👨‍💻 Author: Azhar Saleem

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Dataset Overview

Welcome to the Google Places Comprehensive Business Dataset! This dataset has been meticulously scraped from Google Maps and presents extensive information about businesses across several countries. Each entry in the dataset provides detailed insights into business operations, location specifics, customer interactions, and much more, making it an invaluable resource for data analysts and scientists looking to explore business trends, geographic data analysis, or consumer behaviour patterns.

Key Features

• Business Details: Includes unique identifiers, names, and contact information.
• Geolocation Data: Precise latitude and longitude for pinpointing business locations on a map.
• Operational Timings: Detailed opening and closing hours for each day of the week, allowing analysis of business activity patterns.
• Customer Engagement: Data on review counts and ratings, offering insights into customer satisfaction and business popularity.
• Additional Attributes: Links to business websites, time zone information, and country-specific details enrich the dataset for comprehensive analysis.

Potential Use Cases

This dataset is ideal for a variety of analytical projects, including: - Market Analysis: Understand business distribution and popularity across different regions. - Customer Sentiment Analysis: Explore relationships between customer ratings and business characteristics. - Temporal Trend Analysis: Analyze patterns of business activity throughout the week. - Geospatial Analysis: Integrate with mapping software to visualise business distribution or cluster businesses based on location.

Dataset Structure

The dataset contains 46 columns, providing a thorough profile for each listed business. Key columns include:

• business_id: A unique Google Places identifier for each business, ensuring distinct entries.
• phone_number: The contact number associated with the business. It provides a direct means of communication.
• name: The official name of the business as listed on Google Maps.
• full_address: The complete postal address of the business, including locality and geographic details.
• latitude: The geographic latitude coordinate of the business location, useful for mapping and spatial analysis.
• longitude: The geographic longitude coordinate of the business location.
• review_count: The total number of reviews the business has received on Google Maps.
• rating: The average user rating out of 5 for the business, reflecting customer satisfaction.
• timezone: The world timezone the business is located in, important for temporal analysis.
• website: The official website URL of the business, providing further information and contact options.
• category: The category or type of service the business provides, such as restaurant, museum, etc.
• claim_status: Indicates whether the business listing has been claimed by the owner on Google Maps.
• plus_code: A sho...

A set of PYTHON programs to implement image processing of ground and aerial images by offering via graphical user interface (GUI) 1) plot-level metrics extraction through a series of algorithms for image conversion, band math, radiometric/geometric calibrations, segmentation, masking, adaptive region of interest (ROI), gridding, heatmap, and batch process, 2) GIS interface for GeoTIFF pixels to Lat/Lon, UTM conversion, read/write shapefile, Lat/Lon to ROI, grid to polygon, and 3) utility GUI functions for zooming, panning, rotation, images to video, file I/O, and histogram. Resources in this dataset:Resource Title: IMAP: Image Mapping & Analytics for Phenotyping. File Name: IMAP.zip

This study focuses on the use of citizen science and GIS tools for collecting and analyzing data on Rose Swanson Mountain in British Columbia, Canada. While several organizations collect data on wildlife habitats, trail mapping, and fire documentation on the mountain, there are few studies conducted on the area and citizen science is not being addressed. The study aims to aggregate various data sources and involve citizens in the data collection process using ArcGIS Dashboard and ArcGIS Survey 123. These GIS tools allow for the integration and analysis of different kinds of data, as well as the creation of interactive maps and surveys that can facilitate citizen engagement and data collection. The data used in the dashboard was sourced from BC Data Catalogue, Explore the Map, and iNaturalist. Results show effective citizen participation, with 1073 wildlife observations and 3043 plant observations. The dashboard provides a user-friendly interface for citizens to tailor their map extent and layers, access surveys, and obtain information on each attribute included in the pop-up by clicking. Analysis on classification of fuel types, ecological communities, endangered wildlife species presence and critical habitat, and scope of human activities can be conducted based on the distribution of data. The dashboard can provide direction for researchers to develop research or contribute to other projects in progress, as well as advocate for natural resource managers to use citizen science data. The study demonstrates the potential for GIS and citizen science to contribute to meaningful discoveries and advancements in areas.

In this course, you will learn to work within the free and open-source R environment with a specific focus on working with and analyzing geospatial data. We will cover a wide variety of data and spatial data analytics topics, and you will learn how to code in R along the way. The Introduction module provides more background info about the course and course set up. This course is designed for someone with some prior GIS knowledge. For example, you should know the basics of working with maps, map projections, and vector and raster data. You should be able to perform common spatial analysis tasks and make map layouts. If you do not have a GIS background, we would recommend checking out the West Virginia View GIScience class. We do not assume that you have any prior experience with R or with coding. So, don't worry if you haven't developed these skill sets yet. That is a major goal in this course. Background material will be provided using code examples, videos, and presentations. We have provided assignments to offer hands-on learning opportunities. Data links for the lecture modules are provided within each module while data for the assignments are linked to the assignment buttons below. Please see the sequencing document for our suggested order in which to work through the material. After completing this course you will be able to: prepare, manipulate, query, and generally work with data in R. perform data summarization, comparisons, and statistical tests. create quality graphs, map layouts, and interactive web maps to visualize data and findings. present your research, methods, results, and code as web pages to foster reproducible research. work with spatial data in R. analyze vector and raster geospatial data to answer a question with a spatial component. make spatial models and predictions using regression and machine learning. code in the R language at an intermediate level.

Map Data Platform Market Outlook

According to our latest research, the map data platform market size globally stood at USD 6.9 billion in 2024, reflecting robust expansion across diverse industry verticals. The market is experiencing a strong growth trajectory with a CAGR of 15.2% from 2025 to 2033. By the end of 2033, the global map data platform market is forecasted to reach USD 22.5 billion. This impressive growth is primarily driven by the surging demand for real-time geospatial analytics, rapid advancements in location-based services, and widespread integration of mapping technologies across sectors such as automotive, transportation, and retail.

The primary growth factor propelling the map data platform market is the increasing adoption of connected and autonomous vehicles. Automotive manufacturers are leveraging sophisticated map data platforms to enhance navigation, safety, and driver assistance features. The integration of high-definition mapping, real-time traffic updates, and advanced geocoding is critical for enabling autonomous driving and smart mobility solutions. This surge in automotive applications is further complemented by the proliferation of Internet of Things (IoT) devices, which rely on accurate geospatial data for asset tracking, fleet management, and location-based analytics. As a result, the automotive and transportation sectors are becoming significant contributors to the overall market growth, driving innovation and investment in map data platforms.

Another notable driver is the rapid expansion of location-based services (LBS) across multiple industries. Retailers, logistics companies, and government agencies are increasingly utilizing map data platforms to optimize operations, personalize customer experiences, and enhance decision-making processes. The widespread use of smartphones, coupled with advancements in mobile mapping technologies, has led to a surge in demand for real-time navigation, geofencing, and location-aware marketing. These trends are pushing platform providers to continuously innovate, offering scalable, cloud-based solutions that can handle vast volumes of geospatial data and deliver actionable insights to end-users. The convergence of artificial intelligence and big data analytics with mapping technologies is further amplifying the value proposition of map data platforms.

The evolution of smart cities and infrastructure development projects worldwide is also fueling the growth of the map data platform market. Governments and urban planners are increasingly relying on geospatial intelligence to manage resources, monitor public utilities, and enhance citizen services. The integration of mapping and visualization tools enables real-time monitoring of traffic, utilities, and public safety, supporting data-driven urban planning and sustainable development initiatives. As cities continue to invest in digital transformation, the demand for robust, scalable, and secure map data platforms is expected to accelerate, creating new opportunities for market players and stakeholders.

From a regional perspective, North America currently dominates the map data platform market, driven by the presence of leading technology companies, early adoption of advanced mapping solutions, and significant investments in autonomous vehicles and smart infrastructure. Europe follows closely, with strong growth in automotive and transportation sectors, while Asia Pacific is emerging as a high-growth region due to rapid urbanization, increasing smartphone penetration, and government initiatives supporting smart city projects. Latin America and the Middle East & Africa are also witnessing gradual adoption, supported by digital transformation efforts in retail, logistics, and public sector applications.

Component Analysis

The map data platform market by component is segmented into platform and services, each playing a distinct role in the ecosystem. The platform segment encompasses core mapping engines, geospatial data repositories, and APIs that enable developers and enterprises to integrate mapping functionalities into their applications. The rising demand for customizable and scalable platforms has led to significant investments in cloud-based mapping solutions, which offer high performance, real-time updates, and seamless integration with third-party systems. Platform providers are focusing on enhancing user experience through intuitive interfaces, advanced analytics,

This is a web map used for testing search and rescue workflows. See the SAR and First Responders Geospatial Tookit for more information. You can search for this map in Explorer for ArcGIS to view the data.

Xverum’s Point of Interest (POI) Data is a comprehensive dataset containing 230M+ verified locations across 5000 business categories. Our dataset delivers structured geographic data, business attributes, location intelligence, and mapping insights, making it an essential tool for GIS applications, market research, urban planning, and competitive analysis.

With regular updates and continuous POI discovery, Xverum ensures accurate, up-to-date information on businesses, landmarks, retail stores, and more. Delivered in bulk to S3 Bucket and cloud storage, our dataset integrates seamlessly into mapping, geographic information systems, and analytics platforms.

🔥 Key Features:

Extensive POI Coverage: ✅ 230M+ Points of Interest worldwide, covering 5000 business categories. ✅ Includes retail stores, restaurants, corporate offices, landmarks, and service providers.

Geographic & Location Intelligence Data: ✅ Latitude & longitude coordinates for mapping and navigation applications. ✅ Geographic classification, including country, state, city, and postal code. ✅ Business status tracking – Open, temporarily closed, or permanently closed.

Continuous Discovery & Regular Updates: ✅ New POIs continuously added through discovery processes. ✅ Regular updates ensure data accuracy, reflecting new openings and closures.

Rich Business Insights: ✅ Detailed business attributes, including company name, category, and subcategories. ✅ Contact details, including phone number and website (if available). ✅ Consumer review insights, including rating distribution and total number of reviews (additional feature). ✅ Operating hours where available.

Ideal for Mapping & Location Analytics: ✅ Supports geospatial analysis & GIS applications. ✅ Enhances mapping & navigation solutions with structured POI data. ✅ Provides location intelligence for site selection & business expansion strategies.

Bulk Data Delivery (NO API): ✅ Delivered in bulk via S3 Bucket or cloud storage. ✅ Available in structured format (.json) for seamless integration.

🏆Primary Use Cases:

Mapping & Geographic Analysis: 🔹 Power GIS platforms & navigation systems with precise POI data. 🔹 Enhance digital maps with accurate business locations & categories.

Retail Expansion & Market Research: 🔹 Identify key business locations & competitors for market analysis. 🔹 Assess brand presence across different industries & geographies.

Business Intelligence & Competitive Analysis: 🔹 Benchmark competitor locations & regional business density. 🔹 Analyze market trends through POI growth & closure tracking.

Smart City & Urban Planning: 🔹 Support public infrastructure projects with accurate POI data. 🔹 Improve accessibility & zoning decisions for government & businesses.

💡 Why Choose Xverum’s POI Data?

• 230M+ Verified POI Records – One of the largest & most detailed location datasets available.
• Global Coverage – POI data from 249+ countries, covering all major business sectors.
• Regular Updates – Ensuring accurate tracking of business openings & closures.
• Comprehensive Geographic & Business Data – Coordinates, addresses, categories, and more.
• Bulk Dataset Delivery – S3 Bucket & cloud storage delivery for full dataset access.
• 100% Compliant – Ethically sourced, privacy-compliant data.

Access Xverum’s 230M+ POI dataset for mapping, geographic analysis, and location intelligence. Request a free sample or contact us to customize your dataset today!

Map Data Services Market Outlook

According to our latest research, the global map data services market size reached USD 7.8 billion in 2024, reflecting robust momentum driven by the proliferation of location-based technologies and digital transformation across industries. The market is poised for sustained expansion, projected to attain a value of USD 18.9 billion by 2033, growing at a healthy CAGR of 10.3% during the forecast period. This growth is primarily fueled by increasing demand for real-time geospatial intelligence, the integration of Internet of Things (IoT) with mapping platforms, and the rising adoption of advanced analytics for business and urban planning solutions.

The surge in demand for accurate and real-time geographic information systems (GIS) is a key driver for the map data services market. Organizations across transportation, logistics, and government sectors are increasingly leveraging map data services for efficient route optimization, fleet management, and disaster response. The expansion of smart cities and the need for intelligent urban infrastructure have led to a significant uptick in the use of data visualization and analytics tools. Additionally, the proliferation of connected devices and the integration of artificial intelligence (AI) in mapping platforms are enabling enhanced predictive analytics and automation, further propelling market growth. The push towards digital transformation and the emergence of Industry 4.0 have made map data services indispensable for enterprises seeking to optimize operations and gain actionable insights from spatial data.

Another critical growth factor is the widespread adoption of location-based services (LBS) in consumer applications. With the increasing penetration of smartphones and mobile internet, end-users are demanding more personalized and context-aware services, ranging from navigation and ride-hailing to targeted marketing and retail analytics. This trend has prompted businesses to invest heavily in data hosting and mapping capabilities to deliver seamless user experiences. Moreover, advancements in cloud computing have democratized access to sophisticated mapping tools, enabling small and medium enterprises to harness the power of geospatial data without significant upfront investments. The continued evolution of mapping APIs and integration with third-party platforms is also opening new avenues for innovation, particularly in retail, utilities, and telecom sectors.

The market is also witnessing a paradigm shift towards cloud-based deployment models, which offer scalability, cost-effectiveness, and ease of integration with existing IT infrastructure. Cloud-based map data services are gaining traction among enterprises seeking to manage large volumes of spatial data, facilitate real-time collaboration, and ensure business continuity. This shift is further accelerated by the growing need for remote accessibility and the increasing frequency of natural disasters, which demand agile and resilient mapping solutions for disaster management and urban planning. The convergence of big data analytics, machine learning, and cloud technologies is expected to drive the next wave of innovation in the map data services market, enabling organizations to extract deeper insights and make data-driven decisions with greater precision.

From a regional perspective, North America remains the largest market for map data services, owing to the presence of leading technology providers, high digital adoption rates, and significant investments in smart infrastructure. Asia Pacific, however, is emerging as the fastest-growing region, driven by rapid urbanization, government initiatives for smart cities, and the proliferation of mobile technologies. Europe continues to exhibit steady growth, supported by robust regulatory frameworks and increased focus on sustainable urban development. Meanwhile, Latin America and the Middle East & Africa are gradually catching up, fueled by infrastructure modernization and the expansion of digital services. The regional landscape underscores the global nature of the map data services market, with each geography presenting unique opportunities and challenges.

Service Type Analysis

The map data services market is segmented by service type into data hosting, data mapping, data visualization, data analytics, and others. Data hosting has become a fundamental pillar, as organizations increasingly require secure, scalable, and reliable platforms to store and manage vast volumes

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

GIS project files and imagery data required to complete the Introduction to Planetary Image Analysis and Geologic Mapping in ArcGIS Pro tutorial. These data cover the area in and around Jezero crater, Mars.

MAP Data Authoring and Validation Market Outlook

According to our latest research, the global MAP Data Authoring and Validation market size in 2024 is valued at USD 4.28 billion, reflecting the rapidly increasing demand for accurate mapping data across multiple industries. The market is experiencing a robust growth trajectory, with a recorded CAGR of 13.2% from 2025 to 2033. By 2033, the MAP Data Authoring and Validation market is forecasted to reach an impressive USD 12.42 billion. This growth is primarily driven by the proliferation of autonomous vehicles, smart city initiatives, and the critical importance of precise geospatial data in modern applications, as per our latest research findings.

The MAP Data Authoring and Validation market is witnessing exponential expansion due to the escalating integration of advanced mapping solutions in the automotive and transportation sectors. The surge in demand for autonomous vehicles and connected mobility solutions necessitates highly accurate and real-time map data, which, in turn, propels the adoption of authoring and validation tools. Furthermore, the evolution of smart cities and IoT-enabled urban infrastructure is generating an unprecedented need for reliable geospatial data to optimize city planning, utility management, and emergency response systems. These factors collectively contribute to the sustained growth of the market, as organizations increasingly prioritize data accuracy, consistency, and validation to enhance operational efficiency and decision-making processes.

Another significant growth factor for the MAP Data Authoring and Validation market is the rapid digital transformation across industries, particularly in logistics, utilities, and government sectors. The shift towards digital workflows and automation, coupled with regulatory mandates for accurate geospatial information, is compelling enterprises to invest in sophisticated software and services for map data creation and validation. Additionally, the rise of location-based services, mobile mapping applications, and real-time navigation solutions is accelerating the market’s momentum. The growing adoption of cloud-based platforms further amplifies accessibility and scalability, enabling organizations to manage large volumes of spatial data efficiently while ensuring compliance with evolving data standards.

Technological advancements are also playing a pivotal role in driving the MAP Data Authoring and Validation market. The integration of artificial intelligence, machine learning, and big data analytics into mapping solutions is enhancing the precision, automation, and speed of data authoring and validation processes. These technologies facilitate the rapid detection and correction of errors, automate data enrichment, and enable predictive analytics for proactive decision-making. Moreover, the increasing interoperability of mapping platforms with other enterprise systems, such as ERP and GIS, is unlocking new opportunities for cross-functional data utilization and business intelligence. As industries continue to embrace digital innovation, the demand for advanced MAP Data Authoring and Validation solutions is expected to accelerate further.

From a regional perspective, the MAP Data Authoring and Validation market exhibits robust growth across North America, Europe, and Asia Pacific, with North America currently holding the largest market share. The region’s dominance is attributed to the early adoption of advanced mapping technologies, strong presence of automotive and technology giants, and significant investments in smart infrastructure projects. Europe follows closely, driven by stringent regulatory frameworks and a thriving automotive sector. Meanwhile, Asia Pacific is emerging as the fastest-growing region, fueled by rapid urbanization, expanding transportation networks, and government-led digitalization initiatives. Latin America and the Middle East & Africa are also witnessing steady growth, albeit at a more measured pace, as regional players increase their focus on geospatial data management and smart city development.

The Data Mapping Software market is booming, projected to reach $643.52 million by 2033 with a 7.8% CAGR. Discover key trends, leading companies (Dell Boomi, Informatica, IBM), and regional insights in this comprehensive market analysis. Explore cloud-based vs. on-premise solutions & unlock the power of efficient data integration.

This collection contains supplementary information for the manuscript “Genetic mapping and QTL analysis for peanut smut resistance”, which reports the genetic map and quantitative trait loci associated with resistance to peanut smut, a disease caused by the fungus Thecaphora frezii. The information includes genotyping data of a 103 recombinant inbred line (RIL) population {susceptible Arachis hypogaea subsp.hypogaea × resistant synthetic amphidiploid [(A. correntina × A. cardenasii) × A. batizocoi]⁴ˣ} and parental lines, generated with the Axiom_Arachis2 SNP array. For more information about this dataset contact: Renee Arias: Renee.Arias@usda.gov or Alicia Massa: Alicia.Massa@usda.gov Resources in this dataset:Resource Title: RILs of the mapping population. File Name: RIL_population.JPGResource Title: Data Dictionary. File Name: readme.txtResource Title: Supplementary Data 1: SNP genotypes as called by the Axiom Analysis Suite File name: SD01_RILs_SNPs_whole_Axiom_Arachis2.txt . File Name: SD01_RILs_SNPs_whole_Axiom_Arachis2.txt.zipResource Description: Supplementary Data 1: SNP genotypes as called by the Axiom Analysis Suite File name: SD01_RILs_SNPs_whole_Axiom_Arachis2.txt Single nucleotide polymorphism genotyping of a 103 RIL population and parental lines generated with the Arachis_Axiom2 SNP array. Resource Software Recommended: Axiom_Arachis2,url: https://www.thermofisher.com/us/en/home/life-science/microarray-analysis/microarray-analysis-instruments-software-services/microarray-analysis-software/axiom-analysis-suite.html Resource Title: Supplementary Data 2: Genotyping calls in VCF format File name: SD02_RILs_SNPs_whole_Axiom_Arachis2.vcf. File Name: SD02_core_RILs_SNPs_AxiomArachis2.vcf.zipResource Description: Supplementary Data 2: Genotyping calls in VCF format File name: SD02_RILs_SNPs_whole_Axiom_Arachis2.vcf Core SNP set used to characterize the RIL population and progenitors.

The global Business Mapping Software market is poised for significant expansion, projected to reach an estimated USD 5,000 million by 2025 and growing at a compound annual growth rate (CAGR) of XX% through 2033. This robust growth is underpinned by the increasing demand for advanced data visualization and spatial analytics across diverse industries. Key drivers include the burgeoning need for optimized logistics and supply chain management, enhanced customer relationship management (CRM) through location intelligence, and improved operational efficiency via dynamic route planning and site selection. The manufacturing sector, in particular, leverages business mapping software for factory layout optimization, resource allocation, and risk assessment in global operations. Similarly, the automotive industry is integrating these solutions for advanced navigation systems, fleet management, and the development of autonomous driving technologies, which heavily rely on precise geospatial data. The financial services sector is also a significant adopter, utilizing mapping software for fraud detection, risk analysis, and identifying optimal branch locations. The market's trajectory is further bolstered by emerging trends such as the widespread adoption of cloud-based solutions, offering greater scalability, accessibility, and cost-effectiveness compared to traditional on-premise installations. This shift democratizes access to sophisticated mapping tools for small and medium-sized enterprises. The integration of AI and machine learning with business mapping platforms is another transformative trend, enabling predictive analytics, pattern recognition, and more intelligent decision-making. However, the market faces certain restraints, including the initial high cost of implementation for some advanced features, the need for specialized skills to leverage the full potential of these tools, and concerns around data privacy and security, especially when dealing with sensitive customer or operational information. Despite these challenges, the continuous innovation and increasing integration of geospatial capabilities into core business processes are expected to drive sustained market growth and adoption across a wide spectrum of industries. Here's a comprehensive report description for Business Mapping Software, incorporating all your specified elements:

The booming drone imagery services market is projected to reach $15.2 billion by 2033, with a 15% CAGR. This comprehensive analysis explores market drivers, trends, restraints, and key players, offering insights into this rapidly expanding sector. Learn about applications in agriculture, construction, and more.

The global Data Asset Map System market reached a value of USD XXX million in 2025 and is expected to expand at a CAGR of XX% during the forecast period, reaching a value of USD XXX million by 2033. The growth of the market is driven by the increasing adoption of data governance solutions, the growing need for data analytics, and the increasing complexity of data management. The market is segmented based on type (cloud-based, local deployment), application (data governance, intelligent analytics engine), and region (North America, South America, Europe, Middle East & Africa, Asia Pacific). The cloud-based segment is expected to dominate the market during the forecast period due to its flexibility, scalability, and cost-effectiveness. The data governance segment is expected to be the largest application segment due to the increasing need for data governance solutions to manage and protect data assets. The North America region is expected to be the largest regional market due to the presence of a large number of data-driven organizations and the early adoption of data management solutions. The global data asset map system market is estimated to reach a valuation of USD 1,645.6 million by 2026, expanding at a CAGR of 30.5% over the forecast period. The surging demand for effective data management, the advent of AI and machine learning, and the increasing adoption of cloud-based solutions are some of the key factors driving market growth.

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Geographic Information System Analytics Market Size 2024-2028

The geographic information system analytics market size is forecast to increase by USD 12 billion at a CAGR of 12.41% between 2023 and 2028.

The GIS Analytics Market analysis is experiencing significant growth, driven by the increasing need for efficient land management and emerging methods in data collection and generation. The defense industry's reliance on geospatial technology for situational awareness and real-time location monitoring is a major factor fueling market expansion. Additionally, the oil and gas industry's adoption of GIS for resource exploration and management is a key trend. Building Information Modeling (BIM) and smart city initiatives are also contributing to market growth, as they require multiple layered maps for effective planning and implementation. The Internet of Things (IoT) and Software as a Service (SaaS) are transforming GIS analytics by enabling real-time data processing and analysis.
Augmented reality is another emerging trend, as it enhances the user experience and provides valuable insights through visual overlays. Overall, heavy investments are required for setting up GIS stations and accessing data sources, making this a promising market for technology innovators and investors alike.

What will be the Size of the GIS Analytics Market during the forecast period?

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The geographic information system analytics market encompasses various industries, including government sectors, agriculture, and infrastructure development. Smart city projects, building information modeling, and infrastructure development are key areas driving market growth. Spatial data plays a crucial role in sectors such as transportation, mining, and oil and gas. Cloud technology is transforming GIS analytics by enabling real-time data access and analysis. Startups are disrupting traditional GIS markets with innovative location-based services and smart city planning solutions. Infrastructure development in sectors like construction and green buildings relies on modern GIS solutions for efficient planning and management. Smart utilities and telematics navigation are also leveraging GIS analytics for improved operational efficiency.
GIS technology is essential for zoning and land use management, enabling data-driven decision-making. Smart public works and urban planning projects utilize mapping and geospatial technology for effective implementation. Surveying is another sector that benefits from advanced GIS solutions. Overall, the GIS analytics market is evolving, with a focus on providing actionable insights to businesses and organizations.

How is this Geographic Information System Analytics Industry segmented?

The geographic information system analytics industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

End-user

  Retail and Real Estate
  Government
  Utilities
  Telecom
  Manufacturing and Automotive
  Agriculture
  Construction
  Mining
  Transportation
  Healthcare
  Defense and Intelligence
  Energy
  Education and Research
  BFSI


Components

  Software
  Services


Deployment Modes

  On-Premises
  Cloud-Based


Applications

  Urban and Regional Planning
  Disaster Management
  Environmental Monitoring Asset Management
  Surveying and Mapping
  Location-Based Services
  Geospatial Business Intelligence
  Natural Resource Management


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    UK


  APAC

    China
    India
    South Korea


  Middle East and Africa

    UAE


  South America

    Brazil


  Rest of World

By End-user Insights

The retail and real estate segment is estimated to witness significant growth during the forecast period.

The GIS analytics market analysis is witnessing significant growth due to the increasing demand for advanced technologies in various industries. In the retail sector, for instance, retailers are utilizing GIS analytics to gain a competitive edge by analyzing customer demographics and buying patterns through real-time location monitoring and multiple layered maps. The retail industry's success relies heavily on these insights for effective marketing strategies. Moreover, the defense industries are integrating GIS analytics into their operations for infrastructure development, permitting, and public safety. Building Information Modeling (BIM) and 4D GIS software are increasingly being adopted for construction project workflows, while urban planning and designing require geospatial data for smart city planning and site selection.

The oil and gas industry is leveraging satellite imaging and IoT devices for land acquisition and mining operations. In the public sector, gover

FlowMapper.org is a web-based framework for automated production and design of origin-destination flow maps. FlowMapper has four major features that contribute to the advancement of existing flow mapping systems. First, users can upload and process their own data to design and share customized flow maps. The ability to save data, cartographic design and map elements in a project file allows users to easily share their data and/or cartographic design with others. Second, users can generate customized flow symbols to support different flow map reading tasks such as comparing flow magnitudes and directions and identifying flow and location clusters that are strongly connected with each other. Third, FlowMapper supports supplementary layers such as node symbols, choropleth, and base maps to contextualize flow patterns with location references and characteristics. Finally, the web-based architecture of FlowMapper supports server-side computational capabilities to process and normalize large flow data and reveal natural patterns of flows.

Supporting material for the article "Smart Grids Data Analysis: A Systematic Mapping Study" accepted for publication in IEEE Transaction of Industrial Informatics journal. In this material, you can find the list with references of the 359 papers included.The review includes 359 papers, initially 267 papers were reviewed, and a 2nd round increased the number. Additional diagrams to those included in the paper refer to this first round. After the paper was reviewed, new papers from 2018-2019 were added (92). The final outcome of the review is a total of 359 articles (2007-2019). Included files:------------------+ SMS-PapersList.pdf: list of included papes in the SMS with the index used in the article;+ SMS-PapersList-Small.pdf: same list, but with smaller font (less pages) + SMS-Mined-Scopus-IEEE-ACM-WoS-SpringerLink-ScienceDirect.zip: bib files from the 2129 articles mined from the digital repositories at the beginning of the SMS process;+ SMS-Filtered-267-bib.zip: bib files from the 267 SMS articles with metadata about the SMS categories (using JabRef version 2.10b2);+ SMS-Abstracts-267papers.zip: abstracts from the 267 SMS articles;+ SMS-2018-2019-bib-Addendum.zip: contains an addendum of articles (92) in bib format that were added after the paper was reviewed to include articles from 2018-2019.+ SMS-Top-Terms-Bigrams-Trigrams-csv.zip: csv files with the top terms, bigrams, trigrams from all the categories;+ SMS-source.zip: R source code for bubble-plots and for text-mining (environment used: RStudio 1.1.383, R version 3.4.4 (2018-03-15) platform x86_64-pc-linux-gnu, Ubuntu 14.04 kernel 3.13.0-153);+ SMS-HiRes-Images.zip: high resolution figures;+ SMS-top-trigrams.png, SMS-top-bigrams.png, SMS-top-terms.png: graphics for all the top terms in the abstracts;