Cartography Software Market Outlook

According to our latest research, the global cartography software market size reached USD 2.15 billion in 2024, driven by increasing demand for advanced mapping solutions across diverse sectors. The market is expected to expand at a CAGR of 9.2% between 2025 and 2033, with the market size forecasted to reach USD 4.79 billion by 2033. This robust growth is primarily attributed to rapid urbanization, the proliferation of geospatial data, and growing integration of GIS technologies in government and commercial applications.

The primary growth factor propelling the cartography software market is the accelerating adoption of geospatial intelligence and geographic information systems (GIS) across various sectors. Governments, urban planners, and commercial enterprises are increasingly leveraging cartography software for enhanced decision-making, spatial data visualization, and resource management. The surge in smart city initiatives and infrastructure development projects worldwide is further boosting demand for sophisticated mapping tools. These tools enable stakeholders to visualize complex datasets, analyze spatial relationships, and optimize planning processes, thereby improving efficiency and reducing operational costs.

Another significant driver is the technological evolution within the cartography software landscape. The integration of artificial intelligence, machine learning, and cloud computing has transformed traditional mapping solutions into dynamic, interactive, and real-time platforms. These advancements have broadened the application scope of cartography software, making it indispensable in fields such as disaster management, environmental monitoring, and business intelligence. The ability to process large volumes of geospatial data quickly and accurately has enhanced the value proposition of cartography solutions, attracting investments from both public and private sectors.

Furthermore, the growing need for disaster risk management and environmental monitoring is catalyzing the adoption of cartography software. Governments and humanitarian organizations are increasingly utilizing these tools to map vulnerable areas, monitor climate change impacts, and plan emergency response strategies. The software’s capability to provide real-time situational awareness and predictive analytics is critical in mitigating risks and enhancing preparedness. As climate-related challenges intensify, the reliance on advanced cartographic solutions is expected to deepen, further fueling market growth.

From a regional perspective, North America currently dominates the cartography software market, supported by substantial investments in geospatial infrastructure and a high concentration of technology-driven enterprises. However, Asia Pacific is poised for the fastest growth, driven by rapid urbanization, expanding infrastructure projects, and increasing government focus on smart city development. Europe also holds a significant share, benefiting from robust regulatory frameworks and widespread adoption of GIS technologies across various sectors. The Middle East & Africa and Latin America are emerging as promising markets, with growing awareness of the benefits of digital mapping in resource management and urban planning.

Component Analysis

The cartography software market by component is bifurcated into software and services. The software segment captures the largest market share, accounting for over 65% in 2024, owing to the widespread adoption of advanced mapping solutions across government, commercial, and utility sectors. Modern cartography software platforms offer comprehensive features such as data visualization, spatial analysis, and real-time collaboration, making them indispensable tools for urban planners, environmental agencies, and businesses. The proliferation of open-source platforms and the availability of customizable mapping solutions have further accelerated the adoption of cartography software globally.
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Heritage tourism has been booming all around the world during the recent past. However, current heritage tourism maps have been locked into the traditional cartographic paradigms in standard formats and are thus incapable of exhibiting the local cultures and the stories behind them. To address this issue, this paper introduces the cultural schema theory into narrative cartographic design and proposes a novel theoretical framework for making heritage tourism maps. We use a typical ‘Suzhou Classical Gardens’ Narrative Map to demonstrate the usefulness and practicability of the proposed theoretical framework. We finally summarize five cartographic design guidelines for making heritage tourism maps. This study is believed to shed fresh light on cartographic design research.

This is technical cartography created with traditional methods of aerial photography, today in fact considered outdated. The Gauss representation was used, in the National Geodetic System (international ellipsoid oriented towards Rome Monte Mario); each sheet shows the parameters with intervals of 1 dm graphic. The orientation and dimensions of the sheets are determined by local needs for the representation of the mapped territories (urbanized areas inserted in the smallest possible number of sheets and centered with respect to them). The cartography it is built according to the rules contained in a special tender specification for the execution of the works which provides for a maximum error in the plan of 0.40 m, in the height of 0.40 m and an equidistance for the contour lines of 1 m For the dimensions of the roofs of the buildings, a tolerance of 0.60m has been established.

The digital map market, currently valued at $25.55 billion in 2025, is experiencing robust growth, projected to expand at a Compound Annual Growth Rate (CAGR) of 13.39% from 2025 to 2033. This expansion is fueled by several key drivers. The increasing adoption of location-based services (LBS) across diverse sectors like automotive, logistics, and smart city initiatives is a primary catalyst. Furthermore, advancements in technologies such as AI, machine learning, and high-resolution satellite imagery are enabling the creation of more accurate, detailed, and feature-rich digital maps. The shift towards cloud-based deployment models offers scalability and cost-effectiveness, further accelerating market growth. While data privacy concerns and the high initial investment costs for sophisticated mapping technologies present some challenges, the overall market outlook remains overwhelmingly positive. The competitive landscape is dynamic, with established players like Google, TomTom, and ESRI vying for market share alongside innovative startups offering specialized solutions. The segmentation of the market by solution (software and services), deployment (on-premise and cloud), and industry reveals significant opportunities for growth in sectors like automotive navigation, autonomous vehicle development, and precision agriculture, where real-time, accurate mapping data is crucial. The Asia-Pacific region, driven by rapid urbanization and technological advancements in countries like China and India, is expected to witness particularly strong growth. The market's future hinges on continuous innovation. We anticipate a rise in the demand for 3D maps, real-time updates, and integration with other technologies like the Internet of Things (IoT) and augmented reality (AR). Companies are focusing on enhancing the accuracy and detail of their maps, incorporating real-time traffic data, and developing tailored solutions for specific industry needs. The increasing adoption of 5G technology promises to further boost the market by enabling faster data transmission and real-time updates crucial for applications like autonomous driving and drone delivery. The development of high-precision mapping solutions catering to specialized sectors like infrastructure management and disaster response will also fuel future growth. Ultimately, the digital map market is poised for continued expansion, driven by technological advancements and increased reliance on location-based services across a wide spectrum of industries. Recent developments include: December 2022 - The Linux Foundation has partnered with some of the biggest technology companies in the world to build interoperable and open map data in what is an apparent move t. The Overture Maps Foundation, as the new effort is called, is officially hosted by the Linux Foundation. The ultimate aim of the Overture Maps Foundation is to power new map products through openly available datasets that can be used and reused across applications and businesses, with each member throwing their data and resources into the mix., July 27, 2022 - Google declared the launch of its Street View experience in India in collaboration with Genesys International, an advanced mapping solutions company, and Tech Mahindra, a provider of digital transformation, consulting, and business re-engineering solutions and services. Google, Tech Mahindra, and Genesys International also plan to extend this to more than around 50 cities by the end of the year 2022.. Key drivers for this market are: Growth in Application for Advanced Navigation System in Automotive Industry, Surge in Demand for Geographic Information System (GIS); Increased Adoption of Connected Devices and Internet. Potential restraints include: Complexity in Integration of Traditional Maps with Modern GIS System. Notable trends are: Surge in Demand for GIS and GNSS to Influence the Adoption of Digital Map Technology.

Correlation of the drug names appearing in four Han Dynasty excavated text with the Historical GIS data for those drugs, as geo-located in the fifth-cenutry 本草經集注. These data forms the back bone for maps published in the article "Mapping the Bencao" in Asian Medicine, 2023 as well as for the interactive Tableau map, titled "Mapping Drugs in Han Dynasty Excavated Texts" https://public.tableau.com/app/profile/dr.michael.stanley.baker/viz/MappingDrugsinHanDynastyExcavatedTexts/Terrain

The Geologic Map Index of Alaska (Map Index) is a GIS web feature service paired with an interactive web map application that provides access to an actively growing geographic index of geology-related maps of Alaska and adjacent areas. This online research tool provides the locations and outlines of most DGGS and U.S. Geological Survey (USGS) geologic maps of Alaska in a single, interactive web application. It allows searches of the map database by geographic area of interest, keywords, publishing agency, dates, and other criteria. The search results link DGGS's comprehensive, multi-agency publications database, where users can view and download publications for free. Map Index provides access to traditional geologic maps and sample location, geologic hazards, and geologic resources maps. In addition, DGGS plans to add outlines and data to the application for new and remaining geologic maps published by DGGS, USGS, U.S. Bureau of Mines, and U.S. Bureau of Land Management. Reports without maps can be accessed through DGGS's comprehensive publications database, .

The main purpose of the research on map emotional semantics is to describe and express the emotional responses caused by people observing images through computer technology. Nowadays, map application scenarios tend to be diversified, and the increasing demand for emotional information of map users bring new challenges for cartography. However, the lack of evaluation of emotions in the traditional map drawing process makes it difficult for the resulting maps to reach emotional resonance with map users. The core of solving this problem is to quantify the emotional semantics of maps, it can help mapmakers to better understand map emotions and improve user satisfaction. This paper aims to perform the quantification of map emotional semantics by applying transfer learning methods and the efficient computational power of convolutional neural networks (CNN) to establish the correspondence between visual features and emotions. The main contributions of this paper are as follows: (1) a Map Sentiment Dataset containing five discrete emotion categories; (2) three different CNNs (VGG16, VGG19, and InceptionV3) are applied for map sentiment classification task and evaluated by accuracy performance; (3) six different parameter combinations to conduct experiments that would determine the best combination of learning rate and batch size; and (4) the analysis of visual variables that affect the sentiment of a map according to the chart and visualization results. The experimental results reveal that the proposed method has good accuracy performance (around 88%) and that the emotional semantics of maps have some general rules. A Map Sentiment Dataset with five discrete emotions is constructedMap emotional semantics are classified by deep learning approachesVisual variables Influencing map sentiment are analyzed. A Map Sentiment Dataset with five discrete emotions is constructed Map emotional semantics are classified by deep learning approaches Visual variables Influencing map sentiment are analyzed.

Data Base Topographic means the base of reference built from the “traditional” contents of a technical map obtainable with the process of stereorestitution on a large-medium scale, such as to support the integration of “thematic” data specific to the various functions of the public administration, with the aim of ensuring that both the starting and the thematic data can then be used for information exchanges, for synthesis and for the representation of information at the various scales. the project of the Topographic Data Base proposes the definition of the contents and their organisation in such a way as to be able to automatically reproduce the traditional paper, as is the case with numerical cartography products, and to aggregate the constituent elements of numerical cartography into objects present in the territory and referable in all of their geometric components, such as a building, the road traffic area of a given toponymous road, a dam, the territory of a given municipality, etc.

The herbologist and doula at the Community Health Centre for a BC First Nation currently offers workshops to the community on local traditional medicines and plants. Certain plants only grow during specific times of the year, making the window to offer workshops fairly short. This project was a collaboration between students from the Entry-to-Practice PharmD Program at the University of British Columbia and the First Nation to create a booklet outlining the workshops offered each season, corresponding with the availability of plants used in traditional medicines. The project members interviewed the herbologist to gather relevant information. A booklet was created to present the workshops offered by the herbologist and information on the plants’ availability by season and traditional uses.

Topographic Map 1:1,000. Geographical area where it is located: Canary Islands. Year of flight 2007. Reference System ITRF93, Elipsoide WGS84, REGCAN95 Geodesic Network (version 2001), UTM Husso 28 projection system and altitudes referring to the average sea level determined on each island. Storage format: DGN v8. Level curves every 1 meter and director level curves every 5 meters. The series presents the traditional content of topographic cartography. Physical geography: relief, hydrography and land uses. Human geography: population centers and constructions, natural resources and industry, communication routes, administrative divisions and geodesic supports. Toponymy and labeling. Photogrammetric flight Analog scale 1:5,000. Islands and dates: The Iron: 20/06/2007-13/03/2008, Fuerteventura: 11/06/2007-06/07/2007, Gran Canaria: 26/05/2007-06/11/2007, La Gomera: 25/05/2007-04/08/2007, La Palma: 25/05/2007-04/08/2007, Lanzarote: 06/07/2007-09/11/2007, Tenerife: 22/05/2007-17/10/2007.

Integrated Topographic Map 1:1,000/1:5,000. Made from two flights: a low flight (GSD digital flight 8.5 cm/pixel), for urban areas) and a high flight (digital flight GSD 22 cm/pixel for the rest of the zones). Reference System ITRF93, Elipsoide WGS84, REGCAN95 Geodesic Network (version 2001), UTM Husso 28 projection system and altitudes referring to the average sea level determined on each island. Storage format: DGN v8, SHP and DXF. The series presents the traditional content of topographic cartography. Physical geography: relief, hydrography and land uses. Human geography: population centers and constructions, natural resources and industry, communication routes, administrative divisions and geodesic supports. Toponymy and labeling. Scope: Tenerife Dates: low flight (205, GSD 8.5 cm/pixel). 31/03/2014 to 01/05/2014. High flight (204, GSD 22 cm/pixel). 27/03/2014 to 05/04/2014.

Map of cultural heritage of La Roca del Vallès is a set of geographical information relating to the different places of heritage and tourist value in the municipality. The data set shows the location of the architectural, archaeological, cultural and natural heritage elements of the municipality; using a viewfinder on an Google Maps background. Finally, for each asset or element of interest, along with its spatial representation, a description record, information of interest, and one or more images are provided.

This data release presents geologic map data for the bedrock geology of the Aztec 1-degree by 2-degree quadrangle, New Mexico. Geologic mapping incorporates new interpretive contributions and compilation from published geologic map data sources primarily ranging from 1:24,000 to 1:50,000 scale. Much of the geology incorporated from published geologic maps is adjusted based on digital elevation model and natural-color image data sources to improve spatial resolution of the data. Spatial adjustments and new interpretations also eliminate mismatches at source map boundaries. This data set represents only the bedrock geology; deposits of unconsolidated, surficial materials that are typically, but not exclusively, Quaternary in age, are not included in this database. Bedrock in the context of this database includes all metamorphic, sedimentary, and igneous rocks regardless of age. Bedrock geology is continuous to the extent that map units and structures can be appropriately constrained, including throughout areas overlain by surficial deposits. Line features that are projected through areas overlain by surficial deposits are generally attributed with lower identity and existence confidence, larger locational confidence values, and a compilation method in the MethodID field indicating features were projected beneath cover (see Turner and others [2022] for a description of MethodID field). Map units represented in this database range from Paleoproterozic and Mesoproterozic metamorphic and intrusive rocks to Pliocene and Quaternary sedimentary and volcanic rocks. Map units and structures in this data set reflect multiple events that are significant at regional and continental scales including multiple Proterozoic accreted terranes, magmatic episodes, supracrustal depositional environments, and continental margin environments, Ancestral Rocky Mountains, Laramide orogeny, Southern Rocky Mountains volcanism, and Rio Grande rift in the Phanerozoic. Map units are organized within geologic provinces as described by the Seamless Integrated Geologic Mapping (SIGMa) (Turner and others, 2022) extension to the Geologic Map Schema (GeMS) (USGS, 2020). Geologic provinces are used to organize map units based on time-dependent, geologic events rather than geographic or rock type groupings that are typical of traditional geologic maps. The detail of geologic mapping is approximately 1:100,000-scale depending on the scale of published geologic maps and new mapping based on field observations or interpretation from basemap data. The database follows the schema and structure of SIGMa (Turner and others, 2022) that is an extension to GeMS (USGS, 2020). Turner, K.J., Workman, J.B., Colgan, J.P., Gilmer, A.K., Berry, M.E., Johnstone, S.A., Warrell, K.F., Dechesne, M., VanSistine, D.P., Thompson, R.A., Hudson, A.M., Zellman, K.L., Sweetkind, D., and Ruleman, C.A., 2022, The Seamless Integrated Geologic Mapping (SIGMa) extension to the Geologic Map Schema (GeMS): U.S. Geological Survey Scientific Investigations Report 2022–5115, 33 p., https://doi.org/ 10.3133/ sir20225115. U.S. Geological Survey National Cooperative Geologic Mapping Program, 2020, GeMS (Geologic Map Schema)-A standard format for the digital publication of geologic maps: U.S. Geological Survey Techniques and Methods, book 11, chap. B10, 74 p., https://doi.org/10.3133/tm11B10.

The El Pilar Project has been conducting research at El Pilar, Belize and Guatemala since 1993, and was founded on a base of survey work that goes back to 1983. This unusual archaeological program recognizes the present environment as a part of the ancient Maya past. Our mission is the preservation and conservation of endangered resources through local and international education. Addressing tensions between culture and nature, we use the past as a reference to build a responsible future. Weaving together traditional knowledge and practice with scientific inquiry and interpretation, we promote a deeper awareness of heritage through local partnership.

The University of California Santa Barbara (UCSB) Maya Forest GIS is an essential tool to organize and use the numerous geographic resources involved in our studies, and provide reliable datasets for the project.

HEPGIS is a web-based interactive geographic map server that allows users to navigate and view geo-spatial data, print maps, and obtain data on specific features using only a web browser. It includes geo-spatial data used for transportation planning. HEPGIS previously received ARRA funding for development of Economically distressed Area maps. It is also being used to demonstrate emerging trends to address MPO and statewide planning regulations/requirements , enhanced National Highway System, Primary Freight Networks, commodity flows and safety data . HEPGIS has been used to help implement MAP-21 regulations and will help implement the Grow America Act, particularly related to Ladder of Opportunities and MPO reforms.

This data release presents geologic map data for the bedrock geology of the Blanca Peak, Walsenburg, Trinidad, and Alamosa 30' x 60' quadrangles, Colorado. Geologic mapping incorporates new interpretive contributions and compilation from published geologic map data sources primarily ranging from 1:24,000 to 1:50,000 scale. Much of the geology incorporated from published geologic maps is adjusted based on digital elevation model and natural-color image data sources to improve spatial resolution of the data. Spatial adjustments and new interpretations also eliminate mismatches at source map boundaries. This data set represents only the bedrock geology; deposits of unconsolidated, surficial materials that are typically, but not exclusively, Quaternary in age, are not included in this database. Bedrock in the context of this database includes all metamorphic, sedimentary, and igneous rocks regardless of age. Bedrock geology is continuous to the extent that map units and structures can be appropriately constrained, including throughout areas overlain by surficial deposits. Line features that are projected through areas overlain by surficial deposits are generally attributed with lower identity and existence confidence, larger locational confidence values, and a compilation method in the MethodID field indicating features were projected beneath cover (see Turner and others [2022] for a description of MethodID field). Map units represented in this database range from Paleoproterozic and Mesoproterozic metamorphic and intrusive rocks to Pliocene and Quaternary sedimentary and volcanic rocks. Map units and structures in this data set reflect multiple events that are significant at regional and continental scales including multiple Proterozoic accreted terranes, magmatic episodes, supracrustal depositional environments, and continental margin environments, Ancestral Rocky Mountains, Laramide orogeny, Southern Rocky Mountains volcanism, and Rio Grande rift in the Phanerozoic. Map units are organized within geologic provinces as described by the Seamless Integrated Geologic Mapping (SIGMa) (Turner and others, 2022) extension to the Geologic Map Schema (GeMS) (USGS, 2020). Geologic provinces are used to organize map units based on time-dependent, geologic events rather than geographic or rock type groupings that are typical of traditional geologic maps. The detail of geologic mapping is approximately 1:100,000-scale depending on the scale of published geologic maps and new mapping based on field observations or interpretation from basemap data. The database follows the schema and structure of SIGMa (Turner and others, 2022) that is an extension to GeMS (USGS, 2020). Turner, K.J., Workman, J.B., Colgan, J.P., Gilmer, A.K., Berry, M.E., Johnstone, S.A., Warrell, K.F., Dechesne, M., VanSistine, D.P., Thompson, R.A., Hudson, A.M., Zellman, K.L., Sweetkind, D., and Ruleman, C.A., 2022, The Seamless Integrated Geologic Mapping (SIGMa) extension to the Geologic Map Schema (GeMS): U.S. Geological Survey Scientific Investigations Report 2022–5115, 33 p., https://doi.org/ 10.3133/ sir20225115. U.S. Geological Survey National Cooperative Geologic Mapping Program, 2020, GeMS (Geologic Map Schema)-A standard format for the digital publication of geologic maps: U.S. Geological Survey Techniques and Methods, book 11, chap. B10, 74 p., https://doi.org/10.3133/tm11B10.

The Electronic Cartography market has witnessed transformative growth over the past decade, evolving from traditional mapping techniques to sophisticated digital platforms that enable the creation, analysis, and dissemination of geographical information. This market encompasses advanced tools and technologies used i

Choropleth maps are fundamental tools for geographic data analysis, primarily relying on color to convey information. Consequently, the design of their color schemes is of paramount importance in choropleth map production. The traditional coloring methods offered by GIS tools such as ArcGIS and QGIS are not user-friendly for non-professionals. These tools provide numerous color schemes, making selection difficult, and cannot also easily fulfill personalized coloring needs, such as requests for 'summer-like' map colors. To address these shortcomings, we develop a novel system that leverages a large language model and map color design principles to generate contextually relevant and user-aligned choropleth map color schemes. The system follows a three-stage process: Data processing, which provides an overview and classification of the data; Color Concept Design, where color theme and mode are conceptualized based on data characteristics and user intentions; and Color Scheme Design, where specific colors are assigned to classes. Our system incorporates an interactive interface for choropleth map color design and allows users to customize color choices flexibly. Through user studies and evaluations, the system demonstrates acceptable usability, accuracy, and flexibility, with users highlighting its efficiency and ease of use.

V Map Level 2, or “Smart Map Level 2” is a compilation containing vector data along with encoded information (attributes). It is a vector map corresponding to the information resolution of a traditional topographic map in a scale of 1:50000. Data stored in VMap Level 2 is information about administrative boundaries, terrain, environment, hydrography, industry, transport, physiography, vegetation, aeronautics, buildings, built-up areas, transmission lines. V Map Level 2, or “Smart Map Level 2” is a compilation containing vector data along with encoded information (attributes). It is a vector map corresponding to the information resolution of a traditional topographic map in a scale of 1:50000. Data stored in VMap Level 2 is information about administrative boundaries, terrain, environment, hydrography, industry, transport, physiography, vegetation, aeronautics, buildings, built-up areas, transmission lines.

This feature layer contains an index of published geologic maps covering the state of Alaska from both DGGS and USGS. Map outlines of traditional geologic maps are available, as well as sample location, geologic hazards, and geologic resources maps. Some maps may be categorized under multiple themes. In some cases, the only bounding box (or map extent) is available for the geologic map. Thus, some areas of the map extent for a record is unmapped. Publications that do not represent data in horizontal, 2- or 3-dimensional space or are text-only reports can be accessed through DGGS's comprehensive publications database (https://dggs.alaska.gov/pubs).