Shapefiles information containing the basic information about the spatial structure of the STIB-MIVB network: route of the lines and position of the stops of the "commercial" network, that is the basic itineraries "to" and "from".

This polygon shapefile represents filters used with I-Site Studio software to filter ground observations collected by terrestrial laser scanner (TLS) survey in Grapevine Canyon near Scotty's Castle, Death Valley National Park, from July 12-14, 2016. Filters were used to remove extraneous data from features such as vegetation, fences, power lines, and atmospheric interference. The resulting points were used to produce a digital terrain model of the area (GrapevineCanyon_TIN.zip in this data release).

The Department of City Planning aggregates information about 30,000+ facilities and program sites that are owned, operated, funded, licensed, or certified by a City, State, or Federal agency in the City of New York into a central database called the City Planning Facilities Database (FacDB). These facilities generally help to shape quality of life in the city’s neighborhoods, and this dataset is the basis for a series of planning activities. This public data resource allows all New Yorkers to understand the breadth of government resources in their neighborhoods. The data is also complemented with a new interactive web map that enables users to easily filter the data for their needs. Users are strongly encouraged to read the database documentation, particularly with regard to analytical limitations.

Questions about this database can be directed to dcpopendata@planning.nyc.gov

All previously released versions of this data are available at BYTES of the BIG APPLE- Archive

description: The City Planning Facilities Database (FacDB) aggregates information about 35,000+ public and private facilities and program sites that are owned, operated, funded, licensed or certified by a City, State, or Federal agency in the City of New York. It captures facilities that generally help to shape quality of life in the city s neighborhoods, including schools, day cares, parks, libraries, public safety services, youth programs, community centers, health clinics, workforce development programs, transitional housing, and solid waste and transportation infrastructure sites. To facilitate analysis and mapping, the data is available in coma-separated values (CSV) file format, ESRI Shapefile, and GeoJSon. The data is also complemented with a new interactive web map that enables users to easily filter the data for their needs. Users are strongly encouraged to read the database documentation, particularly with regard to analytical limitations.; abstract: The City Planning Facilities Database (FacDB) aggregates information about 35,000+ public and private facilities and program sites that are owned, operated, funded, licensed or certified by a City, State, or Federal agency in the City of New York. It captures facilities that generally help to shape quality of life in the city s neighborhoods, including schools, day cares, parks, libraries, public safety services, youth programs, community centers, health clinics, workforce development programs, transitional housing, and solid waste and transportation infrastructure sites. To facilitate analysis and mapping, the data is available in coma-separated values (CSV) file format, ESRI Shapefile, and GeoJSon. The data is also complemented with a new interactive web map that enables users to easily filter the data for their needs. Users are strongly encouraged to read the database documentation, particularly with regard to analytical limitations.

Analysis of ‘Facilities Database - Shapefile’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/a0709aa5-f873-45b3-87f1-fdb65d4ddf0d on 13 February 2022.

--- Dataset description provided by original source is as follows ---

The City Planning Facilities Database (FacDB) aggregates information about 35,000+ public and private facilities and program sites that are owned, operated, funded, licensed or certified by a City, State, or Federal agency in the City of New York. It captures facilities that generally help to shape quality of life in the city’s neighborhoods, including schools, day cares, parks, libraries, public safety services, youth programs, community centers, health clinics, workforce development programs, transitional housing, and solid waste and transportation infrastructure sites. To facilitate analysis and mapping, the data is available in coma-separated values (CSV) file format, ESRI Shapefile, and GeoJSon. The data is also complemented with a new interactive web map that enables users to easily filter the data for their needs. Users are strongly encouraged to read the database documentation, particularly with regard to analytical limitations.

For data dictionary, please follow this link

All previously released versions of this data are available at BYTES of the BIG APPLE- Archive

--- Original source retains full ownership of the source dataset ---

This data set was originally created as part of the Monmouth County Contour Database (2003). It is a line-based feature class that comprised of modeled 2' contours. For fastest download choose File Geodatabase (fgdb) or Spreadsheet. Due to the dataset's large size, the entirety of the contour GIS layer cannot be downloaded as a single shapefile. If you require a shapefile, please use the Search/Filter Tools to create a subset of the data that will be small enough to download in shapefile format.

County boundaries for: Crittendon, AR; Shelby, TN; Tipton, TN; Fayette, TN; DeSoto, MS; Marshall, MS; Tunica, MS. Filtered from US Census TIGER/Line portal: https://www.census.gov/cgi-bin/geo/shapefiles/index.php.

The Census Planning Database is produced by the U.S. Census Bureau. It assembles a range of housing, demographic, socioeconomic, and census operational data that can be used for survey and census planning.

The Planning Database uses selected Census and selected 2012-2016 American Community Survey (ACS) estimates. In addition to variables extracted from the census and ACS databases, operational variables include the 2010 Census Mail Return Rate for each block group and tract.

This dataset is a subset of the 2018 Census Planning Database, filtered for the state of Connecticut, and including variables relating to hard to count populations. This dataset also includes two variables from the Federal Communications Commission dataset "Residential Fixed Internet Access Service Connections per 1000 Households by Census Tract." More information about the FCC data can be found here: https://www.fcc.gov/reports-research/maps/residential-fixed-internet-access-service-connections-per-1000-households-by-census-tract-dec-2016/

Other variables from the Census Planning Database relating to geography, population, households, housing units, and census operations at the tract and block level can also be found on the CT Data Portal with the tag "Census 2020."

This layer contains favorable geochemistry for high-temperature geothermal systems, as interpreted by Richard "Rick" Zehner. The data is compiled from the data obtained from the USGS. The original data set combines 15,622 samples collected in the State of Colorado from several sources including 1) the original Geotherm geochemical database, 2) USGS NWIS (National Water Information System), 3) Colorado Geological Survey geothermal sample data, and 4) original samples collected by R. Zehner at various sites during the 2011 field season. These samples are also available in a separate shapefile FlintWaterSamples.shp. Data from all samples were reportedly collected using standard water sampling protocols (filtering through 0.45 micron filter, etc.) Sample information was standardized to ppm (micrograms/liter) in spreadsheet columns. Commonly-used cation and silica geothermometer temperature estimates are included. Shapefile containing favorable geochemistry for high-temperature geothermal systems, as interpreted by Richard "Rick" Zehner. Coordinate System: Universal Transverse Mercator (UTM) WGS 1984 Zone 13N, Linear Unit: Meter, Angular Unit: Degree, Prime Meridian: Greenwich

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Primary roads are generally divided, limited-access highways within the interstate highway system or under State management, and are distinguished by the presence of interchanges. These highways are accessible by ramps and may include some toll highways. The MAF/TIGER Feature Classification Code (MTFCC) is S1100 for primary roads. Secondary roads are main arteries, usually in the U.S. Highway, State Highway, and/or County Highway system. These roads have one or more lanes of traffic in each direction, may or may not be divided, and usually have at-grade intersections with many other roads and driveways. They usually have both a local name and a route number. The MAF/TIGER Feature Classification Code (MTFCC) is S1200 for secondary roads.

The Census Planning Database is produced by the U.S. Census Bureau. It assembles a range of housing, demographic, socioeconomic, and census operational data that can be used for survey and census planning.

The Planning Database uses selected Census and selected 2012-2016 American Community Survey (ACS) estimates. In addition to variables extracted from the census and ACS databases, operational variables include the 2010 Census Mail Return Rate for each block group and tract.

This dataset is a subset of the 2018 Census Planning Database, filtered for the state of Connecticut, and including variables relating to hard to count populations. Other variables from the Census Planning Database relating to geography, population, households, housing units, and census operations at the tract and block level can also be found on the CT Data Portal with the tag "Census 2020."

Domestic names from the U.S. Board on Geographic Names Geographic Names Information Systems (GNIS) dataset filtered to San Juan County WA. The original data has been modified to create a shapefile from the geometry information and filtered to only include names in San Juan County WA.

A supplementary dataset related to the paper discussing preparation of a digital elevation model derived from DMR 5G (LiDAR-based DEM of the Czech Republic) cleaned of modern artificial features. It includes data used as a clipping mask and data produced during the testing phase.

Contents:

• ..\clipping_buffers.gdb\ - Clipping buffers based on ZABAGED dataset used for masking the original data stored as ESRI geodatabase.
• ..\drainages\ - Drainages with Strahler order higher than four (potential watercourses) for the original and filtered DEMs.
  • drainages_filtered - Drainges identified in the filtered DEM stored as GeoTIFF.
  • drainages_original - Drainges identified in the original DEM stored as GeoTIFF.
• ..\LSC\ - Locations with significant land surface curvature for the original and filtered DEMs.
  • LSC_filtered - Significant LSC identified in the filtered DEM stored as GeoTIFF.
  • LSC_original - Significant LSC identified in the original DEM stored as GeoTIFF.
• ..\visibility\ - Viewsheds computed over the original and filtered DEMs.
  • Libice\ - Sample viewsheds computed for the early medieval hillfort of Libice.
    • Libice_visibility_filtered - Viewshed based on the filtered DEM stored as GeoTIFF.
    • Libice_visibility_original - Viewshed based on the original DEM stored as GeoTIFF.
    • observer_points - Observer points used for calculating the viewsheds.
  • regular_grid\ - Cumulative viewsheds calculated for regularly spaced points in a 10 x 10 km grid with a visibility radius of 5 km and an observer height of 2 m; a total of 574 viewsheds.
    • visibility_filtered - Cumulative viewshed for the filtered DEM stored as GeoTIFF.
    • visibility_original - Cumulative viewshed for the original DEM stored as GeoTIFF.
    • visibility_test_buffers - Buffers used for the viewshed calculations stored as ESRI shapefile.
    • visibility_test_observers - Observer points used for the viewshed calculations stored as ESRI shapefile.

Preprint version of the related paper:

Novák, David and Pružinec, Filip, Potential and Implications of Automated Pre-Processing of Lidar-Based Digital Elevation Models for Large-Scale Archaeological Landscape Analysis. Available at SSRN: https://ssrn.com/abstract=4063514

In the United States, the federal government manages approximately 28% of the land in the United States. Most federal lands are west of the Mississippi River, where almost half of the land by area is managed by the federal government. Federal lands include 193 million acres managed by the US Forest Service in 154 National Forests and 20 National Grasslands, Bureau of Land Management lands that cover 247 million acres in Alaska and the Western United States, 150 million acres managed for wildlife conservation by the US Fish and Wildlife Service, 84 million acres of National Parks and other lands managed by the National Park Service, and over 30 million acres managed by the Department of Defense. The Bureau of Reclamation manages a much smaller land base than the other agencies included in this layer but plays a critical role in managing the country's water resources. The agencies included in this layer are:Bureau of Land ManagementDepartment of DefenseNational Park ServiceUS Fish and Wildlife ServiceUS Forest ServiceDataset SummaryPhenomenon Mapped: United States federal lands managed by six federal agenciesGeographic Extent: 50 United States and the District of Columbia, Puerto Rico, US Virgin Islands, Guam, American Samoa, and Northern Mariana Islands. The layer also includes National Monuments and Wildlife Refuges in the Pacific Ocean, Atlantic Ocean, and the Caribbean Sea.Data Coordinate System: WGS 1984Visible Scale: The data is visible at all scales but draws best at scales greater than 1:2,000,000Source: BLM, DOD, USFS, USFWS, NPS, PADUS 3.0Publication Date: Various - Esri compiled and published this layer in May 2025. See individual agency views for data vintage.There are six layer views available that were created from this service. Each layer uses a filter to extract an individual agency from the service. For more information about the layer views or how to use them in your own project, follow these links:USA Bureau of Land Management LandsUSA Department of Defense LandsUSA National Park Service LandsUSA Fish and Wildlife Service LandsUSA Forest Service LandsWhat can you do with this Layer?This layer is suitable for both visualization and analysis across the ArcGIS system. This layer can be combined with your data and other layers from the ArcGIS Living Atlas of the World in ArcGIS Online and ArcGIS Pro to create powerful web maps that can be used alone or in a story map or other application.Because this layer is part of the ArcGIS Living Atlas of the World it is easy to add to your map:In ArcGIS Online, you can add this layer to a map by selecting Add then Browse Living Atlas Layers. A window will open. Type "federal lands" in the search box and browse to the layer. Select the layer then click Add to Map.In ArcGIS Pro, open a map and select Add Data from the Map Tab. Select Data at the top of the drop down menu. The Add Data dialog box will open on the left side of the box, expand Portal if necessary, then select Living Atlas. Type "federal lands" in the search box, browse to the layer then click OK.In both ArcGIS Online and Pro you can change the layer's symbology and view its attribute table. You can filter the layer to show subsets of the data using the filter button in Online or a definition query in Pro.The data can be exported to a file geodatabase, a shapefile or other format and downloaded using the Export Data button on the top right of this webpage.This layer can be used as an analytic input in both Online and Pro through the Perform Analysis window Online or as an input to a geoprocessing tool, model, or Python script in Pro.The ArcGIS Living Atlas of the World provides an easy way to explore many other beautiful and authoritative maps on hundreds of topics like this one.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.

The For-Hire Vehicle (“FHV”) trip records include fields capturing the dispatching base license number and the pick-up date, time, and taxi zone location ID (shape file below). These records are generated from the FHV Trip Record submissions made by bases. Note: The TLC publishes base trip record data as submitted by the bases, and we cannot guarantee or confirm their accuracy or completeness. Therefore, this may not represent the total amount of trips dispatched by all TLC-licensed bases. The TLC performs routine reviews of the records and takes enforcement actions when necessary to ensure, to the extent possible, complete and accurate information.

For trip record data including TLC taxi zone location IDs, location names and corresponding boroughs for each ID can be found here. A shapefile containing the boundaries for the taxi zones can be found here.

The GIS Department has now created an Open Data Site for the free distribution of GIS Data. This site allows you to search for layers by key words or by themes. You can download the data in Excel spreadsheet format, or via ArcGIS Shapefile format. You can also filter the selection prior to downloading the data. Additionally, we have links to our public facing Mapping websites and story boards.

The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation.In order for others to use the information in the Census MAF/TIGER database in a geographic information system (GIS) or for other geographic applications, the Census Bureau releases to the public extracts of the database in the form of TIGER/Line Shapefiles.The Incorporated Areas data includes both Incorporated Cities and Census Designated Places. The LSAD (Legal/Statistical Area Description) field can be used to filter for either of these distinctions (25 for Cities, 57 for Census Designated Place). LSAD codes can be found here: LSAD codesThe full Kansas geospatial catalog is administered by the Kansas Data Access & Support Center (DASC) and can be found at the following URL: https://hub.kansasgis.org/

This map package includes the official Tribal areas that NTIA recognizes for their grant programs. The map package includes the following layers. Alaska Native Villages - this layer represents Alaska Native Villages and is created by Census. The layer was downloaded on Jan. 28, 2025, from here: TIGER/Line® Shapefiles.Native Hawaiian Areas - this layer represents Native Hawaiian Areas and is created by Census. The layer was downloaded on Jan. 28, 2025, from here: TIGER/Line® Shapefiles and has been filtered to only include Native Hawaiian Areas. BIA AIAN National LAR - this layer represents American Indian Lands and is created by the BIA. The layer was accessed here: BIA Access Open Data and was exported on Jan. 28, 2025. The layer was filtered to only include lands across the continental U.S. BIA AIAN LAR Supplemental - this layer is a supplemental dataset to the LAR. The layer was accessed here: BIA Access Open Data and was exported on Jan. 28, 2025.BIA AIAN Tribal Statistical Areas - this layer represents Tribal Statistical Areas located in Oklahoma. The layer was accessed here: BIA Access Open Data and was exported on Jan. 28, 2025.This map package was created on Jan. 28, 2025 and was created using ArcGIS Pro 3.4.0. If you have any questions regarding the map package please e-mail NTIAanalytics@ntia.gov.ResourcesCensus DataBIA Open DataBIA Data DisclaimerBy using this product, the user agrees to the below terms and conditions:No warranty is made by the Bureau of Indian Affairs (BIA) for the use of the data for purposes not intended by the BIA. This GIS Dataset may contain errors. There is no impact on the legal status of the land areas depicted herein and no impact on land ownership. No legal inference can or should be made from the information in this GIS Dataset. The GIS Dataset is prepared strictly for illustrative and reference purposes only and should not be used, and is not intended for legal, survey, engineering or navigation purposes. These data have been developed from the best available sources. Although efforts have been made to ensure that the data are accurate and reliable, errors and variable conditions originating from source documents and/or the translation of information from source documents to the systems of record continue to exist. Users must be aware of these conditions and bear responsibility for the appropriate use of the information with respect to possible errors, scale, resolution, rectification, positional accuracy, development methodology, time period, environmental and climatic conditions and other circumstances specific to these data. The user is responsible for understanding the accuracy limitations of the data provided herein. The burden for determining fitness for use lies entirely with the user. The user should refer to the accompanying metadata notes for a description of the data and data development procedures.Census Use RestraintsThe TIGER/Line Shapefile products are not copyrighted however TIGER/Line and Census TIGER are registered trademarks of the U.S. Census Bureau. These products are free to use in a product or publication, however acknowledgement must be given to the U.S. Census Bureau as the source. The boundary information in the TIGER/Line Shapefiles are for statistical data collection and tabulation purposes only; their depiction and designation for statistical purposes does not constitute a determination of jurisdictional authority or rights of ownership or entitlement and they are not legal land descriptions. Coordinates in the TIGER/Line shapefiles have six implied decimal places, but the positional accuracy of these coordinates is not as great as the six decimal places suggest.

A dataset within the Harmonized Database of Western U.S. Water Rights (HarDWR). For a detailed description of the database, please see the meta-record v2.0. Changelog v2.0 - No changes v1.0 - Initial public release Description Borders of all Water Management Areas (WMAs) across the 11 western-most states of the coterminous United States are available filtered through a single source. The legal name for this set of boundaries varies state-by-state. The data is provided as two compressed shapefiles. One, stateWMAs, contains data for all 11 states. For 10 of those states, Arizona being the exception, the polygons represent the legal management boundaries used by those states to manage their surface and groundwater resources respectively. WMAs refer to the set of boundaries a particular state uses to manage its water resources. Each set of boundaries was collected from the states individually, and then merged into one spatial layer. The merging process included renaming some columns to enable merging with all other source layers, as well as removing columns deemed not required for followup analysis. The retained columns for each boundary are: basinNum - the state provided unique numerical ID; basinName - the state provided English name of the area, where applicable; state - the state name; and uniID - a unique identifier we created by concatenating the state name, and underscore, and the state numerical ID. Arizona is unique within this collection of states in that surface and groundwater resources are managed using two separate sets of boundaries. During our followup analysis (Grogan et al., in review) we decided to focus on one set of boundaries, those for surface water. This is due to the recommendation of our hydrologists that the surface water boundary set is a more realist representation of how water moves across the landscape, as a few of the groundwater boundaries are based on political and/or economic considerations. Therefore, the Arizona surface WMAs are included within stateWMAs. The Arizona groundwater WMAs are provided as a separate file, azGroundWMAs, as a companion to the first file for completeness and general reference. WMA spatial boundary data sources by state: Arizona: Arizona Surface Water Watersheds; Collected February, 2020; https://gisdata2016-11-18t150447874z-azwater.opendata.arcgis.com/datasets/surface-watershed/explore?location=34.158174%2C-111.970823%2C7.50 Arizona: Arizona Ground Water Basins; Collected February, 2020; https://gisdata2016-11-18t150447874z-azwater.opendata.arcgis.com/datasets/groundwater-basin-2/explore?location=34.158174%2C-111.970823%2C7.50 California: California CalWater 2.2.1; Collected February, 2020; https://www.mlml.calstate.edu/mpsl-mlml/data-center/data-entry-tools/data-tools/gis-shapefile-layers/ Colorado: Colorado Water District Boundaries; Collected February, 2020; https://www.colorado.gov/pacific/cdss/gis-data-category Idaho: Idaho Department of Water Resources (IDWR) Administrative Basins; Collected November, 2015; https://data-idwr.opendata.arcgis.com/datasets/fb0df7d688a04074bad92ca8ef74cc26_4/explore?location=45.018686%2C-113.862284%2C6.93 Montana: Collected June, 2019; Directly contacted Montana Department of Natural Resources and Conservation (DNRC) Office of Information Technology (OIT) Nevada: Nevada State Engineer Admin Basin Boundaries; Collected April, 2020 https://ndwr.maps.arcgis.com/apps/mapviewer/index.html?layers=1364d0c3a0284fa1bcd90f952b2b9f1c New Mexico: New Mexico Office of the State Engineer (OSE) Declared Groundwater Basins; Collected April, 2020 https://geospatialdata-ose.opendata.arcgis.com/datasets/ose-declared-groundwater-basins/explore?location=34.179783%2C-105.996542%2C7.51 Oregon: Oregon Water Resources Department (OWRD) Administrative Basins; Collected February, 2020; https://www.oregon.gov/OWRD/access_Data/Pages/Data.aspx Utah: Utah Adjudication Books; Collected April, 2020; https://opendata.gis.utah.gov/datasets/utahDNR::utah-adjudication-books/explore?location=39.497165%2C-111.587782%2C-1.00 Washington: Washington Water Resource Inventory Areas (WRIA); Collected June, 2017; https://ecology.wa.gov/Research-Data/Data-resources/Geographic-Information-Systems-GIS/Data Wyoming: Wyoming State Engineer's Office Board of Control Water Districts; Collected June, 2019; Directly contacted Wyoming State Engineer's Office

IMPORTANT IN THE OPEN DATA PORTAL THERE IS ONE FEATURE CLASS FOR ALL POTENTIOMETRIC SURFACE MAPS. IF YOU WANT JUST ONE TIME PERIOD CLICK ON THE TABLE TAB, THEN CLICK ON THE DATE FIELD. IN THE FILTER BOX ON THE RIGHT ENTER THE MAP YOU WANT (MAY 2000, SEPTEMBER 2015, ETC.). WHEN YOU CLICK THE DOWNLOAD DATASET BUTTON SELECT SPREADSHEET OR KML OR SHAPEFILE UNDER THE FILTERED DATASET OPTION. YOU WILL ONLY GET THE FILTERED DATA FROM THIS DOWNLOAD.Contour lines are created for the potentiometric surface of the upper Floridan aquifer from water level data submitted by the water management districts. The points associated with the water level data are added to Geostatistical Analyst and ordinary kriging is used to interpolate water level elevation values between the points. The Geostatistical Analyst layer is then converted to a grid (using GA Layer to grid tool) and then contour lines (using the Contour tool). Post editing is done to smooth the lines and fix areas that are hydrologically incorrect. The rules established for post editing are: 1) rivers intersecting the UFA follow the rule of V’s; 2) potentiometric surface contour line values don’t exceed the topographic digital elevation model (DEM) in unconfined areas; and 3) potentiometric surface contour lines don’t violate valid measured water level data. Errors are usually located where potentiometric highs are adjacent to potentiometric lows (areas where the gradient is high). Expert knowledge or additional information is used to correct the contour lines in these areas. Some additional data may be river stage values in rivers that intersect the Floridan aquifer or land elevation in unconfined areas. Contour lines created prior to May 2012 may be calculated using a different method. The potentiometric surface is only meant to describe water level elevation based on existing data for the time period measured. The contour interval for the statewide map is 10 feet and is not meant to supersede regional (water management district) or local (city) scale potentiometric surface maps.