Expands the use of internal data for creating Geographic Information System (GIS) maps. SSA's Database Systems division developed a map users guide for GIS data object publishing and was made available in an internal Sharepoint site for access throughout the agency. The guide acts as the reference for publishers of GIS objects across the life-cycle in our single, central geodatabase implementation.

Aerial photography collected by Pictometry International Corp. between Feb. 25, 2020 to March 4, 2020. Original pixel resolution is 0.5 feet.

Suggested use: Use tiled Map Service for large scale mapping when high resolution color imagery is needed.A web app to view tile and block metadata such as year, sensor, and cloud cover can be found here. CoverageState of AlaskaProduct TypeTile CacheImage BandsRGBSpatial Resolution50cmAccuracy5m CE90 or betterCloud Cover<10% overallOff Nadir Angle<30 degreesSun Elevation>30 degreesWMS version of this data: https://geoportal.alaska.gov/arcgis/services/ahri_2020_rgb_cache/MapServer/WMSServer?request=GetCapabilities&service=WMSWMTS version of this data:https://geoportal.alaska.gov/arcgis/rest/services/ahri_2020_rgb_cache/MapServer/WMTS/1.0.0/WMTSCapabilities.xml

The zip file contains a large tiff mosaic stitched together from a series of aerial photographs of the Calhoun CZO area taken in 1933, when the area was being acquired by the US Forest Service. USFS archaeologist Mike Harmon delivered the black-and-white photographs, known to him as the 'Sumter National Forest Purchase Aerials', to us in a box. The photographs include most of the Enoree District of the Sumter National Forest, including the entirety of the Calhoun CZO, not just the long-term plots and small watersheds. The photographs were scanned and georectified, then color-balanced and stitched together following 'seams' - high-contrast features such as rivers and roads ('seamlined'). In addition to the main tiff are four files that can be used to properly geolocate the composite image in ArcGIS.

The multilayer pdf file includes a smaller version of the seamlined 1933 aerial photography mosaic raster layer, as well as this aerial mosaic transparent over slope map (for a 3D-like 1933 image raster). Other layers include contours, roads, boundaries, sampling locations, 1.5 m DEM, 1.5m slope, 1m 2013 NAIP aerial imagery, and 2014 canopy height. The pdf file includes both 'interfluve order' and 'landshed order.' These two layers mean the same thing, but the landshed is the area unit around the interfluve that is used for statistics; this dataset has been QC'ed. The Interfluve Order network was used to delineate the landsheds and agrees with it >95% of the time, but has a few inaccuracies (it was automated by the computer) that were fixed manually. Use the network for viewing and considering the landscape at large, but for the specific interfluve order, check the color of the 'Landshed Order' dataset to verify its accuracy.

Date Range Comments: The exact date these photos were taken is unknown, but the year is thought to be 1933.The flight date is prior to the USFS land purchases for the Enoree District of the Sumter National Forest; the photos are thus known as the "pre-purchase photos").

This web map references the live tiled map service from the OpenStreetMap (OSM) project. OpenStreetMap (OSM) is an open collaborative project to create a free editable map of the world. Volunteers gather location data using GPS, local knowledge, and other free sources of information and upload it. The resulting free map can be viewed and downloaded from the OpenStreetMap server: https://www.OpenStreetMap.org. See that website for additional information about OpenStreetMap. It is made available as a basemap for GIS work in ESRI products under a Creative Commons Attribution-ShareAlike license. Tip: This service is one of the basemaps used in the ArcGIS.com map viewer. Simply click one of those links to launch the interactive application of your choice, and then choose Open Street Map from the Basemap control to start using this service. You'll also find this service in the Basemap gallery in ArcGIS Explorer Desktop and ArcGIS Desktop 10. Tip: Here are some well known locations as they appear in this web map, accessed by launching the web map with a URL that contains location parameters: Athens, Cairo, Jakarta, Moscow, Mumbai, Nairobi, Paris, Rio De Janeiro, Shanghai

This is a connection to the Allegheny County's Geographic Information Systems Group's Open Data Portal. They are pleased to share some of our most comprehensive data sets with the public. You can solve important local issues by exploring and downloading relevant open data, analyzing and combining the datasets using maps, and discovering and building apps.

These datasets are available in a number of formats. You can choose to download them, use REST APIs, or view them directly in an interactive web map. API's provide access as REST, HTML, JSON, GeoJSON, etc.

Please contact Allegheny for any questions or suggestions on datasets at GISHelp@AlleghenyCounty.US

Link to State of South Dakota GIS Data.

Color infrared (CIR) representation of NAIP 2016 60cm aerial imagery. Band1=NearIR, Band2=R, Band3=G.This service is offered by the California Department of Fish and Wildlife (CDFW). For more information about CDFW map services, please visit: https://wildlife.ca.gov/Data/GIS/Map-Services

Color infrared (CIR) imagery acquired during NAIP 2005 flights. The source CIR 1-meter resolution imagery was purchased from the North West Group (NWG) by three state agencies (California Dept. of Fish and Game, California Dept. of Transportation, and California Dept. of Water Resources). No access constraints, but there are use constraints. CIR coverage was not available in all areas. THIS CIR IMAGERY IS NOT A NAIP PRODUCT. Band1=NearIR, Band2=R, Band3=G.This service is offered by the California Department of Fish and Wildlife (CDFW). For more information about CDFW map services, please visit: https://wildlife.ca.gov/Data/GIS/Map-Services

The data release for the geologic map of the Salmon National Forest and vicinity, east-central Idaho, is a Geologic Map Schema (GeMS)-compliant version that updates the GIS files for the geologic map published in U.S. Geological Survey (USGS) Geologic Investigations Series Map I-2765 (Evans and Green, 2003). The updated digital data present the attribute tables and geospatial features (points, lines and polygons) in the format that meets GeMS requirements. This data release presents the geologic map as shown on the plates and captured in geospatial data for the published map. Minor errors, such as mistakes in line decoration or differences between the digital data and the map image, are corrected in this version. The database represents the geology for the 11,265 square kilometer, geologically complex Salmon National Forest in two plates, at a publication scale of 1:100,000. The map covers primarily Lemhi County, but also includes minor parts of Beaverhead, Custer, Idaho, Ravalli and Valley Counties. New geologic mapping was undertaken between 1990 and 2002 and synthesized with older published maps, providing significant stratigraphic and structural data, age data for intrusive rocks, and interpretations of geologic development. These GIS data supersede those in the interpretive report: Evans, K.V., Green, G.N., 2003, Geologic Map of the Salmon National Forest and Vicinity, East-Central Idaho: U.S. Geological Survey Geologic Investigations Series Map I-2765, scale 1:100,000, https://doi.org/10.3133/i2765.

GIS Data Management Market Outlook

The global GIS Data Management market size is projected to grow from USD 12.5 billion in 2023 to USD 25.6 billion by 2032, exhibiting a CAGR of 8.4% during the forecast period. This impressive growth is driven by the increasing adoption of geographic information systems (GIS) across various sectors such as urban planning, disaster management, and agriculture. The rising need for effective data management systems to handle the vast amounts of spatial data generated daily also significantly contributes to the market's expansion.

One of the primary growth factors for the GIS Data Management market is the burgeoning demand for spatial data analytics. Businesses and governments are increasingly leveraging GIS data to make informed decisions and strategize operational efficiencies. With the rapid urbanization and industrialization worldwide, there's an unprecedented need to manage and analyze geographic data to plan infrastructure, monitor environmental changes, and optimize resource allocation. Consequently, the integration of GIS with advanced technologies like artificial intelligence and machine learning is becoming more prominent, further fueling market growth.

Another significant factor propelling the market is the advancement in GIS technology itself. The development of sophisticated software and hardware solutions for GIS data management is making it easier for organizations to capture, store, analyze, and visualize geographic data. Innovations such as 3D GIS, real-time data processing, and cloud-based GIS solutions are transforming the landscape of geographic data management. These advancements are not only enhancing the capabilities of GIS systems but also making them more accessible to a broader range of users, from small enterprises to large governmental agencies.

The growing implementation of GIS in disaster management and emergency response activities is also a critical factor driving market growth. GIS systems play a crucial role in disaster preparedness, response, and recovery by providing accurate and timely geographic data. This data helps in assessing risks, coordinating response activities, and planning resource deployment. With the increasing frequency and intensity of natural disasters, the reliance on GIS data management systems is expected to grow, resulting in higher demand for GIS solutions across the globe.

Geospatial Solutions are becoming increasingly integral to the GIS Data Management landscape, offering enhanced capabilities for spatial data analysis and visualization. These solutions provide a comprehensive framework for integrating various data sources, enabling users to gain deeper insights into geographic patterns and trends. As organizations strive to optimize their operations and decision-making processes, the demand for robust geospatial solutions is on the rise. These solutions not only facilitate the efficient management of spatial data but also support advanced analytics and real-time data processing. By leveraging geospatial solutions, businesses and governments can improve their strategic planning, resource allocation, and environmental monitoring efforts, thereby driving the overall growth of the GIS Data Management market.

Regionally, North America holds a significant share of the GIS Data Management market, driven by high technology adoption rates and substantial investments in GIS technologies by government and private sectors. However, Asia Pacific is anticipated to witness the highest growth rate during the forecast period. The rapid urbanization, economic development, and increasing adoption of advanced technologies in countries like China and India are major contributors to this growth. Governments in this region are also focusing on smart city projects and infrastructure development, which further boosts the demand for GIS data management solutions.

Component Analysis

The GIS Data Management market is segmented by component into software, hardware, and services. The software segment is the largest and fastest-growing segment, driven by the continuous advancements in GIS software capabilities. GIS software applications enable users to analyze spatial data, create maps, and manage geographic information efficiently. The integration of GIS software with other enterprise systems and the development of user-friendly interfaces are key factors propelling the growth of this segment. Furthermore, the rise of mobile GIS applications, which allow field data collectio

A Normalized Difference Vegetation Index (NDVI) was applied to the source NAIP 2022 60cm imagery. NDVI=(NearIR-Red)/(NearIR+Red). The color ramp (produced by ESRI) goes from brown (less healthy vegetation) to red to green (healthier vegetation or more "greenness").This service is offered by the California Department of Fish and Wildlife (CDFW). For more information about CDFW map services, please visit: https://wildlife.ca.gov/Data/GIS/Map-Services

This service delivers all 4 bands of the NAIP 2016 60cm aerial imagery and may be slower than other related NAIP 2016 services because of the amount and/or format of data being served. Band1=R, Band2=G, Band3=B, Band4=NearIR.This service is offered by the California Department of Fish and Wildlife (CDFW). For more information about CDFW map services, please visit: https://wildlife.ca.gov/Data/GIS/Map-Services

ArcGIS API application that shows study site extents, sampling and sensor locations, LIDAR, glacier extents, aerial imagery extents with downloads.

Please use the links below https://bcczo.colorado.edu/gisarc/arcapi.html

For more in-depth Lidar visit our friends at OpenTopgraphy and click http://criticalzone.org/boulder/data/dataset/2921/ HERE They are large storage for all our Lidar data.

The Cumberland County GIS Data Viewer provides the general public with parcel, zoning, hydrology, soils, utilities and topographic data. You can search for a specific address, street name, parcel number (PIN), or by the owner's name.

The data release for the geologic map of the Butte 1 degree x 2 degrees quadrangle, Montana, is a Geologic Map Schema (GeMS)-compliant version that updates the GIS files for the geologic map published in Montana Bureau of Mines and Geology Open File Report MBMG 363 (Lewis, 1998). The updated digital data present the attribute tables and geospatial features (points, lines and polygons) in the format that meets GeMS requirements. This data release presents the geologic map as shown on the plates and captured in geospatial data for the published map. Minor errors, such as mistakes in line decoration or differences between the digital data and the map image, are corrected in this version. The database represents the geology for the 4.4 million acre, geologically complex Butte 1 x 2 degrees quadrangle, at a publication scale of 1:250,000. The map covers parts of Deer Lodge, Granite, Jefferson, Lewis and Clark, Missoula, Powell, Ravalli, and Silver Bow Counties. These GIS data supersede ...

The U.S. Geological Survey (USGS) has compiled a geodatabase containing mineral-related geospatial data for 10 countries of interest in Southwest Asia (area of study): Afghanistan, Cambodia, Laos, India, Indonesia, Iran, Nepal, North Korea, Pakistan, and Thailand. The data can be used in analyses of the extractive fuel and nonfuel mineral industries and related economic and physical infrastructure integral for the successful operation of the mineral industries within the area of study as well as the movement of mineral products across domestic and global markets. This geodatabase reflects the USGS ongoing commitment to its mission of understanding the nature and distribution of global mineral commodity supply chains by updating and publishing the georeferenced locations of mineral commodity production and processing facilities, mineral exploration and development sites, and mineral commodity exporting ports for the countries in the area of study. The geodatabase contains data feat ...

The Digital Geomorphic-GIS Map of Gulf Islands National Seashore (5-meter accuracy and 1-foot resolution 2006-2007 mapping), Mississippi and Florida is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (guis_geomorphology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (guis_geomorphology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (guis_geomorphology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. 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, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) A GIS readme file (guis_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (guis_geomorphology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (guis_geomorphology_metadata_faq.pdf). Please read the guis_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). 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: U.S. 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 (guis_geomorphology_metadata.txt or guis_geomorphology_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 1:26,000 and United States National Map Accuracy Standards features are within (horizontally) 13.2 meters or 43.3 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

This U.S. Geological Survey (USGS) data release for the geologic map of the Arlington quadrangle, Carbon County, Wyoming, is a Geologic Map Schema (GeMS, 2020)-compliant version of the printed geologic map published in USGS Geologic Map Quadrangle GQ-643 (Hyden and others, 1967). The database represents the geology for the 35,776-acre map plate at a publication scale of 1:24,000. References: Hyden, H.J., King, J.S., and Houston, R.S., 1967, Geologic map of the Arlington quadrangle, Carbon County, Wyoming: U.S. Geological Survey, Geologic Quadrangle Map GQ-643, scale 1:24,000; https://doi.org/10.3133/gq643. U.S. Geological Survey National Cooperative Geologic Mapping Program, 2020, GeMS (Geologic Map Schema) - A standard format for the digital publication of geologic maps: U.S. Geological Survey Techniques and Methods, book 11, chap. B10, 74 p., https://doi.org//10.3133/tm11B10.

This data set consists of 6 classes of zoning features: zoning districts, special purpose districts, special purpose district subdistricts, limited height districts, commercial overlay districts, and zoning map amendments.

All previously released versions of this data are available at BYTES of the BIG APPLE - Archive.