The establishment of a BES Multi-User Geodatabase (BES-MUG) allows for the storage, management, and distribution of geospatial data associated with the Baltimore Ecosystem Study. At present, BES data is distributed over the internet via the BES website. While having geospatial data available for download is a vast improvement over having the data housed at individual research institutions, it still suffers from some limitations. BES-MUG overcomes these limitations; improving the quality of the geospatial data available to BES researches, thereby leading to more informed decision-making. BES-MUG builds on Environmental Systems Research Institute's (ESRI) ArcGIS and ArcSDE technology. ESRI was selected because its geospatial software offers robust capabilities. ArcGIS is implemented agency-wide within the USDA and is the predominant geospatial software package used by collaborating institutions. Commercially available enterprise database packages (DB2, Oracle, SQL) provide an efficient means to store, manage, and share large datasets. However, standard database capabilities are limited with respect to geographic datasets because they lack the ability to deal with complex spatial relationships. By using ESRI's ArcSDE (Spatial Database Engine) in conjunction with database software, geospatial data can be handled much more effectively through the implementation of the Geodatabase model. Through ArcSDE and the Geodatabase model the database's capabilities are expanded, allowing for multiuser editing, intelligent feature types, and the establishment of rules and relationships. ArcSDE also allows users to connect to the database using ArcGIS software without being burdened by the intricacies of the database itself. For an example of how BES-MUG will help improve the quality and timeless of BES geospatial data consider a census block group layer that is in need of updating. Rather than the researcher downloading the dataset, editing it, and resubmitting to through ORS, access rules will allow the authorized user to edit the dataset over the network. Established rules will ensure that the attribute and topological integrity is maintained, so that key fields are not left blank and that the block group boundaries stay within tract boundaries. Metadata will automatically be updated showing who edited the dataset and when they did in the event any questions arise. Currently, a functioning prototype Multi-User Database has been developed for BES at the University of Vermont Spatial Analysis Lab, using Arc SDE and IBM's DB2 Enterprise Database as a back end architecture. This database, which is currently only accessible to those on the UVM campus network, will shortly be migrated to a Linux server where it will be accessible for database connections over the Internet. Passwords can then be handed out to all interested researchers on the project, who will be able to make a database connection through the Geographic Information Systems software interface on their desktop computer. This database will include a very large number of thematic layers. Those layers are currently divided into biophysical, socio-economic and imagery categories. Biophysical includes data on topography, soils, forest cover, habitat areas, hydrology and toxics. Socio-economics includes political and administrative boundaries, transportation and infrastructure networks, property data, census data, household survey data, parks, protected areas, land use/land cover, zoning, public health and historic land use change. Imagery includes a variety of aerial and satellite imagery. See the readme: http://96.56.36.108/geodatabase_SAL/readme.txt See the file listing: http://96.56.36.108/geodatabase_SAL/diroutput.txt

The Intermodal Passenger Connectivity Database (IPCD) dataset was compiled on August 10, 2021 and was updated October 19, 2022 from the Bureau of Transportation Statistics (BTS) and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). The IPCD is a nationwide database of passenger transportation terminals, with data on the availability of connections among the various scheduled public transportation modes at each facility. IPCD is no longer being updated, the latest information is from 2022. The IPCD data covers the following types of passenger transportation terminals/stops: 1. Scheduled airline service airports. 2. Intercity bus stations (includes stations served by regular scheduled intercity bus service such as Greyhound, Trailways, code sharing buses such as Amtrak Thruway feeder buses, supplemental buses that provide additional frequencies along rail routes, and airport bus services from locations that are outside of the airport metropolitan area). 3. Intercity and transit ferry terminals. 4. Light-rail transit stations. 5. Heavy-rail transit stations. 6. Passenger-rail stations on the national rail network served by intercity rail and/or commuter rail services. 7. Bikeshare stations belonging to bikeshare systems that are open to the general public, IT-automated, and station based (contain hubs to which users can grab and return a bike). The bikeshare stations only include those from the latest IPCD data collection in 2022. Please consult the latest bikeshare layer (https://doi.org/10.21949/1522020) for the most current information. The IPCD includes data elements describing the location of the above types of terminals as well as the availability of intercity, commuter, and transit rail; scheduled air service; intercity and transit bus; intercity and transit ferry services; and bikeshare availability. Transit bus service locations are not specifically included in the database. However, the status of transit bus as a connecting mode is included for each bikeshare facility in the database. A data dictionary, or other source of attribute information, is accessible at https://doi.org/10.21949/1529035

Intermodal Passenger Connectivity DatabaseThis National Geospatial Data Asset (NGDA) dataset, shared as a Bureau of Transportation Statistics (BTS) feature layer, displays the Intermodal Passenger Connectivity Database (IPCD). The IPCD is a nationwide data table of rail, air, bus and ferry passenger transportation terminals. According to BTS, IPCD is a "nationwide database of passenger transportation terminals, with data on the availability of connections among the various scheduled public transportation modes at each facility." The types of passenger transportation terminals include:Scheduled airline service airportsIntercity bus stationsIntercity and transit ferry terminalsLight-rail transit stationsHeavy-rail transit stationsPassenger-rail stationsBike-share stationsThe data describes the availability and locations of the above types of passenger transportation terminals. Note, transit bus service locations are not specifically included.Niagara Frontier Transportation Authority (NFTA) - MilitaryData currency: current Federal Service (Intermodal Passenger Connectivity Database IPCD)NGDAID: 144 (Intermodal Passenger Connectivity Database (IPCD))For more information:Intermodal Passenger Connectivity Database IPCDMetadataSupport documentation: IPCD (data dictionary)For feedback please contact: Esri_US_Federal_Data@esri.comNGDA Theme CommunityThis data set is part of the NGDA Transportation Theme Community. Per the Federal Geospatial Data Committee (FGDC), Transportation is defined as the "means and aids for conveying persons and/or goods. The transportation system includes both physical and non-physical components related to all modes of travel that allow the movement of goods and people between locations".For other NGDA Content: Esri Federal Datasets

SSURGO consists of spatial data and a comprehensive relational database with tables that describe soil properties, interpretations and productivity values. The USDA Natural Resources Conservation Service (NRCS, formerly Soil Conservation Service) provides a download of the statewide SSURGO database that includes vector and raster spatial data, database tables and their relationship classes, and a user guide. To access SSURGO, go to the USDA NRCS Geospatial Data Gateway. To download the database, on the right side of the page, click on the Direct Data Download link under, I Want To... The Direct Data / NAIP Download page will then open. Click on the Soils Geographic Databases link. Then click on the folder named gSSURGO by State (date in folder name). Scroll through the list and select gSSURGO_NJ.zip. Then click on the Download button on the upper right. A message will open that Your Download is In Progress. You will then be prompted to select a file download location.

Background HealthCyberMap aims at mapping parts of health information cyberspace in novel ways to deliver a semantically superior user experience. This is achieved through "intelligent" categorisation and interactive hypermedia visualisation of health resources using metadata, clinical codes and GIS. HealthCyberMap is an ArcView 3.1 project. WebView, the Internet extension to ArcView, publishes HealthCyberMap ArcView Views as Web client-side imagemaps. The basic WebView set-up does not support any GIS database connection, and published Web maps become disconnected from the original project. A dedicated Internet map server would be the best way to serve HealthCyberMap database-driven interactive Web maps, but is an expensive and complex solution to acquire, run and maintain. This paper describes HealthCyberMap simple, low-cost method for "patching" WebView to serve hypermaps with dynamic database drill-down functionality on the Web.

   Results
   The proposed solution is currently used for publishing HealthCyberMap GIS-generated navigational information maps on the Web while maintaining their links with the underlying resource metadata base.


   Conclusion
   The authors believe their map serving approach as adopted in HealthCyberMap has been very successful, especially in cases when only map attribute data change without a corresponding effect on map appearance. It should be also possible to use the same solution to publish other interactive GIS-driven maps on the Web, e.g., maps of real world health problems.

The California Natural Resources Agency’s Access for All Initiative and 30x30 set a goal of equitable access for all to the state’s natural and open spaces. This dashboard helps illustrate the current challenges and highlights opportunities.

The Access Explorer shows statewide measures of the population living within a half mile of any open space such as a park with public access contained within the Conserved Areas database, whether it meets the 30x30 definition of conserved or not.

You can then compare those measures to areas that meet the 30x30 definition or to the population overall.

The Access Explorer is a work in progress. Enhancements will be informed by an Outdoors for All roadmap due out in early 2023.

The demographics were compiled from 'https://doc.arcgis.com/en/esri-demographics/' target='_blank' rel='nofollow ugc noopener noreferrer'>ESRI Demographics in March 2022.

This dataset supports the research article "From GIS to HBIM and Back: Multiscale Performance and Condition Assessment for Networks of Public Heritage Buildings and Construction Components" and includes:

• Data Structure (Excel file) → A structured database containing attribute information about historic buildings, based on the Italian regulatory provisions for the assessment and reduction of seismic risk in the national cultural heritage (Ministero della Cultura, 2008).
• Python Scripts → Custom scripts developed for data processing and interoperability between GIS and HBIM environments.
• Dynamo Revit Scripts → Visual programming scripts designed for automated data transfer and integration between GIS and HBIM.

The Dynamo Revit scripts (e.g. Import DB_Module C_Floors.dyn in DYNAMO.zip) originally contained a database connection string, which has been removed for security reasons.
To use the script with a database, users should manually input their connection string in the appropriate section of the script, following this format:
Server=your_server_address; Database=your_database; Uid=your_username; Pwd=your_password.

Laatste update: 07 december 2023Er zijn verschillende manieren om vanuit ArcGIS een verbinding te maken met een database. Om te verbinden met een Oracle Database is het mogelijk om gebruik te maken van Oracle Easy Connect.Alle Esri producten die verbinding kunnen maken met een database kunnen met Easy Connect werken, dus ook bijvoorbeeld ArcGIS Pro en ArcGIS Server. Hiervoor is het wel belangrijk dat Oracle zodanig is geconfigureerd dat dit mogelijk is. Wanneer er gekozen is voor een full install van de Oracle client moet het sqlnet.ora bestand zodanig geconfigureerd worden dat Easy Connect mogelijk is. De Oracle server moet geconfigureerd zijn om Easy Connect syntax te accepteren.

City of Penticton external Production web service published to the external folder on server. Source of the water layer in the External Production Web Map on ArcGIS Online. This mxd is based on the water editing template from ArcGIS solutions. The database schema is based on the Canadian Local Government Data Model. Version 1.0 Data source is CITYGIS02(PRD)

This packaged data collection contains two sets of two additional model runs that used the same inputs and parameters as our primary model, with the exception being we implemented a "maximum corridor length" constraint that allowed us to identify and visualize the corridors as being well-connected (≤15km) or moderately connected (≤45km). This is based on an assumption that corridors longer than 45km are too long to sufficiently accommodate dispersal. One of these sets is based on a maximum corridor length that uses Euclidean (straight-line) distance, while the other set is based on a maximum corridor length that uses cost-weighted distance. These two sets of corridors can be compared against the full set of corridors from our primary model to identify the remaining corridors, which could be considered poorly connected. This package includes the following data layers: Corridors classified as well connected (≤15km) based on Cost-weighted Distance Corridors classified as moderately connected (≤45km) based on Cost-weighted Distance Corridors classified as well connected (≤15km) based on Euclidean Distance Corridors classified as moderately connected (≤45km) based on Euclidean Distance Please refer to the embedded metadata and the information in our full report for details on the development of these data layers. Packaged data are available in two formats: Geodatabase (.gdb): A related set of file geodatabase rasters and feature classes, packaged in an ESRI file geodatabase. ArcGIS Pro Map Package (.mpkx): The same data included in the geodatabase, presented as fully-symbolized layers in a map. Note that you must have ArcGIS Pro version 2.0 or greater to view. See Cross-References for links to individual datasets, which can be downloaded in raster GeoTIFF (.tif) format.

This site provides access to download an ArcGIS geodatabase or shapefiles for the 2017 Texas Address Database, compiled by the Center for Water and the Environment (CWE) at the University of Texas at Austin, with guidance and funding from the Texas Division of Emergency Management (TDEM). These addresses are used by TDEM to help anticipate potential impacts of serious weather and flooding events statewide. This is part of the Texas Water Model (TWM), a project to adapt the NOAA National Water Model [1] for use in Texas public safety. This database was compiled over the period from June 2016 to December 2017. A number of gaps remain (towns and cities missing address points), see Address Database Gaps spreadsheet below [4]. Additional datasets include administrative boundaries for Texas counties (including Federal and State disaster-declarations), Councils of Government, and Texas Dept of Public Safety Regions. An Esri ArcGIS Story Map [5] web app provides an interactive map-based portal to explore and access these data layers for download.

The address points in this database include their "height above nearest drainage" (HAND) as attributes in meters and feet. HAND is an elevation model developed through processing by the TauDEM method [2], built on USGS National Elevation Data (NED) with 10m horizontal resolution. The HAND elevation data and 10m NED for the continental United States are available for download from the Texas Advanced Computational Center (TACC) [3].

The complete statewide dataset contains about 9.28 million address points representing a population of about 28 million. The total file size is about 5GB in shapefile format. For better download performance, the shapefile version of this data is divided into 5 regions, based on groupings of major watersheds identified by their hydrologic unit codes (HUC). These are zipped by region, with no zipfile greater than 120mb: - North Tx: HUC1108-1114 (0.52 million address points) - DFW-East Tx: HUC1201-1203 (3.06 million address points) - Houston-SE Tx: HUC1204 (1.84 million address points) - Central Tx: HUC1205-1210 (2.96 million address points) - Rio Grande-SW Tx: HUC2111-1309 (2.96 million address points)

Additional state and county boundaries are included (Louisiana, Mississippi, Arkansas), as well as disaster-declaration status.

Compilation notes: The Texas Commission for State Emergency Communications (CSEC) provided the first 3 million address points received, in a single batch representing 213 of Texas' 254 counties. The remaining 41 counties were primarily urban areas comprising about 6.28 million addresses (totaling about 9.28 million addresses statewide). We reached the GIS data providers for these areas (see Contributors list below) through these emergency communications networks: Texas 9-1-1 Alliance, the Texas Emergency GIS Response Team (EGRT), and the Texas GIS 9-1-1 User Group. The address data was typically organized in groupings of counties called Councils of Governments (COG) or Regional Planning Commissions (RPC) or Development Councils (DC). Every county in Texas belongs to a COG, RPC or DC. We reconciled all counties' addresses to a common, very simple schema, and merged into a single geodatabase.

November 2023 updates: In 2019, TNRIS took over maintenance of the Texas Address Database, which is now a StratMap program updated annually [6]. In 2023, TNRIS also changed its name to the Texas Geographic Information Office (TxGIO). The datasets available for download below are not being updated, but are current as of the time of Hurricane Harvey.

References: [1] NOAA National Water Model [https://water.noaa.gov/map] [2] TauDEM Downloads [https://hydrology.usu.edu/taudem/taudem5/downloads.html] [3] NFIE Continental Flood Inundation Mapping - Data Repository [https://web.corral.tacc.utexas.edu/nfiedata/] [4] Address Database Gaps, Dec 2017 (download spreadsheet below) [5] Texas Address and Base Layers Story Map [https://www.hydroshare.org/resource/6d5c7dbe0762413fbe6d7a39e4ba1986/] [6] TNRIS/TxGIO StratMap Address Points data downloads [https://tnris.org/stratmap/address-points/]

[Metadata] Description: Location of public shoreline access ways on Oahu as of 2008. June 2024: Hawaii Statewide GIS Program staff removed extraneous fields that had been added as part of a 2016 GIS database conversion and were no longer needed. For additional information, please refer to metadata at https://files.hawaii.gov/dbedt/op/gis/data/shoreline_public_access_oah.pdf or contact Hawaii Statewide GIS Program, Office of Planning, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.

Tempe Census Census Tracts and internet access by household. Data source: U.S. Census Bureau, 2013-2017 American Community Survey 5-Year Estimates, table BD28011 (Internet Subscription in Household). Also includes "low response scores" from the the Census Bureau's data from the 2018 Planning Database (PDB), which was established to prepare for the upcoming 2020 Census.For more information on the low response score, see the United States Census Bureau 2018 Planning Database:https://www.census.gov/topics/research/guidance/planning-databases.htmlLayer generally supports 2020 Census story map Ensuring a Complete Count in the 2020 Census.

The important attributes are nzsegment (primary key), which can be used to join the watershed polygons to the river network, and the old_nzreach (which can be used to retrieve values from REC1 river classification, and other previously calculated properties). The shape_area gives the area of the watershed in meters squared. REC2 (River Environment Classification, v2.3)The River Environment Classification (REC) is a database of catchment spatial attributes, summarised for every segment in New Zealand's network of rivers. The attributes were compiled for the purposes of river classification, while the river network description has been used to underpin models.Typically, models (e.g. CLUES and TopNet) would use the dendritic (branched) linkages of REC river segments to perform their calculations. Since its release and use over the last decade, some errors in the location and connectivity of these linkages have been identified. The current revision corrects those errors, and updates a number of spatial attributes with the latest data.REC2 provides a recut framework of rivers for modelling and classification. It is built on a newer version of the 30m digital elevation model, in which the original 20m contours were supplemented with, for example, more spot elevation data and a better coastline contour. Boundary errors were minimised by processing contiguous areas (such as the whole of the North Island) together, which wasn't possible a decade ago. Major updates include the revision of catchment land use information, by overlaying with the latest land cover database (LCDB3, current as at 2008), and the update of river and rainfall statistics with data from 1960-2006.The river network and associated attributes have been assembled within an ArcGIS geodatabase. Topological connectivity has been established to allow upstream and downstream tracing within the network. REC2 can be downloaded as a zip file and used directly in ArcMap. Alternatively, the layers can be extracted as shape files.NIWA acknowledges funding from the Terrestrial and Freshwater Biodiversity Information System (TFBIS) towards the preparation of REC v2.

The ZIP file consist of GIS files and an Access database with information about the excavations, findings and other metadata about the archaeological survey.

The ZIP file consist of GIS files and an Access database with information about the excavations, findings and other metadata about the archaeological survey.

A preliminary archaeological investigation was carried out on parcels Styrstad 11:6 and Agetomta 2:3 (Styrstad socken, Norrköping's municipality) in May 2005, in connection to the construction of a new villa. Several structures of unclear natures were discovered along with stone chips. These are probably connected to a now destroyed prehistoric settlement in the area. No further archaeological investigations were stipulated y Riksantikvarieämbetet UV Öst.

The ZIP file consist of GIS files and an Access database with information about the excavations, findings and other metadata about the archaeological survey.

The information in the abstract is translated from the archaeological report: Due to reconstruction of the power grid between mellan Åtvidaberg and Broddebo and on the property Domra in Västervik municipality, the Swedish National Heritage Board's contract archaeology division, UV Öst, has performed several preliminary investigations and stage 2 surveys in Gullebo, Mosshult and Broddebo, Gärserum parish, Åtvidaberg municipality, during summer and autunm of 2005. Two surveys have previously been performed in the area, in connection with rebuilding of the National Road 35. Prehistoric remains, such as graves, were discovered nearby the village sites of Gullebo, Mosshult och Broddebo during these surveys, as well as several potential settlement locations. The result showed a settlement site just north of Broddebo village. The current survey found, among other things, two hearths and a possible agricultural layer damaged by ploughing. UV Öst suggests no further archaeological measures since the trenching for the power lines could be made without affecting the archaeological remains.

Purpose:

The information in the purpose is translated from the archaeological report: The purpose of the preliminary investigation and the stage 2 survey, was to determine whether any archaeological remains were going to be affected by the planned trenching and, if possible, to try to avoid them. The results were going to form the basis for possible future decisions by the County Administrative Board concerning the matter.

The ZIP file consist of GIS files and an Access database with information about the excavations, findings and other metadata about the archaeological survey.

This database contains all of the LCRI monitoring protocol products.

Essential Facilities map service is published to GISPortal for various APPs such as WebEOC, Hurrtrak. Map service published on September 1, 2020.

FC was created and is maintained by BSO GIS Unit as a single source of facilities deemed essential by BSO. Used in apps & map services (i.e. POI). Useful for retrieving DLE Stations; Fire Stations; Jails; all BSO essential facilities. Useful in EOC, RTCC.Date Updated: 4/24/2020 Source: N/AMODIFICATIONS: removed HOSPITALrecs (EFCLASS=MEDICAL); added new BLDGTYPE "BSO DLE SUB STATION"; REFER TO Documentation.Coordinates: GCS_WGS_1984 Documentation: Update Essential Facilities Feature Class.docx .docx http://bsoteams.sheriff.bso/itd/gis/DOCS/ADMINISTRATION/Data%20Management/Data%20Source%20Updates/EssentialFacilities/

Mxd Location: \app2016share\MXD\AGENCYWIDE\Essential_Facilities.mxd

Data Type: SDE Feature Class Database Platform: SQL Server Server: GEODB Connection Properties: GEODB Authentication Type: Database authentication User name: gis Database: GIS Version: sde.DEFAULT Description: Instance default version. Feature Class: GIS.BSO.EssentialFacilitiesBSO Feature Type: Simple Geometry Type: Point Coordinates have Z values: No Coordinates have measures: No

Geographic Coordinate System: GCS_WGS_1984 Datum: D_WGS_1984 Prime Meridian: Greenwich Angular Unit: Degree