The data contain a polygon shapefile (.shp format) with 122,567 polygons corresponding to the vehicles (car, bus, truck, and boat) in 0.24m spatial resolution image with 57,856x42,496 pixel dimensions. The original image was obtained by the Infraestrutura de Dados Espaciais do Distrito Federal - IDE/DF(2022). Geoportal/DF. Available at: https://www.geoportal.seduh.df.gov.br/geoportal/ (accessed on January 8, 2022). The vectors correspond to the image taken in 2016.

The dataset contains locations and attributes of car sharing locations. The points are the general locations where the Car Sharing currently exist. A database provided by the District Department of Transportation identified Car sharing locations.

The feature class indicates the specific types of motorized vehicles allowed on the designated routes and their seasons of use. The feature class is designed to be consistent with the MVUM (Motor Vehicle Use Map). It is compiled from the GIS Data Dictionary data and Infra tabular data that the administrative units have prepared for the creation of their MVUMs. Only trails with the symbol value of 5-12, 16, 17 are Forest Service System trails and contain data concerning their availability for motorized use. This data is published and refreshed on a unit by unit basis as needed. Individual unit's data must be verified and proved consistent with the published MVUMs prior to publication in the EDW. Click this link for full metadata description: Metadata _

The feature class indicates the specific types of motorized vehicles allowed on the designated routes and their seasons of use. The feature class is designed to be consistent with the MVUM (Motor Vehicle Use Map). It is compiled from the GIS Data Dictionary data and NRM Infra tabular data that the administrative units have prepared for the creation of their MVUMs. Only roads with a SYMBOL attribute value of 1, 2, 3, 4, 11, and 12 are Forest Service System roads and contain data concerning their availability for OHV (Off Highway Vehicle) use. This data is published and refreshed on a unit by unit basis as needed. Data for each individual unit must be verified and proved consistent with the published MVUMs prior to publication.The Forest Service's Natural Resource Manager (NRM) Infrastructure (Infra) is the agency standard for managing and reporting information about inventory of constructed features and land units as well as the permits sold to the general public and to partners. Metadata

Fireline GIS Mapping in Vehicles Market Outlook

As per our latest research, the global Fireline GIS Mapping in Vehicles market size was valued at USD 1.48 billion in 2024 and is expected to reach USD 4.26 billion by 2033, expanding at a robust CAGR of 12.6% during the forecast period. This remarkable growth is primarily driven by the increasing frequency and intensity of wildfires, the urgent need for real-time situational awareness in emergency response, and the rapid integration of advanced geospatial technologies into first responder vehicles. The adoption of GIS mapping solutions is transforming how fire departments and emergency services coordinate, strategize, and execute high-stakes operations, making these systems indispensable for modern firefighting and disaster response efforts.

One of the pivotal growth factors propelling the Fireline GIS Mapping in Vehicles market is the escalating incidence of wildfires and large-scale urban fires globally. Climate change has led to longer, more severe fire seasons, particularly in regions such as North America, Australia, and Southern Europe. As a result, fire departments and emergency agencies are under immense pressure to deploy resources more efficiently and ensure the safety of both personnel and affected communities. GIS mapping technologies, when integrated into vehicles, provide real-time data visualization, enable dynamic route planning, and facilitate the rapid identification of fire perimeters, hotspots, and safe zones. This capability significantly enhances decision-making and operational effectiveness, fueling increased demand for advanced GIS solutions across public and private sectors.

Another significant driver is the technological advancement in vehicle-mounted hardware and software ecosystems. The proliferation of high-speed mobile internet, robust onboard computing platforms, and sophisticated sensors has made it feasible to deploy high-resolution mapping and analytics tools directly within fire trucks, emergency response vehicles, and utility vehicles. Vendors are increasingly offering interoperable solutions that seamlessly integrate with existing command and control systems, mobile data terminals, and satellite communication devices. These innovations not only improve the accuracy and timeliness of geospatial data but also support advanced features such as predictive modeling, automated resource allocation, and remote collaboration among multiple agencies. Such technological convergence is expected to further accelerate market expansion over the coming years.

In addition, the growing emphasis on inter-agency collaboration and data sharing is catalyzing the adoption of Fireline GIS Mapping in Vehicles. Government mandates and industry standards are evolving to promote the interoperability of GIS platforms, ensuring that fire departments, government agencies, and private contractors can coordinate seamlessly during complex incidents. Cloud-based deployment models and service-oriented architectures are making it easier to scale GIS solutions, provide secure access to critical data, and enable rapid deployment in both urban and remote environments. This trend is particularly pronounced in regions with fragmented emergency response infrastructures, where centralized, real-time mapping is essential for effective disaster management.

From a regional perspective, North America currently dominates the global Fireline GIS Mapping in Vehicles market, accounting for over 38% of the total market share in 2024. This leadership is attributed to substantial investments in wildfire management technologies, a high incidence of catastrophic fires, and strong government support for digital transformation initiatives within public safety agencies. Europe follows closely, driven by stringent regulatory frameworks and the increasing adoption of smart city solutions. The Asia Pacific region is emerging as the fastest-growing market, with a projected CAGR of 14.2% through 2033, fueled by rapid urbanization, rising awareness of disaster preparedness, and expanding government initiatives in countries such as Australia, Japan, and China.

The Municipal ZEV Clean Vehicle (CV) Rebate Program provides rebates to cities, towns, villages and counties (including New York City boroughs) to purchase or lease (for at least 36 months) new clean vehicles for fleet use.Service layer is updated annually, last updated 12/04/2024.For more information, see https://www.dec.ny.gov/chemical/8394.htmlFor more information or to download layer see https://gis.ny.gov/gisdata/inventories/details.cfm?DSID=1383Download the metadata to learn more information about how the data was created and details about the attributes. Use the links within the metadata document to expand the sections of interest. https://services6.arcgis.com/DZHaqZm9cxOD4CWM/arcgis/rest/services/Municipal_Zero_Emission_Vehicle_Rebates/FeatureServer1. The NYS DEC asks to be credited in derived products. 2. Secondary distribution of the data is not allowed. 3. Any documentation provided is an integral part of the data set. Failure to use the documentation in conjunction with the digital data constitutes a misuse of the data. 4. Although every effort has been made to ensure the accuracy of information, errors may be reflected in the data supplied. The user must be aware of data conditions and bear responsibility for the appropriate use of the information with respect to possible errors, original map scale, collection methodology, currency of data, and other conditions.

Fireline GIS Mapping in Vehicles Market Outlook

According to our latest research, the Global Fireline GIS Mapping in Vehicles market size was valued at $1.2 billion in 2024 and is projected to reach $3.4 billion by 2033, expanding at a CAGR of 12.7% during 2024–2033. The primary factor propelling the growth of this market globally is the increasing frequency and intensity of wildfires, which has prompted fire departments, government agencies, and private contractors to adopt advanced Geographic Information System (GIS) solutions for real-time situational awareness and enhanced response capabilities. As wildfires become more unpredictable due to climate change, the integration of GIS mapping technologies in vehicles is rapidly becoming indispensable for efficient wildfire management, emergency response, and asset tracking, driving robust market expansion across multiple regions and industry verticals.

Regional Outlook

North America currently dominates the Fireline GIS Mapping in Vehicles market, accounting for the largest share, with an estimated market value of $540 million in 2024 and expected to reach $1.5 billion by 2033. This region’s leadership position is primarily attributed to its mature emergency response infrastructure, widespread adoption of advanced vehicle telematics, and robust government policies supporting wildfire management. The United States, in particular, has invested heavily in GIS mapping technologies for both public and private firefighting fleets, leveraging real-time data analytics and cloud-based platforms to enhance coordination during wildfire events. Additionally, the region benefits from a high level of technological innovation and a proactive approach to integrating emerging digital solutions into first responder operations, further cementing its market dominance.

Asia Pacific is projected to be the fastest-growing region in the Fireline GIS Mapping in Vehicles market, with a remarkable CAGR of 15.8% from 2024 to 2033. This growth is fueled by increasing wildfire incidents across Australia, Southeast Asia, and parts of China, coupled with rapid urbanization and expanding vehicle fleets dedicated to emergency response. Significant investments in smart city initiatives and government mandates for disaster preparedness are driving the adoption of GIS mapping technologies in emergency vehicles. Furthermore, the proliferation of cloud-based solutions and mobile GIS applications is enabling even smaller municipalities and rural fire departments to access advanced mapping tools, thereby accelerating market penetration and technological advancement in the region.

Emerging economies in Latin America, the Middle East, and Africa are witnessing gradual but steady adoption of Fireline GIS Mapping in Vehicles solutions, although growth is tempered by budgetary constraints, limited technological infrastructure, and inconsistent policy frameworks. In these regions, localized demand is primarily concentrated in countries prone to seasonal wildfires and where international aid or government-backed modernization programs are in place. Challenges such as lack of skilled personnel, inadequate data connectivity, and the need for region-specific customization of GIS platforms persist. However, ongoing efforts to strengthen disaster response capabilities and increasing awareness of the benefits of real-time GIS mapping are expected to create new opportunities for market growth in these emerging markets over the forecast period.

Report Scope

Total Cars: Describes the total amount of cars present at the time share. {String} Company: Describes the car share company/owner. {String}

The dataset contains locations and attributes of Vehicle Detection Systems, created from a database provided by the District Department of Transportation.

For source data: https://data.census.gov/table/ACSDP5Y2023.DP04For more information about this dataset, please contact egis@isd.lacounty.gov

This layer shows household size by number of vehicles available. This is shown by tract, county, and state centroids. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the count and percentage of households with no vehicle available. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B08201 Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

Police Car Routes are areas which patrol cars are dispatched. In Cambridge there are many route cars and cruisers have one officer in each car. This is different from Sector cars which have 2 officers per car. This layer is used for response by Cambridge Public Safety.

Average vehicles per household by neighborhoods in Johns Creek, GA.Neighborhood boundaries are created and maintained by Johns Creek, GA.Demographics data is from Esri GeoEnrichment Services.

The Massachusetts Vehicle Census (MVC) is the first state-level dataset in the nation that joins vehicle-level odometer readings with vehicle attribute and registration transaction histories. This powerful resource allows policymakers, researchers, and other stakeholders understand state and local trends in vehicle usage and ownership.

The feature class indicates the specific types of motorized vehicles allowed on the designated routes and their seasons of use. The feature class is designed to be consistent with the MVUM (Motor Vehicle Use Map). It is compiled from the GIS Data Dictionary data and NRM Infra tabular data that the administrative units have prepared for the creation of their MVUMs. Only roads with a SYMBOL attribute value of 1, 2, 3, 4, 11, and 12 are Forest Service System roads and contain data concerning their availability for OHV (Off Highway Vehicle) use. This data is published and refreshed on a unit by unit basis as needed. Data for each individual unit must be verified and proved consistent with the published MVUMs prior to publication.The Forest Service's Natural Resource Manager (NRM) Infrastructure (Infra) is the agency standard for managing and reporting information about inventory of constructed features and land units as well as the permits sold to the general public and to partners. Go to this url for full metadata description: http://data.fs.usda.gov/geodata/edw/edw_resources/meta/S_USA.Road_MVUM.xml

Discover the booming digital map ecosystem market, projected to reach $450 billion by 2033. Explore key drivers, regional trends, and leading companies shaping this rapidly evolving landscape, including autonomous vehicle integration and LBS advancements. Learn more about market size, CAGR, and segmentation analysis in this comprehensive report.

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Car Parks in York. *Please note that the data published within this dataset is a live API link to CYC's GIS server. Any changes made to the master copy of the data will be immediately reflected in the resources of this dataset.The date shown in the "Last Updated" field of each GIS resource reflects when the data was first published.