Digital Maps Market Size And Forecast

Digital Maps Market size was valued at USD 25.95 Billion in 2024 and is projected to reach USD 100.9 Billion by 2031, growing at a CAGR of 18.50% from 2024 to 2031.

Global Digital Maps Market Drivers

Increasing smartphone penetration: The growing number of smartphone users and the widespread availability of internet connectivity have made digital maps easily accessible. Advancements in mapping technology: The development of more accurate and detailed digital maps, incorporating real-time traffic updates and navigation features, has increased their appeal to users. Growth of the ride-sharing and delivery services industry: These industries rely heavily on accurate and up-to-date digital maps for navigation and route optimization.

Global Digital Maps Market Restraints

Data privacy concerns: The collection and use of location data raise privacy concerns, which can hinder the adoption of digital maps. Map inaccuracies: Despite advancements in mapping technology, inaccuracies and errors can still occur, leading to user dissatisfaction. Competition from free mapping services: The availability of free mapping services from tech giants like Google and Apple can limit the market for premium digital mapping solutions.

The datasets are in MID/MIF formats to be processed in QGIS with use of self-written open source software. The datasets are used to model single or multiple socio-economic scenarios of regional spatial development and to build graded suitability maps.

The datasets contain:

• the 10x10 km grid, topographic layers (navigable rivers, railways, paved roads, settlements, and river ports), and semantic description of each unit area of the Novosibirsk region;
• thematic maps (accessibility maps) on navigational rivers, paved roads, railways, river ports, and settlements.

In hydrological and geological studies in the Murray Basin, composite images derived from Landsat Thematic Mapper (TM) digital data enable excellent delineation of both ancient and active groundwater discharge zones, including strong zoning within active salinas. Differentiation of aeolian deposits, including lunettes, is possible only where there are distinctive vegetation associations.

Nurses play a crucial role in suicide prevention, yet the integration of artificial intelligence and machine learning technologies into nursing practice remains understudied. This research examines how these technologies can enhance nurses’ ability to identify and intervene with at-risk patients. A systematic bibliometric analysis and thematic mapping approach was employed. The Web of Science database was searched for relevant publications from January 2019 to October 2024. The initial search yielded 883 publications, with 257 meeting the inclusion criteria after systematic screening. Analysis revealed six distinct research clusters, with machine learning-based behavioral prediction emerging as the dominant theme. Findings indicate significant potential for integrating artificial intelligence-supported tools into nursing workflows, particularly in risk assessment and early intervention. Natural language processing and ecological momentary assessment emerged as promising approaches for enhancing nurse-patient communication and monitoring. These findings suggest opportunities for nurses to leverage artificial intelligence technologies in suicide prevention while maintaining the essential human element of care. This study provides evidence-based guidance for nurses implementing artificial intelligence-supported suicide prevention tools while maintaining therapeutic relationships and professional judgment in clinical practice.

Legacy product - no abstract available