The geospatial data analytics market, currently valued at $86.39 billion in 2025, is projected to experience robust growth, driven by a compound annual growth rate (CAGR) of 12.81% from 2025 to 2033. This expansion is fueled by several key factors. Increasing reliance on location intelligence across diverse sectors like agriculture (precision farming), utilities (network optimization), defense (surveillance and intelligence), and government (urban planning and resource management) is a major catalyst. Advances in technologies such as AI, machine learning, and cloud computing are enhancing the analytical capabilities of geospatial data, leading to more accurate insights and predictive modeling. Furthermore, the growing availability of high-resolution satellite imagery and sensor data is significantly expanding the data pool for analysis, contributing to market growth. The market is segmented by type (surface analysis, network analysis, geovisualization analysis) and end-user vertical, each contributing uniquely to the overall market value. Competition is fierce, with established players like ESRI, Hexagon AB, and Trimble Inc. alongside emerging technology companies vying for market share. The market's geographic distribution is expected to reflect global technological adoption rates and economic activity. North America and Europe currently hold significant market shares, but the Asia-Pacific region is projected to witness substantial growth due to increasing investments in infrastructure and technological advancements. Government initiatives promoting the use of geospatial technology in various sectors are further bolstering market expansion in developing economies. While data privacy concerns and the need for skilled professionals represent challenges, the overall market outlook remains strongly positive, underpinned by the continuous increase in data generation, sophisticated analytical tools, and the widespread acceptance of location-based services across numerous industries. The forecast period (2025-2033) anticipates a continued trajectory of expansion, with significant market penetration across a wider range of applications. Recent developments include: June 2023: Intermap Technologies leveraged its high-resolution elevation data access to perform imagery correction services for a national government organization to support the development projects in El Salvador and Honduras in Central America. In partnership with GeoSolutions, Intermap enables the creation of precision maps that are invaluable resources in supporting community safety and resiliency., March 2023: Mach9, the company building the fastest technologies for geospatial production, introduced its first product. The new product leverages computer vision and AI to produce faster 2D and 3D CAD and GIS engineering deliverables. This product launch comes amidst Mach9's pivot to a software-first business model, which is a move that is primarily driven by the rising demand for tools that accelerate geospatial data processing and analysis for infrastructure management.. Key drivers for this market are: Increase in Adoption of Smart City Development, Introduction of 5G to Boost Market Growth. Potential restraints include: Increase in Adoption of Smart City Development, Introduction of 5G to Boost Market Growth. Notable trends are: Defense and Intelligence to be the Largest End-user Industry.

The U.S. Army Corps of Engineers Geospatial Open Data provides shared and trusted USACE geospatial data, services and applications for use by our partner agencies and the public.

This dataset has a data dictionary that can be downloaded here. The NM Office of the State Engineer (OSE) "Point of Diversions" (POD) layer includes well locations, surface declarations, or surface permits. These data were extracted from the OSE W.A.T.E.R.S. (Water Administration Technical Engineering Resource System) database and geo-located (mapped). These data have varying degrees of accuracy and have not been validated. This message is to alert users of this data to various changes regarding how this POD data is generated and maintained by the NM Office of the State Engineer. In addition, all attribute fields are fully described in the metadata, including descriptions of field codes. Please read the metadata accompanying this GIS data layer for further information. Any questions regarding this GIS data should be directed NM OSE Information Technology Systems Bureau GIS at the contact information given below. Stephen N. Hayes NMOSE ITSB GIS Data Manager(505) 827-6321 PO Box 25102 Santa Fe, NM 87504 stephen.hayes@ose.nm.gov

JSON files to test code described in the article "Tweet2r a package to capture from streaming, storing and describing large tweets data sets as spatio-temporal data"

Bolton & Menk, an engineering planning and consulting firm from the Midwestern United States has released a series of illustrated children’s books as a way of helping young people discover several different professions that typically do not get as much attention as other more traditional ones do.Topics of the award winning book series include landscape architecture, civil engineering, water resource engineering, urban planning and now Geographic Information Systems (GIS). The books are available free online in digital format, and easily accessed via a laptop, smart phone or tablet.The book Lindsey the GIS Specialist – A GIS Mapping Story Tyler Danielson, covers some the basics of what geographic information is and the type of work that a GIS Specialist does. It explains what the acronym GIS means, the different types of geospatial data, how we collect data, and what some of the maps a GIS Specialist creates would be used for.Click here to check out the GIS Specialist – A GIS Mapping Story e-book

The Spatial Analysis Software market is experiencing robust growth, driven by the increasing adoption of cloud-based solutions, the expanding use of drones and other data acquisition technologies for precise geographic data collection, and the rising demand for advanced analytics across diverse sectors. The market's expansion is fueled by the need for efficient geospatial data processing and interpretation in applications such as urban planning, infrastructure development, environmental monitoring, and precision agriculture. Key trends include the integration of Artificial Intelligence (AI) and Machine Learning (ML) for automating analysis and improving accuracy, the proliferation of readily available satellite imagery and sensor data, and the growing adoption of 3D modeling and visualization techniques. While data security concerns and the high initial investment costs for advanced software solutions pose some restraints, the overall market outlook remains positive, with a projected compound annual growth rate (CAGR) exceeding 10% (a reasonable estimate based on the rapid technological advancements and market penetration observed in related sectors). This growth is expected to be particularly strong in the North American and Asia-Pacific regions, driven by substantial government investments in infrastructure projects and burgeoning private sector adoption. The segmentation by application (architecture, engineering, and other sectors) reflects the versatility of spatial analysis software, enabling its use across various industries. Similarly, the choice between cloud-based and locally deployed solutions caters to specific organizational needs and technical capabilities. The competitive landscape is characterized by both established players and emerging technology companies, showcasing the dynamic nature of the market. Major players like Autodesk, Bentley Systems, and Trimble are leveraging their existing portfolios to integrate advanced spatial analysis capabilities, while smaller companies are focusing on niche applications and innovative analytical techniques. The ongoing advancements in both hardware and software, coupled with increasing data availability and affordability, are set to further fuel the market's growth in the coming years. The historical period (2019-2024) likely witnessed moderate growth as the market matured, laying the foundation for the accelerated expansion expected during the forecast period (2025-2033). Continued innovation and industry convergence will be key drivers shaping the future trajectory of the Spatial Analysis Software market.

This data set contains reduced-resolution QuickBird imagery and geospatial data for the entire Barrow QuickBird image area 156.15° W - 157.07° W, 71.15° N - 71.41° N) and the Barrow B4 Quadrangle (156.29° W - 156.89° W, 71.25° N - 71.40° N), for use in Geographic Information Systems (GIS) and remote sensing software. The original QuickBird data sets were acquired by DigitialGlobe from 1 to 2 August 2002, and consist of orthorectified satellite imagery. Federal Geographic Data Committee (FGDC)-compliant metadata for all value-added data sets are provided in text, HTML, and XML formats.

Accessory layers include: 1:250,000- and 1:63,360-scale USGS Digital Raster Graphic (DRG) mosaic images (GeoTIFF format); 1:250,000- and 1:63,360-scale USGS quadrangle index maps (ESRI Shapefile format); an index map for the 62 QuickBird tiles (ESRI Shapefile format); and a simple polygon layer of the extent of the Barrow QuickBird image area and the Barrow B4 quadrangle area (ESRI Shapefile format).

The baseline geospatial data support education, outreach, and multi-disciplinary research of environmental change in Barrow, which is an area of focused scientific interest.

Data are available either via FTP or on CD-ROM.

Microsoft T-Drive dataset

MyGeoHub is a science gateway for researchers working with geospatial data. Based on the HUBzero cyberinfrastructure framework, it provides general-purpose software modules enabling geospatial data management, processing and visualization. Termed “GABBs” (Geospatial Data Analysis Building Blocks), these modules can be leveraged to build geospatial data driven tools with minimal programming and construct dynamic workflows chaining both local and remote tools and data sources. We will present examples of such end-to-end workflows demonstrating the underlying software building blocks that have also found use beyond the MyGeoHub gateway in other science domains.

Blacksburg streets, suitable for constructing address finders and networks created and maintained annually by Town of Blacksburg Engineering & GIS in August 2018. This data is being preserved and distributed by Virginia Tech University Libraries. This data is meant for general use only. Virginia Tech’s University Library is acting as a steward for this data and any questions about its use should refer to the Town of Blacksburg Engineering & GIS group.

The input file contains supply data (based on data from geoportal of piedmont and OSM data) and flood map (based on data from geoportal of piedmont) for the Alessandria area in Italy, detailing both basic and disrupted flood scenarios to be analyzed in GIS software. It includes information on closed bridges during flood events. The output file presents the analysis results for both the basic and disrupted scenarios.

an index map for the 62 QuickBird tiles (ESRI Shapefile format)

The construction of this data model was adapted from the Telvent Miner & Miner ArcFM MultiSpeak data model to provide interface functionality with Milsoft Utility Solutions WindMil engineering analysis program. Database adaptations, GPS data collection, and all subsequent GIS processes were performed by Southern Geospatial Services for the Town of Apex Electric Utilities Division in accordance to the agreement set forth in the document "Town of Apex Electric Utilities GIS/GPS Project Proposal" dated March 10, 2008. Southern Geospatial Services disclaims all warranties with respect to data contained herein. Questions regarding data quality and accuracy should be directed to persons knowledgeable with the forementioned agreement.The data in this GIS with creation dates between March of 2008 and April of 2024 were generated by Southern Geospatial Services, PLLC (SGS). The original inventory was performed under the above detailed agreement with the Town of Apex (TOA). Following the original inventory, SGS performed maintenance projects to incorporate infrastructure expansion and modification into the GIS via annual service agreements with TOA. These maintenances continued through April of 2024.At the request of TOA, TOA initiated in house maintenance of the GIS following delivery of the final SGS maintenance project in April of 2024. GIS data created or modified after April of 2024 are not the product of SGS.With respect to SGS generated GIS data that are point features:GPS data collected after January 1, 2013 were surveyed using mapping grade or survey grade GPS equipment with real time differential correction undertaken via the NC Geodetic Surveys Real Time Network (VRS). GPS data collected prior to January 1, 2013 were surveyed using mapping grade GPS equipment without the use of VRS, with differential correction performed via post processing.With respect to SGS generated GIS data that are line features:Line data in the GIS for overhead conductors were digitized as straight lines between surveyed poles. Line data in the GIS for underground conductors were digitized between surveyed at grade electric utility equipment. The configurations and positions of the underground conductors are based on TOA provided plans. The underground conductors are diagrammatic and cannot be relied upon for the determination of the actual physical locations of underground conductors in the field.

Line layer depicting biking trails in Blacksburg created and maintained annually by Town of Blacksburg Engineering & GIS in August 2018. This data is being preserved and distributed by Virginia Tech University Libraries. This data is meant for general use only. Virginia Tech’s University Library is acting as a steward for this data and any questions about its use should refer to the Town of Blacksburg Engineering & GIS group.

The global Geographic Information System (GIS) solutions market size was valued at USD XX million in 2025 and is projected to expand at a CAGR of XX % over the forecast period, reaching USD XXX million by 2033. The growing adoption of GIS solutions across various industries, such as agriculture, oil & gas, architecture, engineering and construction, transportation, mining, government, healthcare, and others, is driving market growth. The increasing need for accurate and timely geospatial data for decision-making, along with the advancements in cloud computing, artificial intelligence (AI), and machine learning (ML), are key trends contributing to market expansion. However, data security concerns and the high cost of implementation and maintenance may restrain market growth to some extent. Key players in the GIS solutions market include ESRI, Hexagon, Pitney Bowes, SuperMap, Bentley System, GE, GeoStar, Zondy Cyber Group, Caliper, Hitachi Solutions, and KCI. North America holds a significant share of the market due to the early adoption of GIS solutions and the presence of major players. Asia Pacific is expected to witness substantial growth over the forecast period owing to the increasing infrastructure development and urbanization in the region.

Data contains historical polygons of in-channel islands within the Sacramento San Joaquin Delta. Data consists of merged datasets from 1929, 1940, 1949, 1952, 1995, 2002, and 2017. The 2017 polygons are digitized from the 2017 Delta LiDAR imagery by the Division of Engineering, Geomatics Branch, Geospatial Data Support Section. The older pre-2017 polygons were all digitized by staff in the Delta Levees Program. Data can be queried for a single year or date range using the 'Year' field. Historical data was compiled and merged from datasets provided by the Delta Levees program. Data coverage differs between years. Absences or gaps in historical data may occur. Older acquisitions generally have a smaller footprint than recent imagery acquisitions. The 2017 in-channel islands cover the Legal Delta, and also include Chipps Island.

The UK geospatial analytics market is projected to reach a value of USD 1.85 billion by 2033, expanding at a CAGR of 11.26% during the forecast period (2025-2033). The increasing demand for geospatial data for decision-making across various industry verticals, such as defense, intelligence, healthcare, and transportation, is driving market growth. The government's emphasis on smart city projects and the adoption of location-based services are also contributing to the market's expansion. Key market trends include the growing adoption of cloud-based geospatial analytics platforms, the increasing use of artificial intelligence (AI) and machine learning (ML) for geospatial data analysis, and the emergence of 5G technology, which enables real-time data collection and processing. The market is segmented by type (surface analysis, network analysis, geovisualization) and end-user vertical (agriculture, utility and communication, defense and intelligence, government, mining and natural resources, automotive and transportation, healthcare, real estate and construction). Key players in the UK geospatial analytics market include SAS Institute Inc, Trimble, General Electric, Accenture, Bluesky International Ltd, ESRI Inc, Oracle Corporation, Bentley Systems Inc, and Hexagon. Recent developments include: April 2023: EDF used Esri UK corporate GIS to build a geospatial site for the Hinkley Point C nuclear power station, one of Europe's most extensive and complicated building projects. The portal provides a single picture of the entire project. They are facilitating greater cooperation and enabling new digital workflows, Assisting employees and contractors in improving safety and productivity. When the building of the nuclear reactors began, the portal has recently been expanded to include Tier-1 contractors, and it presently has over 1,500 users., April 2021: Esri UK launched a new cooperation with Tetra Tech, a worldwide consulting and engineering services company, to enhance indoor mapping capabilities by combining their expertise. Esri UK was to contribute to the partnership's robust GIS system, which had multiple indoor mapping capabilities, such as interactive floor plans and indoor location capabilities. Tetra Tech was to add 3D terrestrial laser scanning, data analytics, and CAD capabilities to GIS. They were to collaborate to provide customers with an end-to-end interior mapping solution to capitalize on an expanding need for indoor mapping for facilities management at central workplaces, campuses, or hospitals.. Key drivers for this market are: Increasing in Demand for Location Intelligence, Advancements of Big Data Analytics. Potential restraints include: High Costs and Operational Concerns, Concerns related to Geoprivacy and Confidential Data. Notable trends are: Location data will hold the significant share.

The U.S. Geological Survey (USGS), in cooperation with the city of Harrisonville, Missouri, assessed flooding of Muddy Creek resulting from varying precipitation magnitudes and durations, antecedent soil moisture conditions, and channel conditions. The precipitation scenarios were used to develop a library of flood-inundation maps that included a 3.8-mile reach of Muddy Creek and tributaries within and adjacent to the city. Hydrologic and hydraulic models of the upper Muddy Creek Basin were used to assess streamflow magnitudes associated with simulated precipitation amounts and the resulting flood-inundation conditions. The U.S. Army Corps of Engineers Hydrologic Engineering Center-Hydrologic Modeling System (HEC–HMS; version 4.4.1) was used to simulate the amount of streamflow produced from a range of rainfall events. The Hydrologic Engineering Center-River Analysis System (HEC–RAS; version 5.0.7) was then used to route streamflows and map resulting areas of flood inundation. The hydrologic and hydraulic models were calibrated to the September 28, 2019; May 27, 2021; and June 25, 2021, runoff events representing a range of antecedent moisture conditions and hydrologic responses. The calibrated HEC–HMS model was used to simulate streamflows from design rainfall events of 30-minute to 24-hour durations and ranging from a 100- to 0.1-percent annual exceedance probability. Flood-inundation maps were produced for USGS streamflow stages of 1.0 feet (ft), or near bankfull, to 4.0 ft, or a stage exceeding the 0.1-percent annual exceedance probability interval precipitation, using the HEC–RAS model. The consequence of each precipitation duration-frequency value was represented by a 0.5-ft increment inundation map based on the generated peak streamflow from that rainfall event and the corresponding stage at the Muddy Creek stage reference _location. Seven scenarios were developed with the HEC–HMS hydrologic model with resulting streamflows routed in a HEC-RAS hydraulic model and these scenarios varied by antecedent soil-moisture and channel conditions. The same precipitation scenarios were used in each of the seven antecedent moisture and channel conditions and the simulation results were assigned to a flood-inundation map condition based on the generated peak flow and corresponding stage at the Muddy Creek reference _location. This data release includes: 1) tables summarizing the model results including the flood-inundation map condition of each model scenario for dry (CNI; Muddy_Creek_summary_table_1_1.csv), normal (CNII; Muddy_Creek_summary_table_1_2.csv), and wet (CNIII; Muddy_Creek_summary_table_1_3.csv) antecedent soil moisture conditions (MuddyCreek_summary_tables.zip); 2) a shapefile dataset of the streamflow inundation extents at Muddy Creek reference _location stages of 1.0 to 4.0 feet (MuddyCreek_inundation_extents.zip containing MudHarMO.shp); 3) a raster dataset of the streamflow depths at Muddy Creek reference _location stages of 1.0 to 4.0 feet (MuddyCreek_inundation_depths.zip containing MudharMO_X.tif where X = 1,2,3,4,5,6,7 corresponding to inundation map stages of 1.0, 1.5 , 2.0, 2.5, 3.0, 3.5, 4.0 feet)); 4) tables of hydrologic and hydraulic model performance and calibration metrics, locations of continuous pressure transducers (PTs; MuddyCreek_PT_locations.zip) and high-water marks (HWMs; MuddCreek_HWM_locations.zip) used in assessment of model calibration and validation, and time series of pressure transducer data (MuddyCreek_PT_time_series.zip) found in MuddyCreek_model_performance_calibration_metrics.zip; 5) hydrologic and hydraulic model run files used in the simulation of dry hydrologic response conditions (CN_I conditions) and effects of proposed detention storage (MuddyCreek_dry_detention.zip); 6) hydrologic and hydraulic model run files used in the simulation and calibration of dry hydrologic response conditions (CN_I conditions) and current (2019) existing channel conditions (MuddyCreek_dry_existing_conditions.zip); 7) hydrologic and hydraulic model run files used in the simulation of normal hydrologic response conditions (CN_II conditions) and effects of cleaned culverts (MuddyCreek_normal_clean_culverts.zip); 8) hydrologic and hydraulic model run files used in the simulation of normal hydrologic response conditions (CN_II conditions) and effects of detention storage (MuddyCreek_normal_detention.zip); 9) hydrologic and hydraulic model run files used in the simulation and calibration of normal hydrologic response conditions (CN_II conditions) and current (2019) existing channel conditions (MuddyCreek_normal_existing_conditions.zip); 10) hydrologic and hydraulic model run files used in the simulation of wet hydrologic response conditions (CN_III conditions) and effects of proposed detention storage (MuddyCreek_wet_detention.zip); 11) hydrologic and hydraulic model run files used in the simulation and calibration of wet hydrologic response conditions (CN_III) and current (2019) existing channel conditions (MuddyCreek_wet_existing_conditions.zip). 12) Service definition files of the Muddy Creek water depths of inundated areas (MuddyCreek_Inundation_depths.sd) and Muddy Creek inundation area polygons (MuddyCreek_inundation_extents.sd) added on September 7, 2022.

Geospatial data about Colorado DOT Engineering Regions. Export to CAD, GIS, PDF, CSV and access via API.

Town of Blacksburg, Virginia August 2018 map. Displays a polygon layer depicting parks in Blacksburg. This data is being preserved and distributed by Virginia Tech University Libraries. This data is meant for general use only. Virginia Tech’s University Library is acting as a steward for this data and any questions about its use should refer to the Town of Blacksburg Engineering & GIS group.