Seattle Parks and Recreation ARCGIS park feature map layer web services are hosted on Seattle Public Utilities' ARCGIS server. This web services URL provides a live read only data connection to the Seattle Parks and Recreations Hand Carry Boat Launch dataset.

This dataset is complementary to the “Deforestation-corrected SRTM-DEM” and “Height above the nearest drainage (HAND) dataset for eighteen drainage thresholds” dataset, also available in this repository. This mask of polygons delimits areas inside and outside the Interfluve between the rivers Purus and Madeira where validations of the drainage extraction were not done and deforestation features were not corrected.

This dataset provides a map that shows contours for likely flood extent related to elevation within a watershed. The files were generated using a commonly accepted approach to terrain-based analyses for determining flood extent, called Height Above Natural Drainage (HAND), to analyze terrain information in the dataset . The complete 126 file set includes watersheds based on the national HUC-12 (Hydrologic Unit Code). Files are named using the unique HUC-12 code identifier used by the US Geological Survey (https://water.usgs.gov/GIS/huc.html). Each datafile is formatted as a raster GeoTIFF derived from 1-meter LIDAR https://tnris.org/stratmap/elevation-lidar/ Datasets were generated using the HAND-TauDEM workflow that can be accessed publicly in a github repository at https://github.com/dhardestylewis/HAND-TauDEM Files were processed using open-source software, including TauDEM and Python GIS libraries. Data was discretized in one foot intervals (1 ft ~= 0.3048 m) in order to reduce file size (see separate dataset for raw Height Above Nearest Drainage). (2021-03-25)

The Interim Digital Geologic-GIS Map of Arches National Park and Vicnity, Utah is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data format: 1.) a 10.1 file geodatabase (arch_geology.gdb). The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (arch_geology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (arch_geology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). Upon request, the GIS data is also available in ESRI 10.1 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, two additional files comprise a GRI digital geologic-GIS dataset or map: 1.) A GIS readme file (arch_geology_gis_readme.pdf), and 2.) a user-friendly FAQ PDF version of the metadata (arch_geology_metadata_faq.pdf). Please read the arch_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. 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: 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: Utah Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (arch_geology_metadata.txt or arch_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 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).

Summary This feature class documents the fire history on CMR from 1964 - present. This is 1 of 2 feature classes, a polygon and a point. This data has a variety of different origins which leads to differing quality of data. Within the polygon feature class, this contains perimeters that were mapped using a GPS, hand digitized, on-screen digitized, and buffered circles to the estimated acreage. These 2 files should be kept together. Within the point feature class, fires with only a location of latitude/longitude, UTM coordinate, TRS and no estimated acreage were mapped using a point location. GPS started being used in 1992 when the technology became available. Records from FMIS (Fire Management Information System) were reviewed and compared to refuge records. Polygon data in FMIS only occurs from 2012 to current and many acreage estimates did not match. This dataset includes ALL fires no matter the size. This feature class documents the fire history on CMR from 1964 - present. This is 1 of 2 feature classes, a polygon and a point. This data has a variety of different origins which leads to differing quality of data. Within the polygon feature class, this contains perimeters that were mapped using a GPS, hand digitized, on-screen digitized, and buffered circles to the estimated acreage. These 2 files should be kept together. Within the point feature class, fires with only a location of latitude/longitude, UTM coordinate, TRS and no estimated acreage were mapped using a point location. GPS started being used in 1992 when the technology became available. Data origins include: Data origins include: 1) GPS Polygon-data (Best), 2) GPS Lat/Long or UTM, 3)TRS QS, 4)TRS Point, 6)Hand digitized from topo map, 7) Circle buffer, 8)Screen digitized, 9) FMIS Lat/Long. Started compiling fire history of CMR in 2007. This has been a 10 year process.FMIS doesn't include fires polygons that are less than 10 acres. This dataset has been sent to FMIS for FMIS records to be updated with correct information. The spreadsheet contains 10-15 records without spatial information and weren't included in either feature class. Fire information from 1964 - 1980 came from records Larry Eichhorn, BLM, provided to CMR staff. Mike Granger, CMR Fire Management Officer, tracked fires on an 11x17 legal pad and all this information was brought into Excel and ArcGIS. Frequently, other information about the fires were missing which made it difficult to back track and fill in missing data. Time was spent verifiying locations that were occasionally recorded incorrectly (DMS vs DD) and converting TRS into Lat/Long and/or UTM. CMR is divided into 2 different UTM zones, zone 12 and zone 13. This occasionally caused errors in projecting. Naming conventions caused confusion. Fires are frequently names by location and there are several "Soda Creek", "Rock Creek", etc fires. Fire numbers were occasionally missing or incorrect. Fires on BLM were included if they were "Assists". Also, fires on satellite refuges and the district were also included. Acreages from GIS were compared to FMIS acres. Please see documentation in ServCat (URL) to see how these were handled.

This is a simple graphic that was deemed to be pleasant for use in our Hub Site.

URL: https://web.corral.tacc.utexas.edu/nfiedata/pin2flood/texas/ The current National Water Model and its Flood Inundation Mapping (FIM) service use 10-meter Height Above Nearest Drainage (HAND) hydrological terrain. In the Pin2Flood project (https://gis.tdem.texas.gov/portal/apps/storymaps/stories/72f0ec81a7654da688518f486122abed), funded by the Texas Division of Emergency Management (TDEM), ORNL computed the 3-meter HAND and associated synthetic rating curves for the State of Texas, covering 287,535 river streams (1.5km/stream) in 209 HUC8s. This archived dataset includes the HAND raster and the synthetic rating curve table for each of the 209 HUC8s in Texas. It is hosted at the Texas Advanced Computing Center (TACC). This 3-meter HAND is derived from the Fathom 3-meter DEM and NHDPlus V21 using an accelerated version of NOAA's Flood Inundation Mapping version 3 (FIM3, https://github.com/NOAA-OWP/inundation-mapping/tree/dev-fim3)

This layer depicts polygons representing land within the Treasure Valley Model boundary classified as either "irrigated", "non-irrigated" or "semi-irrigated", where the semi-irrigated classification typically depicts residential land. The original line work that was used as a basis to create this dataset, is the Farm Service Agency’s (FSA) 2014 Common Land Unit (CLU) dataset. Field boundaries were then further refined using National Agriculture Imagery Program (NAIP) imagery, Digital Ortho Photo Quadrangle (DOQQ) imagery, or other high resolution imagery. Attribute assignments for irrigation status (irrigated, non-irrigated, and semi-irrigated) are determined using available Landsat imagery as background reference. Landsat imagery is typically 30-meter (Landsat5) or 15-meter (Landsat7) resolution. National Agriculture Inventory Program (NAIP) imagery, Digital Ortho Photo Quadrangle (DOQQ) imagery, and other in-house, scanned aerial imagery is used for determining irrigation status and refining the polygon geometry. The interpretation and classification process is described in detail in the report, "2006 Irrigated Land Classification for the Eastern Snake Plain Aquifer" archived on the IDWR website: Legal Actions > Delivery Call Actions > SWC > Archived Matters > Technical Working Group Documents (https://idwr.idaho.gov/legal-actions/delivery-call-actions/SWC/archived-matters.html#twg-documents)

This dataset (lineaments_ln_ll.shp) comprises structural features compiled into GIS format from existing literature, published up to 2003. The data represent fault/lineament locations known or inferred in the Alberta Plains. We have chosen to digitize and publish all lineaments from source maps even where they extended beyond the Alberta boundary. Each compiled feature is characterized by a set of attributes including: affected formations (oldest affected and oldest non-affected stratigraphic unit), fault type, fault sense of displacement, evidence used to infer the fault/lineament, original reference information and publication scale, and an estimate of the georeferencing error. The completeness of the captured attribute set varies for each feature as a function of the level of detail in the source article. The data set should be used cautiously. First, the original authors' interpretation of subsurface faults, particularly of 'basement faults', from air photo or satellite imagery lineaments is tenuous. Second, the vast majority of faults inferred in the foreland basin (Alberta Plains) east of the deformation front are normal-slip faults. although only the dip slip component has been inferred, some of these faults may also have a strike-slip component, generally not accounted for. Third, the location of lineaments includes cumulative errors inherent in the process of transferring into GIS lineaments traced by hand in the pre-computer era on small scale (regional) paper-copy maps. Such errors include spatial imprecisions in original lineament identification and drawing and errors in georefencing of the source map, as well as minor errors introduced during lineament digitization. Although each of them is minor at the scale of the original map, the cumulative effect of these errors may be significant and even misleading for large-scale (township or larger) projects.

*The data for this dataset is updated daily. The date(s) displayed in the details section on our Open Data Portal is based on the last date the metadata was updated and not the refresh date of the data itself.*Database of hand samples, stored in FGS Wells database. Samples are located at 3000 Commonwealth Blvd or the FGS Repository

River hydraulic geometry is an important input to hydraulic and hydrologic models that route flow along streams, determine the relationship between stage and discharge, and map the potential for flood inundation give the flow in a stream reach. Traditional approaches to quantify river geometry have involved river cross-sections, such as are required for input to the HEC-RAS model. Extending such cross-section based models to large scales has proven complex, and, in this presentation, an alternative approach, the Height Above Nearest Drainage, or HAND, is described. As we have implemented it, HAND uses multi-directional flow directions derived from a digital elevation model (DEM) using the Dinifinity method in TauDEM software (http://hydrology.usu.edu/taudem) to determine the height of each grid cell above the nearest stream along the flow path from that cell to the stream. With this information, and the depth of flow in the stream, the potential for and depth of flood inundation can be determined. Furthermore, by dividing streams into reaches or segments, the area draining to each reach can be isolated and a series of threshold depths applied to the grid of HAND values in that isolated reach catchment, to determine inundation volume, surface area and wetted bed area. Dividing these by length yields reach average cross section area, width, and wetted perimeter. Together with slope (also determined from the DEM) and roughness (Manning's n) these provide all the inputs needed for establishing a Manning's equation uniform flow assumption stage-discharge rating curve and for mapping potential inundation from discharge. This presentation will describe the application of this approach across the continental US in conjunction with NOAA’s National Water Model for prediction of stage and flood inundation potential in each of the 2.7 million reaches of the National Hydrography Plus (NHDPlus) dataset, the vast majority of which are ungauged. The continental US scale application has been enabled through the use of high performance parallel computing at the National Center for Supercomputing Applications (NCSA) and the CyberGIS Center at the University of Illinois.

Presentation at 2018 AWRA Spring Specialty Conference: Geographic Information Systems (GIS) and Water Resources X, Orlando, Florida, April 23-25, http://awra.org/meetings/Orlando2018/.

[Metadata] Description: Land Study Bureau's Detailed Agricultural land productivity ratings for Kauai, Oahu, Maui, Molokai, Lanai and Hawaii. Source: Land Study Bureau's Detailed Land Classification, 1965-1972. Aerial Photos hand drafted onto paper overlays of the U.S.G.S., 1:24,000 topographic and orthophoto quads. Ratings were developed for both over-all productivity, and for specific crops. This layer represents only the over-all productivity ratings.May 2024: Hawaii Statewide GIS Program staff removed extraneous fields that had been added as part of the 2016 GIS database conversion and were no longer needed.For more information, please refer to metadata at https://files.hawaii.gov/dbedt/op/gis/data/lsb.pdf or contact Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.

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/]

This database was prepared using a combination of materials that include aerial photographs, topographic maps (1:24,000 and 1:250,000), field notes, and a sample catalog. Our goal was to translate sample collection site locations at Yellowstone National Park and surrounding areas into a GIS database. This was achieved by transferring site locations from aerial photographs and topographic maps into layers in ArcMap. Each field site is located based on field notes describing where a sample was collected. Locations were marked on the photograph or topographic map by a pinhole or dot, respectively, with the corresponding station or site numbers. Station and site numbers were then referenced in the notes to determine the appropriate prefix for the station. Each point on the aerial photograph or topographic map was relocated on the screen in ArcMap, on a digital topographic map, or an aerial photograph. Several samples are present in the field notes and in the catalog but do not correspond to an aerial photograph or could not be found on the topographic maps. These samples are marked with “No” under the LocationFound field and do not have a corresponding point in the SampleSites feature class. Each point represents a field station or collection site with information that was entered into an attributes table (explained in detail in the entity and attribute metadata sections). Tabular information on hand samples, thin sections, and mineral separates were entered by hand. The Samples table includes everything transferred from the paper records and relates to the other tables using the SampleID and to the SampleSites feature class using the SampleSite field.

This oblique aerial photograph from the Lake Andes Wetland Management District was taken from Cahalan WPA in Harding County, SD in 1967. The photograph shows two sets of brood ponds. It is not intended for GIS use.

This vector dataset contains FAO processed administrative boundaries from multiple sources, produced in 2022 for the Hand-in-Hand Initiative Geospatial Platform publishing. The data was sourced and processed from the United Nations second administrative level boundaries (UN-SALB) programme, complemented with Hand-in-Hand Initiative and geospatial platform data from official geospatial data producers. Country boundaries are processed against UN official recognized borders (UN-map 2018), administrative subdivision checked for geometry a topology, validated, and corrected. Attributes are standardized to the UN-SALB programme schema and coding system. Processed by UN-FAO-CSI AgroInformatics geospatial analysis team, the data is used for thematic mapping, geospatially enabled statistics location-based integration, and Hand-in-Hand geospatial analysis (GIS-MCDA, suitability/location analysis, agricultural typologies, zonal statistics extraction).

Get an introduction to the basic components of a GIS. Learn fundamental concepts that underlie the use of a GIS with hands-on experience with maps and geographic data.

Data was hand drawn on USGS Topographic quads by foresters of the Vermont Department of Forests, Parks, & Recreation using orthophotos, survey data, and personal knowledge of the area as references.

This application replaces the legacy ParcelViewer platform (retired 8/8/2025) and offers an enhanced, mobile-friendly interface.

Key features include:

• Property lookups by address, owner, or parcel ID
• Zoning and land use information
• Historical aerial imagery — VGIN Orthoimagery, from the Virginia Base Mapping Program (VBMP)
  • 2002
  • 2007
  • 2011
  • 2015
  • 2018
  • 2022
• Deatils about property valuations, ownership history, and improvement information
• Public school districts, voting precincts, and emergency service zones
• Environmental layers, hydrography, utility data, and more

Note: The application opens to a login screen, but public access is available—just click through the disclaimer to continue.

Mobile compatible — works on modern browsers including Chrome, Firefox, and Edge.

Need help? Use the Help link in the left-hand menu once inside the app. You’ll also find a feedback form there or access it directly here: iGIS Feedback Survey.

Data updates: Real estate and parcel data is updated monthly, with plans to increase update frequency in the future.

The integration of citizen science, volunteered geographic information (VGI), and Web/mobile geographic information systems (GIS) has demonstrated significant potential in enhancing disaster response efforts. However, delivering timely, comprehensive and trustworthy information remains a major challenge, particularly when relying on passive data collection from social media. While researchers have developed specialized platforms for natural hazards and advanced models for data analysis, few studies present a holistic lifecycle from stakeholder-oriented design through development, especially with attention to the design phase. To address this gap, this paper introduces an agile and iterative user-centered framework for designing and developing a participatory mobile GIS application for collecting reliable, first-hand observations. A pilot study conducted during real-world hurricane events demonstrated the application’s ability to operate both in real time and offline, enabling the collection of precise geotagged data, categorized labels, and diverse media formats. The results highlight the potential of this active, stakeholder-centered approach to support intelligent disaster response strategies and complement passive and authoritative data sources. This paper advances the integration of citizen science and mobile GIS by providing a framework that follows user-centered design principles to inform future disaster response applications.