The USGS, in cooperation with the U.S. Bureau of Land Management (BLM), created a series of geospatial mapping products of the Scotts Creek Watershed in Lake County, California, using National Agriculture Imagery Program (NAIP) imagery from 2018, 2020 and 2022 and Open Street Map (OSM) from 2019. The imagery was downloaded from United States Department of Agriculture (USDA) - Natural Resources Conservation Service (NRCS) Geospatial Data Gateway (https://datagateway.nrcs.usda.gov/) and Geofabrik GmbH - Open Street Map (https://www.geofabrik.de/geofabrik/openstreetmap.html), respectively. The imagery was classified using Random Forest (RF) Modeling to produce land cover maps with three main classifications - bare, vegetation, and shadows. An updated roads and trails map for the Upper Scotts Creek Watershed, including the BLM Recreational Area, was created to estimate road and trail densities in the watershed. Separate metadata records for each product (Land_Cover_Maps_Scotts_Cree ...

This dataset was acquired from the USGS dataset accessed through the USDA Geospatial Data Gateway. It is a polygon shapefile representing the generalized geology of the US state of Texas.

The vertical land change activity focuses on the detection, analysis, and explanation of topographic change. These detection techniques include both quantitative methods, for example, using difference metrics derived from multi-temporal topographic digital elevation models (DEMs), such as, light detection and ranging (lidar), National Elevation Dataset (NED), Shuttle Radar Topography Mission (SRTM), and Interferometric Synthetic Aperture Radar (IFSAR), and qualitative methods, for example, using multi-temporal aerial photography to visualize topographic change. The geographic study area of this activity is Perry County, Kentucky. Available multi-temporal lidar, NED, SRTM, IFSAR, and other topographic elevation datasets, as well as aerial photography and multi-spectral image data were identified and downloaded for this study area county. Available mine maps and mine portal locations were obtained from the Kentucky Mine Mapping Information System, Division of Mine Safety, 300 Sower Boulevard, Frankfort, KY 40601 at http://minemaps.ky.gov/Default.aspx?Src=Downloads. These features were used to spatially locate the study areas within Perry County. Previously developed differencing methods (Gesch, 2006) were used to develop difference raster datasets of NED/SRTM (1950-2000 date range) and SRTM/IFSAR (2000-2008 date range). The difference rasters were evaluated to exclude difference values that were below a specified vertical change threshold, which was applied spatially by National Land Cover Dataset (NLCD) 1992 and 2006 land cover type, respectively. This spatial application of the vertical change threshold values improved the overall ability to detect vertical change because threshold values in bare earth areas were distinguished from threshold values in heavily vegetated areas. Lidar high-resolution (1.5 m) DEMs were acquired for Perry County, Kentucky from U.S. Department of Agriculture, Natural Resources Conservation Service Geospatial Data Gateway at https://gdg.sc.egov.usda.gov/GDGOrder.aspx#. ESRI Mosaic Datasets were generated from lidar point-cloud data and available topographic DEMs for the specified study area. These data were analyzed to estimate volumetric changes on the land surface at three different periods with lidar acquisitions collected for Perry County, KY on 3/29/12 to 4/6/12. A recent difference raster dataset time span (2008-2012 date range) was analyzed by differencing the Perry County lidar-derived DEM and an IFSAR-derived dataset. The IFSAR-derived data were resampled to the resolution of the lidar DEM (approximately 1-m resolution) and compared with the lidar-derived DEM. Land cover based threshold values were applied spatially to detect vertical change using the lidar/IFSAR difference dataset. Perry County lidar metadata reported that the acquisition required lidar to be collected with an average of 0.68 m point spacing or better and vertical accuracy of 15 cm root mean square error (RMSE) or better. References: Gesch, Dean B., 2006, An inventory and assessment of significant topographic changes in the United States Brookings, S. Dak., South Dakota State University, Ph.D. dissertation, 234 p, at https://topotools.cr.usgs.gov/pdfs/DGesch_dissertation_Nov2006.pdf.

The Watershed Boundary Dataset (WBD) from The National Map (TNM) defines the perimeter of drainage areas formed by the terrain and other landscape characteristics. The drainage areas are nested within each other so that a large drainage area, such as the Upper Mississippi River, is composed of multiple smaller drainage areas, such as the Wisconsin River. Each of these smaller areas can further be subdivided into smaller and smaller drainage areas. The WBD uses six different levels in this hierarchy, with the smallest averaging about 30,000 acres. The WBD is made up of polygons nested into six levels of data respectively defined by Regions, Subregions, Basins, Subbasins, Watersheds, and Subwatersheds. For additional information on the WBD, go to https://nhd.usgs.gov/wbd.html. The USGS National Hydrography Dataset (NHD) service is a companion dataset to the WBD. The NHD is a comprehensive set of digital spatial data that encodes information about naturally occurring and constructed bodies of surface water (lakes, ponds, and reservoirs), paths through which water flows (canals, ditches, streams, and rivers), and related entities such as point features (springs, wells, stream gages, and dams). The information encoded about these features includes classification and other characteristics, delineation, geographic name, position and related measures, a "reach code" through which other information can be related to the NHD, and the direction of water flow. The network of reach codes delineating water and transported material flow allows users to trace movement in upstream and downstream directions. In addition to this geographic information, the dataset contains metadata that supports the exchange of future updates and improvements to the data. The NHD is available nationwide in two seamless datasets, one based on 1:24,000-scale maps and referred to as high resolution NHD, and the other based on 1:100,000-scale maps and referred to as medium resolution NHD. Additional selected areas in the United States are available based on larger scales, such as 1:5,000-scale or greater, and referred to as local resolution NHD. For more information on the NHD, go to https://nhd.usgs.gov/index.html. Hydrography data from The National Map supports many applications, such as making maps, geocoding observations, flow modeling, data maintenance, and stewardship. Hydrography data is commonly combined with other data themes, such as boundaries, elevation, structures, and transportation, to produce general reference base maps. The National Map viewer allows free downloads of public domain WBD and NHD data in either Esri File or Personal Geodatabase, or Shapefile formats. The Watershed Boundary Dataset is being developed under the leadership of the Subcommittee on Spatial Water Data, which is part of the Advisory Committee on Water Information (ACWI) and the Federal Geographic Data Committee (FGDC). The USDA Natural Resources Conservation Service (NRCS), along with many other federal agencies and national associations, have representatives on the Subcommittee on Spatial Water Data. As watershed boundary geographic information systems (GIS) coverages are completed, statewide and national data layers will be made available via the Geospatial Data Gateway to everyone, including federal, state, local government agencies, researchers, private companies, utilities, environmental groups, and concerned citizens. The database will assist in planning and describing water use and related land use activities. Resources in this dataset:Resource Title: Watershed Boundary Dataset (WBD). File Name: Web Page, url: https://www.nrcs.usda.gov/wps/portal/nrcs/detail/national/water/watersheds/dataset/?cid=nrcs143_021630 Web site for the Watershed Boundary Dataset (WBD), including links to:

Review Data Availability (Status Maps) Obtain Data by State, County, or Other Area Obtain Seamless National Data offsite link image
Geospatial Data Tools National Technical and State Coordinators Information about WBD dataset

Connecticut off shore baseline for use with DSAS software. Created by J Stocker, modified by K O'Brien, reviewed by JS 9/25/2013.

ArcGIS Online (AGOL) Feature Layer which includes the MDOT SHA 2050 Mean Higher High Water 2% Annual Chance (50YR Storm) - Depth Grid geospatial data product.MDOT SHA 2050 Mean Higher High Water 2% Annual Chance (50YR Storm) - Depth Grid consists of a depth grid image service depicting conditions of mean higher high water based on the 2% annual chance (50-Year Storm) event for coastal areas throughout the State of Maryland in year 2050. This data product supports Maryland Department of Transportation State Highway Administration (MDOT SHA) leadership and planners as they endeavor to mitigate or prevent the impacts of sea level change resulting from land surface subsidence and rising sea levels.MDOT SHA 2050 Mean Higher High Water 2% Annual Chance (50YR Storm) - Depth Grid data was produced as a result of efforts by the Maryland Department of Transportation State Highway Administration (MDOT SHA), Eastern Shore Regional GIS Cooperative (ESRGC), Salisbury University (SU), United States Corps of Engineers (USACE), National Oceanic & Atmospheric Administration (NOAA), and the United States Geological Survey (USGS). The US Army Corps of Engineers provide the sea level change estimate. Sea level change is localized using water elevations collected from a qualifying National Oceanic and Atmospheric Administration (NOAA) tidal reference station - NOAA observations are transformed from tidal datum to North American Vertical Datum of 1988. A final correction for glacial isostatic adjustment and land creates an sea level change value for the official project year, 2050.MDOT SHA 2050 Mean Higher High Water 2% Annual Chance (50YR Storm) - Depth Grid data was task-based, and will only be updated on an As-Needed basis where necessary.Last Updated: 10/07/2019For additional information, contact the MDOT SHA Geospatial Technologies:Email: GIS@mdot.maryland.govFor information related to the data, visit the Eastern Shore Regional GIS Cooperative (ESRGC) websiteWebsite: https:www.esrgc.org/mapServices/For additional data, visit the MDOT GIS Open Data Portal:Website: https://data.imap.maryland.gov/pages/mdot/For additional information related to the Maryland Department of Transportation (MDOT):Website: https://www.mdot.maryland.gov/For additional information related to the Maryland Department of Transportation State Highway Administration (MDOT SHA):Website: https://www.roads.maryland.gov/Home.aspxMDOT SHA Geospatial Data Legal Disclaimer:The Maryland Department of Transportation State Highway Administration (MDOT SHA) makes no warranty, expressed or implied, as to the use or appropriateness of geospatial data, and there are no warranties of merchantability or fitness for a particular purpose or use. The information contained in geospatial data is from publicly available sources, but no representation is made as to the accuracy or completeness of geospatial data. MDOT SHA shall not be subject to liability for human error, error due to software conversion, defect, or failure of machines, or any material used in the connection with the machines, including tapes, disks, CD-ROMs or DVD-ROMs and energy. MDOT SHA shall not be liable for any lost profits, consequential damages, or claims against MDOT SHA by third parties.

Shorelines are continuously moving in response to winds, waves, tides, sediment supply, changes in relative sea level, and human activities. Shoreline changes are generally not constant through time and frequently switch from negative (erosion) to positive (accretion) and vice versa. Cyclic and non-cyclic processes change the position of the shoreline over a variety of timescales, from the daily and seasonal effects of winds and waves, to changes in sea level over a century to thousands of years. The shoreline "rate of change" statistic thus reflects a cumulative summary of the processes that altered the shoreline for the time period analyzed.

ArcGIS Online (AGOL) Feature Layer which includes the MDOT SHA 2050 Mean Higher High Water 0.2% Annual Chance (500YR Storm) - Depth Grid geospatial data product.MDOT SHA 2050 Mean Higher High Water 0.2% Annual Chance (500YR Storm) - Depth Grid consists of a depth grid image service depicting conditions of mean higher high water based on the 0.2% annual chance (500-Year Storm) event for coastal areas throughout the State of Maryland in year 2050. This data product supports Maryland Department of Transportation State Highway Administration (MDOT SHA) leadership and planners as they endeavor to mitigate or prevent the impacts of sea level change resulting from land surface subsidence and rising sea levels.MDOT SHA 2050 Mean Higher High Water 0.2% Annual Chance (500YR Storm) - Depth Grid data was produced as a result of efforts by the Maryland Department of Transportation State Highway Administration (MDOT SHA), Eastern Shore Regional GIS Cooperative (ESRGC), Salisbury University (SU), United States Corps of Engineers (USACE), National Oceanic & Atmospheric Administration (NOAA), and the United States Geological Survey (USGS). The US Army Corps of Engineers provide the sea level change estimate. Sea level change is localized using water elevations collected from a qualifying National Oceanic and Atmospheric Administration (NOAA) tidal reference station - NOAA observations are transformed from tidal datum to North American Vertical Datum of 1988. A final correction for glacial isostatic adjustment and land creates an sea level change value for the official project year, 2050.MDOT SHA 2050 Mean Higher High Water 0.2% Annual Chance (500YR Storm) - Depth Grid data was task-based, and will only be updated on an As-Needed basis where necessary.Last Updated: 10/07/2019For additional information, contact the MDOT SHA Geospatial Technologies:Email: GIS@mdot.maryland.govFor information related to the data, visit the Eastern Shore Regional GIS Cooperative (ESRGC) websiteWebsite: https:www.esrgc.org/mapServices/For additional data, visit the MDOT GIS Open Data Portal:Website: https://data.imap.maryland.gov/pages/mdot/For additional information related to the Maryland Department of Transportation (MDOT):Website: https://www.mdot.maryland.gov/For additional information related to the Maryland Department of Transportation State Highway Administration (MDOT SHA):Website: https://www.roads.maryland.gov/Home.aspxMDOT SHA Geospatial Data Legal Disclaimer:The Maryland Department of Transportation State Highway Administration (MDOT SHA) makes no warranty, expressed or implied, as to the use or appropriateness of geospatial data, and there are no warranties of merchantability or fitness for a particular purpose or use. The information contained in geospatial data is from publicly available sources, but no representation is made as to the accuracy or completeness of geospatial data. MDOT SHA shall not be subject to liability for human error, error due to software conversion, defect, or failure of machines, or any material used in the connection with the machines, including tapes, disks, CD-ROMs or DVD-ROMs and energy. MDOT SHA shall not be liable for any lost profits, consequential damages, or claims against MDOT SHA by third parties.

ArcGIS Online (AGOL) Feature Layer which includes the MDOT SHA 2100 Mean Sea Level 1% Annual Chance (100YR Storm) - Depth Grid geospatial data product.MDOT SHA 2100 Mean Sea Level 1% Annual Chance (100YR Storm) - Depth Grid consists of a depth grid image service depicting conditions of sea level change based on the 1% annual chance event (100-Year Storm) scenario for coastal areas throughout the State of Maryland in year 2100. This data product supports Maryland Department of Transportation State Highway Administration (MDOT SHA) leadership and planners as they endeavor to mitigate or prevent the impacts of sea level change resulting from land surface subsidence and rising sea levels.MDOT SHA 2100 Mean Sea Level 1% Annual Chance (100YR Storm) - Depth Grid data was produced as a result of efforts by the Maryland Department of Transportation State Highway Administration (MDOT SHA), Eastern Shore Regional GIS Cooperative (ESRGC), Salisbury University (SU), United States Corps of Engineers (USACE), National Oceanic & Atmospheric Administration (NOAA), and the United States Geological Survey (USGS). The US Army Corps of Engineers provide the sea level change estimate. Sea level change is localized using water elevations collected from a qualifying National Oceanic and Atmospheric Administration (NOAA) tidal reference station - NOAA observations are transformed from tidal datum to North American Vertical Datum of 1988. A final correction for glacial isostatic adjustment and land creates an sea level change value for the official project year, 2100.MDOT SHA 2100 Mean Sea Level 1% Annual Chance (100YR Storm) - Depth Grid data was task-based, and will only be updated on an As-Needed basis where necessary.Last Updated: 10/09/2019For additional information, contact the MDOT SHA Geospatial Technologies:Email: GIS@mdot.maryland.govFor information related to the data, visit the Eastern Shore Regional GIS Cooperative (ESRGC) websiteWebsite: https:www.esrgc.org/mapServices/For additional data, visit the MDOT GIS Open Data Portal:Website: https://data.imap.maryland.gov/pages/mdot/For additional information related to the Maryland Department of Transportation (MDOT):Website: https://www.mdot.maryland.gov/For additional information related to the Maryland Department of Transportation State Highway Administration (MDOT SHA):Website: https://www.roads.maryland.gov/Home.aspxMDOT SHA Geospatial Data Legal Disclaimer:The Maryland Department of Transportation State Highway Administration (MDOT SHA) makes no warranty, expressed or implied, as to the use or appropriateness of geospatial data, and there are no warranties of merchantability or fitness for a particular purpose or use. The information contained in geospatial data is from publicly available sources, but no representation is made as to the accuracy or completeness of geospatial data. MDOT SHA shall not be subject to liability for human error, error due to software conversion, defect, or failure of machines, or any material used in the connection with the machines, including tapes, disks, CD-ROMs or DVD-ROMs and energy. MDOT SHA shall not be liable for any lost profits, consequential damages, or claims against MDOT SHA by third parties.

ArcGIS Online (AGOL) Feature Layer which includes the MDOT SHA 2100 Mean Sea Level 10% Annual Chance (10YR Storm) - Depth Grid geospatial data product.MDOT SHA 2100 Mean Sea Level 10% Annual Chance (10YR Storm) - Depth Grid consists of a depth grid image service depicting conditions of sea level change based on the 10% annual chance event (10-Year Storm) scenario for coastal areas throughout the State of Maryland in year 2100. This data product supports Maryland Department of Transportation State Highway Administration (MDOT SHA) leadership and planners as they endeavor to mitigate or prevent the impacts of sea level change resulting from land surface subsidence and rising sea levels.MDOT SHA 2100 Mean Sea Level 10% Annual Chance (10YR Storm) - Depth Grid data was produced as a result of efforts by the Maryland Department of Transportation State Highway Administration (MDOT SHA), Eastern Shore Regional GIS Cooperative (ESRGC), Salisbury University (SU), United States Corps of Engineers (USACE), National Oceanic & Atmospheric Administration (NOAA), and the United States Geological Survey (USGS). The US Army Corps of Engineers provide the sea level change estimate. Sea level change is localized using water elevations collected from a qualifying National Oceanic and Atmospheric Administration (NOAA) tidal reference station - NOAA observations are transformed from tidal datum to North American Vertical Datum of 1988. A final correction for glacial isostatic adjustment and land creates an sea level change value for the official project year, 2100.MDOT SHA 2100 Mean Sea Level 10% Annual Chance (10YR Storm) - Depth Grid data was task-based, and will only be updated on an As-Needed basis where necessary.Last Updated: 10/09/2019For additional information, contact the MDOT SHA Geospatial Technologies:Email: GIS@mdot.maryland.govFor information related to the data, visit the Eastern Shore Regional GIS Cooperative (ESRGC) websiteWebsite: https:www.esrgc.org/mapServices/For additional data, visit the MDOT GIS Open Data Portal:Website: https://data.imap.maryland.gov/pages/mdot/For additional information related to the Maryland Department of Transportation (MDOT):Website: https://www.mdot.maryland.gov/For additional information related to the Maryland Department of Transportation State Highway Administration (MDOT SHA):Website: https://www.roads.maryland.gov/Home.aspxMDOT SHA Geospatial Data Legal Disclaimer:The Maryland Department of Transportation State Highway Administration (MDOT SHA) makes no warranty, expressed or implied, as to the use or appropriateness of geospatial data, and there are no warranties of merchantability or fitness for a particular purpose or use. The information contained in geospatial data is from publicly available sources, but no representation is made as to the accuracy or completeness of geospatial data. MDOT SHA shall not be subject to liability for human error, error due to software conversion, defect, or failure of machines, or any material used in the connection with the machines, including tapes, disks, CD-ROMs or DVD-ROMs and energy. MDOT SHA shall not be liable for any lost profits, consequential damages, or claims against MDOT SHA by third parties.

Aeromagnetic data were collected along flight lines by instruments in an aircraft that recorded magnetic-field intensity values and location. In surveys such as this one where the data were originally collected in digital form and not digitized from contour maps, the information we provide typically includes latitude, longitude, magnetic anomaly in nanoTeslas, and intermediate values used to derive the magnetic anomaly such as total magnetic field.

The Gap Analysis Program produces data and tools that help meet critical national challenges such as biodiversity conservation, renewable energy development, climate change adaptation, and infrastructure investment. The Protected Areas Database of the United States (PAD-US) is the official inventory of protected open space in the United States. With over 715 million acres in thousands of holdings, the spatial data in PAD-US include public lands held in trust by national, State, and some local governments, and by some nonprofit conservation organizations. For additional information, visit the PAD-US Metadata record: https://gapanalysis.usgs.gov/padus/data/metadata/

ArcGIS Online (AGOL) Feature Layer which includes the MDOT SHA 2015 Mean Sea Level 4% Annual Chance (25YR Storm) - Depth Grid geospatial data product.MDOT SHA 2015 Mean Sea Level 4% Annual Chance (25YR Storm) - Depth Grid consists of a depth grid image service depicting conditions of sea level change based on the 4% annual chance event (25-Year Storm) scenario for coastal areas throughout the State of Maryland in year 2015. This data product supports Maryland Department of Transportation State Highway Administration (MDOT SHA) leadership and planners as they endeavor to mitigate or prevent the impacts of sea level change resulting from land surface subsidence and rising sea levels.MDOT SHA 2015 Mean Sea Level 4% Annual Chance (25YR Storm) - Depth Grid data was produced as a result of efforts by the Maryland Department of Transportation State Highway Administration (MDOT SHA), Eastern Shore Regional GIS Cooperative (ESRGC), Salisbury University (SU), United States Corps of Engineers (USACE), National Oceanic & Atmospheric Administration (NOAA), and the United States Geological Survey (USGS). The US Army Corps of Engineers provide the sea level change estimate. Sea level change is localized using water elevations collected from a qualifying National Oceanic and Atmospheric Administration (NOAA) tidal reference station - NOAA observations are transformed from tidal datum to North American Vertical Datum of 1988. A final correction for glacial isostatic adjustment and land creates an sea level change value for the official project year, 2015.MDOT SHA 2015 Mean Sea Level 4% Annual Chance (25YR Storm) - Depth Grid data was task-based, and will only be updated on an As-Needed basis where necessary.Last Updated: 10/07/2019For additional information, contact the MDOT SHA Geospatial Technologies:Email: GIS@mdot.maryland.govFor information related to the data, visit the Eastern Shore Regional GIS Cooperative (ESRGC) websiteWebsite: https:www.esrgc.org/mapServices/For additional data, visit the MDOT GIS Open Data Portal:Website: https://data.imap.maryland.gov/pages/mdot/For additional information related to the Maryland Department of Transportation (MDOT):Website: https://www.mdot.maryland.gov/For additional information related to the Maryland Department of Transportation State Highway Administration (MDOT SHA):Website: https://www.roads.maryland.gov/Home.aspxMDOT SHA Geospatial Data Legal Disclaimer:The Maryland Department of Transportation State Highway Administration (MDOT SHA) makes no warranty, expressed or implied, as to the use or appropriateness of geospatial data, and there are no warranties of merchantability or fitness for a particular purpose or use. The information contained in geospatial data is from publicly available sources, but no representation is made as to the accuracy or completeness of geospatial data. MDOT SHA shall not be subject to liability for human error, error due to software conversion, defect, or failure of machines, or any material used in the connection with the machines, including tapes, disks, CD-ROMs or DVD-ROMs and energy. MDOT SHA shall not be liable for any lost profits, consequential damages, or claims against MDOT SHA by third parties.

Connecticut Railroads is a 1:24,000-scale, feature-based layer that includes railroad features on the U.S. Geological Survey (USGS) 7.5 minute topographic quadrangle maps for the State of Connecticut. This layer only includes features located in Connecticut. The layer is based on information from USGS topographic quadrangle maps published between 1969 and 1984 and does not represent the railroad system in Connecticut at any one particular point in time. The layer does not depict current conditions and excludes many railroads that have been built, modified, or removed since the time these topographic quadrangle maps were published. The layer includes railroad tracks, bridges, drawbridges, roundhouses, sidings, tracks, tunnels, underpasses, and stations. It does not include train schedule or track related information. Features are linear and represent railroad track centerlines. Attribute information is comprised of codes to cartographically represent (symbolize) rail features on a map. This layer was originally published in 1994. The 2005 edition includes the same rail features published in 1994, but the attribute information has been slightly modified and made easier to use.

45 data sources of hydrological/hydromet, water quality, water resource, environmental, agro-environmental and development indicators. Datasets include: Achieving National Development Strategy in Tajikistan (Nurek), Water Transition, Central Asia Hydrometeorology Modernization Project, Lake Levels, Night Lights, Landscan Population Density, Satellite Precipitation, Solar Energy Data, Earth Wind Map, Land Cover Comparison, Earth Engine NDVI Analysis, Kyrgyz Republic DRM Portal, Climate Adaptation and Mitigation Program for Aral Sea Basin, Croplands, Watershed Mapper, Forest Cover, Kyrgyz Republic Hydromet Portal, World Water Quality, Human Footprint, Glacier Inventory, MODIS layers, Cropping Extent, Fire Data, Surface Water Explorer, Human Influence Index, Development Data, GADAS (Agriculture) Wind Potential, ESRI Water Balance, Air Quality, Tajikistan Hydromet Website, Open Street Map Data, Land-Water Changes, Himawari, GEOGRLAM RAPP, Google Earth Data, GEOSS Portal, USGS Global Visualization Viewer (GloVis), STRM Topography Data, UNEP Database, DIVA GIS Country Boundaries, ARCGIS Hub- Water Bodies, ARCGIS Hub- World Cities, WUEMoCA, World Bank Climate Change Portal

As one of the cornerstones of the U.S. Geological Survey's (USGS) National Geospatial Program, The National Map is a collaborative effort among the USGS and other Federal, State, and local partners to improve and deliver topographic information for the United States. It has many uses ranging from recreation to scientific analysis to emergency response. This mines point-feature datasets was developed for The National Map Gazetteer as the Federal and national standard (ANSI INCITS 446-2008) for geographic nomenclature based on the Geographic Names Information System (GNIS). NOTE: As a names database with locational information, GNIS is concerned with named features and may not include features that are unnamed.

The USGS Data Collaboration Announcement (DCA) Portal serves as a central platform for facilitating partnerships that enhance geospatial data acquisition as part of the 3D National Topography Model (3DNTM). Through the FY25 3DHP DCA, the portal focuses on integrating 3D Elevation Program (3DEP) and 3D Hydrography Program (3DHP) data acquisition, providing tools, workflows, and funding guidance for collaborative projects among federal, state, and local agencies. This coordinated approach allows for the development of seamless, high-resolution datasets that improve resource management and decision-making.The portal enables agencies to pool funding and align priorities to achieve shared goals in mapping projects. It supports initiatives such as elevation-derived hydrography (EDH), seamless integration of elevation and hydrography datasets, and improvements in 3D data quality. This helps address challenges in areas like flood risk management, water resource planning, and disaster preparedness. Participants benefit from transparent processes, joint funding agreements, and technical resources designed to streamline project implementation.In addition to collaboration tools, the portal provides access to detailed information about priority data requirements, application timelines, and partnership opportunities. It fosters innovation by supporting projects that advance the USGS mission of producing accurate, reliable geospatial data critical for federal and state mapping needs. The DCA Portal exemplifies a model for efficient, collaborative data development that enhances national geospatial infrastructure.

ArcGIS Online (AGOL) Feature Layer which includes the MDOT SHA 2015 Mean Higher High Water 4% Annual Chance (25YR Storm) - Depth Grid geospatial data product.MDOT SHA 2050 Mean Higher High Water 4% Annual Chance (25YR Storm) - Depth Grid consists of a depth grid image service depicting conditions of mean higher high water based on the 4% annual chance (25-Year Storm) event for coastal areas throughout the State of Maryland in year 2050. This data product supports Maryland Department of Transportation State Highway Administration (MDOT SHA) leadership and planners as they endeavor to mitigate or prevent the impacts of sea level change resulting from land surface subsidence and rising sea levels.MDOT SHA 2050 Mean Higher High Water 4% Annual Chance (25YR Storm) - Depth Grid data was produced as a result of efforts by the Maryland Department of Transportation State Highway Administration (MDOT SHA), Eastern Shore Regional GIS Cooperative (ESRGC), Salisbury University (SU), United States Corps of Engineers (USACE), National Oceanic & Atmospheric Administration (NOAA), and the United States Geological Survey (USGS). The US Army Corps of Engineers provide the sea level change estimate. Sea level change is localized using water elevations collected from a qualifying National Oceanic and Atmospheric Administration (NOAA) tidal reference station - NOAA observations are transformed from tidal datum to North American Vertical Datum of 1988. A final correction for glacial isostatic adjustment and land creates an sea level change value for the official project year, 2050.MDOT SHA 2050 Mean Higher High Water 4% Annual Chance (25YR Storm) - Depth Grid data was task-based, and will only be updated on an As-Needed basis where necessary.Last Updated: 10/07/2019For additional information, contact the MDOT SHA Geospatial Technologies:Email: GIS@mdot.maryland.govFor information related to the data, visit the Eastern Shore Regional GIS Cooperative (ESRGC) websiteWebsite: https:www.esrgc.org/mapServices/For additional data, visit the MDOT GIS Open Data Portal:Website: https://data.imap.maryland.gov/pages/mdot/For additional information related to the Maryland Department of Transportation (MDOT):Website: https://www.mdot.maryland.gov/For additional information related to the Maryland Department of Transportation State Highway Administration (MDOT SHA):Website: https://www.roads.maryland.gov/Home.aspxMDOT SHA Geospatial Data Legal Disclaimer:The Maryland Department of Transportation State Highway Administration (MDOT SHA) makes no warranty, expressed or implied, as to the use or appropriateness of geospatial data, and there are no warranties of merchantability or fitness for a particular purpose or use. The information contained in geospatial data is from publicly available sources, but no representation is made as to the accuracy or completeness of geospatial data. MDOT SHA shall not be subject to liability for human error, error due to software conversion, defect, or failure of machines, or any material used in the connection with the machines, including tapes, disks, CD-ROMs or DVD-ROMs and energy. MDOT SHA shall not be liable for any lost profits, consequential damages, or claims against MDOT SHA by third parties.

This layer presents the best-known point and perimeter locations of wildfire occurrences within the United States over the past 7 days. Points mark a location within the wildfire area and provide current information about that wildfire. Perimeters are the line surrounding land that has been impacted by a wildfire.Consumption Best Practices:

As a service that is subject to very high usage, ensure peak performance and accessibility of your maps and apps by avoiding the use of non-cacheable relative Date/Time field filters. To accommodate filtering events by Date/Time, we suggest using the included "Age" fields that maintain the number of days or hours since a record was created or last modified, compared to the last service update. These queries fully support the ability to cache a response, allowing common query results to be efficiently provided to users in a high demand service environment. When ingesting this service in your applications, avoid using POST requests whenever possible. These requests can compromise performance and scalability during periods of high usage because they too are not cacheable.Source:  Wildfire points are sourced from Integrated Reporting of Wildland-Fire Information (IRWIN) and perimeters from National Interagency Fire Center (NIFC). Current Incidents: This layer provides a near real-time view of the data being shared through the Integrated Reporting of Wildland-Fire Information (IRWIN) service. IRWIN provides data exchange capabilities between participating wildfire systems, including federal, state and local agencies. Data is synchronized across participating organizations to make sure the most current information is available. The display of the points are based on the NWCG Fire Size Classification applied to the daily acres attribute.Current Perimeters: This layer displays fire perimeters posted to the National Incident Feature Service. It is updated from operational data and may not reflect current conditions on the ground. For a better understanding of the workflows involved in mapping and sharing fire perimeter data, see the National Wildfire Coordinating Group Standards for Geospatial Operations.Update Frequency:  Every 15 minutes using the Aggregated Live Feed Methodology based on the following filters:Events modified in the last 7 daysEvents that are not given a Fire Out DateIncident Type Kind: FiresIncident Type Category: Prescribed Fire, Wildfire, and Incident Complex

Area Covered: United StatesWhat can I do with this layer? The data includes basic wildfire information, such as location, size, environmental conditions, and resource summaries. Features can be filtered by incident name, size, or date keeping in mind that not all perimeters are fully attributed.Attribute InformationThis is a list of attributes that benefit from additional explanation. Not all attributes are listed.Incident Type Category: This is a breakdown of events into more specific categories.Wildfire (WF) -A wildland fire originating from an unplanned ignition, such as lightning, volcanos, unauthorized and accidental human caused fires, and prescribed fires that are declared wildfires.Prescribed Fire (RX) - A wildland fire originating from a planned ignition in accordance with applicable laws, policies, and regulations to meet specific objectives.Incident Complex (CX) - An incident complex is two or more individual incidents in the same general proximity that are managed together under one Incident Management Team. This allows resources to be used across the complex rather than on individual incidents uniting operational activities.IrwinID: Unique identifier assigned to each incident record in both point and perimeter layers.

Acres: these typically refer to the number of acres within the current perimeter of a specific, individual incident, including unburned and unburnable islands.Discovery: An estimate of acres burning upon the discovery of the fire.Calculated or GIS:  A measure of acres calculated (i.e., infrared) from a geospatial perimeter of a fire.Daily: A measure of acres reported for a fire.Final: The measure of acres within the final perimeter of a fire. More specifically, the number of acres within the final fire perimeter of a specific, individual incident, including unburned and unburnable islands.

Dates: the various systems contribute date information differently so not all fields will be populated for every fire.FireDiscovery: The date and time a fire was reported as discovered or confirmed to exist. May also be the start date for reporting purposes.

Containment: The date and time a wildfire was declared contained. Control: The date and time a wildfire was declared under control.ICS209Report: The date and time of the latest approved ICS-209 report.Current: The date and time a perimeter is last known to be updated.FireOut: The date and time when a fire is declared out.ModifiedOnAge: (Integer) Computed days since event last modified.DiscoveryAge: (Integer) Computed days since event's fire discovery date.CurrentDateAge: (Integer) Computed days since perimeter last modified.CreateDateAge: (Integer) Computed days since perimeter entry created.

GACC: A code that identifies one of the wildland fire geographic area coordination centers. A geographic area coordination center is a facility that is used for the coordination of agency or jurisdictional resources in support of one or more incidents within a geographic coordination area.Fire Mgmt Complexity: The highest management level utilized to manage a wildland fire event.Incident Management Organization: The incident management organization for the incident, which may be a Type 1, 2, or 3 Incident Management Team (IMT), a Unified Command, a Unified Command with an IMT, National Incident Management Organization (NIMO), etc. This field is null if no team is assigned.Unique Fire Identifier: Unique identifier assigned to each wildland fire. yyyy = calendar year, SSUUUU = Point Of Origin (POO) protecting unit identifier (5 or 6 characters), xxxxxx = local incident identifier (6 to 10 characters)RevisionsJan 4, 2021: Added Integer fields 'Days Since...' to Current_Incidents point layer and Current_Perimeters polygon layer. These fields are computed when the data is updated, reflecting the current number of days since each record was last updated. This will aid in making 'age' related, cache friendly queries.Mar 12, 2021: Added second set of 'Age' fields for Event and Perimeter record creation, reflecting age in Days since service data update.Apr 21, 2021: Current_Perimeters polygon layer is now being populated by NIFC's newest data source. A new field was added, 'IncidentTypeCategory' to better distinguish Incident types for Perimeters and now includes type 'CX' or Complex Fires. Five fields were not transferrable, and as a result 'Comments', 'Label', 'ComplexName', 'ComplexID', and 'IMTName' fields will be Null moving forward.Apr 26, 2021: Updated Incident Layer Symbology to better clarify events, reduce download size and overhead of symbols. Updated Perimeter Layer Symbology to better distingish between Wildfires and Prescribed Fires.May 5, 2021: Slight modification to Arcade logic for Symbology, refining Age comparison to Zero for fires in past 24-hours.Aug 16, 2021: Enabled Time Series capability on Layers (off by default) using 'Fire Discovery Date' for Incidents and 'Creation Date' for Perimeters.This layer is provided for informational purposes and is not monitored 24/7 for accuracy and currency.If you would like to be alerted to potential issues or simply see when this Service will update next, please visit our Live Feed Status Page!

ArcGIS Online (AGOL) Feature Layer which includes the MDOT SHA 2015 Mean Sea Level 1% Annual Chance (100YR Storm) - Depth Grid geospatial data product.MDOT SHA 2015 Mean Sea Level 1% Annual Chance (100YR Storm) - Depth Grid consists of a depth grid image service depicting conditions of sea level change based on the 1% annual chance event (100-Year Storm) scenario for coastal areas throughout the State of Maryland in year 2015. This data product supports Maryland Department of Transportation State Highway Administration (MDOT SHA) leadership and planners as they endeavor to mitigate or prevent the impacts of sea level change resulting from land surface subsidence and rising sea levels.MDOT SHA 2015 Mean Sea Level 1% Annual Chance (100YR Storm) - Depth Grid data was produced as a result of efforts by the Maryland Department of Transportation State Highway Administration (MDOT SHA), Eastern Shore Regional GIS Cooperative (ESRGC), Salisbury University (SU), United States Corps of Engineers (USACE), National Oceanic & Atmospheric Administration (NOAA), and the United States Geological Survey (USGS). The US Army Corps of Engineers provide the sea level change estimate. Sea level change is localized using water elevations collected from a qualifying National Oceanic and Atmospheric Administration (NOAA) tidal reference station - NOAA observations are transformed from tidal datum to North American Vertical Datum of 1988. A final correction for glacial isostatic adjustment and land creates an sea level change value for the official project year, 2015.MDOT SHA 2015 Mean Sea Level 1% Annual Chance (100YR Storm) - Depth Grid data was task-based, and will only be updated on an As-Needed basis where necessary.Last Updated: 10/07/2019For additional information, contact the MDOT SHA Geospatial Technologies:Email: GIS@mdot.maryland.govFor information related to the data, visit the Eastern Shore Regional GIS Cooperative (ESRGC) websiteWebsite: https:www.esrgc.org/mapServices/For additional data, visit the MDOT GIS Open Data Portal:Website: https://data.imap.maryland.gov/pages/mdot/For additional information related to the Maryland Department of Transportation (MDOT):Website: https://www.mdot.maryland.gov/For additional information related to the Maryland Department of Transportation State Highway Administration (MDOT SHA):Website: https://www.roads.maryland.gov/Home.aspxMDOT SHA Geospatial Data Legal Disclaimer:The Maryland Department of Transportation State Highway Administration (MDOT SHA) makes no warranty, expressed or implied, as to the use or appropriateness of geospatial data, and there are no warranties of merchantability or fitness for a particular purpose or use. The information contained in geospatial data is from publicly available sources, but no representation is made as to the accuracy or completeness of geospatial data. MDOT SHA shall not be subject to liability for human error, error due to software conversion, defect, or failure of machines, or any material used in the connection with the machines, including tapes, disks, CD-ROMs or DVD-ROMs and energy. MDOT SHA shall not be liable for any lost profits, consequential damages, or claims against MDOT SHA by third parties.