This dataset is a qualitative assessment of geothermal potential for the U.S. using Enhanced Geothermal Systems (EGS) and based on the levelized cost of electricity with CLASS 1 being most favorable and CLASS 5 being least favorable. This dataset does not include shallow EGS resources located near hydrothermal sites or the U.S. Geological Survey assessment of undiscovered hydrothermal resources. The source data for deep EGS includes temperature at depth from 3 to 10 kilometer (km) were provided by the Southern Methodist University Geothermal Laboratory (Blackwell & Richards, 2009) and the analyses for regions with temperatures ≥150°C were performed by NREL (2009). CLASS 999 regions have temperatures less than 150°C at a 10-km depth and were not assessed for deep EGS potential. Temperature at depth data for deep EGS in Alaska and Hawaii are not currently available.

This submission contains an ESRI map package (.mpk) with an embedded geodatabase for GIS resources used or derived in the Nevada Machine Learning project, meant to accompany the final report. The package includes layer descriptions, layer grouping, and symbology. Layer groups include: new/revised datasets (paleo-geothermal features, geochemistry, geophysics, heat flow, slip and dilation, potential structures, geothermal power plants, positive and negative test sites), machine learning model input grids, machine learning models (Artificial Neural Network (ANN), Extreme Learning Machine (ELM), Bayesian Neural Network (BNN), Principal Component Analysis (PCA/PCAk), Non-negative Matrix Factorization (NMF/NMFk) - supervised and unsupervised), original NV Play Fairway data and models, and NV cultural/reference data.

See layer descriptions for additional metadata. Smaller GIS resource packages (by category) can be found in the related datasets section of this submission. A submission linking the full codebase for generating machine learning output models is available through the "Related Datasets" link on this page, and contains results beyond the top picks present in this compilation.

This data layer contains geothermal resource areas and their technical potential used in long-term electric system modeling for Integrated Resource Planning and SB 100. Geothermal resource areas are delineated by Known Geothermal Resource Areas (KGRAs) (Geothermal Map of California, 2002), other geothermal fields (CalGEM Field Admin Boundaries, 2020), and Bureau of Land Management (BLM) Geothermal Leasing Areas (California BLM State Office GIS Department, 2010). The fields that are considered in our assessment have enough information known about the geothermal reservoir that an electric generation potential was estimated by USGS (Williams et al. 2008) or estimated by a BLM Environmental Impact Statement (El Centro Field Office, 2007). For the USGS identified geothermal systems, any point that lies within 2 km of a field is summed to represent the total mean electrical generation potential from the entire field.

Geothermal field boundaries are constructed for identified geothermal systems that lie outside of an established geothermal field. A circular footprint is assumed with a radius determined by the area needed to support the mean resource potential estimate, assuming a 10 MW/km² power density.

Several geothermal fields have power plants that are currently generating electricity from the geothermal source. The total production for each geothermal field is estimated by the CA Energy Commission’s Quarterly Fuel and Energy Report that tracks all power plants greater than 1 MW. The nameplate capacity of all generators in operation as of 2021 were used to inform how much of the geothermal fields are currently in use. This source yields inconsistent results for the power plants in the Geysers. Instead, an estimate from the net energy generation from those power plants is used. Using these estimates, the net undeveloped geothermal resource potential can be calculated.

Finally, we apply the protected area layer for geothermal to screen out those geothermal fields that lie entirely within a protected area. The protected area layer is compiled from public and private lands that have special designations prohibiting or not aligning with energy development.

This layer is featured in the CEC 2023 Land-Use Screens for Electric System Planning data viewer.

For more information about this layer and its use in electric system planning, please refer to the Land Use Screens Staff Report in the CEC Energy Planning Library.

Change Log:

Version 1.1 (January 18, 2024)

• ProtectedArea_Exclusion field was updated to correct for the changes to the Protected Area Layer. A Development Focus Area on Bureau of Land Management (BLM) land that overlays the Coso Hot Springs allows its resource potential to be considered in the statewide estimate.

Data Dictionary:

Total_MWe_Mean: The estimated resource potential from each geothermal field. All geothermal fields, except for Truckhaven, was given an estimate by Williams et al. 2008. If more than one point resource intersects (within 2km of) the field, the sum of the individual geothermal systems was used to estimate the magnitude of the resource coming from the entire geothermal field. Estimates are given in MW.

Total_QFER_NameplateCapacity: The total nameplate capacities of all generators in operation as of 2021 that intersects (within 2 km of) a geothermal field. The resource potential already in use for the Geysers is determined by Lovekin et al. 2004. Estimates are given in MW.

ProtectedArea_Exclusion: Binary value representing whether a field is excluded by the land-use screen or not. Fields that are excluded have a value of 1; those that aren’t have a value of 0.

NetUndevelopedRP: The net undeveloped resource potential for each geothermal field. This field is determined by subtracting the total resource potential in use (Total_QFER_NameplateCapacity) from the total estimated resource potential (Total_MWe_Mean). Estimates are given in MW.

Acres_GeothermalField: This is the geodesic acreage of each geothermal field. Values are reported in International Acres using a NAD 1983 California (Teale) Albers (Meters) projection.

References:

1. Geothermal Map of California, S-11. California Department of Conservation, 2002. https://www.conservation.ca.gov/calgem/geothermal/maps/Pages/index.aspx
2. CalGEM Field Admin Boundaries, 2020. https://gis.conservation.ca.gov/server/rest/services/CalGEM/Admin_Bounds/MapServer
   
3. California BLM State Office GIS Department, California BLM Verified and Potential Geothermal Leases in California, 2010. https://databasin.org/datasets/5ec77a1438ab4402bf09ef9bfd7f04d9/
   
4. Williams, Colin F., Reed, Marshall J., Mariner, Robert H., DeAngelo, Jacob, Galanis, S. Peter, Jr. 2008. "Assessment of moderate- and high-temperature geothermal resources of the United States: U.S. Geological Survey Fact Sheet 2008-3082." 4 p. https://certmapper.cr.usgs.gov/server/rest/services/geothermal/westus_favoribility_systems/MapServer/0
5. El Centro Field Office, Bureau of Land Management (2007). Final Environmental Impact Statement for the Truckhaven Geothermal Leasing Area (Publication Index Number: BLM/CA/ES-2007-017+3200). United States Department of the Interior Bureau of Land Management.
6. Lovekin, James W., Subir K. Sanyal, Christopher W. Klein. 2004. “New Geothermal Site Identification and Qualification.” Richmond, California:

This dataset contains several memos describing geothermal targets outlined by Flint personnel in Colorado. Phase 1 involved an ASTER and LANDSAT thermal infrared imagery assessment conducted by CIRES of the University of Colorado, which identified areas of warm ground that might indicate geothermal heating. CIRES used the thermal ground anomalies, together with other GIS layers, to come up with a set of areas ("polygons") having high geothermal potential.

This was followed by a "ground truthing" or site assessment by Geothermal Development Associates of Reno Nevada, during the summer and fall of 2011. Of the many areas targeted and visited, several stood out for their overall geothermal potential.

In the first memo, "Colorado Targets", GDA's Richard "Rick" Zehner describes the geothermal geology of the following properties, which were deemed to have the highest geothermal potential: 1. Routt (aka Strawberry Park) Hot Springs in Routt County; 2. Rico area, Delores County; 3. Pagosa Springs, Archuleta County; 4. San Luis Valley, Alamosa and Conejos Counties; 5. Lemon Hot Springs, San Miguel County

The second memo, "Comments on Rick's Report", from CIRES investigators, is a critical evaluation of Zehner's memo, in relation to CIRES' satellite thermal anomaly maps.

The third memo, "Penrose Area" is a detailed description of preliminary investigations into the geothermal potential of that area in Fremont County.

This dataset is a compilation of existing and new publicly-available geoscience data that were used to conduct a geothermal play fairway analysis (PFA) in north-western Argentina in the Jujuy and Salta provinces. The 'Model_Input_Datasets' folder includes the original ArcGIS shapefiles and rasters that were used to build the geological favorability models for heat, permeability and fluid. Detailed metadata for each dataset (e.g. provenance; use constraints etc.) can be viewed for each file in ArcCatalog. The 'Area_One' shapefile represents the study area boundary that was used to define the processing extent for the PFA models. The favorability models were built using the ModelBuilder tool in ESRI ArcGIS (this model was run using ESRI ArcMap version 10.7.1). The 'Python_Scripts' folder includes python scripts for building each of the four favorability models (heat, permeability, fluid and overall geothermal favorability). The 'ProcessingNotes_for_PFA_model_development' file (.xlsx or .pdf format) includes a description of the various steps used to weight individual data attribute fields, data layers themselves, and overall model development. This file complements the python scripts.

This dataset accompanies a paper submitted to Geothermics by Lindsey et al., 2021, 'Geothermal play fairway analysis in north-western Argentina'.

This submission contains geospatial (GIS) data on water table gradient and depth, subcrop gravity and magnetic, propsectivity, heat flow, physiographic, boron and BHT for the Southwest New Mexico Geothermal Play Fairway Analysis by LANL Earth & Environmental Sciences. GIS data is in ArcGIS map package format.

In the recent years the use of geothermal energy through implementation of low enthalpy geothermal production systems for both electricity and heating have been growing rapidly in north-western Europe. Geothermal exploration and production takes largely place in sedimentary basins at depths from 2 to 5 km. Geothermal activities can take considerable advantage of a wealth of existing oil and gas data. To governmental bodies, such as geological surveys, it is a major challenge to put relevant oil and gas data and derived subsurface structural, temperature, and flow property models available to the geothermal community and to facilitate in quantitative assessment of geothermal potential of targeted areas, for both heat and electricity production (EGS) . In order to face this challenge, TNO has developed a public web-based 3D information system connected to a geothermal performance assessment tool. The public information system (thermoGIS) includes high resolution 3D geological models covering the complete onshore of the Netherlands, outlining key geothermal reservoirs and allowing to assess relevant parameters and underlying uncertainties therein. State-of-the-art 3D modeling techniques have been used and developed to obtain the reservoir structures, flow properties and temperatures, using constraints from over a thousand deep wells, and detailed subsurface mapping from 3D and 2D seismic. Users can obtain key reservoir parameters, and underlying uncertainties at any location and for any reservoir. In an automated workflow these parameters are fed into the performance assessment tool, in order to asses the probability of success to meet minimum requirements on key performance indicators such as Coefficient of Performance (COP), power produced, and Unit Technical Cost (UTC). The use of the ThermoGIS will aid exploration business decisions and Dutch governmental institutions, law makers and insurance companies.

This file contains file geodatabases of the Mount St. Helens seismic zone (MSHSZ), Wind River valley (WRV) and Mount Baker (MB) geothermal play-fairway sites in the Washington Cascades. The geodatabases include input data (feature classes) and output rasters (generated from modeling and interpolation) from the geothermal play-fairway in Washington State, USA. These data were gathered and modeled to provide an estimate of the heat and permeability potential within the play-fairways based on: mapped volcanic vents, hot springs and fumaroles, geothermometry, intrusive rocks, temperature-gradient wells, slip tendency, dilation tendency, displacement, displacement gradient, max coulomb shear stress, sigma 3, maximum shear strain rate, and dilational strain rate at 200m and 3 km depth. In addition this file contains layer files for each of the output rasters. For details on the areas of interest please see the 'WA_State_Play_Fairway_Phase_1_Technical_Report' in the download package.

This submission also includes a file with the geothermal favorability of the Washington Cascade Range based off of an earlier statewide assessment. Additionally, within this file there are the maximum shear and dilational strain rate rasters for all of Washington State.

This layer identifies locations and phases for geothermal well sites across West Chester University. | Publication Date: April 2018, Last Updated: April 2018 | West Chester University’s Geography and Planning department upholds its mission to provide spatial analysis expertise in order to solve many problems regarding spatial applications that facilitates research, sustainability goals, planning and communal integration.This dataset was curated by West Chester University’s Department of Geography and Planning and presented using West Chester University's Open GIS Data

Shallow Geothermal Energy Potential Map consists of a spatial and borehole data base. The Serial Shallow Geothermal Energy Potential Map at a scale of 1:50,000 will be the beginning of the estimation of shallow geothermal resources in terms of the application of optimal technologies and estimation of Poland's energy resources. In the pilot project, carried out between 2017 and 2022, maps were made in the grid of the Detailed Geological Map of Poland at a scale of 1:50 000 and in the grid of the topographic map at a scale of 1:10 000 for areas of urban agglomerations. The analysis covered areas: • in the scale of 1:10 000: o Warsaw (90 sheets), o Wrocław (48 sheets); • in the scale of 1:50 000: o Jelenia Góra region (1 sheet), o Bielsko-Biała region (3 sheets) o Rabka-Zdrój region (2 sheets) o Krynica-Zdrój region (3 sheets). Currently, the project is carried out at a scale of 1:50 000 and covers the following areas: • Gdańsk region (6 sheets), • Supraśl region (2 sheets), • Mielnik region (2 sheets), • Kazimierz Dolny region (4 sheets), • Jelenia Góra region (Sudety Mountains) (5 sheets). The following maps were made on the basis of the study entitled ‘Instruction for making shallow geothermal energy potential and environmental conditions Maps' : • thermal conductivity maps λ [W/m*K] at depths of 40, 70, 100 and 130 m below ground level; • unit heat output maps qv [W/m] for 1800 h of heat pump operation per year at depths of 40, 70, 100 and 130 m below ground level; • unit heat output maps qv [W/m] for 2100 h of heat pump operation per year at a depth of 40, 70, 100 and 130 m below ground level; • Borehole heat exchangers feasibility map according to environmental conditions. To supplement the shallowe geothermal potential maps, were created maps showing the locations of potential geoenvironmental conflicts, where the drilling of boreholes for ground source heat exchangers (GHE), and thus the installation of ground source heat pumps (GHP), is generally possible, where additional information is required or it is generally not possible. Such maps are helpful for the efficient design of individual GHP installations as well as for the determination, of the extent to which low-temperature geothermal energy can meet the heat demand of a region or urban agglomeration for example by local authorities. The maps are complemented by a nationwide GIS database for shallowe geothermal, which will include geological documentations for the purposes of obtaining geothermal heat, collected in the resources of the Central Geological Archives of Polish Geological Institute. In addition, the effective thermal conductivity leff [W/m*K] in the 0÷100m depth interval was determined for selected boreholes from the Central Hydrogeological Databank (deeper than 100 m). On the base of it point map of shallowe geothermal potential for the area of whole Poland was created. The parameterisation was carried out using the thermal conductivity conversion tables from the PORT PC Guidelines, 2013. In the pilot project, 14 011 boreholes were calculated from the Central Hydrogeological Databank. In the current project, the parameterisation will be carried out on the basis of thermal conductivity measurements (both in the fild and in the laboratory) the thermal conductivity conversion tables from the PORT PC Guidelines, 2021.

These are map packages used to visualize geochemical particle-tracking analysis results in ArcGIS. It includes individual map packages for several regions of New Mexico including: Acoma, Rincon, Gila, Las Cruces, Socorro and Truth or Consequences.

The main objective of the undertaking is the long-term support by PIG-PIB for the development of shallow geothermal installations - as one of the renewable energies - using the Earth's natural heat in the form of ground heat pump installations and thus the involvement of PIG-PIB in the process of improving air purity in Poland, by providing specialist planning tools for the quantitative and qualitative assessment of geological and thermal conditions. The aim of the research is to create GIS information layers including: Potential of Shallow Geothermal Energy Maps, Maps of the possibility of constructing borehole heat exchangers taking into account environmental conditions. The maps will be supplemented by a nationwide GIS database for low-temperature geothermal energy (BDGNT) and a layer created on the basis of the analysis of boreholes from the CBDH database in accordance with the PORT PC guidelines from 2013: thermal conductivity λ [W/m*K] to a depth of 100 m below ground level.

The Engineered Geothermal System (EGS) Exploration Methodology Project is developing an exploration approach for EGS through the integration of geoscientific data. The Project chose the Dixie Valley Geothermal System in Nevada as a field laboratory site for methodology calibration purposes because, in the public domain, it is a highly characterized geothermal system in the Basin and Range with a considerable amount of geoscience and most importantly, well data. The overall project area is 2500km2 with the Calibration Area (Dixie Valley Geothermal Wellfield) being about 170km2. The project was subdivided into five tasks (1) collect and assess the existing public domain geoscience data; (2) design and populate a GIS database; (3) develop a baseline (existing data) geothermal conceptual model, evaluate geostatistical relationships, and generate baseline, coupled EGS favorability/trust maps from +1km above sea level (asl) to -4km asl for the Calibration Area at 0.5km intervals to identify EGS drilling targets at a scale of 5km x 5km; (4) collect new geophysical and geochemical data, and (5) repeat Task 3 for the enhanced (baseline + new ) data. Favorability maps were based on the integrated assessment of the three critical EGS exploration parameters of interest: rock type, temperature and stress. A complimentary trust map was generated to compliment the favorability maps to graphically illustrate the cumulative confidence in the data used in the favorability mapping. The Final Scientific Report (FSR) is submitted in two parts with Part I describing the results of project Tasks 1 through 3 and Part II covering the results of project Tasks 4 through 5 plus answering nine questions posed in the proposal for the overall project. FSR Part I presents (1) an assessment of the readily available public domain data and some proprietary data provided by Terra-Gen Power, LLC, (2) a re-interpretation of these data as required, (3) an exploratory geostatistical data analysis, (4) the baseline geothermal conceptual model, and (5) the EGS favorability/trust mapping. The conceptual model presented applies to both the hydrothermal system and EGS in the Dixie Valley region. FSR Part II presents (1) 278 new gravity stations; (2) enhanced gravity-magnetic modeling; (3) 42 new ambient seismic noise survey stations; (4) an integration of the new seismic noise data with a regional seismic network; (5) a new methodology and approach to interpret this data; (5) a novel method to predict rock type and temperature based on the newly interpreted data; (6) 70 new magnetotelluric (MT) stations; (7) an integrated interpretation of the enhanced MT data set; (8) the results of a 308 station soil CO2 gas survey; (9) new conductive thermal modeling in the project area; (10) new convective modeling in the Calibration Area; (11) pseudo-convective modeling in the Calibration Area; (12) enhanced data implications and qualitative geoscience correlations at three scales (a) Regional, (b) Project, and (c) Calibration Area; (13) quantitative geostatistical exploratory data analysis; and (14) responses to nine questions posed in the proposal for this investigation. Enhanced favorability/trust maps were not generated because there was not a sufficient amount of new, fully-vetted (see below) rock type, temperature, and stress data. The enhanced seismic data did generate a new method to infer rock type and temperature. However, in the opinion of the Principal Investigator for this project, this new methodology needs to be tested and evaluated at other sites in the Basin and Range before it is used to generate the referenced maps. As in the baseline conceptual model, the enhanced findings can be applied to both the hydrothermal system and EGS in the Dixie Valley region.

This submission includes the final project report of the Snake River Plain Play Fairway Analysis project as well as a separate appendix for the final report. The final report outlines the application of Play Fairway Analysis (PFA) to geothermal exploration, specifically within the Snake River Plain volcanic province. The goals of the report are to use PFA to lower risk and cost of geothermal exploration and stimulate development of geothermal power resources in Idaho. Further use of this report could include the application of PFA for geothermal exploration throughout the geothermal industry. The report utilizes ArcGIS and Python for data analysis which used to developed a systematic workflow to automate data analysis. The appendix for the report includes ArcGIS maps and data compilation information regarding the report.

Active Management of Integrated Geothermal-CO2 Storage Reservoirs in Sedimentary Formations: An Approach to Improve Energy Recovery and Mitigate Risk: FY1 Final Report The purpose of phase 1 is to determine the feasibility of integrating geologic CO2 storage (GCS) with geothermal energy production. Phase 1 includes reservoir analyses to determine injector/producer well schemes that balance the generation of economically useful flow rates at the producers with the need to manage reservoir overpressure to reduce the risks associated with overpressure, such as induced seismicity and CO2 leakage to overlying aquifers. Based on a range of well schemes, techno-economic analyses of the levelized cost of electricity (LCOE) are conducted to determine the economic benefits of integrating GCS with geothermal energy production. In addition to considering CO2 injection, reservoir analyses are conducted for nitrogen (N2) injection to investigate the potential benefits of incorporating N2 injection with integrated geothermal-GCS, as well as the use of N2 injection as a potential pressure-support and working-fluid option. Phase 1 includes preliminary environmental risk assessments of integrated geothermal-GCS, with the focus on managing reservoir overpressure. Phase 1 also includes an economic survey of pipeline costs, which will be applied in Phase 2 to the analysis of CO2 conveyance costs for techno-economics analyses of integrated geothermal-GCS reservoir sites. Phase 1 also includes a geospatial GIS survey of potential integrated geothermal-GCS reservoir sites, which will be used in Phase 2 to conduct sweet-spot analyses that determine where promising geothermal resources are co-located in sedimentary settings conducive to safe CO2 storage, as well as being in adequate proximity to large stationary CO2 sources.

This report is one in a series of digital maps, data files, and reports generated by the US Geological Survey (USGS) to provide geologic information for the Interior Columbia Basin Ecosystem Management Project (ICBEMP), a US Forest Service and Bureau of Land Management interagency project. The various digital maps and data files that were provided by teh USGS and that are available in this and other reports are being used in a geographic information system (GIS)-based ecosystem assessment. The assessment will include a comprehensive analysis of past, present, and future ecosystem conditions within the general area of the Columbia River Basin east of the Cascade Mountains.

There are 487 onshore oil and gas fields in California encompassing 3,392 square miles of aggregated area. The California State Water Resources Control Board (State Water Board) initiated a Regional Monitoring Program (RMP) in July 2015, intended to determine where and to what degree groundwater quality may be at potential risk to contamination related to oil and gas development activities including well stimulation, well integrity issues, produced water ponds, and underground injection. The first step in monitoring groundwater in and near oil and gas fields is to prioritize the 487 fields using consistent statewide analysis of available data that indicate potential risk of groundwater to oil and gas development. There were limited existing data on potential groundwater risk factors available for oil and gas fields across the state. During 2014-2016, the U.S. Geological Survey (USGS) extracted and compiled data from various sources, including the California Division of Oil, Gas, and Geothermal Resources (DOGGR) and the Department of Water Resources (DWR). Geospatial data from the DOGGR were used in the prioritization analysis. Dataset include geospatial data for 222,637 petroleum wells, administrative boundaries for 514 oil, gas, and geothermal fields, and boundaries for DOGGR's 6 juristictional districts. The data were downloaded from DOGGR's Geographic Information System (GIS) Mapping website at http://www.conservation.ca.gov/dog/maps. The DOGGR GIS Mapping website is periodally updated, and the datasets downloaded by the U.S. Geological Survey in 2014 may no longer be available on the DOGGR website.

Location of seismic lines carried out under DOE funded project Advanced Seismic Data Analysis Program (The Hot Pot Project). ArcGIS map package containing topographic base map, Township and Range layer, Oski BLM and private leases at time of survey, and locations, with selected shot points, of the five seismic lines.

This is a zipped ArcGIS shapefile containing faults mapped for the Tularosa Basin geothermal play fairway analysis project. The faults were interpolated from gravity and seismic (NASA area) data, and from geomorphic features on aerial photography. Field work was also done for validation of faults which had surface expressions.

The German geospatial analytics market is experiencing robust growth, projected to reach €1.30 billion in 2025 and exhibiting a Compound Annual Growth Rate (CAGR) of 11.90% from 2025 to 2033. This expansion is fueled by several key drivers. Increasing adoption of precision agriculture techniques, coupled with the need for efficient resource management in utilities and communication sectors, is significantly boosting demand. Furthermore, the defense and intelligence communities are leveraging geospatial analytics for enhanced surveillance and strategic decision-making, contributing substantially to market growth. Advancements in sensor technologies, coupled with the rise of big data and improved analytical capabilities, are enabling more sophisticated applications across various sectors. The rising adoption of cloud-based geospatial analytics platforms further enhances accessibility and affordability, driving market penetration. Government initiatives promoting digitalization and smart city projects also stimulate market growth by creating demand for advanced geospatial solutions. However, data privacy concerns and the high cost of implementation remain key restraints to market expansion. Segmentation reveals strong growth across all types of geospatial analytics (surface analysis, network analysis, geovisualization), with Agriculture, Utility & Communication, and Defense & Intelligence segments leading the end-user vertical landscape. The competitive landscape includes both global giants like Hexagon, Esri, and Bentley Systems, as well as specialized players such as Geospin and Bluesky International. These companies are strategically investing in R&D to develop advanced algorithms and integrate AI/ML capabilities into their offerings, catering to the evolving needs of their clients. The market is characterized by a mix of established players and innovative startups, leading to increased competition and a focus on delivering advanced, cost-effective solutions. The market's future trajectory suggests a continued rise, driven by technological innovation and increasing data availability, further solidifying geospatial analytics' crucial role in diverse sectors within the German economy. The forecast period of 2025-2033 promises significant expansion, particularly in sectors experiencing rapid digital transformation. Recent developments include: November 2023 - Hexagon’s Manufacturing Intelligence branch unveiled Nexus Connected Worker, a collection of manufacturing software solutions that links employees to up-to-the-minute data for informed insights and reporting on operations, maintenance, quality, and audits. The suite offers strong integration with enterprise systems and serves as a hub for digital depictions of assets, processes, and production sites to aid in real-time decision-making., October 2023 - Bentley Systems announced that Seequent, a subsidiary of Bentley specializing in subsurface technology, has agreed to purchase Flow State Solutions, a top player in geothermal simulation software. The decision strengthens Seequent's position as the top provider of subsurface software for the geothermal sector.. Key drivers for this market are: Increasing in Demand for Location Intelligence, Advancements of Big Data Analytics. Potential restraints include: Increasing in Demand for Location Intelligence, Advancements of Big Data Analytics. Notable trends are: Rollout of 5G will Boost Market Growth.