Geospatial Solutions Market size was valued at USD 282.75 Billion in 2024 and is projected to reach USD 650.14 Billion by 2032, growing at a CAGR of 12.10% during the forecast period 2026-2032.

Geospatial Solutions Market: Definition/ Overview

Geospatial solutions are applications and technologies that use spatial data to address geography, location, and Earth's surface problems. They use tools like GIS, remote sensing, GPS, satellite imagery analysis, and spatial modelling. These solutions enable informed decision-making, resource allocation optimization, asset management, environmental monitoring, infrastructure planning, and addressing challenges in sectors like urban planning, agriculture, transportation, disaster management, and natural resource management. They empower users to harness spatial information for better understanding and decision-making in various contexts.

Geospatial solutions are technologies and methodologies used to analyze and visualize spatial data, ranging from urban planning to agriculture. They use GIS, remote sensing, and GNSS to gather, process, and interpret data. These solutions help users make informed decisions, solve complex problems, optimize resource allocation, and enhance situational awareness. They are crucial in addressing challenges and unlocking opportunities in today's interconnected world, such as mapping land use patterns, monitoring ecosystem changes, and real-time asset tracking.

The U.S. Geological Survey (USGS) has compiled a geodatabase containing mineral-related geospatial data for the People's Republic of China. The data can be used in analyses of the extractive fuel and nonfuel mineral industries and related economic and physical infrastructure integral for the successful operation of the mineral industries within the area of study as well as the movement of mineral products across domestic and global markets. This geodatabase reflects the USGS ongoing commitment to its mission of understanding the nature and distribution of global mineral commodity supply chains by updating and publishing the georeferenced locations of mineral commodity production and processing facilities, mineral exploration and development sites, and mineral commodity exporting ports for the countries in the area of study. The geodatabase contains data feature classes from USGS, foreign governmental, and open-source sources as follows: (1) mineral production and processing facilities, (2) mineral exploration and development sites, (3) mineral occurrence sites and deposits, (4) undiscovered mineral resource tracts for antimony, copper, phosphate, and potash, (5) coal occurrence areas, (6) electric power generating facilities, (7) electric power transmission lines, (8) liquefied natural gas terminals, (9) undiscovered, technically recoverable conventional and continuous hydrocarbon resources (by USGS geologic province), (10) cumulative production and recoverable conventional resources (by province groups), and (11) major mineral exporting maritime ports.

The National Aggregates of Geospatial Data Collection: Population, Landscape, And Climate Estimates, Version 4 (PLACE IV) provides measures of population (head counts) and land area (square kilometers) as totals and by urban and rural designation, within multiple biophysical themes for 248 statistical areas (countries and other territories recognized by the United Nations (UN)), UN geographic regions and subregions, and World Bank economic classifications. It improves upon previous versions by providing these estimates at both the national level, and where possible, at subnational administrative level 1 for the years 2000, 2005, 2010, 2015, and 2020, and by 5-year and broad age groups for the year 2010.

Spatial coverage index compiled by East View Geospatial of set "Colombia 1:200,000 Scale Geological Maps". Source data from SGNC (publisher). Type: Geoscientific - Geology. Scale: 1:200,000. Region: South America.

Based on open access data, 79 Mediterranean passenger ports are analyzed to compare their infrastructure, hinterland accessibility and offered multi-modality categories. Comparative Geo-spatial analysis is also carried out by using the data normalization method in order to visualize the ports' performance on maps. These data driven comprehensive analytical results can bring added value to sustainable development policy and planning initiatives in the Mediterranean Region. The analyzed elements can be also contributed to the development of passenger port performance indicators. The empirical research methods used for the Mediterranean passenger ports can be replicated for transport nodes of any region around the world to determine their relative performance on selected criteria for improvement and planning.

The Mediterranean passenger ports were initially categorized into cruise and ferry ports. The cruise ports were identified from the member list of the Association for the Mediterranean Cruise Ports (MedCruise), representing more than 80% of the cruise tourism activities per country. The identified cruise ports were mapped by selecting the corresponding geo-referenced ports from the map layer developed by the European Marine Observation and Data Network (EMODnet). The United Nations (UN) Code for Trade and Transport Locations (LOCODE) was identified for each of the cruise ports as the common criteria to carry out the selection. The identified cruise ports not listed by the EMODnet were added to the geo-database by using under license the editing function of the ArcMap (version 10.1) geographic information system software. The ferry ports were identified from the open access industry initiative data provided by the Ferrylines, and were mapped in a similar way as the cruise ports (Figure 1).

Based on the available data from the identified cruise ports, a database (see Table A1–A3) was created for a Mediterranean scale analysis. The ferry ports were excluded due to the unavailability of relevant information on selected criteria (Table 2). However, the cruise ports serving as ferry passenger ports were identified in order to maximize the scope of the analysis. Port infrastructure and hinterland accessibility data were collected from the statistical reports published by the MedCruise, which are a compilation of data provided by its individual member port authorities and the cruise terminal operators. Other supplementary sources were the European Sea Ports Organization (ESPO) and the Global Ports Holding, a cruise terminal operator with an established presence in the Mediterranean. Additionally, open access data sources (e.g. the Google Maps and Trip Advisor) were consulted in order to identify the multi-modal transports and bridge the data gaps on hinterland accessibility by measuring the approximate distances.

This dataset contains model-based place (incorporated and census designated places) estimates in GIS-friendly format. PLACES covers the entire United States—50 states and the District of Columbia —at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at four geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates are Behavioral Risk Factor Surveillance System (BRFSS) 2022 or 2021 data, Census Bureau 2020 population estimates, and American Community Survey (ACS) 2018–2022 estimates. The 2024 release uses 2022 BRFSS data for 36 measures and 2021 BRFSS data for 4 measures (high blood pressure, high cholesterol, cholesterol screening, and taking medicine for high blood pressure control among those with high blood pressure) that the survey collects data on every other year. These data can be joined with the 2020 Census place boundary file in a GIS system to produce maps for 40 measures at the place level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software. https://cdcarcgis.maps.arcgis.com/home/item.html?id=3b7221d4e47740cab9235b839fa55cd7

Contains information about facilities or sites subject to environmental regulation, including key facility information along with associated environmental interests for use in mapping and reporting applications.

The Geospatial Imagery Analytics Marketsize was valued at USD 11.88 USD Billion in 2023 and is projected to reach USD 83.39 USD Billion by 2032, exhibiting a CAGR of 32.1 % during the forecast period.Geospatial analytics gathers, manipulates, and displays geographic information system (GIS) data and imagery including GPS and satellite photographs. Geospatial data analytics rely on geographic coordinates and specific identifiers such as street address and zip code. geospatial visualization enables businesses to better understand complex information and make informed decisions. They can quickly see patterns and trends and assess the impact of different variables by visualizing data in a spatial context. The field encompasses several techniques and algorithms, such as spatial interpolation, spatial regression, spatial clustering, and spatial autocorrelation analysis, which help extract insights from various geospatial data sources. The growing adoption of location-based services in various industries, including agriculture, defense, and urban planning, is driving the demand for geospatial imagery analytics. Recent developments include: August 2023: onX, a digital navigation company, partnered with Planet Labs PBC, a satellite imagery provider, to introduce a new feature called ‘Recent Imagery’. This feature offers onX app users updated satellite imagery maps every two weeks, enhancing the user experience across onX Hunt, onX Offroad, and onX Backcountry apps. This frequent data update helps outdoor enthusiasts access real-time information for safer and more informed outdoor activities., August 2023: Quant Data & Analytics, a provider of data products and enterprise solutions for real estate and retail, partnered with Satellogic Inc. to utilize Satellogic’s high-resolution satellite imagery to enhance property technology in Saudi Arabia and the Gulf region., April 2023: Astraea, a spatiotemporal data and analytics platform, introduced a new ordering service that grants customers scalable access to top-tier commercial satellite imagery from providers such as Planet Labs PBC and others., May 2022: Satellogic Inc. established a partnership with UP42. This geospatial developer platform enables direct access to Satellogic’s satellite tasking capabilities, including high-resolution multispectral and wide-area hyperspectral imagery, through the UP42 API-based platform., April 2022: TomTom International BV, a geolocation tech company, broadened its partnership with Maxar Technologies, a space solution provider. This expansion involves integrating high-resolution global satellite imagery from Maxar’s Vivid imagery base maps into TomTom’s product lineup, enhancing their visualization solutions for customers.. Key drivers for this market are: Growing Demand for Location-based Insights across Diverse Industries to Fuel Market Growth. Potential restraints include: Complexity and Cost Associated with Data Acquisition and Processing May Hamper Market Growth. Notable trends are: Growing Implementation of Touch-based and Voice-based Infotainment Systems to Increase Adoption of Intelligent Cars.

Dataset

This dataset was created by jembovski

Released under CC0: Public Domain

Contents

This table describes the marine geospatial data holdings that are available from the Ministry of Primary Industries.This is the underlying table for the which is shown on the open data portal Open data siteHere is the link to the actual catalogue, which can be down loaded.The data can be updated here into this table. it was loaded as requested by the Spatial Intelligence - water team, MPI. Initially the request included the requirement for the team to update the table but this was not followed up and there haven't been any edits to the Catalogue since July 2021.

Geospatial Analytics Market Outlook

In 2023, the global geospatial analytics market size was valued at approximately USD 55 billion and is projected to reach around USD 165 billion by 2032, growing at a CAGR of 12.5% during the forecast period. The market is driven by technological advancements and the increasing need for geospatial data across various industries.

One of the key growth factors of the geospatial analytics market is the rapid advancement in geospatial technologies such as Geographic Information Systems (GIS), remote sensing, and global positioning systems (GPS). These technologies have significantly enhanced the accuracy and efficiency of data collection, analysis, and interpretation. Additionally, the integration of artificial intelligence (AI) and machine learning (ML) algorithms with geospatial analytics has further augmented its capabilities, making it an indispensable tool for decision-making across diverse sectors.

Another significant driver of the geospatial analytics market is the growing adoption of location-based services and real-time data analysis. With the proliferation of smartphones and IoT devices, there is an increasing demand for applications that provide real-time location data. This has led to a surge in the use of geospatial analytics in urban planning, transportation and logistics, and disaster management. Companies and governments are leveraging geospatial data to optimize routes, manage resources efficiently, and respond swiftly to emergencies.

Furthermore, the rising awareness about climate change and environmental sustainability has propelled the use of geospatial analytics in climate change adaptation and environmental monitoring. Governments and organizations are increasingly relying on geospatial data to understand environmental changes, assess risks, and devise strategies for climate resilience. This trend is particularly significant in regions prone to natural disasters, where timely and accurate geospatial data can save lives and minimize damages.

From a regional perspective, North America holds a significant share of the geospatial analytics market, driven by the presence of major technology companies and extensive government initiatives focused on smart city development and environmental conservation. Europe follows closely, with substantial investments in geospatial technologies for urban planning and infrastructure development. The Asia Pacific region is expected to witness the highest growth rate during the forecast period, fueled by rapid urbanization, industrialization, and government initiatives to enhance geospatial infrastructure.

Component Analysis

The geospatial analytics market is segmented into three main components: software, hardware, and services. Each of these components plays a pivotal role in the functioning and advancement of geospatial analytics. Starting with software, which encompasses a wide array of applications such as Geographic Information Systems (GIS), remote sensing software, and enterprise geospatial solutions. GIS software, in particular, is integral to the collection, storage, analysis, and visualization of geospatial data, enabling organizations to make informed decisions based on spatial patterns and relationships.

Hardware components in the geospatial analytics market include devices and equipment used for data collection and processing, such as GPS devices, drones, LiDAR sensors, and remote sensing satellites. These hardware components are essential for acquiring high-resolution geospatial data from various sources, providing a comprehensive view of geographical areas. The evolution of drone technology and advancements in satellite imaging have significantly enhanced the capability to capture accurate and detailed geospatial information, driving the demand for advanced hardware solutions.

Services in the geospatial analytics market encompass a range of offerings, including consulting, integration, maintenance, and support services. These services are crucial for the successful implementation and operation of geospatial analytics solutions. Consulting services help organizations identify the most suitable geospatial technologies and strategies to meet their specific needs. Integration services ensure seamless deployment of geospatial solutions within existing IT infrastructures, while maintenance and support services provide ongoing technical assistance and updates to keep the systems running smoothly.

The interplay between software, hardware, and services is critical for the effective utilization

These geospatial data and their accompanying report outline many areas of coal in the United States beneath more than 3,000 ft of overburden. Based on depth, these areas may be targets for injection and storage of supercritical carbon dioxide. Additional areas where coal exists beneath more than 1,000 ft of overburden are also outlined; these may be targets for geologic storage of carbon dioxide in conjunction with enhanced coalbed methane production. These areas of deep coal were compiled as polygons into a shapefile for use in a geographic information system (GIS). The coal-bearing formation names, coal basin or field names, geographic provinces, coal ranks, coal geologic ages, and estimated individual coalbed thicknesses (if known) of the coal-bearing formations were included. An additional point shapefile, coal_co2_projects.shp, contains the locations of pilot projects for carbon dioxide injection into coalbeds. This report is not a comprehensive study of deep coal in the United States. Some areas of deep coal were excluded based on geologic or data-quality criteria, while others may be absent from the literature and still others may have been overlooked by the authors.

The geospatial analytics market size is predicted to rise from $93.49 billion in 2024 to $362.45 billion by 2035, growing at a CAGR of 13.1% from 2024 to 2035.

From May 2017 to November 2019, the U.S. Geological Survey conducted bathymetric surveys of New York City's East of Hudson Reservoirs. Bathymetry data were collected at Kensico Reservoir from June to August, 2018. Depth data were collected primarily with a multibeam echosounder. Quality assurance points were measured with a single-beam echosounder. Water surface elevations were established using real-time kinematic (RTK) and static global navigation satellite system (GNSS) surveys and submersible pressure transducers. Measured sound velocity profiles were used to correct echosounder depth measurements for thermal stratification. Digital elevation models were created by combining the measured bathymetry data with lidar elevation data surrounding the reservoirs; gaps in the combined data were estimated (for example the tops of submerged islands) or interpolated. Files included in this Data Release include: grids (tiff format) of reservoir bed elevation, data source, and cell data standard deviation; shapefiles of elevation contours at a 2-foot interval and of single-beam echosounder quality assurance points; and text files (comma-separated value format) of elevation-area-capacity table, measured GNSS points, water surface elevation time series (tides) used to process echosounder data, measured sound velocity profiles, and average sound velocity profiles used to process echosounder data. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

This dataset includes the inputs and results for developing a transportation geo-typology that categorizes every location in the United States in terms of their main drivers of transportation demand and supply. It provides the raw inputs to the census tract level microtypes and county or CBSA level geotypes as well as the final typology labels at both the tract (microtype) and county/CBSA (geotype) levels. Inputs include information on the street network, economic characteristics, topography, commute patterns, and land use. The methodology is published in "Popovich, N., Spurlock, C. A., Needell, Z., Jin, L., Wenzel, T., Sheppard, C., & Asudegi, M. (2021). A methodology to develop a geospatial transportation typology. Journal of transport geography, 93, 103061".

Explore the historical Whois records related to hexagon-geospatial.com (Domain). Get insights into ownership history and changes over time.

The U.S. Geological Survey (USGS) has compiled a geodatabase containing mineral-related geospatial data for 10 countries of interest in Southwest Asia (area of study): Afghanistan, Cambodia, Laos, India, Indonesia, Iran, Nepal, North Korea, Pakistan, and Thailand. The data can be used in analyses of the extractive fuel and nonfuel mineral industries and related economic and physical infrastructure integral for the successful operation of the mineral industries within the area of study as well as the movement of mineral products across domestic and global markets. This geodatabase reflects the USGS ongoing commitment to its mission of understanding the nature and distribution of global mineral commodity supply chains by updating and publishing the georeferenced locations of mineral commodity production and processing facilities, mineral exploration and development sites, and mineral commodity exporting ports for the countries in the area of study. The geodatabase contains data feature classes from USGS, foreign governmental, and open-source sources as follows: (1) mineral production and processing facilities, (2) mineral exploration and development sites, (3) mineral occurrence sites and deposits, (4) undiscovered mineral resource tracts for copper, phosphate, and potash, (5) coal occurrence areas, (6) electric power generating facilities, (7) electric power transmission lines, (8) liquefied natural gas terminals, (9) undiscovered, technically recoverable conventional and continuous hydrocarbon resources (by USGS geologic province), (10) cumulative production and recoverable conventional resources (by oil- and gas-producing nation), and (11) major mineral exporting maritime ports.

Spatial coverage index compiled by East View Geospatial of set "USGS 1:31,680 Scale Topographic Maps". Source data from USGS (publisher). Type: Topographic. Scale: 1:31,680. Region: North America.

Progress Needed on Identifying Expenditures, Building and Utilizing a Data Infrastructure, and Reducing Duplicative Efforts The federal government collects, maintains, and uses geospatial information—data linked to specific geographic locations—to help support varied missions, including national security and natural resources conservation. To coordinate geospatial activities, in 1994 the President issued an executive order to develop a National Spatial Data Infrastructure—a framework for coordination that includes standards, data themes, and a clearinghouse. GAO was asked to review federal and state coordination of geospatial data. GAO’s objectives were to (1) describe the geospatial data that selected federal agencies and states use and how much is spent on geospatial data; (2) assess progress in establishing the National Spatial Data Infrastructure; and (3) determine whether selected federal agencies and states invest in duplicative geospatial data. To do so, GAO identified federal and state uses of geospatial data; evaluated available cost data from 2013 to 2015; assessed FGDC’s and selected agencies’ efforts to establish the infrastructure; and analyzed federal and state datasets to identify duplication. What GAO Found Federal agencies and state governments use a variety of geospatial datasets to support their missions. For example, after Hurricane Sandy in 2012, the Federal Emergency Management Agency used geospatial data to identify 44,000 households that were damaged and inaccessible and reported that, as a result, it was able to provide expedited assistance to area residents. Federal agencies report spending billions of dollars on geospatial investments; however, the estimates are understated because agencies do not always track geospatial investments. For example, these estimates do not include billions of dollars spent on earth-observing satellites that produce volumes of geospatial data. The Federal Geographic Data Committee (FGDC) and the Office of Management and Budget (OMB) have started an initiative to have agencies identify and report annually on geospatial-related investments as part of the fiscal year 2017 budget process. FGDC and selected federal agencies have made progress in implementing their responsibilities for the National Spatial Data Infrastructure as outlined in OMB guidance; however, critical items remain incomplete. For example, the committee established a clearinghouse for records on geospatial data, but the clearinghouse lacks an effective search capability and performance monitoring. FGDC also initiated plans and activities for coordinating with state governments on the collection of geospatial data; however, state officials GAO contacted are generally not satisfied with the committee’s efforts to coordinate with them. Among other reasons, they feel that the committee is focused on a federal perspective rather than a national one, and that state recommendations are often ignored. In addition, selected agencies have made limited progress in their own strategic planning efforts and in using the clearinghouse to register their data to ensure they do not invest in duplicative data. For example, 8 of the committee’s 32 member agencies have begun to register their data on the clearinghouse, and they have registered 59 percent of the geospatial data they deemed critical. Part of the reason that agencies are not fulfilling their responsibilities is that OMB has not made it a priority to oversee these efforts. Until OMB ensures that FGDC and federal agencies fully implement their responsibilities, the vision of improving the coordination of geospatial information and reducing duplicative investments will not be fully realized. OMB guidance calls for agencies to eliminate duplication, avoid redundant expenditures, and improve the efficiency and effectiveness of the sharing and dissemination of geospatial data. However, some data are collected multiple times by federal, state, and local entities, resulting in duplication in effort and resources. A new initiative to create a national address database could potentially result in significant savings for federal, state, and local governments. However, agencies face challenges in effectively coordinating address data collection efforts, including statutory restrictions on sharing certain federal address data. Until there is effective coordination across the National Spatial Data Infrastructure, there will continue to be duplicative efforts to obtain and maintain these data at every level of government.https://www.gao.gov/assets/d15193.pdfWhat GAO Recommends GAO suggests that Congress consider assessing statutory limitations on address data to foster progress toward a national address database. GAO also recommends that OMB improve its oversight of FGDC and federal agency initiatives, and that FGDC and selected agencies fully implement initiatives. The agencies generally agreed with the recommendations and identified plans to implement them.

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 52M+ 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.