Ground response--GIS data, June 2010. Downloadable GIS data includes: One ESRI ArcGIS 9.3 geodatabase, consisting of a set of 4 feature classes; Metadata for each feature class, in HTML format (for ease of reading outside of GIS software); One ArcGIS map document (ending in the .mxd extension), containing specifications for data presentation in ArcMap; One ArcGIS layer file for each feature class (ending in the .lyr extension), containing specifications for data presentation in the free ArcGIS Explorer (as well as ArcMap); README file

The location of proposed water lines in public water systems in the Commonwealth of Kentucky. A proposed water line depicts a linear feature for which a water project is proposed. Proposed water lines are mapped for water line extension, upgrade, and rehab/replacement projects.

This dataset consists of long-term (less than 68 years) shoreline change rates for the exposed coast of the north coast of Alaska from Icy Cape to Cape Prince of Wales. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.4, an ArcGIS extension developed by the U.S. Geological Survey. Rates of shoreline change were calculated using a linear regression rate-of-change (lrr) method based on available shoreline data between 1948 and 2016. A reference baseline was used as the originating point for the orthogonal transects cast by the DSAS software. The transects intersect each shoreline establishing measurement points, which are then used to calculate shoreline change rates.

A catalogue service that conforms to the HTTP protocol binding of the OpenGIS Catalogue Service ISO Metadata Application Profile specification (version 2.0.2)

This dataset consists of short-term (~33 years) shoreline change rates for the north coast of Alaska between Point Barrow and Icy Cape. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using an end point rate-of-change method based on available shoreline data between 1979 and 2012. A reference baseline was used as the originating point for the orthogonal transects cast by the DSAS software. Transects intersect each shoreline establishing measurement points, which are then used to calculate short-term rates.

The data provided here denotes the authors’ revised service areas for a subset of 377 Public Housing Authorities (PHAs) for which HUD previously estimated service areas. Using HUD administrative data on the location of Housing Choice Voucher holders, HUD’s estimated service areas were revised to better capture voucher activity. Specifically, the authors developed two different tests and correction procedures. The first assesses if the estimated service area omits a sizable share of voucher holder locations (so is “too small”), and if so, adjusts to include census designated places or counties containing at least 5 percent of a PHA’s voucher holders. The second test checks whether the estimated service boundary includes areas the PHA does not appear to serve and that are clearly served by another PHA (so is “too large”), in this case adjusting by removing those areas. 148 of the 377 PHA estimated service areas were found to be too small, too large, or both, and so have revised service areas that differ from HUD’s estimated service areas. The detailed methodology is provided below. Additionally, a spreadsheet is supplied that identifies geographies that were added to and dropped from HUD’s estimated services to create the revised service areas for affected PHAs.

This is an experimental dataset that is designed to aid researchers in studying the HCV program. The methodology and the service areas themselves have not been validated by HUD’s Office of Public and Indian Housing (PIH) or the Public Housing Agencies. For additional discussion of the approach, see Tauber et al. (2024); please contact the authors with any questions or comments.Data Dictionary: DD_Extensions to Estimated Housing Authority Service Areas MethodologyMethodology: Extensions to Estimated Housing Authority Service Areas Methodology

Reference:Tauber, Kristen, Ingrid Gould Ellen, and Katherine O’Regan. 2024. “Whom Do We Serve? Refining Public Housing Agency Service Areas.” Cityscape 26(1) (2024): 395-400.

The location of proposed wastewater lines in public wastewater systems in the Commonwealth of Kentucky. A proposed wastewater line depicts a linear feature for which a wastewater project is proposed. Proposed wastewater lines are mapped for wastewater line extension, upgrade, and rehab/replacement projects.

Data set is a delination of groundwater basins in NM. Updated September 2005 with the declaration of all the existing declared basins by extension.

This dataset consists of rate-of-change statistics for the coastal bluffs at Barter Island, Alaska for the time period 1950 to 2020. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 5.0, an ArcGIS extension developed by the U.S. Geological Survey. A reference baseline was used as the originating point for the orthogonal transects cast by the DSAS software. The transects intersect each bluff line establishing measurement points, which are then used to calculate bluff-change rates.

The agsview extension for CKAN provides view plugins designed to display Esri ArcGIS Server data directly within CKAN resources. Specifically, it enables visualization of ArcGIS Map services and Feature layer services, leveraging an Esri Leaflet Viewer for interactive display. As such, this extension enhances CKAN by providing native support for displaying commonly used geospatial data formats, increasing the usability of CKAN for geospatial data catalogs through built-in rendering capabilities when used by your organization's CKAN end users. Key Features: ArcGIS Feature Layer Viewer (agsfsview): Allows visualization of ArcGIS Feature Layers found within either MapServices or FeatureServices, offering a means by which you or your end users can expose specific layers, enabling selective display of datasets. Configuration option: ags_url: Specifies the ArcGIS Server layer endpoint, including the layer ID for targeted data access ensuring the correct layer or service is connected to your CKAN resource. Configuration option: basemapurl: Allows customization of the basemap by specifying either an Esri basemap name or a generic tile URL template, to tailor the visual context of the displayed ArcGIS data. ArcGIS MapService Viewer (agsmsview): Provides functionality to render ArcGIS MapServices, giving control over which layers within the service are displayed. Configuration option: ags_url: Defines the ArcGIS Server MapService endpoint, directing the viewer to the desired MapService resource for inclusion in your CKAN resource. Configuration option: list_ids: Enables filtering of layers within the MapService by providing a comma-delimited list of layer IDs for selective display. An empty list will display all layers, offering you flexibility in configuring the data viewed in CKAN. Configuration option: basemapurl: Permits customization of the basemap, accepting either an Esri basemap name or a generic tile URL template, ensuring flexibility in the map presentation. Configurable Default Basemap: Using your CKAN .ini configuration, you can set a default basemap for all ArcGIS views, providing consistency and improving usability. You can specify either an Esri basemap name or a tile URL template as the default. Technical Integration: The agsview extension integrates with CKAN by adding view plugins (agsfsview and agsmsview). To enable the extension, you must add the plugin names to the ckan.plugins setting in the CKAN configuration file (e.g., production.ini). After updating you CKAN file, and restarting the CKAN instance, the ArcGIS viewers become available options when creating a CKAN resource in the 'View' section assuming the resource has URLs that are supported by the viewing feature. Benefits & Impact: By implementing the agsview extension, CKAN instances can natively display ArcGIS Server MapServices and Feature Layers, eliminating the need for external viewers or custom development. This significantly enhances CKAN's utility for organizations managing and sharing geospatial data, as users can readily visualize Esri ArcGIS data directly within the CKAN interface. The configuration options further allow for customization of the display, improving the user experience.

Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate orthogonal transects at a user-defined separation along the coast, and calculate rates of change (linear regression, endpoint rate, average of rates, average of endpoints, jackknife).

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. We converted the photointerpreted data into a GIS-usable format employing three fundamental processes: (1) orthorectify, (2) digitize, and (3) develop the geodatabase. All digital map automation was projected in Universal Transverse Mercator (UTM) projection, Zone 16, using North American Datum of 1983 (NAD83). To produce a polygon vector layer for use in ArcGIS, we converted each raster-based image mosaic of orthorectified overlays containing the photointerpreted data into a grid format using ArcGIS (Version 9.2, © 2006 Environmental Systems Research Institute, Redlands, California). In ArcGIS, we used the ArcScan extension to trace the raster data and produce ESRI shapefiles. We digitally assigned map attribute codes (both map class codes and physiognomic modifier codes) to the polygons, and checked the digital data against the photointerpreted overlays for line and attribute consistency. Ultimately, we merged the individual layers into a seamless layer of INDU and immediate environs. At this stage, the map layer has only map attribute codes assigned to each polygon. To assign meaningful information to each polygon (e.g., map class names, physiognomic definitions, link to NVC association and alliance codes), we produced a feature class table along with other supportive tables and subsequently related them together via an ArcGIS Geodatabase. This geodatabase also links the map to other feature class layers produced from this project, including vegetation sample plots, accuracy assessment sites, and project boundary extent. A geodatabase provides access to a variety of interlocking data sets, is expandable, and equips resource managers and researchers with a powerful GIS tool.

PBOT often requires the construction of curb extension when corners are reconstructed. This dataset delineates Portland street segments which are exempted from curb extension construction (TRN 1.28 -- Curb Extensions for Building and Planning Actions).-- Additional Information: Category: Transportation - Right of Way Mgmt Purpose: Identify street segments exempted from curb extension construction. Update Frequency: As Needed-- Metadata Link: https://www.portlandmaps.com/metadata/index.cfm?&action=DisplayLayer&LayerID=54718

eXtension Foundation, the University of New Hampshire, and Virginia Tech have developed a mapping and data exploration tool to assist Cooperative Extension staff and administrators in making strategic planning and programming decisions. The tool, called the National Extension Web-mapping Tool (or NEWT), is the key in efforts to make spatial data available within cooperative extension system. NEWT requires no GIS experience to use. NEWT provides access for CES staff and administrators to relevant spatial data at a variety of scales (national, state, county) in useful formats (maps, tables, graphs), all without the need for any experience or technical skills in Geographic Information System (GIS) software. By providing consistent access to relevant spatial data throughout the country in a format useful to CES staff and administrators, NEWT represents a significant advancement for the use of spatial technology in CES. Users of the site will be able to discover the data layers which are of most interest to them by making simple, guided choices about topics related to their work. Once the relevant data layers have been chosen, a mapping interface will allow the exploration of spatial relationships and the creation and export of maps. Extension areas to filter searches include 4-H Youth & Family, Agriculture, Business, Community, Food & Health, and Natural Resources. Users will also be able to explore data by viewing data tables and graphs. This Beta release is open for public use and feedback. Resources in this dataset:Resource Title: Website Pointer to NEWT National Extension Web-mapping Tool Beta. File Name: Web Page, url: https://www.mapasyst.org/newt/ The site leads the user through the process of selecting the data in which they would be most interested, then provides a variety of ways for the user to explore the data (maps, graphs, tables).

Open the Data Resource: https://doi.org/10.5066/P9EJ6PGT The marsh-forest boundary in the Chesapeake Bay was determined by geoprocessing high-resolution (1 square meter) land use and land cover data sets. Perpendicular transects were cast at standard intervals (30 meters) along the boundary within a GIS by repurposing the Digital Shoreline Analysis System (DSAS) Version 5.0, an ArcGIS extension developed by the U.S. Geological Survey. Average and maximum slope values were assigned to each transect from surface elevation data. The same values were also provided as points at the center of the transect where it crossed over the boundary. The slope values across the marsh-forest transition zone and at the boundary itself provide comprehensive data layers for local, state and federal managers to improve understanding of salt marsh migration. This additionally aids the U.S. Geological Survey in its effort to assess the coastal vulnerability and response of salt marsh ecosystems, including the Chesapeake Bay region.

The Washington State Surface Geology Map scale at a scale of 1:24,000 geodatabase was made accessible through the Washington State Department of Natural Resources, Division of Geology and Earth Resources. The data are provided in ESRI ArcGIS 10.0 file geodatabase format (see Read Me file). The projection is in Lambert Conformal Conic, NAD83 HARN datum. Data available for download include:- One ESRI ArcGIS 10.0 geodatabase, consisting of a set of 11 feature classes, 7 relationship classes, and one geodatabase table.- Metadata for each feature class, in both XML and HTML formats (for ease of reading outside of GIS software)- One shapefile depicting the outline of Washington State.- One ArcGIS map document (ending in the .mxd extension), containing specifications for data presentation in ArcMap- One ArcGIS layer file for each feature class (ending in the .lyr extension), containing specifications for data presentation in an ArcGIS viewing application- One Geologic Map Codes document (PDF) defining the symbology used in the map.- The README file These digital data and metadata are provided as is, as available, and with all faults basis. Neither Department of Natural Resources nor any of its officials and employees makes any warranty of any kind for this information, express or implied, including but not limited to any warranties of merchantability or fitness for a particular purpose, nor shall the distribution of this information constitute any warranty. This resource was provided by the Washington State Department of Natural Resources, Division of Geology and Earth Resources and made available for distribution through the National Geothermal Data System.

This dataset consists of short-term (less than 39 years) shoreline change rates for the mainland coast of Alaska sheltered by barrier islands from the Hulahula River to the Colville River. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 5.1, an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1979 and 2017. A reference baseline was used as the originating point for the orthogonal transects cast by the DSAS software. The transects intersect each shoreline establishing measurement points, which are then used to calculate short-term rates.

Charlottesville is well located for onsite solar power energy generation. This dataset shows an estimate of solar energy generation potential for rooftop solar PV systems in Charlottesville, VA. This data was created using LiDAR data, the Area Solar Radiation tool available with the ArcGIS Spatial Analyst extension, and local market estimations for cost and PV panel production potentials.

For more information check out our website, as well as this ESRI page describing the process.

This map consists of short-term (~50 years) shoreline change rates for the lower 48 states of the United States and Hawaii. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.1, an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change for the lower 48 states were calculated using an end-point rate method based on shorelines from 1970 or 1978 and 2000 to provide an approximately 30-yr short-term rate. Short-term rates of shoreline change for Hawaii were calculated using a weighted linear regression rate based on all available shoreline data between 1950 and 2008. A reference baseline was used as the originating point for the orthogonal transects cast by the DSAS software. The transects intersect each shoreline establishing measurement points, which are then used to calculate short-term rates.

Link to the ScienceBase Item Summary page for the item described by this metadata record. Service Protocol: Link to the ScienceBase Item Summary page for the item described by this metadata record. Application Profile: Web Browser. Link Function: information