USFS Region 01 Mushroom Hunter Helper displays fire history activity from the last two years. The data is not dynamically updated, but updated once every year when previous years fire perimeters become available (usually in March). The underlying base data is a service provide by the Enterprise Data Warehouse and ESRI. For information about this Web Mapping Application and or access to the data, please contact the Northern Region Geospatial Group or your local National Forest.
Digital Map Market Size 2025-2029
The digital map market size is forecast to increase by USD 31.95 billion at a CAGR of 31.3% between 2024 and 2029.
The market is driven by the increasing adoption of intelligent Personal Digital Assistants (PDAs) and the availability of location-based services. PDAs, such as smartphones and smartwatches, are becoming increasingly integrated with digital map technologies, enabling users to navigate and access real-time information on-the-go. The integration of Internet of Things (IoT) enables remote monitoring of cars and theft recovery. Location-based services, including mapping and navigation apps, are a crucial component of this trend, offering users personalized and convenient solutions for travel and exploration. However, the market also faces significant challenges.
Ensuring the protection of sensitive user information is essential for companies operating in this market, as trust and data security are key factors in driving user adoption and retention. Additionally, the competition in the market is intense, with numerous players vying for market share. Companies must differentiate themselves through innovative features, user experience, and strong branding to stand out in this competitive landscape. Security and privacy concerns continue to be a major obstacle, as the collection and use of location data raises valid concerns among consumers.
What will be the Size of the Digital Map Market during the forecast period?
Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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In the market, cartographic generalization and thematic mapping techniques are utilized to convey complex spatial information, transforming raw data into insightful visualizations. Choropleth maps and dot density maps illustrate distribution patterns of environmental data, economic data, and demographic data, while spatial interpolation and predictive modeling enable the estimation of hydrographic data and terrain data in areas with limited information. Urban planning and land use planning benefit from these tools, facilitating network modeling and location intelligence for public safety and emergency management.
Spatial regression and spatial autocorrelation analyses provide valuable insights into urban development trends and patterns. Network analysis and shortest path algorithms optimize transportation planning and logistics management, enhancing marketing analytics and sales territory optimization. Decision support systems and fleet management incorporate 3D building models and real-time data from street view imagery, enabling effective resource management and disaster response. The market in the US is experiencing robust growth, driven by the integration of Geographic Information Systems (GIS), Global Positioning Systems (GPS), and advanced computer technology into various industries.
How is this Digital Map Industry segmented?
The digital map industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.
Application
Navigation
Geocoders
Others
Type
Outdoor
Indoor
Solution
Software
Services
Deployment
On-premises
Cloud
Geography
North America
US
Canada
Europe
France
Germany
UK
APAC
China
India
Indonesia
Japan
South Korea
Rest of World (ROW)
By Application Insights
The navigation segment is estimated to witness significant growth during the forecast period. Digital maps play a pivotal role in various industries, particularly in automotive applications for driver assistance systems. These maps encompass raster data, aerial photography, government data, and commercial data, among others. Open-source data and proprietary data are integrated to ensure map accuracy and up-to-date information. Map production involves the use of GPS technology, map projections, and GIS software, while map maintenance and quality control ensure map accuracy. Location-based services (LBS) and route optimization are integral parts of digital maps, enabling real-time navigation and traffic data.
Data validation and map tiles ensure data security. Cloud computing facilitates map distribution and map customization, allowing users to access maps on various devices, including mobile mapping and indoor mapping. Map design, map printing, and reverse geocoding further enhance the user experience. Spatial analysis and data modeling are essential for data warehousing and real-time navigation. The automotive industry's increasing adoption of connected cars and long-term evolution (LTE) technologies have fueled the demand for digital maps. These maps enable driver assistance app
Comprehensive dataset of 466 Map stores in United States as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.
Interactive visualization of tariff rates imposed by the United States on countries around the world
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Dataset Card for 2025 AI Market Maps
Curated By: Joy Larkin Last Updated: 20 June 2025 Language(s) (NLP): English License: MIT Repository: https://github.com/joylarkin/Awesome-AI-Market-Maps
Dataset Description
An Awesome List of 200+ Artificial Intelligence Startup Market Maps from 2025 and 2024. As these things go, this awesome list was inspired out of an ongoing personal frustration — I have been searching for a frequently updated and well-resourced list of recent… See the full description on the dataset page: https://huggingface.co/datasets/joylarkin/2025AIMarketMaps.
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The 119th Congressional Districts dataset reflects boundaries from January 03, 2025 from the United States Census Bureau (USCB), and the attributes are updated every Sunday from the United States House of Representatives and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). Source data from USDOT is at https://catalog.data.gov/dataset/congressional-districts3Congressional Districts feature layer is updated as-needed and we expect to update it more regularly in the future.Attribute SchemaSTATEFP: The STATEFP is the State fips code.CD119FP: The CD119FP is the Office number of the corresponding district.GEOID: The GEOID is a concatenation of the state fips code and the district number. GEOIDFQ: The GEOIDFQ attribute facilitates joining Census Bureau spatial data to Census Bureau summary file data from data.census.gov. It stands for the "Fully Qualified Geographic Identifier".NAMELSAD: The NAMELSAD is the Congressional District labeled name.LSAD: The LSAD is the Legal/Statistical Area Description.CDSESSN: The CDSESSN is the Congress District Session.MTFCC: The MTFCC is the MAF/TIGER Feature Class Code for "Congressional District".FUNCSTAT: The functional status (FUNCSTAT) code defines the current functional status of a geographic entityALAND: The ALAND is the Land Area (square meters).AWATER: The AWATER is the Water Area (square meters).INTPTLAT: The INTPTLAT is the Latitude.INTPLON: The INTPLON is the Longitude.OFFICE_ID: The OFFICE_ID is the Office number of the corresponding district.BIOGUIDE_ID: The BIOGUIDE_ID is the Biographical Directory of the US Congress.OFFICE_AUDIT_ID: PREFIX: The Prefix is the Member's title.FIRSTNAME: The FIRSTNAME is the Member's first name.MIDDLENAME: The MIDDLENAME is the Member's middle name.LASTNAME: The LASTNAME is the Member's last name.SUFFIX: The SUFFIX is the Member's suffix.LISTING_NAME: The LISTING_NAME is the Member's last name and first name.PHONE: The PHONE is the last five digits in the office phone number to reach the Member.WEBSITEURL: The WEBSITEURL is the Member's website link.VACANT: The VACANT field is a 'Y' or 'N' for the Member's vacancy.CONTACTFORMURL: The CONTACTFORMURL is direct access to the Member's contact form.PHOTOURL: The PHOTOURL is the link to a photo of the Member.FACE_BOOK_URL: The FACE_BOOK_URL is a link to the Member's Facebook link.TWITTER_URL: The TWITTER_URL is the Member's Twitter link.YOUTUBE_URL: The YOUTUBE_URL is the Member's Youtube link.INSTAGRAM_URL: The INSTAGRAM_URL is the Member's Instagram link.FLICKR_URL: The FLICKR_URL is the Member's Flicker link.PARTY: The PARTY is the party that the Member represents.DISTRICT: The DISTRICT is the district number.VACANCY: ROOM_NUM: The ROOM_NUM is the Member's office room number.HOB: is the Room Code 'Cannon House Office Building', 'Longworth House Office Building', 'Rayburn House Office Building'.COMMITTEE_ASSIGNMENTS: The COMMITTEE_ASSIGNMENTS are the committees that the Member is assigned to.LAST_UPDATED:For more informationhttps://www.census.gov/programs-surveys/geography/technical-documentation/records-layout/gaz-record-layouts.htmlhttps://www.congress.gov/help/field-values/member-bioguide-idshttps://www2.census.gov/geo/pdfs/reference/LSADCodes.pdf
This dataset provides information on 3 in Kansas, United States as of June, 2025. It includes details such as email addresses (where publicly available), phone numbers (where publicly available), and geocoded addresses. Explore market trends, identify potential business partners, and gain valuable insights into the industry. Download a complimentary sample of 10 records to see what's included.
This is a database of tornadoes that have affected the Huntsville Forecast area this year. National Weather Service Storm Survey information regarding the tornadoes that occurred so far in 2025 within the NWS Huntsville County Warning Area (CWA). Included are storm survey damage points with pictures where available, tornado damage paths, and estimated damage swath information where applicable.
This dataset provides information on 30 in New York, United States as of June, 2025. It includes details such as email addresses (where publicly available), phone numbers (where publicly available), and geocoded addresses. Explore market trends, identify potential business partners, and gain valuable insights into the industry. Download a complimentary sample of 10 records to see what's included.
HD Map For Autonomous Vehicles Market Size 2024-2028
The HD map for autonomous vehicles market size is forecast to increase by USD 14 billion at a CAGR of 40.5% between 2023 and 2029
The market is experiencing significant growth, driven by the increasing adoption of autonomous vehicles and the development of advanced connected infrastructure. The integration of high-definition maps into autonomous systems enables vehicles to navigate complex environments more accurately and efficiently, reducing the risk of accidents and improving overall performance. HD map creation for autonomous vehicles is a complex process involving data acquisition, aggregation, and integration of advanced technologies such as AI and machine learning. However, the high cost associated with the technology remains a significant challenge for market expansion. Manufacturers must continue to innovate and find cost-effective solutions to make HD maps an essential component of autonomous vehicles, rather than a luxury. Companies seeking to capitalize on this market opportunity should focus on collaborating with infrastructure providers, developing scalable and cost-effective HD mapping technologies, and ensuring seamless integration with autonomous systems. By addressing these challenges and leveraging the growing demand for autonomous vehicles and advanced infrastructure, market participants can effectively navigate the strategic landscape and drive long-term success.
What will be the Size of the Market during the forecast period?
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The market is experiencing significant growth as the global push towards advanced driver-assistance systems (ADAS) and fully autonomous vehicles (AVs) continues. HD Maps, which utilize technologies such as Lidar, SLAM (Simultaneous Localization and Mapping), and digital cameras, play a crucial role in enabling AVs to navigate roads safely and efficiently. These maps provide real-time, high-precision data to AV systems, allowing them to identify and respond to road conditions, obstacles, and other vehicles in real time. The market is expected to reach a substantial size in the coming years, driven by the increasing demand for shared mobility services, including ride-sharing and robo-taxi services.
The integration of 5G networks is also expected to accelerate the adoption of HD Maps, as they enable faster and more reliable data transmission between vehicles and maps. The market is witnessing continuous innovation, with companies investing heavily in research and development to improve the accuracy and coverage of HD Maps. Additionally, the integration of HD Maps with other technologies, such as sensor fusion and deep learning algorithms, is expected to further enhance the capabilities of AVs. Overall, the HD Map market for autonomous vehicles is a dynamic and rapidly evolving market, poised for significant growth in the coming years.
How is this Industry segmented?
The industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.
Solution
Cloud-based
Embedded
Vehicle Type
Passenger
Commercial
Geography
North America
US
Europe
Germany
UK
APAC
China
Japan
Middle East and Africa
South America
By Solution Insights
The cloud-based segment is estimated to witness significant growth during the forecast period. HD maps are a critical component in the advancement of autonomous vehicles. These high-definition maps offer enhanced accuracy and precision for navigation, while their cloud-based infrastructure ensures accessibility and ease of updates. This enables autonomous vehicles to navigate complex and unfamiliar environments more effectively. Notable industry players, such as NavInfo Co. Ltd. (Navinfo), HERE Global BV (HERE), TomTom NV (TomTom), and NVIDIA Corp. (NVIDIA), prioritize cloud-based solutions and real-time services for their HD mapping offerings. The integration of 5G networks further enhances the capabilities of HD maps, contributing to the growth of autonomous driving technology in passenger and commercial vehicles.
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The cloud-based segment was valued at USD 1047.3 million in 2019 and showed a gradual increase during the forecast period.
Regional Analysis
North America is estimated to contribute 40% to the growth of the global market during the forecast period. Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.
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The market in North America is primarily driven by the United States, where the increasing deployment of
Important Note: This item is in mature support as of June 2023 and will be retired in December 2025. This map shows per capita income (income per person) in the U.S. in 2022 in a multiscale map by country, state, county, ZIP Code, tract, and block group. ArcGIS Online subscription required. Per capita income is calculated by taking the sum of all incomes and dividing by the total population.The pop-up is configured to include the following information for each geography level:2022 Per capita incomeTotal population2027 projected per capita incomePermitted use of this data is covered in the DATA section of the Esri Master Agreement (E204CW) and these supplemental terms.
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According to Cognitive Market Research, the global HD Map for Autonomous Vehicle Market size will be USD 1624.8 million in 2025. It will expand at a compound annual growth rate (CAGR) of 31.50% from 2025 to 2033.
North America held the major market share for more than 37% of the global revenue with a market size of USD 601.18 million in 2025 and will grow at a compound annual growth rate (CAGR) of 29.3% from 2025 to 2033.
Europe accounted for a market share of over 29% of the global revenue with a market size of USD 471.19 million.
APAC held a market share of around 24% of the global revenue with a market size of USD 389.95 million in 2025 and will grow at a compound annual growth rate (CAGR) of 33.5% from 2025 to 2033.
South America has a market share of more than 3.8% of the global revenue with a market size of USD 61.74 million in 2025 and will grow at a compound annual growth rate (CAGR) of 30.5% from 2025 to 2033.
Middle East had a market share of around 4.00% of the global revenue and was estimated at a market size of USD 64.99 million in 2025 and will grow at a compound annual growth rate (CAGR) of 30.8% from 2025 to 2033.
Africa had a market share of around 2.20% of the global revenue and was estimated at a market size of USD 35.75 million in 2025 and will grow at a compound annual growth rate (CAGR) of 31.2% from 2025 to 2033.
Commercial Vehicles is the fastest growing segment of the HD Map for Autonomous Vehicle Market industry
Market Dynamics of HD Map for Autonomous Vehicle Market
Key Drivers for HD Map for Autonomous Vehicle Market
Rising adoption of autonomous and semi-autonomous vehicles fuel the market demand
The global shift toward autonomous and semi-autonomous vehicles is significantly propelling the demand for HD maps. With increasing consumer inclination toward advanced driver-assistance systems (ADAS) and partial automation features such as lane centering, adaptive cruise control, and self-parking, automakers are integrating high-definition maps into vehicle systems for enhanced precision. HD maps support sensor fusion and real-time decision-making by providing centimeter-level accuracy, which is essential for safe navigation. As Level 2 and Level 3 vehicles become more mainstream, particularly in North America, Europe, and East Asia, the dependency on detailed geospatial data is expanding rapidly. According to the 2025 report by the World Economic Forum in partnership with Boston Consulting Group, about 4% of newly sold personal vehicles in 2035 are projected to be equipped with Level 4 autonomous capabilities. This growth trajectory is further supported by regulatory encouragement and pilot testing of autonomous technologies, creating a solid foundation for market expansion.
https://reports.weforum.org/docs/WEF_Autonomous_Vehicles_2025.pdf
Increasing demand for real-time navigation and safety features boosts the industry
The rising demand for real-time navigation and vehicle safety systems is a core driver of the HD map market. Traditional maps fall short in offering the dynamic data required for autonomous driving, such as lane-level information, road gradients, and obstacle detection. HD maps bridge this gap by providing enriched geospatial content that complements vehicle sensors, enabling safer and more reliable driving decisions. Consumers are increasingly valuing safety-centric features, and automakers are responding with integrated solutions that rely on continuously updated and context-aware HD maps. These maps enhance situational awareness in complex traffic scenarios, support predictive navigation, and reduce the risk of collisions. As real-time responsiveness becomes a critical factor in vehicular operations, the demand for HD mapping solutions continues to surge.
Restraint Factor for the HD Map for Autonomous Vehicle Market
High cost of map creation and frequent updates limit market growth
One of the primary constraints hindering the widespread adoption of HD maps is the high cost associated with their creation and maintenance. Generating centimeter-level accurate maps requires advanced hardware such as LiDAR, high-resolution cameras, and precise GPS systems, all of which involve substantial capital expenditure. Moreover, these maps must be frequently updated to reflect real-time changes in road conditions, traffic patterns, construction zones, and signage. The continual need for accurate, up-to-date data further increases ...
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The global digital map service market size is projected to grow significantly, from approximately $18.9 billion in 2023 to an estimated $53.1 billion by 2032, reflecting a compelling Compound Annual Growth Rate (CAGR) of 12.5%. This robust growth is driven by the increasing adoption of digital mapping technologies across diverse industries and the rising demand for real-time geographic and navigation data in both consumer and enterprise applications.
One of the primary growth factors for the digital map service market is the expanding use of digital maps in the automotive sector, particularly in the development of Advanced Driver Assistance Systems (ADAS) and autonomous vehicles. These technologies rely heavily on precise and up-to-date mapping data for navigation, obstacle detection, and other functionalities, making digital maps indispensable. Additionally, the proliferation of mobile devices and the integration of mapping services in applications such as ride-sharing, logistics, and local search have significantly contributed to market expansion.
Another significant driver is the increasing reliance on Geographic Information Systems (GIS) across various industries. GIS technology enables organizations to analyze spatial information, improve decision-making processes, and enhance operational efficiencies. Industries such as government, defense, agriculture, and urban planning utilize GIS for land use planning, disaster management, and resource allocation, among other applications. The continuous advancements in GIS technology and the integration of artificial intelligence (AI) and machine learning (ML) are expected to further propel market growth.
The rising demand for real-time location data is also a crucial factor fueling the growth of the digital map service market. Real-time location data is essential for applications such as fleet management, asset tracking, and public safety. Businesses leverage this data to optimize routes, monitor assets, and enhance customer service. The increasing implementation of Internet of Things (IoT) devices and the growing importance of location-based services are likely to sustain the demand for real-time mapping solutions in the coming years.
Regionally, North America leads the digital map service market, driven by the high adoption rate of advanced technologies and the presence of major players in the region. However, the Asia Pacific region is expected to witness the fastest growth, attributed to rapid urbanization, increasing smartphone penetration, and government initiatives to develop smart cities. Europe, Latin America, and the Middle East & Africa are also anticipated to experience substantial growth, fueled by the rising demand for digital mapping solutions across various sectors.
In the digital map service market, the service type segment includes mapping and navigation, geographic information systems (GIS), real-time location data, and others. Mapping and navigation services hold a significant share in the market, primarily due to their extensive use in personal and commercial navigation systems. These services provide detailed road maps, traffic updates, and route planning, which are essential for everyday commuting and logistics operations. The continuous advancements in navigation technologies, such as integration with AI and ML for predictive analytics, are expected to enhance the accuracy and functionality of these services.
Geographic Information Systems (GIS) represent another critical segment within the digital map service market. GIS technology is widely used in various applications, including urban planning, environmental management, and disaster response. The ability to analyze and visualize spatial data in multiple layers allows organizations to make informed decisions and optimize resource allocation. The integration of GIS with other emerging technologies, such as drones and remote sensing, is further expanding its application scope and driving market growth.
Real-time location data services are gaining traction due to their importance in applications like fleet management, asset tracking, and location-based services. These services provide up-to-the-minute information on the geographical position of assets, vehicles, or individuals, enabling businesses to improve operational efficiency and customer satisfaction. The growing adoption of IoT devices and the increasing need for real-time visibility in supply chain operations are expected to bolster the demand for real-time location data services.</p&
This map package includes the official Tribal areas that NTIA recognizes for their grant programs. The map package includes the following layers. Alaska Native Villages - this layer represents Alaska Native Villages and is created by Census. The layer was downloaded on Jan. 28, 2025, from here: TIGER/Line® Shapefiles.Native Hawaiian Areas - this layer represents Native Hawaiian Areas and is created by Census. The layer was downloaded on Jan. 28, 2025, from here: TIGER/Line® Shapefiles and has been filtered to only include Native Hawaiian Areas. BIA AIAN National LAR - this layer represents American Indian Lands and is created by the BIA. The layer was accessed here: BIA Access Open Data and was exported on Jan. 28, 2025. The layer was filtered to only include lands across the continental U.S. BIA AIAN LAR Supplemental - this layer is a supplemental dataset to the LAR. The layer was accessed here: BIA Access Open Data and was exported on Jan. 28, 2025.BIA AIAN Tribal Statistical Areas - this layer represents Tribal Statistical Areas located in Oklahoma. The layer was accessed here: BIA Access Open Data and was exported on Jan. 28, 2025.This map package was created on Jan. 28, 2025 and was created using ArcGIS Pro 3.4.0. If you have any questions regarding the map package please e-mail IFA Analytics.ResourcesCensus DataBIA Open DataBIA Data DisclaimerBy using this product, the user agrees to the below terms and conditions:No warranty is made by the Bureau of Indian Affairs (BIA) for the use of the data for purposes not intended by the BIA. This GIS Dataset may contain errors. There is no impact on the legal status of the land areas depicted herein and no impact on land ownership. No legal inference can or should be made from the information in this GIS Dataset. The GIS Dataset is prepared strictly for illustrative and reference purposes only and should not be used, and is not intended for legal, survey, engineering or navigation purposes. These data have been developed from the best available sources. Although efforts have been made to ensure that the data are accurate and reliable, errors and variable conditions originating from source documents and/or the translation of information from source documents to the systems of record continue to exist. Users must be aware of these conditions and bear responsibility for the appropriate use of the information with respect to possible errors, scale, resolution, rectification, positional accuracy, development methodology, time period, environmental and climatic conditions and other circumstances specific to these data. The user is responsible for understanding the accuracy limitations of the data provided herein. The burden for determining fitness for use lies entirely with the user. The user should refer to the accompanying metadata notes for a description of the data and data development procedures.Census Use RestraintsThe TIGER/Line Shapefile products are not copyrighted however TIGER/Line and Census TIGER are registered trademarks of the U.S. Census Bureau. These products are free to use in a product or publication, however acknowledgement must be given to the U.S. Census Bureau as the source. The boundary information in the TIGER/Line Shapefiles are for statistical data collection and tabulation purposes only; their depiction and designation for statistical purposes does not constitute a determination of jurisdictional authority or rights of ownership or entitlement and they are not legal land descriptions. Coordinates in the TIGER/Line shapefiles have six implied decimal places, but the positional accuracy of these coordinates is not as great as the six decimal places suggest.
Important Note: This item is in mature support as of June 2023 and will be retired in December 2025. This map shows the median age of the U.S. population in 2022 in a multiscale map by country, state, county, ZIP Code, tract, and block group. In 2022, the median age of the population in the U.S. is 38 years of age.The popup is configured to include the following information for each geography level:Median age of total populationTotal population counts (by 5 year increments)Median age of male populationMale population counts (by 5 year increments)Median age of female populationFemale population counts (by 5 year increments)Permitted use of this data is covered in the DATA section of the Esri Master Agreement (E204CW) and these supplemental terms.
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Inflation Rate in the United States increased to 2.40 percent in May from 2.30 percent in April of 2025. This dataset provides - United States Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.
This dataset provides information on 11 in Massachusetts, United States as of June, 2025. It includes details such as email addresses (where publicly available), phone numbers (where publicly available), and geocoded addresses. Explore market trends, identify potential business partners, and gain valuable insights into the industry. Download a complimentary sample of 10 records to see what's included.
U.S. Government Workshttps://www.usa.gov/government-works
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This map layer is a thematic raster image of MTBS burn severity classes for all inventoried fires occurring in CONUS during calendar year 2022 that do not meet standard MTBS size criteria. These data are published to augment the data that are available from the MTBS program. This product was produced using the methods of the Monitoring Trends in Burn Severity Program (MTBS), however these fires do not meet the size criteria for a standard MTBS assessment. The MTBS Program assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period 1984 and beyond. MTBS typically maps fires using an initial assessment (immediately after the fire) or an extended assessment (peak of green the season after the fire) for low-biomass and high-biomass fires respectively. Refer to MTBS.gov for more information on MTBS methods and criteria. Standard MT ...
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The HD Live Map market is experiencing robust growth, projected to reach a market size of $6,016.4 million in 2025. While the provided CAGR is missing, considering the rapid advancements in autonomous driving technology, connected car infrastructure, and the increasing demand for precise location data across commercial and military applications, a conservative estimate for the CAGR during the forecast period (2025-2033) would be around 15%. This signifies a substantial expansion of the market, driven by factors such as the escalating adoption of Advanced Driver-Assistance Systems (ADAS) and autonomous vehicles, the rising need for real-time traffic updates in smart city initiatives, and the growing deployment of HD maps in military applications for enhanced situational awareness. The market segmentation reveals strong demand across both commercial and military sectors, with the crowdsourcing model gaining traction due to its cost-effectiveness and data aggregation capabilities. Key players like TomTom, Google, and Baidu are leading the market, continuously investing in R&D to enhance map accuracy, detail, and real-time updates. Regional variations are expected, with North America and Asia Pacific leading the market share due to higher technological adoption rates and substantial investments in infrastructure development. The continued growth in the HD Live Map market is further fueled by the increasing integration of 5G technology, which enables faster data transmission and real-time updates critical for autonomous driving and location-based services. Furthermore, government regulations promoting road safety and autonomous vehicle development are creating a favorable environment for market expansion. However, challenges such as high initial investment costs for map creation and maintenance, data security concerns, and the need for continuous map updates could potentially restrain growth to some extent. Nonetheless, the long-term outlook for the HD Live Map market remains positive, fueled by ongoing technological innovation and the increasing demand for precise location intelligence across diverse sectors.
Source data found here: https://hydro.nationalmap.gov/arcgis/rest/services/wbd/MapServerEach drainage area is considered a Hydrologic Unit (HU) and is given a Hydrologic Unit Code (HUC) which serves as the unique identifier for the area. HUC 2s, 6s, 8s, 10s, & 12s, define the drainage Regions, Subregions, Basins, Subbasins, Watersheds and Subwatersheds, respectively, across the United States. Their boundaries are defined by hydrologic and topographic criteria that delineate an area of land upstream from a specific point on a river and are determined solely upon science based hydrologic principles, not favoring any administrative boundaries, special projects, or a particular program or agency. The Watershed Boundary Dataset is delineated and georeferenced to the USGS 1:24,000 scale topographic basemap.Hydrologic Units are delineated to nest in a multi-level, hierarchical drainage system with corresponding HUCs, so that as you move from small scale to large scale the HUC digits increase in increments of two. For example, the very largest HUCs have 2 digits, and thus are referred to as HUC 2s, and the very smallest HUCs have 12 digits, and thus are referred to as HUC 12s.Dataset SummaryPhenomenon Mapped: Watersheds in the United States, as delineated by the Watershed Boundary Dataset (WBD)Geographic Extent: Contiguous United States, Alaska, Hawaii, Puerto Rico, Guam, US Virgin Islands, Northern Marianas Islands and American SamoaProjection: Web MercatorUpdate Frequency: AnnualVisible Scale: Visible at all scales, however USGS recommends this dataset should not be used for scales of 1:24,000 or larger.Source: United States Geological SurveyPublication Date: January 7, 2025What can you do with this layer?This layer is suitable for both visualization and analysis acrossthe ArcGIS system. This layer can be combined with your data and other layers from the ArcGIS Living Atlas of the World in ArcGIS Online and ArcGIS Pro to create powerful web maps that can be used alone or in a story map or other application. Because this layer is part of the ArcGIS Living Atlas of the World it is easy to add to your map:In ArcGIS Online, you can add this layer to a map by selecting Add then Browse Living Atlas Layers. A window will open. Type "Watershed Boundary Dataset" in the search box and browse to the layer. Select the layer then click Add to Map. In ArcGIS Pro, open a map and select Add Data from the Map Tab. Select Data at the top of the drop down menu. The Add Data dialog box will open on the left side of the box, expand Portal if necessary, then select Living Atlas. Type "Watershed Boundary Dataset" in the search box, browse to the layer then click OK.
USFS Region 01 Mushroom Hunter Helper displays fire history activity from the last two years. The data is not dynamically updated, but updated once every year when previous years fire perimeters become available (usually in March). The underlying base data is a service provide by the Enterprise Data Warehouse and ESRI. For information about this Web Mapping Application and or access to the data, please contact the Northern Region Geospatial Group or your local National Forest.