At Driver Technologies, we specialize in collecting high-quality, highly-anonymized, driving data crowdsourced using our dash cam app. Our Traffic Light Map Video Data is built from the millions of miles of driving data captured and is optimized to be trained for whatever computer vision models you need and enhancing various applications in transportation and safety.
What Makes Our Data Unique? What sets our Traffic Light Map Video Data apart is its comprehensive approach to road object detection. By leveraging advanced computer vision models, we analyze the captured video to identify and classify various road objects encountered during an end user's trip. This includes road signs, pedestrians, vehicles, traffic signs, and road conditions, resulting in rich, annotated datasets that can be used for a range of applications.
How Is the Data Generally Sourced? Our data is sourced directly from users who utilize our dash cam app, which harnesses the smartphone’s camera and sensors to record during a trip. This direct sourcing method ensures that our data is unbiased and represents a wide variety of conditions and environments. The data is not only authentic and reflective of current road conditions but is also abundant in volume, offering millions of miles of recorded trips that cover diverse scenarios.
Primary Use-Cases and Verticals The Traffic Light Map Video Data is tailored for various sectors, particularly those involved in transportation, urban planning, and autonomous vehicle development. Key use cases include:
Training Computer Vision Models: Clients can utilize our annotated data to develop and refine their own computer vision models for applications in autonomous vehicles, ensuring better object detection and decision-making capabilities in complex road environments.
Urban Planning and Infrastructure Development: Our data helps municipalities understand road usage patterns, enabling them to make informed decisions regarding infrastructure improvements, safety measures, and traffic light placement. Our data can also aid in making sure municipalities have an accurate count of signs in their area.
Integration with Our Broader Data Offering The Traffic Light Map Video Data is a crucial component of our broader data offerings at Driver Technologies. It complements our extensive library of driving data collected from various vehicles and road users, creating a comprehensive data ecosystem that supports multiple verticals, including insurance, automotive technology, and computer vision models.
In summary, Driver Technologies' Traffic Light Map Video Data provides a unique opportunity for data buyers to access high-quality, actionable insights that drive innovation across mobility. By integrating our Traffic Light Map Video Data with other datasets, clients can gain a holistic view of transportation dynamics, enhancing their analytical capabilities and decision-making processes.
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
Depicted on this map is British North America less than one hundred years after the fall of New France. It also shows the emergence of British influence prior to Confederation. British North America circa 1823 was comprised of Lower Canada, Upper Canada, New Brunswick, Nova Scotia, Prince Edward Island, and Newfoundland (including the Labrador Coast). The Northwest Territories were considered British possessions, while the Hudson’s Bay Company controlled Rupert’s Land. The United States and Britain jointly administered the Oregon Territory. This map along with New France circa 1740 shows the settlement and population in Canada for two important periods in Canadian history prior to Confederation.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
United Kingdom Exports of maps, hydrographic or similar charts (printed) to United States was US$19.82 Million during 2024, according to the United Nations COMTRADE database on international trade. United Kingdom Exports of maps, hydrographic or similar charts (printed) to United States - data, historical chart and statistics - was last updated on July of 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
United States Exports of maps, hydrographic or similar charts (printed) to United Kingdom was US$551.04 Thousand during 2024, according to the United Nations COMTRADE database on international trade. United States Exports of maps, hydrographic or similar charts (printed) to United Kingdom - data, historical chart and statistics - was last updated on June of 2025.
Map Index Sheets from Block and Lot Grid of Property Assessment and based on aerial photography, showing 1983 datum with solid line and NAD 27 with 5 second grid tics and italicized grid coordinate markers and outlines of map sheet boundaries. Each grid square is 3500 x 4500 feet. Each Index Sheet contains 16 lot/block sheets, labeled from left to right, top to bottom (4 across, 4 down): A, B, C, D, E, F, G, H, J, K, L, M, N, P, R, S. The first (4) numeric characters in a parcelID indicate the Index sheet in which the parcel can be found, the alpha character identifies the block in which most (or all) of the property lies.
If viewing this description on the Western Pennsylvania Regional Data Center’s open data portal (http://www.wprdc.org), this dataset is harvested on a weekly basis from Allegheny County’s GIS data portal (http://openac.alcogis.opendata.arcgis.com/). The full metadata record for this dataset can also be found on Allegheny County’s GIS portal. You can access the metadata record and other resources on the GIS portal by clicking on the “Explore” button (and choosing the “Go to resource” option) to the right of the “ArcGIS Open Dataset” text below.
Category: Other
Organization: Allegheny County
Department: Geographic Information Systems Group; Department of Administrative Services
Temporal Coverage: 2004
Data Notes:
Coordinate System: Pennsylvania State Plane South Zone 3702; U.S. Survey Foot
Development Notes: none
Other: none
Related Document(s): Data Dictionary (none)
Frequency - Data Change: As needed
Frequency - Publishing: As needed
Data Steward Name: Eli Thomas
Data Steward Email: gishelp@alleghenycounty.us
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.
For more insights on the market size of various regions, Request Free Sample
The market in North America is primarily driven by the United States, where the increasing deployment of
SafeGraph Places provides baseline information for every record in the SafeGraph product suite via the Places schema and polygon information when applicable via the Geometry schema. The current scope of a place is defined as any location humans can visit with the exception of single-family homes. This definition encompasses a diverse set of places ranging from restaurants, grocery stores, and malls; to parks, hospitals, museums, offices, and industrial parks. Premium sets of Places include apartment buildings, Parking Lots, and Point POIs (such as ATMs or transit stations).
SafeGraph Places is a point of interest (POI) data offering with varying coverage depending on the country. Note that address conventions and formatting vary across countries. SafeGraph has coalesced these fields into the Places schema.
SafeGraph provides clean and accurate geospatial datasets on 51M+ physical places/points of interest (POI) globally. Hundreds of industry leaders like Mapbox, Verizon, Clear Channel, and Esri already rely on SafeGraph POI data to unlock business insights and drive innovation. Easily ingest this data to power your map products today.
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
Link to the ScienceBase Item Summary page for the item described by this metadata record. Service Protocol: Link to the ScienceBase Item Summary page for the item described by this metadata record. Application Profile: Web Browser. Link Function: information
Environmental Sensitivity Index (ESI) maps are an integral component in oil-spill contingency planning and assessment. They serve as a source of information in the event of an oil spill incident. ESI maps contain three types of information: shoreline habitats (classified according to their sensitivity to oiling), sensitive biological resources, and human-use resources. Most often, this information is plotted on 7.5 minute USGS quadrangles, although in the Alaska ESI maps, USGS topographic maps at scales of 1:63,360 and 1:250,000 are used, and in other ESI maps, NOAA charts have been used as the base map. Collections of these maps, grouped by state or a logical geographic area, are published as ESI atlases. Digital data have been published for most of the U.S. shoreline, including Alaska, Hawaii, and Puerto Rico.
Crop year 2014 US map at the county level shows designations across the country under USDA's amended rule. The faster, more efficient process will immediately expand assistance to more than 1,000 counties in 26 states.
Geologic Map of North America (Southern Sheet). Map published by Geological Society of America; database by U.S. Geological Survey. See Catalogue of Registered Services for more information.
The Unpublished Digital Surficial Geologic-GIS Map of Gateway National Recreation Area and Vicinity, New Jersey and New York is composed of GIS data layers and GIS tables in a 10.1 file geodatabase (gwsf_geology.gdb), a 10.1 ArcMap (.MXD) map document (gwsf_geology.mxd), individual 10.1 layer (.LYR) files for each GIS data layer, an ancillary map information (.PDF) document (gate_geology.pdf) which contains source map unit descriptions, as well as other source map text, figures and tables, metadata in FGDC text (.TXT) and FAQ (.HTML) formats, and a GIS readme file (gwsf_gis_readme.pdf). Please read the gwsf_gis_readme.pdf for information pertaining to the proper extraction of the file geodatabase and other map files. To request GIS data in ESRI 10.1 shapefile format contact Stephanie O’Meara (stephanie.omeara@colostate.edu; see contact information below). The data is also available as a 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. Google Earth software is available for free at: http://www.google.com/earth/index.html. 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). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: New Jersey Geological Survey and New York State Museum. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (gwsf_metadata_faq.html; available at http://nrdata.nps.gov/geology/gri_data/gis/gate/gwsf_metadata_faq.html). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:100,000 and United States National Map Accuracy Standards features are within (horizontally) 127 meters or 416.7 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 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: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data projection is NAD83, UTM Zone 18N, however, for the KML/KMZ format the data is projected upon export to WGS84 Geographic, the native coordinate system used by Google Earth. The data is within the area of interest of Gateway National Recreation Area.
Thematic map of foreign guests from the Netherlands, Belgium, Great Britain and the USA in counties and associations. The share of all guests in %.:Guests from the United Kingdom (share of all guests in %) in Rhineland-Palatinate is proven at the association community level.
In the century between Napoleon's defeat and the outbreak of the First World War (known as the "Pax Britannica"), the British Empire grew to become the largest and most powerful empire in the world. At its peak in the 1910s and 1920s, it encompassed almost one quarter of both the world's population and its land surface, and was known as "the empire on which the sun never sets". The empire's influence could be felt across the globe, as Britain could use its position to affect trade and economies in all areas of the world, including many regions that were not part of the formal empire (for example, Britain was able to affect trading policy in China for over a century, due to its control of Hong Kong and the neighboring colonies of India and Burma). Some historians argue that because of its economic, military, political and cultural influence, nineteenth century Britain was the closest thing to a hegemonic superpower that the world ever had, and possibly ever will have. "Rule Britannia" Due to the technological and logistical restrictions of the past, we will never know the exact borders of the British Empire each year, nor the full extent of its power. However, by using historical sources in conjunction with modern political borders, we can gain new perspectives and insights on just how large and influential the British Empire actually was. If we transpose a map of all former British colonies, dominions, mandates, protectorates and territories, as well as secure territories of the East India Trading Company (EIC) (who acted as the precursor to the British Empire) onto a current map of the world, we can see that Britain had a significant presence in at least 94 present-day countries (approximately 48 percent). This included large territories such as Australia, the Indian subcontinent, most of North America and roughly one third of the African continent, as well as a strategic network of small enclaves (such as Gibraltar and Hong Kong) and islands around the globe that helped Britain to maintain and protect its trade routes. The sun sets... Although the data in this graph does not show the annual population or size of the British Empire, it does give some context to how Britain has impacted and controlled the development of the world over the past four centuries. From 1600 until 1920, Britain's Empire expanded from a small colony in Newfoundland, a failing conquest in Ireland, and early ventures by the EIC in India, to Britain having some level of formal control in almost half of all present-day countries. The English language is an official language in all inhabited continents, its political and bureaucratic systems are used all over the globe, and empirical expansion helped Christianity to become the most practiced major religion worldwide. In the second half of the twentieth century, imperial and colonial empires were eventually replaced by global enterprises. The United States and Soviet Union emerged from the Second World War as the new global superpowers, and the independence movements in longstanding colonies, particularly Britain, France and Portugal, gradually succeeded. The British Empire finally ended in 1997 when it seceded control of Hong Kong to China, after more than 150 years in charge. Today, the United Kingdom consists of four constituent countries, and it is responsible for three crown dependencies and fourteen overseas territories, although the legacy of the British Empire can still be seen, and it's impact will be felt for centuries to come.
Layered GeoPDF 7.5 Minute Quadrangle Map. Layers of geospatial data include orthoimagery, roads, grids, geographic names, elevation contours, hydrography, and other selected map features.
Welcome to Apiscrapy, your ultimate destination for comprehensive location-based intelligence. As an AI-driven web scraping and automation platform, Apiscrapy excels in converting raw web data into polished, ready-to-use data APIs. With a unique capability to collect Google Address Data, Google Address API, Google Location API, Google Map, and Google Location Data with 100% accuracy, we redefine possibilities in location intelligence.
Key Features:
Unparalleled Data Variety: Apiscrapy offers a diverse range of address-related datasets, including Google Address Data and Google Location Data. Whether you seek B2B address data or detailed insights for various industries, we cover it all.
Integration with Google Address API: Seamlessly integrate our datasets with the powerful Google Address API. This collaboration ensures not just accessibility but a robust combination that amplifies the precision of your location-based insights.
Business Location Precision: Experience a new level of precision in business decision-making with our address data. Apiscrapy delivers accurate and up-to-date business locations, enhancing your strategic planning and expansion efforts.
Tailored B2B Marketing: Customize your B2B marketing strategies with precision using our detailed B2B address data. Target specific geographic areas, refine your approach, and maximize the impact of your marketing efforts.
Use Cases:
Location-Based Services: Companies use Google Address Data to provide location-based services such as navigation, local search, and location-aware advertisements.
Logistics and Transportation: Logistics companies utilize Google Address Data for route optimization, fleet management, and delivery tracking.
E-commerce: Online retailers integrate address autocomplete features powered by Google Address Data to simplify the checkout process and ensure accurate delivery addresses.
Real Estate: Real estate agents and property websites leverage Google Address Data to provide accurate property listings, neighborhood information, and proximity to amenities.
Urban Planning and Development: City planners and developers utilize Google Address Data to analyze population density, traffic patterns, and infrastructure needs for urban planning and development projects.
Market Analysis: Businesses use Google Address Data for market analysis, including identifying target demographics, analyzing competitor locations, and selecting optimal locations for new stores or offices.
Geographic Information Systems (GIS): GIS professionals use Google Address Data as a foundational layer for mapping and spatial analysis in fields such as environmental science, public health, and natural resource management.
Government Services: Government agencies utilize Google Address Data for census enumeration, voter registration, tax assessment, and planning public infrastructure projects.
Tourism and Hospitality: Travel agencies, hotels, and tourism websites incorporate Google Address Data to provide location-based recommendations, itinerary planning, and booking services for travelers.
Discover the difference with Apiscrapy – where accuracy meets diversity in address-related datasets, including Google Address Data, Google Address API, Google Location API, and more. Redefine your approach to location intelligence and make data-driven decisions with confidence. Revolutionize your business strategies today!
Street Noise-Level — Statistically Interpolated + Processed Measurements
Connect with our experts for the world’s most comprehensive Street Noise-Level Dataset. Access hyper-local and global average noise levels (dBA) from public streets across over 200 countries. This dataset, built using over 35 billion datapoints and developed in collaboration with leading acoustics professionals, provides unparalleled insight into real-world urban soundscapes. Unlike conventional noise models, which rely solely on simulations, our dataset combines real measurements with AI-powered interpolation to deliver statistically robust, highly accurate, and spatially complete noise-level data.
Power Your AI & Urban Analytics with Real-World Noise Insights
What makes this dataset unique? Silencio’s processed and interpolated Street Noise-Level Dataset is the largest and most precise global collection of acoustic data available. It integrates real user-collected measurements with AI-driven modeling, ensuring unmatched ground truth for AI training, urban intelligence, and noise-impact assessments.
Optimized for AI, Urban Planning & Research:
Empower your AI models and spatial analyses with rich, diverse, and realistic noise data. Ideal for sound recognition, smart cities, mobility modeling, noise mapping, real estate analysis, and sustainable urban planning.
Trusted & Compliant:
All data is collected via our mobile app, strictly anonymized, fully consented, and 100% GDPR-compliant — ensuring privacy and ethical integrity.
Historical & Up-to-Date:
Leverage both historical and continuously updated noise data to uncover trends, detect change, and power predictive models.
Hyper-Local & Global Coverage:
With coverage of over 200 countries and high spatial granularity, the dataset provides insights from the city level down to street segments.
Seamless Integration:
Delivered via CSV exports or S3 bucket delivery (APIs coming soon) for easy integration into AI training pipelines, geospatial tools, or analytics platforms.
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
Depicted on this map is British North America less than one hundred years after the fall of New France. It also shows the emergence of British influence prior to Confederation. British North America circa 1823 was comprised of Lower Canada, Upper Canada, New Brunswick, Nova Scotia, Prince Edward Island, and Newfoundland (including the Labrador Coast). The Northwest Territories were considered British possessions, while the Hudson’s Bay Company controlled Rupert’s Land. The United States and Britain jointly administered the Oregon Territory. This map along with New France circa 1740 shows the settlement and population in Canada for two important periods in Canadian history prior to Confederation.
b3_croppedncdf format raster file for the base map. Derived from naturalearthdata.comwibreed_rastThe files wibreed_rast.nc and wiwinter_rast.nc are raster files of the range of Wilson's Warblers in the Americas. They were generated from shapefiles provided to us by BirdLife International. (BirdLife International and NatureServe (2012) Bird species distribution maps of the world. BirdLife International, Cambridge, UK and NatureServe, Arlington, USA). Persons interested in the range map should contact BirdLife International or NatureServe directly.wiwinter_rastThe files wibreed_rast.nc and wiwinter_rast.nc are raster files of the range of Wilson's Warblers in the Americas. They were generated from shapefiles provided to us by BirdLife International. (BirdLife International and NatureServe (2012) Bird species distribution maps of the world. BirdLife International, Cambridge, UK and NatureServe, Arlington, USA). Persons interested in the range map should contact BirdLife International o...
At Driver Technologies, we specialize in collecting high-quality, highly-anonymized, driving data crowdsourced using our dash cam app. Our Traffic Light Map Video Data is built from the millions of miles of driving data captured and is optimized to be trained for whatever computer vision models you need and enhancing various applications in transportation and safety.
What Makes Our Data Unique? What sets our Traffic Light Map Video Data apart is its comprehensive approach to road object detection. By leveraging advanced computer vision models, we analyze the captured video to identify and classify various road objects encountered during an end user's trip. This includes road signs, pedestrians, vehicles, traffic signs, and road conditions, resulting in rich, annotated datasets that can be used for a range of applications.
How Is the Data Generally Sourced? Our data is sourced directly from users who utilize our dash cam app, which harnesses the smartphone’s camera and sensors to record during a trip. This direct sourcing method ensures that our data is unbiased and represents a wide variety of conditions and environments. The data is not only authentic and reflective of current road conditions but is also abundant in volume, offering millions of miles of recorded trips that cover diverse scenarios.
Primary Use-Cases and Verticals The Traffic Light Map Video Data is tailored for various sectors, particularly those involved in transportation, urban planning, and autonomous vehicle development. Key use cases include:
Training Computer Vision Models: Clients can utilize our annotated data to develop and refine their own computer vision models for applications in autonomous vehicles, ensuring better object detection and decision-making capabilities in complex road environments.
Urban Planning and Infrastructure Development: Our data helps municipalities understand road usage patterns, enabling them to make informed decisions regarding infrastructure improvements, safety measures, and traffic light placement. Our data can also aid in making sure municipalities have an accurate count of signs in their area.
Integration with Our Broader Data Offering The Traffic Light Map Video Data is a crucial component of our broader data offerings at Driver Technologies. It complements our extensive library of driving data collected from various vehicles and road users, creating a comprehensive data ecosystem that supports multiple verticals, including insurance, automotive technology, and computer vision models.
In summary, Driver Technologies' Traffic Light Map Video Data provides a unique opportunity for data buyers to access high-quality, actionable insights that drive innovation across mobility. By integrating our Traffic Light Map Video Data with other datasets, clients can gain a holistic view of transportation dynamics, enhancing their analytical capabilities and decision-making processes.