fields, and an ancillary database containing all fields from the original inventories (refer to US_Landslide_v3_ancillary). Please contact gs-haz_landslides_inventory@usgs.gov for more information on how to contribute additional inventories to this community effort. When possible, please cite the constituent inventories as well as this data release. This data release includes: (1) a landslide point file and polygon file in multiple forms (US_Landslide_v3_gpkg, US_Landslide_v3_shp, US_Landslide_v3_csv), (2) an ancillary database with original fields (US_Landslide_v3_ancillary), (3) a spreadsheet that summarizes the confidence rules, their justification, and any extra analyses (us_ls_v3_analyses.csv), (4) a summary file of the changes made between version 2 and version 3 (us_ls_v3_changes.txt), (5) a file containing the references of the constituent inventories (us_ls_v3_references.csv), (6) and a readme (README.txt). Disclaimer: Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Data fields Field Names Definitions USGS_ID Unique USGS identifier for each landslide entry. Date_Min Minimum possible date of landslide occurrence. If date is known to the day, Date_Min will have a value while Date_Max is empty. Time zone is assumed to be local, except for Inventories ‘USGS Earthquake-Triggered Ground Failure’ and ‘USGS Seismogenic Mass Movements’ which are in UTC. Date_Max Maximum possible date of landslide occurrence. If date is known to the day, Date_Max will be empty while Date_Min has a value. Time zone is assumed to be local, except for Inventories ‘USGS Earthquake-Triggered Ground Failure’ and ‘USGS Seismogenic Mass Movements’ which are in UTC. Fatalities Number of fatalities caused by landslide event. Confidence Confidence in landslide (entry) extent, nature, and location. LS_Type Landslide (entry) type. Classification schema of original inventories is often not specified. Inventory Name of original source inventory. Inv_URL URL or link to original source inventory. Info_Source Information source or sub-layer from original source inventory. Notes Unformatted notes field, includes additional information. Lat_N Latitude of point or polygon centroid in WGS 1984 Lon_W Longitude of point or polygon centroid in WGS 1984 Confidence attributes Confidence Definitions 1 Possible landslide (feature) in the area 2 Probable landslide (feature) in the area 3 Likely landslide (feature) at or near this location 5 Moderate confidence in extent or nature of landslide (feature) at this location 8 High confidence in extent or nature of landslide (feature) References Belair, G.M., Jones, E.S., Slaughter, S.L., and Mirus, B.B., 2022, Landslide Inventories across the United States version 2: U.S. Geological Survey data release, https://doi.org/10.5066/P9FZUX6N. Cruden, D.M. and Varnes, D.J., 1996, Landslide Types and Processes, in Turner, K.A. and Schuster R. L., eds., Landslides Investigation and Mitigation: Transportation Research Board, U.S. National Research Council Special Report 247, U.S. National Academy of Sciences, Chapter 3, p. 36-75. ESRI, 2023, ArcGIS Pro (Version 3.1.3), Redlands, CA: Environmental Systems Research Institute, Retrieved from https://www.esri.com/en-us/arcgis/products/arcgis-pro/resources. Hungr, O., Leroueil, S., and Picarelli, L., 2014, The Varnes classification of landslide types, an update, Landslides, 11(2), p. 167-194, https://doi.org/10.1007/s10346-013-0436-y. Jones, E.S., Mirus, B.B, Schmitt, R.G., Baum, R.L., Burns, W.J., Crawford, M., Godt, J.W., Kirschbaum, D.B., Lancaster, J.T., Lindsey, K.O., McCoy, K.E., Slaughter, S., and Stanley, T.A., 2019, Landslide Inventories across the United States: U.S. Geological Survey data release, https://doi.org/10.5066/P9E2A37P. Python Software Foundation, 2023, Python Language Reference, version 3.9, Retrieved from http://www.python.org. QGIS.org, 2022, QGIS Geographic Information System (Version 3.28.4-Firenze), QGIS Association, Retrieved from http://www.qgis.org.

  8. j

    Streams

    • gis.jacksoncountyor.gov
    Updated Sep 8, 2025
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    Jackson County GIS (2025). Streams [Dataset]. https://gis.jacksoncountyor.gov/datasets/streams-2
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    Dataset updated
    Sep 8, 2025
    Dataset authored and provided by
    Jackson County GIS
    Area covered
    Description

    Jackson County Streams layer is derived from Oregon Department of Forestry Hydrography Flowline (May 09, 2025 update) data, which is developed from best available digital elevation models from 2m LiDAR and the 10m National Elevation Dataset. For more information regarding the ODF dataset please see ODF"s ArcGIS Hub - Hydrography Flow Line | ODF ArcGIS Hub. The statewide data is reduced to the Jackson County boundary and is edited, both in geometry and attributes, to meet the County’s needs.The Jackson County Planning Class (JCclass) field is added to the Streams layer. This field reflects Jackson County’s Stream Classifications, as defined in Chapter 13 of the 2004 Land Development Ordinance and in chapter 16 of the 1989 Jackson County Comprehensive Plan. The Stream Classifications are aligned with Statewide Planning Goal 5 and with OAR 660-023-0090. Furthermore, the Stream Classifications are not related to a typical hydrologic class or type, but exclusively the land-use planning designation.Class 1 attributes (JCclass field) are applied to the new Streams flowlines to match the previously approved Class1 flowlines’ geometry. The archived Streams and Irrigation Canals data can be found here - CountyStreams - OverviewClass 2 attributes are applied to the new Streams flowlines using a series of select-by-location processes, involving Class 2 flowlines from Original Streams & Irrigation Canals and USGS 3DHP flowlines, then afterwards a careful and arduous systematic review of Class 2 flowlines results. During the review, geometry and attribute edits were made to better reflect the location and Class 2 designation.Perfect geometry and attributes are unlikely given the complexity of the situation however significant and continuous efforts are made to review and improve the flowlines and attributes with best available GIS data and tools. For step-by-step processing of the Streams flowlines, please contact Jackson County GIS.

  9. l

    Intersections

    • geohub.lacity.org
    • visionzero.geohub.lacity.org
    • +4more
    Updated Nov 14, 2015
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    boegis_lahub (2015). Intersections [Dataset]. https://geohub.lacity.org/datasets/intersections/api
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    Dataset updated
    Nov 14, 2015
    Dataset authored and provided by
    boegis_lahub
    Area covered
    Description

    This intersection points feature class represents current intersections in the City of Los Angeles. Few intersection points, named pseudo nodes, are used to split the street centerline at a point that is not a true intersection at the ground level. The Mapping and Land Records Division of the Bureau of Engineering, Department of Public Works provides the most current geographic information of the public right of way. The right of way information is available on NavigateLA, a website hosted by the Bureau of Engineering, Department of Public Works.Intersection layer was created in geographical information systems (GIS) software to display intersection points. Intersection points are placed where street line features join or cross each other and where freeway off- and on-ramp line features join street line features. The intersection points layer is a feature class in the LACityCenterlineData.gdb Geodatabase dataset. The layer consists of spatial data as a point feature class and attribute data for the features. The intersection points relates to the intersection attribute table, which contains data describing the limits of the street segment, by the CL_NODE_ID field. The layer shows the location of the intersection points on map products and web mapping applications, and the Department of Transportation, LADOT, uses the intersection points in their GIS system. The intersection attributes are used in the Intersection search function on BOE's web mapping application NavigateLA. The intersection spatial data and related attribute data are maintained in the Intersection layer using Street Centerline Editing application. The City of Los Angeles Municipal code states, all public right-of-ways (roads, alleys, etc) are streets, thus all of them have intersections. List of Fields:Y: This field captures the georeferenced location along the vertical plane of the point in the data layer that is projected in Stateplane Coordinate System NAD83. For example, Y = in the record of a point, while the X = .CL_NODE_ID: This field value is entered as new point features are added to the edit layer, during Street Centerline application editing process. The values are assigned automatically and consecutively by the ArcGIS software first to the street centerline spatial data layer, then the intersections point spatial data layer, and then the intersections point attribute data during the creation of new intersection points. Each intersection identification number is a unique value. The value relates to the street centerline layer attributes, to the INT_ID_FROM and INT_ID_TO fields. One or more street centerline features intersect the intersection point feature. For example, if a street centerline segment ends at a cul-de-sac, then the point feature intersects only one street centerline segment.X: This field captures the georeferenced location along the horizontal plane of the point in the data layer that is projected in Stateplane Coordinate System NAD83. For example, X = in the record of a point, while the Y = .ASSETID: User-defined feature autonumber.USER_ID: The name of the user carrying out the edits.SHAPE: Feature geometry.LST_MODF_DT: Last modification date of the polygon feature.LAT: This field captures the Latitude in deciaml degrees units of the point in the data layer that is projected in Geographic Coordinate System GCS_North_American_1983.OBJECTID: Internal feature number.CRTN_DT: Creation date of the polygon feature.TYPE: This field captures a value for intersection point features that are psuedo nodes or outside of the City. A pseudo node, or point, does not signify a true intersection of two or more different street centerline features. The point is there to split the line feature into two segments. A pseudo node may be needed if for example, the Bureau of Street Services (BSS) has assigned different SECT_ID values for those segments. Values: • S - Feature is a pseudo node and not a true intersection. • null - Feature is an intersection point. • O - Intersection point is outside of the City of LA boundary.LON: This field captures the Longitude in deciaml degrees units of the point in the data layer that is projected in Geographic Coordinate System GCS_North_American_1983.

  10. GIS Shapefile - GIS Shapefile, Assessments and Taxation Database, MD...

    • search.dataone.org
    • portal.edirepository.org
    Updated Feb 14, 2018
    + more versions
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    Cary Institute Of Ecosystem Studies; Jarlath O'Neil-Dunne; Morgan Grove (2018). GIS Shapefile - GIS Shapefile, Assessments and Taxation Database, MD Property View 2004, Baltimore City [Dataset]. https://search.dataone.org/view/https%3A%2F%2Fpasta.lternet.edu%2Fpackage%2Fmetadata%2Feml%2Fknb-lter-bes%2F351%2F600
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    Dataset updated
    Feb 14, 2018
    Dataset provided by
    Long Term Ecological Research Networkhttp://www.lternet.edu/
    Authors
    Cary Institute Of Ecosystem Studies; Jarlath O'Neil-Dunne; Morgan Grove
    Time period covered
    Jan 1, 2004 - Jan 1, 2005
    Area covered
    Description

    AT_2004_BACI File Geodatabase Feature Class Thumbnail Not Available Tags Socio-economic resources, Information, Social Institutions, Hierarchy, Territory, BES, Parcel, Property, Property View, A&T, Database, Assessors, Taxation Summary Serves as a basis for performing various analyses based on parcel data. Description Assessments & Taxation (A&T) Database from MD Property View 2004 for Baltimore City. The A&T Database contains parcel data from the State Department of Assessments and Taxation; it incorporates parcel ownership and address information, parcel valuation information and basic information about the land and structure(s) associated with a given parcel. These data form the basis for the 2004 Database, which also includes selected Computer Assisted Mass Appraisal (CAMA) characteristics, text descriptions to make parcel code field data more readily accessible and logical True/False fields which identify parcels with certain characteristics. Documentation for A&T, including a thorough definition for all attributes is enclosed. Complete Property View documentation can be found at http://www.mdp.state.md.us/data/index.htm under the "Technical Background" tab. It should be noted that the A&T Database consists of points and not parcel boundaries. For those areas where parcel polygon data exists the A&T Database can be joined using the ACCTID or a concatenation of the BLOCK and LOT fields, whichever is appropriate. (Spaces may have to be excluded when concatenating the BLOCK and LOT fields). A cursory review of the 2004 version of the A&T Database indicates that it has more accurate data when compared with the 2003 version, particularly with respect to dwelling types. However, for a given record it is not uncommon for numerous fields to be missing attributes. Based on previous version of the A&T Database it is also not unlikely that some of the information is inaccurate. This layer was edited to remove points that did not have a valid location because they failed to geocode. There were 379 such points. A listing of the deleted points is in the table with the suffix "DeletedRecords." Credits Maryland Department of Planning Use limitations BES use only. Extent West -76.713418 East -76.526031 North 39.374429 South 39.197452 Scale Range There is no scale range for this item.

  11. b

    Bird Biodiversity

    • gallatinvalleyplan.bozeman.net
    Updated May 12, 2023
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    Bozeman GIS Community (2023). Bird Biodiversity [Dataset]. https://gallatinvalleyplan.bozeman.net/datasets/bzn-community::bird-biodiversity
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    Dataset updated
    May 12, 2023
    Dataset authored and provided by
    Bozeman GIS Community
    Area covered
    Description

    Model Methods


    1. Extracts layer areas only within the study area. 2. Assigns a score from 1 (lowest) to 3 (highest) to each attribute as described in the attribute selection column. 3. Converts layer from raster to polygon. 4. Renames the attribute field with rankings from GRIDCODE to descriptive scoring field name.

  12. u

    Utah Garfield County Parcels LIR

    • opendata.gis.utah.gov
    • hub.arcgis.com
    • +1more
    Updated Nov 20, 2019
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    Utah Automated Geographic Reference Center (AGRC) (2019). Utah Garfield County Parcels LIR [Dataset]. https://opendata.gis.utah.gov/datasets/utah-garfield-county-parcels-lir/api
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    Dataset updated
    Nov 20, 2019
    Dataset authored and provided by
    Utah Automated Geographic Reference Center (AGRC)
    License

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

    Area covered
    Description

    Update information can be found within the layer’s attributes and in a table on the Utah Parcel Data webpage under LIR Parcels.In Spring of 2016, the Land Information Records work group, an informal committee organized by the Governor’s Office of Management and Budget’s State Planning Coordinator, produced recommendations for expanding the sharing of GIS-based parcel information. Participants in the LIR work group included representatives from county, regional, and state government, including the Utah Association of Counties (County Assessors and County Recorders), Wasatch Front Regional Council, Mountainland and Bear River AOGs, Utah League of Cities and Towns, UDOT, DNR, AGRC, the Division of Emergency Management, Blue Stakes, economic developers, and academic researchers. The LIR work group’s recommendations set the stage for voluntary sharing of additional objective/quantitative parcel GIS data, primarily around tax assessment-related information. Specifically the recommendations document establishes objectives, principles (including the role of local and state government), data content items, expected users, and a general process for data aggregation and publishing. An important realization made by the group was that ‘parcel data’ or ‘parcel record’ products have a different meaning to different users and data stewards. The LIR group focused, specifically, on defining a data sharing recommendation around a tax year parcel GIS data product, aligned with the finalization of the property tax roll by County Assessors on May 22nd of each year. The LIR recommendations do not impact the periodic sharing of basic parcel GIS data (boundary, ID, address) from the County Recorders to AGRC per 63F-1-506 (3.b.vi). Both the tax year parcel and the basic parcel GIS layers are designed for general purpose uses, and are not substitutes for researching and obtaining the most current, legal land records information on file in County records. This document, below, proposes a schedule, guidelines, and process for assembling county parcel and assessment data into an annual, statewide tax parcel GIS layer. gis.utah.gov/data/sgid-cadastre/ It is hoped that this new expanded parcel GIS layer will be put to immediate use supporting the best possible outcomes in public safety, economic development, transportation, planning, and the provision of public services. Another aim of the work group was to improve the usability of the data, through development of content guidelines and consistent metadata documentation, and the efficiency with which the data sharing is distributed.GIS Layer Boundary Geometry:GIS Format Data Files: Ideally, Tax Year Parcel data should be provided in a shapefile (please include the .shp, .shx, .dbf, .prj, and .xml component files) or file geodatabase format. An empty shapefile and file geodatabase schema are available for download at:At the request of a county, AGRC will provide technical assistance to counties to extract, transform, and load parcel and assessment information into the GIS layer format.Geographic Coverage: Tax year parcel polygons should cover the area of each county for which assessment information is created and digital parcels are available. Full coverage may not be available yet for each county. The county may provide parcels that have been adjusted to remove gaps and overlaps for administrative tax purposes or parcels that retain these expected discrepancies that take their source from the legally described boundary or the process of digital conversion. The diversity of topological approaches will be noted in the metadata.One Tax Parcel Record Per Unique Tax Notice: Some counties produce an annual tax year parcel GIS layer with one parcel polygon per tax notice. In some cases, adjacent parcel polygons that compose a single taxed property must be merged into a single polygon. This is the goal for the statewide layer but may not be possible in all counties. AGRC will provide technical support to counties, where needed, to merge GIS parcel boundaries into the best format to match with the annual assessment information.Standard Coordinate System: Parcels will be loaded into Utah’s statewide coordinate system, Universal Transverse Mercator coordinates (NAD83, Zone 12 North). However, boundaries stored in other industry standard coordinate systems will be accepted if they are both defined within the data file(s) and documented in the metadata (see below).Descriptive Attributes:Database Field/Column Definitions: The table below indicates the field names and definitions for attributes requested for each Tax Parcel Polygon record.FIELD NAME FIELD TYPE LENGTH DESCRIPTION EXAMPLE SHAPE (expected) Geometry n/a The boundary of an individual parcel or merged parcels that corresponds with a single county tax notice ex. polygon boundary in UTM NAD83 Zone 12 N or other industry standard coordinates including state plane systemsCOUNTY_NAME Text 20 - County name including spaces ex. BOX ELDERCOUNTY_ID (expected) Text 2 - County ID Number ex. Beaver = 1, Box Elder = 2, Cache = 3,..., Weber = 29ASSESSOR_SRC (expected) Text 100 - Website URL, will be to County Assessor in most all cases ex. webercounty.org/assessorBOUNDARY_SRC (expected) Text 100 - Website URL, will be to County Recorder in most all cases ex. webercounty.org/recorderDISCLAIMER (added by State) Text 50 - Disclaimer URL ex. gis.utah.gov...CURRENT_ASOF (expected) Date - Parcels current as of date ex. 01/01/2016PARCEL_ID (expected) Text 50 - County designated Unique ID number for individual parcels ex. 15034520070000PARCEL_ADD (expected, where available) Text 100 - Parcel’s street address location. Usually the address at recordation ex. 810 S 900 E #304 (example for a condo)TAXEXEMPT_TYPE (expected) Text 100 - Primary category of granted tax exemption ex. None, Religious, Government, Agriculture, Conservation Easement, Other Open Space, OtherTAX_DISTRICT (expected, where applicable) Text 10 - The coding the county uses to identify a unique combination of property tax levying entities ex. 17ATOTAL_MKT_VALUE (expected) Decimal - Total market value of parcel's land, structures, and other improvements as determined by the Assessor for the most current tax year ex. 332000LAND _MKT_VALUE (expected) Decimal - The market value of the parcel's land as determined by the Assessor for the most current tax year ex. 80600PARCEL_ACRES (expected) Decimal - Parcel size in acres ex. 20.360PROP_CLASS (expected) Text 100 - Residential, Commercial, Industrial, Mixed, Agricultural, Vacant, Open Space, Other ex. ResidentialPRIMARY_RES (expected) Text 1 - Is the property a primary residence(s): Y'(es), 'N'(o), or 'U'(nknown) ex. YHOUSING_CNT (expected, where applicable) Text 10 - Number of housing units, can be single number or range like '5-10' ex. 1SUBDIV_NAME (optional) Text 100 - Subdivision name if applicable ex. Highland Manor SubdivisionBLDG_SQFT (expected, where applicable) Integer - Square footage of primary bldg(s) ex. 2816BLDG_SQFT_INFO (expected, where applicable) Text 100 - Note for how building square footage is counted by the County ex. Only finished above and below grade areas are counted.FLOORS_CNT (expected, where applicable) Decimal - Number of floors as reported in county records ex. 2FLOORS_INFO (expected, where applicable) Text 100 - Note for how floors are counted by the County ex. Only above grade floors are countedBUILT_YR (expected, where applicable) Short - Estimated year of initial construction of primary buildings ex. 1968EFFBUILT_YR (optional, where applicable) Short - The 'effective' year built' of primary buildings that factors in updates after construction ex. 1980CONST_MATERIAL (optional, where applicable) Text 100 - Construction Material Types, Values for this field are expected to vary greatly by county ex. Wood Frame, Brick, etc Contact: Sean Fernandez, Cadastral Manager (email: sfernandez@utah.gov; office phone: 801-209-9359)

  13. b

    Estimated Floodplain

    • gallatinvalleyplan.bozeman.net
    Updated May 12, 2023
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    Bozeman GIS Community (2023). Estimated Floodplain [Dataset]. https://gallatinvalleyplan.bozeman.net/datasets/bzn-community::estimated-floodplain
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    Dataset updated
    May 12, 2023
    Dataset authored and provided by
    Bozeman GIS Community
    Area covered
    Description

    Model Methods


    1. Selects flood zones A and AE. 2. Extracts layer areas only within the study area. 3. Adds an empty field for the floodplain score. 4. Calculates a score in the floodplain score field from 1 (lowest) to 3 (highest) for each attribute as described in the attribute selection column.

  14. a

    USA Wetlands

    • cgs-topics-lincolninstitute.hub.arcgis.com
    • sal-urichmond.hub.arcgis.com
    • +2more
    Updated Nov 17, 2021
    + more versions
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    LincolnHub (2021). USA Wetlands [Dataset]. https://cgs-topics-lincolninstitute.hub.arcgis.com/items/c954cfa7cee34d94b3b266356445a7ea
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    Dataset updated
    Nov 17, 2021
    Dataset authored and provided by
    LincolnHub
    Area covered
    Description

    Wetlands are areas where water is present at or near the surface of the soil during at least part of the year. Wetlands provide habitat for many species of plants and animals that are adapted to living in wet habitats. Wetlands form characteristic soils, absorb pollutants and excess nutrients from aquatic systems, help buffer the effects of high flows, and recharge groundwater. Data on the distribution and type of wetland play an important role in land use planning and several federal and state laws require that wetlands be considered during the planning process.The National Wetlands Inventory (NWI) was designed to assist land managers in wetland conservation efforts. The NWI is managed by the US Fish and Wildlife Service.Dataset SummaryPhenomenon Mapped: WetlandsCoordinate System: Web Mercator Auxiliary SphereExtent: 50 United States plus Puerto Rico, the US Virgin Islands and the Northern Mariana IslandsVisible Scale: The data is visible at scales from 1:144,000 to 1:1,000Resolution/Tolerance: 0.0001 meters/0.001 metersNumber of Features: 34,954,623 diced, after applying a 50,000 vertex limit to an original set of 34,950,653 featuresFeature Limit: 10,000Source: U.S. Fish and Wildlife ServicePublication Date: September 29, 2020ArcGIS Server URL: https://landscape11.arcgis.com/arcgis/This layer was created from the September 29, 2020 version of the NWI. This layer includes attributes from the original dataset as well as attributes added by Esri for use in the default pop-up and to allow the user to query and filter the data.NWI derived attributes:Wetland Code - a code that identifies specific attributes of the wetlandWetland Type - one of 8 wetland typesArea - area of the wetland in acresEsri created attributes:System - code indicating the system and subsystem of the wetlandClass - code indicating the class and subclass of the wetlandModifier 1, Modifier 2, Modifier 3, Modifier 4 - these four fields contain letter codes for modifiers applied to the wetland descriptionSystem Name - the name of the system (Marine, Estuarine, Riverine, Lacustrine, or Palustrine)Subsystem Name - the name of the subsystemClass Name - the name of the classSubclass Name - the name of the subclassModifier 1 Name, Modifier 2 Name, Modifier 3 Name , Modifier 4 Name - these four fields contain names for modifiers applied to the wetland descriptionPopup Header - this field contains a text string that is used to create the header in the default pop-up System Text - this field contains a text string that is used to create the system description text in the default pop-upClass Text - this field contains a text string that is used to create the class description text in the default pop-upModifier Text - this field contains a text string that is used to create the modifier description text in the default pop-upSpecies Text - this field contains a text string that is used to create the species description text in the default pop-upCodes, names, and text fields were derived from the publication Classification of Wetlands and Deepwater Habitats of the United States.What can you do with this Feature Layer?Feature layers work throughout the ArcGIS system. Generally your work flow with feature layers will begin in ArcGIS Online or ArcGIS Pro. Below are just a few of the things you can do with a feature service in Online and Pro.ArcGIS OnlineAdd this layer to a map in the map viewer. The layer is limited to scales of approximately 1:144,000 or larger but an imagery layer created from the same data can be used at smaller scales to produce a webmap that displays across the full scale range. The layer or a map containing it can be used in an application.Change the layer’s transparency and set its visibility rangeOpen the layer’s attribute table and make selections and apply filters. Selections made in the map or table are reflected in the other. Center on selection allows you to zoom to features selected in the map or table and show selected records allows you to view the selected records in the table.Change the layer’s style and filter the data. For example, you could set a filter for System Text = 'Palustrine' to create a map of palustrine wetlands only.Add labels and set their propertiesCustomize the pop-upArcGIS ProAdd this layer to a 2d or 3d map. The same scale limit as Online applies in ProUse as an input to geoprocessing. For example, copy features allows you to select then export portions of the data to a new feature class.Change the symbology and the attribute field used to symbolize the dataOpen table and make interactive selections with the mapModify the pop-upsApply Definition Queries to create sub-sets of the layerThis 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.

  15. a

    Service Locations

    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • hub.arcgis.com
    • +1more
    Updated Jan 5, 2025
    + more versions
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    Town of Apex, North Carolina (2025). Service Locations [Dataset]. https://arc-gis-hub-home-arcgishub.hub.arcgis.com/maps/apexnc::service-locations
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    Dataset updated
    Jan 5, 2025
    Dataset authored and provided by
    Town of Apex, North Carolina
    Area covered
    Description

    The construction of this data model was adapted from the Telvent Miner & Miner ArcFM MultiSpeak data model to provide interface functionality with Milsoft Utility Solutions WindMil engineering analysis program. Database adaptations, GPS data collection, and all subsequent GIS processes were performed by Southern Geospatial Services for the Town of Apex Electric Utilities Division in accordance to the agreement set forth in the document "Town of Apex Electric Utilities GIS/GPS Project Proposal" dated March 10, 2008. Southern Geospatial Services disclaims all warranties with respect to data contained herein. Questions regarding data quality and accuracy should be directed to persons knowledgeable with the forementioned agreement.The data in this GIS with creation dates between March of 2008 and April of 2024 were generated by Southern Geospatial Services, PLLC (SGS). The original inventory was performed under the above detailed agreement with the Town of Apex (TOA). Following the original inventory, SGS performed maintenance projects to incorporate infrastructure expansion and modification into the GIS via annual service agreements with TOA. These maintenances continued through April of 2024.At the request of TOA, TOA initiated in house maintenance of the GIS following delivery of the final SGS maintenance project in April of 2024. GIS data created or modified after April of 2024 are not the product of SGS.With respect to SGS generated GIS data that are point features:GPS data collected after January 1, 2013 were surveyed using mapping grade or survey grade GPS equipment with real time differential correction undertaken via the NC Geodetic Surveys Real Time Network (VRS). GPS data collected prior to January 1, 2013 were surveyed using mapping grade GPS equipment without the use of VRS, with differential correction performed via post processing.With respect to SGS generated GIS data that are line features:Line data in the GIS for overhead conductors were digitized as straight lines between surveyed poles. Line data in the GIS for underground conductors were digitized between surveyed at grade electric utility equipment. The configurations and positions of the underground conductors are based on TOA provided plans. The underground conductors are diagrammatic and cannot be relied upon for the determination of the actual physical locations of underground conductors in the field.The Service Locations feature class was created by Southern Geospatial Services (SGS) from a shapefile of customer service locations generated by dataVoice International (DV) as part of their agreement with the Town of Apex (TOA) regarding the development and implemention of an Outage Management System (OMS).Point features in this feature class represent service locations (consumers of TOA electric services) by uniquely identifying the features with the same unique identifier as generated for a given service location in the TOA Customer Information System (CIS). This is also the mechanism by which the features are tied to the OMS. Features are physically located in the GIS based on CIS address in comparison to address information found in Wake County GIS property data (parcel data). Features are tied to the GIS electric connectivity model by identifying the parent feature (Upline Element) as the transformer that feeds a given service location.SGS was provided a shapefile of 17992 features from DV. Error potentially exists in this DV generated data for the service location features in terms of their assigned physical location, phase, and parent element.Regarding the physical location of the features, SGS had no part in physically locating the 17992 features as provided by DV and cannot ascertain the accuracy of the locations of the features without undertaking an analysis designed to verify or correct for error if it exists. SGS constructed the feature class and loaded the shapefile objects into the feature class and thus the features exist in the DV derived location. SGS understands that DV situated the features based on the address as found in the CIS. No features were verified as to the accuracy of their physical location when the data were originally loaded. It is the assumption of SGS that the locations of the vast majority of the service location features as provided by DV are in fact correct.SGS understands that as a general rule that DV situated residential features (individually or grouped) in the center of a parcel. SGS understands that for areas where multiple features may exist in a given parcel (such as commercial properties and mobile home parks) that DV situated features as either grouped in the center of the parcel or situated over buildings, structures, or other features identifiable in air photos. It appears that some features are also grouped in roads or other non addressed locations, likely near areas where they should physically be located, but that these features were not located in a final manner and are either grouped or strung out in a row in the general area of where DV may have expected they should exist.Regarding the parent and phase of the features, the potential for error is due to the "first order approximation" protocol employed by DV for assigning the attributes. With the features located as detailed above, SGS understands that DV identified the transformer closest to the service location (straight line distance) as its parent. Phase was assigned to the service location feature based on the phase of the parent transformer. SGS expects that this protocol correctly assigned parent (and phase) to a significant portion of the features, however this protocol will also obviously incorretly assign parent in many instances.To accurately identify parent for all 17992 service locations would require a significant GIS and field based project. SGS is willing to undertake a project of this magnitude at the discretion of TOA. In the meantime, SGS is maintaining (editing and adding to) this feature class as part of the ongoing GIS maintenance agreement that is in place between TOA and SGS. In lieu of a project designed to quality assess and correct for the data provided by DV, SGS will verify the locations of the features at the request of TOA via comparison of the unique identifier for a service location to the CIS address and Wake County parcel data address as issues arise with the OMS if SGS is directed to focus on select areas for verification by TOA. Additionally, as SGS adds features to this feature class, if error related to the phase and parent of an adjacent feature is uncovered during a maintenance, it will be corrected for as part of that maintenance.With respect to the additon of features moving forward, TOA will provide SGS with an export of CIS records for each SGS maintenance, SGS will tie new accounts to a physical location based on address, SGS will create a feature for the CIS account record in this feature class at the center of a parcel for a residential address or at the center of a parcel or over the correct (or approximately correct) location as determined via air photos or via TOA plans for commercial or other relevant areas, SGS will identify the parent of the service location as the actual transformer that feeds the service location, and SGS will identify the phase of the service address as the phase of it's parent.Service locations with an ObjectID of 1 through 17992 were originally physically located and attributed by DV.Service locations with an ObjectID of 17993 or higher were originally physically located and attributed by SGS.DV originated data are provided the Creation User attribute of DV, however if SGS has edited or verified any aspect of the feature, this attribute will be changed to SGS and a comment related to the edits will be provided in the SGS Edits Comments data field. SGS originated features will be provided the Creation User attribute of SGS. Reference the SGS Edits Comments attribute field Metadata for further information.

  16. a

    Flowlines

    • pend-oreille-county-open-data-pendoreilleco.hub.arcgis.com
    Updated Jun 7, 2024
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    Pend Oreille County (2024). Flowlines [Dataset]. https://pend-oreille-county-open-data-pendoreilleco.hub.arcgis.com/datasets/flowlines
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    Dataset updated
    Jun 7, 2024
    Dataset authored and provided by
    Pend Oreille County
    Area covered
    Description

    *This dataset is authored by ESRI and is being shared as a direct link to the feature service by Pend Oreille County. NHD is a primary hydrologic reference used by our organization.The National Hydrography Dataset Plus High Resolution (NHDplus High Resolution) maps the lakes, ponds, streams, rivers and other surface waters of the United States. Created by the US Geological Survey, NHDPlus High Resolution provides mean annual flow and velocity estimates for rivers and streams. Additional attributes provide connections between features facilitating complicated analyses.For more information on the NHDPlus High Resolution dataset see the User’s Guide for the National Hydrography Dataset Plus (NHDPlus) High Resolution.Dataset SummaryPhenomenon Mapped: Surface waters and related features of the United States and associated territoriesCoordinate System: Web Mercator Auxiliary Sphere Extent: The Contiguous United States, Hawaii, portions of Alaska, Puerto Rico, Guam, US Virgin Islands, Northern Marianas Islands, and American Samoa Visible Scale: Visible at all scales but layer draws best at scales larger than 1:1,000,000Source: USGSPublication Date: July 2022This layer was symbolized in the ArcGIS Map Viewer and while the features will draw in the Classic Map Viewer the advanced symbology will not.Prior to publication, the network and non-network flowline feature classes were combined into a single flowline layer. Similarly, the Area and Waterbody feature classes were merged under a single schema.Attribute fields were added to the flowline and waterbody layers to simplify symbology and enhance the layer's pop-ups. Fields added include Pop-up Title, Pop-up Subtitle, Esri Symbology (waterbodies only), and Feature Code Description. All other attributes are from the original dataset. No data values -9999 and -9998 were converted to Null values.What can you do with this Feature Layer?Feature layers work throughout the ArcGIS system. Generally your work flow with feature layers will begin in ArcGIS Online or ArcGIS Pro. Below are just a few of the things you can do with a feature service in Online and Pro.ArcGIS OnlineAdd this layer to a map in the map viewer. The layer or a map containing it can be used in an application. Change the layer’s transparency and set its visibility rangeOpen the layer’s attribute table and make selections. Selections made in the map or table are reflected in the other. Center on selection allows you to zoom to features selected in the map or table and show selected records allows you to view the selected records in the table.Apply filters. For example you can set a filter to show larger streams and rivers using the mean annual flow attribute or the stream order attribute.Change the layer’s style and symbologyAdd labels and set their propertiesCustomize the pop-upUse as an input to the ArcGIS Online analysis tools. This layer works well as a reference layer with the trace downstream and watershed tools. The buffer tool can be used to draw protective boundaries around streams and the extract data tool can be used to create copies of portions of the data.ArcGIS ProAdd this layer to a 2d or 3d map.Use as an input to geoprocessing. For example, copy features allows you to select then export portions of the data to a new feature class.Change the symbology and the attribute field used to symbolize the dataOpen table and make interactive selections with the mapModify the pop-upsApply Definition Queries to create sub-sets of the layerThis layer is part of the ArcGIS 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.

  17. a

    Pop Up Table

    • sal-urichmond.hub.arcgis.com
    Updated Apr 18, 2023
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    Esri (2023). Pop Up Table [Dataset]. https://sal-urichmond.hub.arcgis.com/datasets/esri::pop-up-table
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    Dataset updated
    Apr 18, 2023
    Dataset authored and provided by
    Esri
    Area covered
    Description

    Wetlands are areas where water is present at or near the surface of the soil during at least part of the year. Wetlands provide habitat for many species of plants and animals that are adapted to living in wet habitats. Wetlands form characteristic soils, absorb pollutants and excess nutrients from aquatic systems, help buffer the effects of high flows, and recharge groundwater. Data on the distribution and type of wetland play an important role in land use planning and several federal and state laws require that wetlands be considered during the planning process.The National Wetlands Inventory (NWI) was designed to assist land managers in wetland conservation efforts. The NWI is managed by the US Fish and Wildlife Service.Dataset SummaryPhenomenon Mapped: WetlandsGeographic Extent: 50 United States plus Puerto Rico, the US Virgin Islands, Guam, American Samoa, and the Northern Mariana IslandsProjection: Web Mercator Auxiliary SphereVisible Scale: This layer preforms well between scales of 1:1,000,000 to 1:1,000. An imagery layer created from this dataset is also available which you can also use to quickly draw wetlands at smaller scales.Source: U.S. Fish and Wildlife ServiceUpdate Frequency: AnnualPublication Date: October 26, 2024This layer was created from the October 26, 2024 version of the NWI. The features were converted from multi-part to a single part using the Multipart To Singlepart tool. Features with more than 50,000 vertices were split with the Dice tool. The Repair Geometry tool was run on the features, using the OGC option.The layer is published with a related table that contains text fields created by Esri for use in the layer's pop-up. Fields in the table are:Popup Header - this field contains a text string that is used to create the header in the default pop-up System Text - this field contains a text string that is used to create the system description text in the default pop-upClass Text - this field contains a text string that is used to create the class description text in the default pop-upModifier Text - this field contains a text string that is used to create the modifier description text in the default pop-upSpecies Text - this field contains a text string that is used to create the species description text in the default pop-upCodes, names, and text fields were derived from the publication Classification of Wetlands and Deepwater Habitats of the United States.What can you do with this layer?Feature layers work throughout the ArcGIS system. Generally your work flow with feature layers will begin in ArcGIS Online or ArcGIS Pro. Below are just a few of the things you can do with a feature service in Online and Pro.ArcGIS OnlineAdd this layer to a map in the map viewer. The layer is limited to scales of approximately 1:1,000,000 or larger but an imagery layer created from the same data can be used at smaller scales to produce a webmap that displays across the full scale range. The layer or a map containing it can be used in an application.Change the layer’s transparency and set its visibility rangeOpen the layer’s attribute table and make selections and apply filters. Selections made in the map or table are reflected in the other. Center on selection allows you to zoom to features selected in the map or table and show selected records allows you to view the selected records in the table.Change the layer’s style and filter the data. For example, you could set a filter for System Name = 'Palustrine' to create a map of palustrine wetlands only.Add labels and set their propertiesCustomize the pop-upArcGIS ProAdd this layer to a 2d or 3d mapUse as an input to geoprocessing. For example, copy features allows you to select then export portions of the data to a new feature class. Change the symbology and the attribute field used to symbolize the dataOpen table and make interactive selections with the mapModify the pop-upsApply Definition Queries to create sub-sets of the layerThis 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.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.

  18. USA Soils Map Units

    • hub.arcgis.com
    • mapdirect-fdep.opendata.arcgis.com
    • +7more
    Updated Apr 5, 2019
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    Esri (2019). USA Soils Map Units [Dataset]. https://hub.arcgis.com/maps/06e5fd61bdb6453fb16534c676e1c9b9
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    Dataset updated
    Apr 5, 2019
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    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. Data from the gSSURGO databasewas used to create this layer. To download ready-to-use project packages of useful soil data derived from the SSURGO dataset, please visit the USA SSURGO Downloader app. Dataset SummaryPhenomenon Mapped: Soils of the United States and associated territoriesGeographic Extent: The 50 United States, Puerto Rico, Guam, US Virgin Islands, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American SamoaCoordinate System: Web Mercator Auxiliary SphereVisible Scale: 1:144,000 to 1:1,000Source: USDA Natural Resources Conservation ServiceUpdate Frequency: AnnualPublication Date: December 2024 What can you do with this layer?ArcGIS OnlineFeature layers work throughout the ArcGIS system. Generally your work flow with feature layers will begin in ArcGIS Online or ArcGIS Pro.Below are just a few of the things you can do with a feature service in Online and Pro.Add this layer to a map in the map viewer. The layer is limited to scales of approximately 1:144,000 or larger but avector tile layercreated from the same data can be used at smaller scales to produce awebmapthat displays across the full scale range. The layer or a map containing it can be used in an application.Change the layer’s transparency and set its visibility rangeOpen the layer’s attribute table and make selections and apply filters. Selections made in the map or table are reflected in the other. Center on selection allows you to zoom to features selected in the map or table and show selected records allows you to view the selected records in the table.Change the layer’s style and filter the data. For example, you could set a filter forFarmland Class= "All areas are prime farmland" to create a map of only prime farmland.Add labels and set their propertiesCustomize the pop-up ArcGIS ProAdd this layer to a 2d or 3d map. The same scale limit as Online applies in ProUse as an input to geoprocessing. For example, copy features allows you to select then export portions of the data to a new feature class.Change the symbology and the attribute field used to symbolize the dataOpen table and make interactive selections with the mapModify the pop-upsApply Definition Queries to create sub-sets of the layerThis layer is part of theLiving Atlas of the Worldthat provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics. Data DictionaryAttributesKey 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 Symbol Map 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 Rating Legend TableThis table has 1:1 relationship with the Map Unit table and was joined using the Legend Key field.Project Scale Survey 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 Version Map 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 Mapunit with Dominant ConditionNon-Irrigated Capability Class - Dominant ConditionNon-Irrigated Capability Class - Proportion of Mapunit 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 Average Component 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 Key Component 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 -

  19. 2021 North Florida TPO National Accessibility Evaluation Data

    • gis-fdot.opendata.arcgis.com
    • mapdirect-fdep.opendata.arcgis.com
    Updated Jul 7, 2023
    + more versions
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    Florida Department of Transportation (2023). 2021 North Florida TPO National Accessibility Evaluation Data [Dataset]. https://gis-fdot.opendata.arcgis.com/content/7caa0a8dfdaf4443b168e988a2ce845f
    Explore at:
    Dataset updated
    Jul 7, 2023
    Dataset authored and provided by
    Florida Department of Transportationhttps://www.fdot.gov/
    Area covered
    Description

    Overview:This document describes the 2021 accessibility data released by the Accessibility Observatory at the University of Minnesota. The data are included in the National Accessibility Evaluation Project for 2021, and this information can be accessed for each state in the U.S. at https://access.umn.edu/research/america. The following sections describe the format, naming, and content of the data files.Data Formats: The data files are provided in a Geopackage format. Geopackage (.gpkg) files are an open-source, geospatial filetype that can contain multiple layers of data in a single file, and can be opened with most GIS software, including both ArcGIS and QGIS.Within this zipfile, there are six geopackage files (.gpkg) structured as follows. Each of them contains the blocks shapes layer, results at the block level for all LEHD variables (jobs and workers), with a layer of results for each travel time (5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60 minutes). {MPO ID}_tr_2021_0700-0859-avg.gpkg = Average Transit Access Departing Every Minute 7am-9am{MPO ID}_au_2021_08.gpkg = Average Auto Access Departing 8am{MPO ID}_bi_2021_1200_lts1.gpkg = Average Bike Access on LTS1 Network{MPO ID}_bi_2021_1200_lts2.gpkg = Average Bike Access on LTS2 Network{MPO ID}_bi_2021_1200_lts3.gpkg = Average Bike Access on LTS3 Network{MPO ID}_bi_2021_1200_lts4.gpkg = Average Bike Access on LTS4 NetworkFor mapping and geospatial analysis, the blocks shape layer within each geopackage can be joined to the blockid of the access attribute data. Opening and Using Geopackages in ArcGIS:Unzip the zip archiveUse the "Add Data" function in Arc to select the .gpkg fileSelect which layer(s) are needed — always select "main.blocks" as this layer contains the Census block shapes; select any other attribute data layers as well.There are three types of layers in the geopackage file — the "main.blocks" layer is the spatial features layer, and all other layers are either numerical attribute data tables, or the "fieldname_descriptions" metadata layer. The numerical attribute layers are named with the following format:[mode]_[threshold]_minutes[mode] is a two-character code indicating the transport mode used[threshold] is an integer indicating the travel time threshold used for this data layerTo use the data spatially, perform a join between the "main.blocks" layer and the desired numerical data layer, using either the numerical "id" fields, or 15-digit "blockid" fields as join fields.

  20. a

    CSDCIOP Dune Crest Points

    • maine.hub.arcgis.com
    Updated Feb 26, 2020
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    State of Maine (2020). CSDCIOP Dune Crest Points [Dataset]. https://maine.hub.arcgis.com/maps/maine::csdciop-dune-crest-points
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    Dataset updated
    Feb 26, 2020
    Dataset authored and provided by
    State of Maine
    Area covered
    Description

    Feature class that compares the elevations between sand dune crests (extracted from available LiDAR datasets from 2010 and 2013) with published FEMA Base Flood Elevations (BFEs) from preliminary FEMA DFIRMS (Panels issued in 2018 and 2019) in coastal York and Cumberland counties (up through Willard Beach in South Portland). Steps to create the dataset included:Shoreline structures from the most recent NOAA EVI LANDWARD_SHORETYPE feature class were extracted using the boundaries of York and Cumberland counties. This included 1B: Exposed, Solid Man-Made structures, 8B: Sheltered, Solid Man-Made Structures; 6B: Riprap, and 8C: Sheltered Riprap. This resulted in the creation of Cumberland_ESIL_Structures and York_ESIL_Structures. Note that ESIL uses the MHW line as the feature base.Shoreline structures from the work by Rice (2015) were extracted using the York and Cumberland county boundaries. This resulted in the creation of Cumberland_Rice_Structures and York_Rice_Structures.Additional feature classes for structures were created for York and Cumberland county structures that were missed. This was Slovinsky_York_Structures and Slovinsky_Cumberland_Structures. GoogleEarth imagery was inspected while additional structures were being added to the GIS. 2012 York and Cumberland County imagery was used as the basemap, and structures were classified as bulkheads, rip rap, or dunes (if known). Also, whether or not the structure was in contact with the 2015 HAT was noted.MEDEP was consulted to determine which permit data (both PBR and Individual Permit, IP, data) could be used to help determine where shoreline stabilization projects may have been conducted adjacent to or on coastal bluffs. A file was received for IP data and brought into GIS (DEP_Licensing_Points). This is a point file for shoreline stabilization permits under NRPA.Clip GISVIEW.MEDEP.Permit_By_Rule_Locations to the boundaries of the study area and output DEP_PBR_Points.Join GISVIEW.sde>GISVIEW.MEDEP.PBR_ACTIVITY to the DEP_PBR_Points using the PBR_ID Field. Then, export this file as DEP_PBR_Points2. Using the new ACTIVITY_DESC field, select only those activities that relate to shoreline stabilization projects:PBR_ACTIVITY ACTIVITY_DESC02 Act. Adjacent to a Protected Natural Resource04 Maint Repair & Replacement of Structure08 Shoreline StabilizationSelect by Attributes > PBR_ACTIVITY IN (‘02’, ‘04’, ‘08’) select only those activities likely to be related to shoreline stabilization, and export the selected data as a DEP_PBR_Points3. Then delete 1 and 2, and rename this final product as DEP_PBR_Points.Next, visually inspect the Licensing and PBR files using ArcMap 2012, 2013 imagery, along with Google Earth imagery to determine the extents of armoring along the shoreline.Using EVI and Rice data as indicators, manually inspect and digitize sections of the coastline that are armored. Classify the seaward shoreline type (beach, mudflat, channel, dune, etc.) and the armor type (wall or bulkhead). Bring in the HAT line and, using that and visual indicators, identify whether or not the armored sections are in contact with HAT. Use Google Earth at the same time as digitizing in order to help constrain areas. Merge digitized armoring into Cumberland_York_Merged.Bring the preliminary FEMA DFIRM data in and use “intersect” to assign the different flood zones and elevations to the digitized armored sections. This was done first for Cumberland, then for York Counties. Delete ancillary attributes, as needed. Resulting layer is Cumberland_Structure_FloodZones and York_Structure_FloodZones.Go to NOAA Digital Coast Data Layers and download newest LiDAR data for York and Cumberland county beach, dune, and just inland areas. This includes 2006 and newer topobathy data available from 2010 (entire coast), and selected areas from 2013 and 2014 (Wells, Scarborough, Kennebunk).Mosaic the 2006, 2010, 2013 and 2014 data (with 2013 and 2014 being the first dataset laying on top of the 2010 data) Mosaic this dataset into the sacobaydem_ftNAVD raster (this is from the MEGIS bare-earth model). This will cover almost all of the study area except for armor along several areas in York. Resulting in LidAR206_2010_2013_Mosaic.tif.Using the LiDAR data as a proxy, create a “seaward crest” line feature class which follows along the coast and extracts the approximate highest point (cliff, bank, dune) along the shoreline. This will be used to extract LiDAR data and compare with preliminary flood zone information. The line is called Dune_Crest.Using an added tool Points Along Line, create points at 5 m spacing along each of the armored shoreline feature lines and the dune crest lines. Call the outputs PointsonLines and PointsonDunes.Using Spatial Analyst, Extract LIDAR elevations to the points using the 2006_2010_2013 Mosaic first. Call this LidarPointsonLines1. Select those points which have NULL values, export as this LiDARPointsonLines2. Then rerun Extract Values to Points using just the selected data and the state MEGIS DEM. Convert RASTERVALU to feet by multiplying by 3.2808 (and rename as Elev_ft). Select by Attributes, find all NULL values, and in an edit session, delete them from LiDARPointsonLines. Then, merge the 2 datasets and call it LidarPointsonLines. Do the same above with dune lines and create LidarPointsonDunes.Next, use the Cumberland and York flood zone layers to intersect the points with the appropriate flood zone data. Create ….CumbFIRM and …YorkFIRM files for the dunes and lines.Select those points from the Dunes feature class that are within the X zone – these will NOT have an associated BFE for comparison with the Lidar data. Export the Dune Points as Cumberland_York_Dunes_XZone. Run NEAR and use the merged flood zone feature class (with only V, AE, and AO zones selected). Then, join the flood zone data to the feature class using FID (from the feature class) and OBJECTID (from the flood zone feature class). Export as Cumberland_York_Dunes_XZone_Flood. Delete ancillary columns of data, leaving the original FLD_ZONE (X), Elev_ft, NEAR_DIST (distance, in m, to the nearest flood zone), FLD_ZONE_1 (the near flood zone), and the STATIC_BFE_1 (the nearest static BFE).Do the same as above, except with the Structures file (Cumberland_York_Structures_Lidar_DFIRM_Merged), but also select those features that are within the X zone and the OPEN WATER. Export the points as Cumberland_York_Structures_XZone. Again, run the NEAR using the merged flood zone and only AE, VE, and AO zones selected. Export the file as Cumberland_York_Structures_XZone_Flood.Merge the above feature classes with the original feature classes. Add a field BFE_ELEV_COMPARE. Select all those features whose attributes have a VE or AE flood zone and use field calculator to calculate the difference between the Elev_ft and the BFE (subtracting the STATIC_BFE from Elev_ft). Positive values mean the maximum wall value is higher than the BFE, while negative values mean the max is below the BFE. Then, select the remaining values with switch selection. Calculate the same value but use the NEAR_STATIC_BFE value instead. Select by Attributes>FLD_ZONE=AO, and use the DEPTH value to enter into the above created fields as negative values. Delete ancilary attribute fields, leaving those listed in the _FINAL feature classes described above the process steps section.

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Raj Kumar Pandey (2022). Duplicate Value Calculator_ArcMap ESRI [Dataset]. https://www.kaggle.com/datasets/rajkumarpandey02/duplicate-value-calculator-arcmap
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Duplicate Value Calculator_ArcMap ESRI

This python script is exclusively applicable to ESRI ArcMap application for GIS.

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zip(49216 bytes)Available download formats
Dataset updated
Sep 21, 2022
Authors
Raj Kumar Pandey
License

http://opendatacommons.org/licenses/dbcl/1.0/http://opendatacommons.org/licenses/dbcl/1.0/

Description

A custom Python Tool Box exclusively for ESRI ArcMap Application. This toolbox contains two tools: 1. Duplicate Value Calculator : - to search duplicate values in a specified Attribute Field of Table /FeautureClass and populate user defined text for such records in another specified Attribute Field of same Table/FeatureClass. If no Attribute Field is selected to populate text, a default Attribute Field will be added with Name as "DUPLICATE_{Name of Field for Search Duplicate values}".

Further, User can imply SQL Expression to limit the records to be searched as per requirement.

Caution : This Tool modifies the SCHEMA of selected Table/FeatureClass if no Attribute Field is selected to populate text for duplicate values. So preconsider to choose both Attribute Fields - One for Duplicate Search and other for Text against duplicate value if You are concerned about to add new field to Your Table/FeatureClass.

  1. Delete Rows : - to delete Rows from input Table/FeatureClass. Put an SQL Expression for records filter, otherwise all rows will be deleted.
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