This spreadsheet is the central tracking document and inventory of 'official 'GIS datasets in development, published, or archived at the Greater Atlantic Regional Fisheries Office (GARFO). All shapefiles, data templates and other documents are described here.

This layer features tropical storm (hurricanes, typhoons, cyclones) tracks, positions, and observed wind swaths from the past hurricane season for the Atlantic, Pacific, and Indian Basins. These are products from the National Hurricane Center (NHC) and Joint Typhoon Warning Center (JTWC). They are part of an archive of tropical storm data maintained in the International Best Track Archive for Climate Stewardship (IBTrACS) database by the NOAA National Centers for Environmental Information.Data SourceNOAA National Hurricane Center tropical cyclone best track archive.Update FrequencyWe automatically check these products for updates every 15 minutes from the NHC GIS Data page.The NHC shapefiles are parsed using the Aggregated Live Feeds methodology to take the returned information and serve the data through ArcGIS Server as a map service.Area CoveredWorldWhat can you do with this layer?Customize the display of each attribute by using the ‘Change Style’ option for any layer.Run a filter to query the layer and display only specific types of storms or areas.Add to your map with other weather data layers to provide insight on hazardous weather events.Use ArcGIS Online analysis tools like ‘Enrich Data’ on the Observed Wind Swath layer to determine the impact of cyclone events on populations.Visualize data in ArcGIS Insights or Operations Dashboards.This map is provided for informational purposes and is not monitored 24/7 for accuracy and currency. Always refer to NOAA or JTWC sources for official guidance.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!

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 Track Field dataset.

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 Track Field dataset.

More MetadataDISCLAIMER** These track data are for illustrative purposes only. The 11.5 mile Phase 2 track data and the maintenance track extension were extracted from the latest proposed data provided by MWAA to the Loudoun County Office of Mapping and Geographic Information on April 25, 2012. These data reflect the extension of the Silver Line from Wiehle Ave in Reston, VA to west of Ashburn, VA and, when completed, will become part of the Washington Metropolitan Area Transit Authority (WMATA) Metrorail system.

CDFW BIOS GIS Dataset, Contact: Eric Zahn, Description: This dataset represents a summary of SDTT data collected from 1996-2006. Any track or sign identified from 15 target animals was recorded. Surveys consisted of transects of approximately one mile in length and 30 feet in width along designated dirt trails and roads throughout open space lands in San Diego County.

This collection grew out of a prototype case tracking and crime mapping application that was developed for the United States Attorney's Office (USAO), Southern District of New York (SDNY). The purpose of creating the application was to move from the traditionally episodic way of handling cases to a comprehensive and strategic method of collecting case information and linking it to specific geographic locations, and collecting information either not handled at all or not handled with sufficient enough detail by SDNY's existing case management system. The result was an end-user application designed to be run largely by SDNY's nontechnical staff. It consisted of two components, a database to capture case tracking information and a mapping component to link case and geographic data. The case tracking data were contained in a Microsoft Access database and the client application contained all of the forms, queries, reports, macros, table links, and code necessary to enter, navigate through, and query the data. The mapping application was developed using Environmental Systems Research Institute's (ESRI) ArcView 3.0a GIS. This collection shows how the user-interface of the database and the mapping component were customized to allow the staff to perform spatial queries without having to be geographic information systems (GIS) experts. Part 1 of this collection contains the Visual Basic script used to customize the user-interface of the Microsoft Access database. Part 2 contains the Avenue script used to customize ArcView to link the data maintained in the server databases, to automate the office's most common queries, and to run simple analyses.

These are map packages used to visualize geochemical particle-tracking analysis results in ArcGIS. It includes individual map packages for several regions of New Mexico including: Acoma, Rincon, Gila, Las Cruces, Socorro and Truth or Consequences.

The Office of Spill Prevention and Response (OSPR) Incident Tracking Database is a statewide oil spill tracking information system. The data are collected by OSPR Field Response Team members for Marine oil spills and by OSPR Inland Pollution Coordinators and Wardens for Inland incidents.

This product aids in the visualization of an NHC official track forecast, the forecast points are connected by black line segments. The track line(s) are not a forecast product, however, and because there are an infinite number of ways to connect a set of forecast points, the lines should not be interpreted as representing a specific forecast for the location of a tropical cyclone in between official forecast points.

Observed Track

GapMaps GIS Data by Azira uses location data on mobile phones sourced by Azira which is collected from smartphone apps when the users have given their permission to track their location. It can shed light on consumer visitation patterns (“where from” and “where to”), frequency of visits, profiles of consumers and much more.

Businesses can utilise GIS data to answer key questions including: - What is the demographic profile of customers visiting my locations? - What is my primary catchment? And where within that catchment do most of my customers travel from to reach my locations? - What points of interest drive customers to my locations (ie. work, shopping, recreation, hotel or education facilities that are in the area) ? - How far do customers travel to visit my locations? - Where are the potential gaps in my store network for new developments?
- What is the sales impact on an existing store if a new store is opened nearby? - Is my marketing strategy targeted to the right audience? - Where are my competitor's customers coming from?

Mobile Location data provides a range of benefits that make it a valuable GIS Data source for location intelligence services including: - Real-time - Low-cost at high scale - Accurate - Flexible - Non-proprietary - Empirical

Azira have created robust screening methods to evaluate the quality of Mobile location data collected from multiple sources to ensure that their data lake contains only the highest-quality mobile location data.

This includes partnering with trusted location SDK providers that get proper end user consent to track their location when they download an application, can detect device movement/visits and use GPS to determine location co-ordinates.

Data received from partners is put through Azira's data quality algorithm discarding data points that receive a low quality score.

Use cases in Europe will be considered on a case to case basis.

The Indoor GIS Software market is experiencing robust growth, driven by the increasing need for precise location-based services within enclosed spaces. The market, valued at approximately $1.5 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching an estimated $5 billion by 2033. This expansion is fueled by several key factors. Firstly, the rising adoption of smart buildings and IoT devices provides a wealth of data that Indoor GIS software can effectively leverage for enhanced operational efficiency and improved user experiences. Secondly, the burgeoning e-commerce sector and the consequent demand for optimized warehouse logistics and efficient supply chain management are significantly boosting market demand. Thirdly, the expansion of applications into sectors like healthcare, retail, and security is further diversifying market opportunities. Cloud-based solutions are witnessing higher adoption due to their scalability, cost-effectiveness, and ease of deployment compared to on-premise solutions. However, concerns regarding data security and privacy, as well as the relatively high initial investment costs for implementing Indoor GIS systems, pose challenges to market growth. Segmentation reveals strong demand across various applications. Warehouse logistics and asset management currently dominate the market share due to the clear ROI benefits of improved inventory management and asset tracking. The military and security sectors also present lucrative growth opportunities, driven by the need for sophisticated indoor navigation and situational awareness. Geographically, North America and Europe currently hold the largest market shares, attributed to the high concentration of technologically advanced businesses and early adoption of Indoor GIS technologies. However, Asia-Pacific is expected to show significant growth in the coming years, propelled by rapid urbanization and expanding industrial sectors in countries like China and India. Companies like Mapedin, Esri, and others are key players driving innovation and shaping the competitive landscape. The ongoing development of advanced features such as real-time location tracking, augmented reality integration, and improved data analytics capabilities will further fuel market growth in the coming years.

CDFW BIOS GIS Dataset, Contact: Melanie Gogol-Prokurat, Description: Vector datasets of CWHR range maps are one component of California Wildlife Habitat Relationships (CWHR), a comprehensive information system and predictive model for California's wildlife. The CWHR System was developed to support habitat conservation and management, land use planning, impact assessment, education, and research involving terrestrial vertebrates in California.

The NOAA National Hurricane Center (NHC) publishes advisory bulletins with named storm conditions and expectations, see [1]. We have also downloaded shapefiles for eighty-four 5-day forecasts (published from August 30 to September 11) of track line, predicted points, ensemble forecasts envelope, and affected shoreline where applicable [2]. NOAA also publishes the best track for major storms [3]. The "best track" is a smoothed version of the advisories track. Web services are also provided by NHC for the advisory points and lines [4] [5]. Another user has constructed the Irma track (shapefile) from the NHC advisory bulletins [6].

FEMA also posts windfield data, including peak wind gust and contours [7]. See FEMA disaster webpage [8] for map and list of counties receiving disaster declarations (map pdf available for download from this page)

References [1] NOAA NHC - Irma storm advisories [http://www.nhc.noaa.gov/archive/2017/IRMA.shtml]
[2] NOAA NHC - Irma 5-day forecasts [https://www.nhc.noaa.gov/gis/archive_forecast_results.php?id=al11&year=2017&name=Hurricane%20IRMA] [3] NOAA NHC - best tracks for 2017 storms [https://www.nhc.noaa.gov/data/tcr/index.php?season=2017&basin=atl] [4] NOAA NHC - Irma advisory points web service [https://services.arcgis.com/XSeYKQzfXnEgju9o/ArcGIS/rest/services/The_2017_Atlantic_Hurricane_season_(to_October_16th)/FeatureServer/1] [5] NOAA NHC - Irma advisory lines web service [https://services.arcgis.com/XSeYKQzfXnEgju9o/ArcGIS/rest/services/The_2017_Atlantic_Hurricane_season_(to_October_16th)/FeatureServer/6] [6] Irma Advisories Track, compiled by David Tarboton [https://www.hydroshare.org/resource/546fa3feeaf242fc8aabf9fe05ab454c/] [7] FEMA public download site for Hurricane Irma 2017 [https://data.femadata.com/NationalDisasters/HurricaneIrma/] [8] FEMA Disaster Declarations and related links [https://www.fema.gov/disaster/4337]

The Digital Geologic-GIS Map of the Tennessee portion of Natchez Trace Parkway, Tennessee 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 (natr_tn_geology.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 (natr_tn_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 (natr_tn_geology.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 (natr_tn_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (natr_tn_geology.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 (natr_tn_geology_metadata_faq.pdf). Please read the natr_tn_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: Tennessee Division of Geology. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (natr_tn_geology_metadata.txt or natr_tn_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 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).

The best track is a subjectively-smoothed representation of the tropical cyclone's location and intensity at 6-h interval over its lifetime. These best track positions and intensity (maximum 1-minute sustained surface wind speed and minimum sea-level pressure) are based on a post-storm assessment of all available data and may differ from values contained in real-time storm advisories. In general, they will not reflect the erratic motion implied by connecting the individual center fix positions. The best track is a living database which serves as the official U.S. National Weather Service historical record of the tropical cyclone.

Track the MV GIS BLAKELY in real-time with AIS data. TRADLINX provides live vessel position, speed, and course updates. Search by MMSI: 657262700, IMO: 8973423

Geographic Information System (GIS) Tools Market Outlook

The global Geographic Information System (GIS) Tools market is poised for significant expansion, with a projected market size of approximately $15.2 billion in 2023, anticipated to reach $28.6 billion by 2032, reflecting a compound annual growth rate (CAGR) of 7.3%. This growth can be attributed to the increasing integration of advanced GIS technologies across various sectors such as agriculture, transportation, and government services, driven by the need for efficient data management and spatial analysis capabilities. The adoption of GIS tools is further influenced by the growing demand for real-time geographic data, which plays a crucial role in decision-making processes across multiple industries.

One of the primary growth factors for the GIS Tools market is the burgeoning demand for high-precision mapping and spatial data analytics. Industries such as agriculture and construction are increasingly relying on GIS technology to optimize resource management and streamline operations. The ability of GIS tools to provide detailed insights into geographical patterns and trends allows companies to make informed decisions, thereby improving operational efficiency and reducing costs. Additionally, advancements in remote sensing technology and data collection methods have significantly enhanced the accuracy and reliability of GIS data, further fueling its adoption across various sectors.

The increasing deployment of GIS tools in urban planning and smart city projects is another key driver of market growth. Governments worldwide are leveraging GIS technology to enhance infrastructure planning, improve public services, and manage environmental resources more effectively. The integration of GIS in smart city initiatives enables authorities to monitor and manage urban environments in real-time, leading to better resource allocation and improved quality of life for residents. As cities continue to expand and evolve, the demand for advanced GIS solutions is expected to grow exponentially, providing significant opportunities for market players.

Furthermore, the rise of location-based services and telematics has expanded the application of GIS tools in the transportation and logistics sectors. Companies are utilizing GIS technology to optimize route planning, track assets, and enhance supply chain management. The integration of GIS with telematics systems allows for real-time monitoring and analysis of vehicle movements, improving fleet efficiency and reducing operational costs. As the transportation industry continues to embrace digital transformation, the demand for GIS tools is likely to increase, further driving market growth.

In terms of regional outlook, North America currently leads the GIS Tools market, driven by high adoption rates of advanced technologies and significant investments in infrastructure development. The presence of major GIS solution providers and a well-established IT infrastructure further contribute to the region's dominance. However, the Asia Pacific region is expected to witness the highest growth during the forecast period, driven by rapid urbanization, increasing government initiatives for infrastructure development, and the growing adoption of GIS technology in emerging economies such as China and India. Europe and the Middle East & Africa regions are also expected to experience steady growth, supported by advancements in GIS applications and the rising need for efficient spatial data management solutions.

The role of a Gis Data Collector is increasingly becoming pivotal in the GIS Tools market. These professionals are responsible for gathering, verifying, and maintaining the spatial data that forms the backbone of GIS applications. With the growing emphasis on high-precision mapping and real-time data analysis, the demand for skilled Gis Data Collectors is on the rise. They play a crucial role in ensuring the accuracy and reliability of geospatial information, which is essential for effective decision-making across various sectors. As industries continue to leverage advanced GIS technologies, the expertise of Gis Data Collectors will be indispensable in facilitating seamless data integration and enhancing the overall quality of GIS solutions.

Component Analysis

The GIS Tools market can be segmented by component into software, hardware, and services, each playing a vital role in the overall market dynamics. The software segment is expected to hold the largest market

Tornado TracksThis feature layer, utilizing data from the National Oceanic and Atmospheric Administration (NOAA), displays tornadoes in the United States, Puerto Rico and U.S. Virgin Islands between 1950 and 2024. A tornado track shows the route of a tornado. Per NOAA, "A tornado is a narrow, violently rotating column of air that extends from a thunderstorm to the ground. Because wind is invisible, it is hard to see a tornado unless it forms a condensation funnel made up of water droplets, dust and debris. Tornadoes can be among the most violent phenomena of all atmospheric storms we experience. The most destructive tornadoes occur from supercells, which are rotating thunderstorms with a well-defined radar circulation called a mesocyclone. (Supercells can also produce damaging hail, severe non-tornadic winds, frequent lightning, and flash floods.)"EF-5 Tornado Track (May 3, 1999) near Oklahoma City, OklahomaData currency: December 30, 2024Data source: Storm Prediction CenterData modifications: Added field "Date_Calc"For more information: Severe Weather 101 - Tornadoes; NSSL Research: TornadoesSupport documentation: SPC Tornado, Hail, and Wind Database Format SpecificationFor feedback, please contact: ArcGIScomNationalMaps@esri.comNational Oceanic and Atmospheric AdministrationPer NOAA, its mission is "To understand and predict changes in climate, weather, ocean, and coasts, to share that knowledge and information with others, and to conserve and manage coastal and marine ecosystems and resources."