This dataset contains locations and attributes of University and College, created as part of the DC Geographic Information System (DC GIS) for the Office of the Chief Technology Officer (OCTO) and participating D.C. government agencies. Information provided by OCTO, EMA, and other sources identified as University Areas and DC GIS staff geo-processed the data. This layer does not represent university areas contained in the campus plans from the DC Office of Zoning.

A map of the University of Mississippi Field Station and accompanying GIS data

Colleges and Universities This feature layer, utilizing data from the National Center for Education Statistics (NCES), displays colleges and universities in the U.S. and its territories. NCES uses the Integrated Postsecondary Education Data System (IPEDS) as the "primary source for information on U.S. colleges, universities, and technical and vocational institutions." According to NCES, this layer "contains directory information for every institution in the 2023-24 IPEDS universe. Includes name, address, city, state, zip code and various URL links to the institution"s home page, admissions, financial aid offices and the net price calculator. Identifies institutions as currently active, and institutions that participate in Title IV federal financial aid programs for which IPEDS is mandatory." University of the District of ColumbiaData currency: 2023Data source: IPEDS Complete Data FilesData modification: Removed fields with coded values and replaced with descriptionsFor more information: Integrated Postsecondary Education Data SystemSupport documentation: Data DictionaryFor feedback, please contact: ArcGIScomNationalMaps@esri.com U.S. Department of Education (ED) Per ED, The mission of the Department of Education (ED) is to promote student achievement and preparation for global competitiveness by fostering educational excellence and ensuring equal access for students of all ages.

Polygon layer of Texas college/university campuses. Update Frequency: As NeededSource: Other SourcesSecurity Level: PublicOwned by TxDOT: FalseRelated LinksData Dictionary PDF [Generated 2025/03/14]

Wake County college and university locations

Lands approved or conveyed to the State of Alaska for a variety of reasons such as general purpose, expansion of communities, University of Alaska, and recreation.

This shape file characterizes the geographic representation of land parcels within the State of Alaska contained by the Ownership - State Owned, Managed - State Tentatively Approved or Patented category. It has been extracted from data sets used to produce the State status plats. This data set includes cases noted on the digital status plats up to one day prior to data extraction.

Each feature has an associated attribute record, including a Land Administration System (LAS) file-type and file-number which serves as an index to related LAS case-file information. Additional LAS case-file and customer information may be obtained at: http://dnr.alaska.gov/projects/las/ Those requiring more information regarding State land records should contact the Alaska Department of Natural Resources Public Information Center directly.

The First International Workshop on Historical GIS was held on Aug 23rd - 24th, 2001 at Fudan University, Shanghai, China. The Workshop was hosted by the Center for Historical Geographical Studies at Fudan, and organized by: Jianxiong GE (Fudan University), Peter Bol (Harvard University), Ruth Mostern (U.C. Berkeley) , and Lex Berman (Harvard University). RELATED WEBSITE: https://sites.fas.harvard.edu/~chgis/pages/agendas/shanghai_2001.html

The Digital Bedrock Geologic-GIS Map of the Fox Creek Quadrangle, Tennessee is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) an ESRI file geodatabase (focr_bedrock_geology.gdb), and a 2.) Open Geospatial Consortium (OGC) geopackage. The file geodatabase format is supported with a 1.) ArcGIS Pro 3.X map file (.mapx) file (focr_bedrock_geology.mapx) and individual Pro 3.X layer (.lyrx) files (for each GIS data layer). Upon request, the GIS data is also available in ESRI shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) a readme file (obed_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (obed_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (focr_bedrock_geology_metadata_faq.pdf). Please read the obed_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. QGIS software is available for free at: https://www.qgis.org/en/site/. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri.htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: University of Tennessee, Tectonics and Structural Geology Research Group. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (focr_bedrock_geology_metadata.txt or focr_bedrock_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:24,000 and United States National Map Accuracy Standards features are within (horizontally) 12.2 meters or 40 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in ArcGIS Pro, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

description: Fundamental GIS: Digital Chart of China, 1:1M, Version 1 consists of vector maps of China and surrounding areas. The maps include roads, railroads, drainage systems, contours, populated places, and urbanized areas for China proper, as well as for China and neighboring countries. The maps are at a scale of one to one million (1:1M). This dataset is produced in collaboration with the University of Washington as part of the China in Time and Space (CITAS) project and the Columbia University Center for International Earth Science Information Network (CIESIN).; abstract: Fundamental GIS: Digital Chart of China, 1:1M, Version 1 consists of vector maps of China and surrounding areas. The maps include roads, railroads, drainage systems, contours, populated places, and urbanized areas for China proper, as well as for China and neighboring countries. The maps are at a scale of one to one million (1:1M). This dataset is produced in collaboration with the University of Washington as part of the China in Time and Space (CITAS) project and the Columbia University Center for International Earth Science Information Network (CIESIN).

Data set that contains information on archaeological remains of the pre historic settlement of the Letolo valley on Savaii on Samoa. It is built in ArcMap from ESRI and is based on previously unpublished surveys made by the Peace Corps Volonteer Gregory Jackmond in 1976-78, and in a lesser degree on excavations made by Helene Martinsson Wallin and Paul Wallin. The settlement was in use from at least 1000 AD to about 1700- 1800. Since abandonment it has been covered by thick jungle. However by the time of the survey by Jackmond (1976-78) it was grazed by cattle and the remains was visible. The survey is at file at Auckland War Memorial Museum and has hitherto been unpublished. A copy of the survey has been accessed by Olof Håkansson through Martinsson Wallin and Wallin and as part of a Masters Thesis in Archeology at Uppsala University it has been digitised.

Olof Håkansson has built the data base structure in the software from ESRI, and digitised the data in 2015 to 2017. One of the aims of the Masters Thesis was to discuss hierarchies. To do this, subsets of the data have been displayed in various ways on maps. Another aim was to discuss archaeological methodology when working with spatial data, but the data in itself can be used without regard to the questions asked in the Masters Thesis. All data that was unclear has been removed in an effort to avoid errors being introduced. Even so, if there is mistakes in the data set it is to be blamed on the researcher, Olof Håkansson. A more comprehensive account of the aim, questions, purpose, method, as well the results of the research, is to be found in the Masters Thesis itself. Direkt link http://uu.diva-portal.org/smash/record.jsf?pid=diva2%3A1149265&dswid=9472

Purpose:

The purpose is to examine hierarchies in prehistoric Samoa. The purpose is further to make the produced data sets available for study.

Prehistoric remains of the settlement of Letolo on the Island of Savaii in Samoa in Polynesia

BY USING THIS WEBSITE OR THE CONTENT THEREIN, YOU AGREE TO THE TERMS OF USE. This point feature class was created by geocoding the facility address as provided by Oakland Schools and ERP to Oakland County's Road Centerline feature class. The resulting points were georeferenced to the facility structure using Oakand County's 2002 orthoimagery at a reference scale of 1:1200.The key attributes include the facility Name, Address and Type (Elementary, Middle, High, Technical and College).

Bedrock Geology of Champaign County, Illinois, map layers (shapefiles). Layers included: 1) Champaign County bedrock units. 2) Champaign County bedrock surface contours. Contour interval of 25 feet. 3) Colchester coal surface contours. Contour interval of 50 feet. 4) Kimmswick Limestone top contours, in the Mahomet dome area. Contour interval of 20 feet. 5) New Albany shale base contour. Contour interval of 100 feet.

This dataset attempts to represent the point locations of every educational program in the state of Minnesota that is currently operational and reporting to the Minnesota Department of Education. It can be used to identify schools, various individual school programs, school districts (by office location), colleges, and libraries, among other programs. Please note that not all school programs are statutorily required to report, and many types of programs can be reported at any time of the year, so this dataset is by nature an incomplete snapshot in time.

Maintenance of these locations is a result of an ongoing project to identify current school program locations where Food and Nutrition Services Office (FNS) programs are utilized. The FNS Office is in the Minnesota Department of Education (MDE). GIS staff at MDE maintain the dataset using school program and physical addresses provided by local education authorities (LEAs) for an MDE database called "MDE ORG". MDE GIS staff track weekly changes to program locations, along with comprehensive reviews each summer. All records have been reviewed for accuracy or edited at least once since January 1, 2020.

Note that there may remain errors due to the number of program locations and inconsistency in reporting from LEAs and other organizations. Some organization types (such as colleges and treatment programs) are not subject to annual reporting requirements, so various records included in this file may in fact be inactive or inaccurately located.

Note that multiple programs may occur at the same location and are represented as separate records. For example, an elementary and secondary school may be in the same building, but each has a separate record in the data layer. Users may leverage the "CLASS" and "ORGTYPE" attributes to filter and sort records according to their needs. In general, records at the same physical address will be located at the same coordinates.

This data is also available in CSV format. For that format only, OBJECTID and Shape columns are removed, and the Shape column is replaced by Latitude and Longitude columns.

This layer shows and identifies the roads owned by West Chester University. | Publication Date: April 2018, Last Updated: April 2018 | West Chester University’s Geography and Planning department upholds its mission to provide spatial analysis expertise in order to solve many problems regarding spatial applications that facilitates research, sustainability goals, planning and communal integration.This dataset was curated by West Chester University’s Department of Geography and Planning and presented using West Chester University's Open GIS Data.

The dataset contains a register of biogas plant sites in Lower Saxony with spatially-resolved and high up-to-date plant information. The register is intended to create a basis for identifying power-to-gas (P2G) potential for biogas plant sites. The dataset is being done within the context of the research project H2-FEE: Flexible energy carriers for the energy transition (running from July 2022 to presumably June 2025) funded by the Lower Saxony Investment and Development Bank (Investitions- und Förderbank Niedersachsen, NBank).

For complete collection of data and models, see https://doi.org/10.21942/uva.c.5290546.Map package for use in ArcGIS Pro containing three-tiered geomorphological data and geographical datasets such as rivers, roads and hillshading. Datasets were used to generate figures for publication: Hierarchical geomorphological mapping in mountainous areas. Matheus G.G. De Jong, Henk Pieter Sterk, Stacy Shinneman & Arie C. Seijmonsbergen. Submitted to Journal of Maps 2020, revisions made in 2021. All data is in MGI Austria GK West projected coordinate system (EPSG: 31254) and was clipped to the study area.

Geotweet Archive v2.0 The Harvard Center for Geographic Analysis (CGA) maintains the Geotweet Archive, a global record of tweets spanning time, geography, and language. The primary purpose of the Archive is to make a comprehensive collection of geo-located tweets available to the academic research community. The Archive extends from 2010 to the present and is updated daily. The number of tweets in the collection totals approximately 10 billion, and it is stored on Harvard University’s High Performance Computing (HPC) cluster. The Harvard HPC supports many applications for working with big spatio-temporal datasets, including two geospatial tools recently deployed by the CGA: OmniSci Immerse, and PostGIS. The Geotweet Archive consists of tweets which carry two types of geospatial signature: 1) GPS-based longitude/latitude generated by the originating device 2) Place-name-centroid-based longitude/latitude from the bounding box provided by Twitter, based on the user-define place designation (typically a town name). Any tweet which carries one or both of these signatures is included in the Archive. Approximately 1-2% of all tweets contain such geographic coordinates, (this percentage needs verification and may vary over time). The current version of the Archive is Version 2.0. The original Version 1.0 archive began in 2012 as part of a project with Ben Lewis of CGA and then Harvard graduate student Todd Mostak, to develop a GPU-powered spatial database called GEOPS. GEOPS formed the basis for technology startup MapD Technologies, which is now OmniSci. OmniSci Immerse software now runs on Harvard’s High Performance Computing (HPC) environment to support interactive exploration and analytics with the Geotweet Archive and any other large datasets. Version 2.0 of the archive represents the results of a merge between the CGA archive, and an archive developed by the Department of Geoinformatics at the University of Salzburg in Austria, as well as several other archives. Clemens Havas and Bernd Resch at University of Salzburg, and Devika Kakkar of Harvard CGA collaborated to deploy Version 2.0. ======================================================== Schema of Geotweet Archive v2.0 Field name_TYPE_Description message_id----BIGINT----Tweet ID tweet_date----TIMESTAMP----Date and time of tweet from Twitter (utc) tweet_text----TEXT ENCODING----Text content of tweet tags----TEXT ENCODING DICT----Tweet hashtags tweet_lang----TEXT ENCODING DICT----Language that the tweet is in source ----TEXT ENCODING DICT----Operating system or application type used to create the tweet place*----TEXT ENCODING NONE----The geographic place as defined by the user, usually a town name. A bounding box determined by Twitter based on this field, from which centroids (see longitude and latitude fields) and the spatial_error field are derived, and used when not overridden by a GPS coordinate. See Twitter tweet object for place. retweets ----SMALLINT----Number of retweets as of last time it was checked tweet_favorites----SMALLINT----Now known as ‘likes’ photo_url----TEXT ENCODING DICT----URL of any image referenced quoted_status_id ----BIGINT----ID number for quote status user_id ----BIGINT----User ID number user_name----TEXT ENCODING NONE----User name user_location*----TEXT ENCODING NONE----User defined location, usually a city or town. See Twitter user object. followers ----SMALLINT----Followers as of the last time checked friends ----SMALLINT----Number of users followed by this user user_favorites----INT----Number of topics the user is interested in status----INT----Code for what user is doing as of last time it was checked user_lang----TEXT ENCODING DICT----User defined language latitude----FLOAT----Latitude from GPS or bounding box based on Place field longitude----FLOAT----Longitude from GPS or bounding box based on Place field data_source*----TEXT ENCODING DICT----The source crawler or dataset for the tweet gps----TEXT ENCODING DICT----Flag for whether lon/lat is from GPS or town name bounding box (SRID – 4326). When both are present, the GPS coordinate takes priority. spatialerror----FLOAT----Estimate in meters horizontal error for lon/lat coordinate. 10m for GPS coordinates, error for bounding boxes calculated as radius of circle with area of bounding box. ===================================================== *data_source_Code U. Salzburg REST API crawler----1 Harvard CGA streaming crawler----2 U. Salzburg streaming API crawler----3 Ryan Qi Wang and Harvard Medical School datasets----4 U. Heidelberg dataset----5 Archive.org dataset----6 ---------------------------------------------------------------------------------------------- Note: Before April of 2015 the default for GPS coordinate capture was turned on for Twitter users. After this date users have had to opt-in to share their precise location. This is one reason for the large decrease in volume of geotweets after this date. A number of automated...

This is a shapefile for the South Branch Potomac River. This file was provided by Dr. Venkatesh Merwade for Purdue University's EAPS 59100 class for downloading DEM for this area.

The Digital Geologic-GIS Map of the Hye Quadrangle, Texas is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) an ESRI file geodatabase (hye_geology.gdb), and a 2.) Open Geospatial Consortium (OGC) geopackage. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (hye_geology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer). Upon request, the GIS data is also available in ESRI shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) a readme file (lyjo_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (lyjo_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (hye_geology_metadata_faq.pdf). Please read the lyjo_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. QGIS software is available for free at: https://www.qgis.org/en/site/. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri.htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: Texas Bureau of Economic Geology, University of Texas at Austin. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (hye_geology_metadata.txt or hye_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:24,000 and United States National Map Accuracy Standards features are within (horizontally) 12.2 meters or 40 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in ArcGIS Pro, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

**THIS NEWER 2016 DIGITAL MAP REPLACES THE OLDER 2014 VERSION OF THE GRI GATE Geomorphological-GIS data. The Unpublished Digital Pre-Hurricane Sandy Geomorphological-GIS Map of the Gateway National Recreation Area: Sandy Hook, Jamaica Bay and Staten Island Units, New Jersey and New York is composed of GIS data layers and GIS tables in a 10.1 file geodatabase (gate_geomorphology.gdb), a 10.1 ArcMap (.MXD) map document (gate_geomorphology.mxd), individual 10.1 layer (.LYR) files for each GIS data layer, an ancillary map information (.PDF) document (gate_geomorphology.pdf) which contains source map unit descriptions, as well as other source map text, figures and tables, metadata in FGDC text (.TXT) and FAQ (.HTML) formats, and a GIS readme file (gate_gis_readme.pdf). Please read the gate_gis_readme.pdf for information pertaining to the proper extraction of the file geodatabase and other map files. To request GIS data in ESRI 10.1 shapefile format contact Stephanie O’Meara (stephanie.omeara@colostate.edu; see contact information below). The data is also available as a 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. Google Earth software is available for free at: http://www.google.com/earth/index.html. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: Rutgers University Institute of Marine and Coastal Sciences. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (gate_metadata_faq.html; available at http://nrdata.nps.gov/geology/gri_data/gis/gate/gate_pre-sandy_metadata_faq.html). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:6,000 and United States National Map Accuracy Standards features are within (horizontally) 5.08 meters or 16.67 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data projection is NAD83, UTM Zone 18N, however, for the KML/KMZ format the data is projected upon export to WGS84 Geographic, the native coordinate system used by Google Earth. The data is within the area of interest of Gateway National Recreation Area.