High resolution orthorectified images combine the image characteristics of an aerial photograph with the geometric qualities of a map. An orthoimage is a uniform-scale image where corrections have been made for feature displacement such as building tilt and for scale variations caused by terrain relief, sensor geometry, and camera tilt. A mathematical equation based on ground control points, sensor calibration information, and a digital elevation model is applied to each pixel to rectify the image to obtain the geometric qualities of a map.

A digital orthoimage may be created from several photographs mosaicked to form the final image. The source imagery may be black-and-white, natural color, or color infrared with a pixel resolution of 1-meter or finer. With orthoimagery, the resolution refers to the distance on the ground represented by each pixel.

The Ontario Imagery Web Map Service (OIWMS) is an open data service available to everyone free of charge. It provides instant online access to the most recent, highest quality, province wide imagery. GEOspatial Ontario (GEO) makes this data available as an Open Geospatial Consortium (OGC) compliant web map service or as an ArcGIS map service. Imagery was compiled from many different acquisitions which are detailed in the Ontario Imagery Web Map Service Metadata Guide linked below. Instructions on how to use the service can also be found in the Imagery User Guide linked below. Note: This map displays the Ontario Imagery Web Map Service Source, a companion ArcGIS web map service to the Ontario Imagery Web Map Service. It provides an overlay that can be used to identify acquisition relevant information such as sensor source and acquisition date. OIWMS contains several hierarchical layers of imagery, with coarser less detailed imagery that draws at broad scales, such as a province wide zooms, and finer more detailed imagery that draws when zoomed in, such as city-wide zooms. The attributes associated with this data describes at what scales (based on a computer screen) the specific imagery datasets are visible. Available Products Ontario Imagery OGC Web Map Service – public linkOntario Imagery ArcGIS Map Service – public linkOntario Imagery Web Map Service Source – public linkOntario Imagery ArcGIS Map Service – OPS internal linkOntario Imagery Web Map Service Source – OPS internal linkAdditional Documentation Ontario Imagery Web Map Service Metadata Guide (PDF)Ontario Imagery Web Map Service Copyright Document (PDF) Imagery User Guide (Word)StatusCompleted: Production of the data has been completed Maintenance and Update FrequencyAnnually: Data is updated every year ContactOntario Ministry of Natural Resources, Geospatial Ontario, imagery@ontario.ca

The Geomatics Division archives contain over 22,000 aerial photographs. The oldest date from 1930, but they are generally located between 1950 and 2003. The set provides a link to an interactive map allowing the download of aerial photographs from multiple years held by the City for the purposes of producing basic cartography. The images are available throughout the island of Montreal or partially depending on the years and scales of aerial photographs. An aerial photograph is a photograph taken from the air. Normally, these are taken vertically, on board an aircraft, using a highly accurate camera. NOTE1: The collection of the Geomatics Division is distinct from that of the Archives de Montréal. NOTE2: The City distributes the photographs in its possession. However, in In the event that a claimant has claims on this subject, he is invited to submit them to the City. NOTE3: Note that for paper-based archival images, the City generally does not have the original slides. Refer to the index for details.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

This dataset features a collection of historical orthorectified aerial photographed images of the Brisbane City Council local government area captured by piloted aircraft during 1946.Prior to satellite imagery, extensive use was made of aerial photography to capture land information. The 1946 imagery service uses the Geocentric Datum of Australia 1994 (GDA94) datum and is projected in Zone 56 of the Map Grid of Australia (MGA56).This dataset is a tile layer, to view the images or to access the data, use the ArcGIS Hub, HTML and API links in the Data and resources section below.

Spring 2023

An aerial imagery basemap of New Zealand in NZTM using the latest quality data from Land Information New Zealand.LINZ Aerial Imagery Basemap - NZTM WMTS: https://ecan.maps.arcgis.com/home/item.html?id=39cf07ebf8a2413696d8fd4d80570b84This basemap is also available in Web Mercator (WGS 84) from: https://basedatanz.maps.arcgis.com/home/item.html?id=a4ac021a9f6d4976bfb3cc6d34739b8bThe LINZ Aerial Imagery Basemap details New Zealand in high resolution - from a nationwide view all the way down to individual buildings.This basemap combines the latest high-resolution aerial imagery down to 5cm in urban areas and 10m satellite imagery to provide full coverage of mainland New Zealand, Chathams and other offshore islands.LINZ Basemaps are powered by data from the LINZ Data Service and other authoritative open data sources, providing you with a basemap that is free to use under an open licence.A XYZ tile API (Web Mercator only) is also available for use in web and mobile applications.See more information or provide your feedback at https://basemaps.linz.govt.nz/.For attribution requirements and data sources see: https://www.linz.govt.nz/data/linz-data/linz-basemaps/data-attribution.

This site provides free access to Iowa geographic map data, including aerial photography, orthophotos, elevation maps, and historical maps. The data is available through an on-line map viewer and through Web Map Service (WMS) connections for GIS. The site was developed by the Iowa State University Geographic Information Systems Support and Research Facility in cooperation with the Iowa Department of Natural Resources, the USDA Natural Resources Conservation Service, and the Massachusetts Institute of Technology. This site was first launched in March 1999.

This Hub contains information, resources and discovery of Commonwealth Historical Aerial Photography across Australia. Geoscience Australia has developed the Historical Aerial Photography (HAP) collection in an online data delivery system. Using the application, uses can search and download the commonwealth photography collection for free. The hub demonstrates the breadth of the collection and showcases the efforts in collecting and curating an extensive physical collection of film and documents.

Geoscience Australia has the most extensive historical aerial photography collection in terms of land coverage and time (from 1928-1996). This online catalogue provides means of easy search of the collection records. The mapping system allows users to understand what information is available and, if digitised, to preview and download the image data.

The application contains a map which users can search areas, current location or an area of interest, as well as customize the search criteria (date range, film number etc). The search results list the available aerial photography or flight line diagram, and if is available for direct download for free.

Aerial photographs were acquired for the Puerto Rico and U.S. Virgin Islands Benthic Mapping Project in 1999 by NOAA Aircraft Operation Centers aircraft and National Geodetic Survey cameras and personnel. Approximately 600, color, 9 by 9 inch photos were taken of the coastal waters of Puerto Rico and the U.S. Virgin Islands at 1:48000 scale. Specific sun angle and maximum percent cloud cover re...

Geoscience Australia has the most extensive historical aerial photography collection in terms of land coverage and time (from 1928-1996). This online catalogue provides means of easy search of the collection records. The mapping system allows users to understand what information is available and, if digitised, to preview and download the image data.

The application contains a map which users can search areas, current location or an area of interest, as well as customize the search criteria (date range, film number etc). The search results list the available aerial photography or flight line diagram, and if is available for direct download for free.

To provide easy access to Minnesota aerial photography images.

This dataset allows users to browse, download, and order Minnesota Department of Natural Resources (DNR) aerial photography products via the Internet. In addition, access to the photo databases is provided via easy-to-use map based interfaces that allow a user to navigate to a particular photo(s). See: "http://www.dnr.state.mn.us/airphotos/search.html"

Web map displaying WI DNR's Wisconsin Leaf-Off Digital Orthophotography imagery layer along with an index layer. This map can be used to identify the year and resolution of each county's imagery in this image service, or as a starting point to create a new map. To open the web map from DNR's GIS Open Data Portal, click the View Metadata: link to the right of the description, then click Open in Map Viewer.*Note that this web map only contains DOPs that Wisconsin DNR has permission to display on a web map. Some counties may have newer DOPs.

Commonwealth historical aerial photography search application embedded. This application allows users to search a map of Australia for nearly a century of aerial photography in our database and download scanned flight diagrams and photographs for free.

This dataset collection contains A0 maps of the Keppel Island region based on satellite imagery and fine-scale habitat mapping of the islands and marine environment. This collection provides the source satellite imagery used to produce these maps and the habitat mapping data.

The imagery used to produce these maps was developed by blending high-resolution imagery (1 m) from ArcGIS Online with a clear-sky composite derived from Sentinel 2 imagery (10 m). The Sentinel 2 imagery was used to achieve full coverage of the entire region, while the high-resolution was used to provide detail around island areas.

The blended imagery is a derivative product of the Sentinel 2 imagery and ArcGIS Online imagery, using Photoshop to to manually blend the best portions of each imagery into the final product. The imagery is provided for the sole purpose of reproducing the A0 maps.

Methods:

The high resolution satellite composite composite was developed by manual masking and blending of a Sentinel 2 composite image and high resolution imagery from ArcGIS Online World Imagery (2019).

The Sentinel 2 composite was produced by statistically combining the clearest 10 images from 2016 - 2019. These images were manually chosen based on their very low cloud cover, lack of sun glint and clear water conditions. These images were then combined together to remove clouds and reduce the noise in the image.

The processing of the images was performed using a script in Google Earth Engine. The script combines the manually chosen imagery to estimate the clearest imagery. The dates of the images were chosen using the EOBrowser (https://www.sentinel-hub.com/explore/eobrowser) to preview all the Sentinel 2 imagery from 2015-2019. The images that were mostly free of clouds, with little or no sun glint, were recorded. Each of these dates was then viewed in Google Earth Engine with high contrast settings to identify images that had high water surface noise due to algal blooms, waves, or re-suspension. These were excluded from the list. All the images were then combined by applying a histogram analysis of each pixel, with the final image using the 40th percentile of the time series of the brightness of each pixel. This approach helps exclude effects from clouds.

The contrast of the image was stretched to highlight the marine features, whilst retaining detail in the land features. This was done by choosing a black point for each channel that would provide a dark setting for deep clear water. Gamma correction was then used to lighten up the dark water features, whilst not ove- exposing the brighter shallow areas.

Both the high resolution satellite imagery and Sentinel 2 imagery was combined at 1 m pixel resolution. The resolution of the Sentinel 2 tiles was up sampled to match the resolution of the high-resolution imagery. These two sets of imagery were then layered in Photoshop. The brightness of the high-resolution satellite imagery was then adjusting to match the Sentinel 2 imagery. A mask was then used to retain and blend the imagery that showed the best detail of each area. The blended tiles were then merged with the overall area imagery by performing a GDAL merge, resulting in an upscaling of the Sentinel 2 imagery to 1 m resolution.


Habitat Mapping:

A 5 m resolution habitat mapping was developed based on the satellite imagery, aerial imagery available, and monitoring site information. This habitat mapping was developed to help with monitoring site selection and for the mapping workshop with the Woppaburra TOs on North Keppel Island in Dec 2019.

The habitat maps should be considered as draft as they don't consider all available in water observations. They are primarily based on aerial and satellite images.

The habitat mapping includes: Asphalt, Buildings, Mangrove, Cabbage-tree palm, Sheoak, Other vegetation, Grass, Salt Flat, Rock, Beach Rock, Gravel, Coral, Sparse coral, Unknown not rock (macroalgae on rubble), Marine feature (rock).

This assumed layers allowed the digitisation of these features to be sped up, so for example, if there was coral growing over a marine feature then the boundary of the marine feature would need to be digitised, then the coral feature, but not the boundary between the marine feature and the coral. We knew that the coral was going to cut out from the marine feature because the coral is on top of the marine feature, saving us time in digitising this boundary. Digitisation was performed on an iPad using Procreate software and an Apple pencil to draw the features as layers in a drawing. Due to memory limitations of the iPad the region was digitised using 6000x6000 pixel tiles. The raster images were converted back to polygons and the tiles merged together.

A python script was then used to clip the layer sandwich so that there is no overlap between feature types.

Habitat Validation:

Only limited validation was performed on the habitat map. To assist in the development of the habitat mapping, nearly every YouTube video available, at the time of development (2019), on the Keppel Islands was reviewed and, where possible, georeferenced to provide a better understanding of the local habitats at the scale of the mapping, prior to the mapping being conducted. Several validation points were observed during the workshop. The map should be considered as largely unvalidated.

data/coastline/Keppels_AIMS_Coastline_2017.shp:
The coastline dataset was produced by starting with the Queensland coastline dataset by DNRME (Downloaded from http://qldspatial.information.qld.gov.au/catalogue/custom/detail.page?fid={369DF13C-1BF3-45EA-9B2B-0FA785397B34} on 31 Aug 2019). This was then edited to work at a scale of 1:5000, using the aerial imagery from Queensland Globe as a reference and a high-tide satellite image from 22 Feb 2015 from Google Earth Pro. The perimeter of each island was redrawn. This line feature was then converted to a polygon using the "Lines to Polygon" QGIS tool. The Keppel island features were then saved to a shapefile by exporting with a limited extent.

data/labels/Keppel-Is-Map-Labels.shp:
This contains 70 named places in the Keppel island region. These names were sourced from literature and existing maps. Unfortunately, no provenance of the names was recorded. These names are not official. This includes the following attributes:
- Name: Name of the location. Examples Bald, Bluff
- NameSuffix: End of the name which is often a description of the feature type: Examples: Rock, Point
- TradName: Traditional name of the location
- Scale: Map scale where the label should be displayed.

data/lat/Keppel-Is-Sentinel2-2016-19_B4-LAT_Poly3m_V3.shp:
This corresponds to a rough estimate of the LAT contours around the Keppel Islands. LAT was estimated from tidal differences in Sentinel-2 imagery and light penetration in the red channel. Note this is not very calibrated and should be used as a rough guide. Only one rough in-situ validation was performed at low tide on Ko-no-mie at the edge of the reef near the education centre. This indicated that the LAT estimate was within a depth error range of about +-0.5 m.

data/habitat/Keppels_AIMS_Habitat-mapping_2019.shp:
This shapefile contains the mapped land and marine habitats. The classification type is recorded in the Type attribute.

Format:

GeoTiff (Internal JPEG format - 538 MB)
PDF (A0 regional maps - ~30MB each)
Shapefile (Habitat map, Coastline, Labels, LAT estimate)

Data Location:

This dataset is filed in the eAtlas enduring data repository at: data\custodian\2020-2029-AIMS\Keppels_AIMS_Regional-maps

This dataset provides a seamless cloud-free 10m resolution satellite imagery layer of the New Zealand mainland and offshore islands.

The imagery was captured by the European Space Agency Sentinel-2 satellites between September 2022 - April 2023.

Data comprises: • 450 ortho-rectified RGB GeoTIFF images in NZTM projection, tiled into the LINZ Standard 1:50000 tile layout. • Satellite sensors: ESA Sentinel-2A and Sentinel-2B • Acquisition dates: September 2022 - April 2023 • Spectral resolution: R, G, B • Spatial resolution: 10 meters • Radiometric resolution: 8-bits (downsampled from 12-bits)

This is a visual product only. The data has been downsampled from 12-bits to 8-bits, and the original values of the images have been modified for visualisation purposes.

Also available on: • Basemaps • NZ Imagery - Registry of Open Data on AWS

🇦🇹 오스트리아 English Bing Maps is a free online map service from Microsoft that allows you to view various spatial data and use spatial services. It is a further development of the MSN Virtual Earth and is part of the search engine Bing. The data and services are provided through the Bing Maps for Enterprise platform and include satellite and aerial images. In the so-called transit area (for public transport connections), stops and timetables of the Wiener Linien as well as several hundred other transport companies and networks in the world are mapped to form the largest existing transit network. In the future, the mapping of real-time connections is also planned in this context.

The NSW Imagery web service provides access to a repository of the Spatial Services (DCS) maintained standard imagery covering NSW, plus additional sourced imagery. It depicts an imagery map of NSW showing a selection of LANDSAT® satellite imagery, standard 50cm orthorectified imageries, High resolution 10cm Town Imageries. It also contains high resolution imageries within multiple areas of NSW within DFSI, Spatial Services maintained projects and captured by AAM, VEKTA and Jacobs (previously SKM). The image web service is updated periodically when new imageries are available. The imageries are shown progressively from scales larger than 1:150,000 higher resolution imagery overlays lower resolution imagery and most recent imagery overlays older imagery within each resolution. The characteristics of each image such as accuracy, resolution, viewing scale, image format etc varies by sensor, location, capture methodology, source and processing. For specific information about the metadata for the imagery used, please refer to the individual data series within the NSW Data Catalogue. As a consequence of the variety of source data, each map displayed by the user within this map service may have a number of copyright permissions. It is emphasised that the user should check the use constraints for each image data series.

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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 applications,

The data set for the Butler Peak quadrangle has been prepared by the Southern California Areal Mapping Project (SCAMP), a cooperative project sponsored jointly by the U.S. Geological Survey and the California Division of Mines and Geology, as part of an ongoing effort to utilize a Geographical Information System (GIS) format to create a regional digital geologic database for southern California. This regional database is being developed as a contribution to the National Geologic Map Data Base of the National Cooperative Geologic Mapping Program of the USGS. Development of the data set for the Butler Peak quadrangle has also been supported by the U.S. Forest Service, San Bernardino National Forest.

The digital geologic map database for the Butler Peak quadrangle has been created as a general-purpose data set that is applicable to other land-related investigations in the earth and biological sciences. For example, the U.S. Forest Service, San Bernardino National Forest, is using the database as part of a study of an endangered plant species that shows preference for particular rock type environments. The Butler Peak database is not suitable for site-specific geologic evaluations at scales greater than 1:24,000 (1 in = 2,000 ft).

This data set maps and describes the geology of the Butler Peak 7.5' quadrangle, San Bernardino County, California. Created using Environmental Systems Research Institute's ARC/INFO software, the data base consists of the following items: (1) a map coverage showing geologic contacts and units,(2) a scanned topographic base at a scale of 1:24,000, and (3) attribute tables for geologic units (polygons), contacts (arcs), and site-specific data (points). In addition, the data set includes the following graphic and text products: (1) A PostScript graphic plot-file containing the geologic map on a 1:24,000 topographic base accompanied by a Description of Map Units (DMU), a Correlation of Map Units (CMU), and a key to point and line symbols; (2) PDF files of the DMU and CMU, and of this Readme, and (3) this metadata file.

The geologic map data base contains original U.S. Geological Survey data generated by detailed field observation and by interpretation of aerial photographs. The map was created by transferring lines from the aerial photographs to a 1:24,000 mylar orthophoto-quadrangle and then to a base-stable topographic map. This map was then scribed, and a .007 mil, right-reading, black line clear film made by contact photographic processes.The black line was scanned and auto-vectorized by Optronics Specialty Company, Northridge, CA. The non-attributed scan was imported into ARC/INFO, where the database was built. Within the database, geologic contacts are represented as lines (arcs), geologic units as polygons, and site-specific data as points. Polygon, arc, and point attribute tables (.pat, .aat, and .pat, respectively) uniquely identify each geologic datum and link it to other tables (.rel) that provide more detailed geologic information.

These medium resolution true color (RGB - Red-Green-Blue bands) images represent the first color aerial photo "basemap" for the Commonwealth from MassGIS. MassGIS (then part of the Executive Office of Environmental Affairs) and the Massachusetts Dept. of Transportation (then the Mass Highway Department) jointly funded the project. The photography for the mainland was captured in April 2001 when deciduous trees were mostly bare and the ground was generally free of snow. Photography for the Elizabeth Islands, Martha's Vineyard, and Nantucket (the "Islands") was captured in April 2003. Imagery is available for the entire state. Original imagery pixel resolution is 1/2-meter.The imagery is served as a tiled cached map service from MassGIS' ArcGIS Online account for fast display.For full metadata and links to download the imagery visit https://www.mass.gov/info-details/massgis-data-2001-2003-aerial-imagery.