18 datasets found
  1. House Sales in Ontario

    • kaggle.com
    Updated Oct 7, 2016
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    Mahdy Nabaee (2016). House Sales in Ontario [Dataset]. https://www.kaggle.com/mnabaee/ontarioproperties/activity
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Oct 7, 2016
    Dataset provided by
    Kaggle
    Authors
    Mahdy Nabaee
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Area covered
    Ontario
    Description

    This dataset includes the listing prices for the sale of properties (mostly houses) in Ontario. They are obtained for a short period of time in July 2016 and include the following fields: - Price in dollars - Address of the property - Latitude and Longitude of the address obtained by using Google Geocoding service - Area Name of the property obtained by using Google Geocoding service

    This dataset will provide a good starting point for analyzing the inflated housing market in Canada although it does not include time related information. Initially, it is intended to draw an enhanced interactive heatmap of the house prices for different neighborhoods (areas)

    However, if there is enough interest, there will be more information added as newer versions to this dataset. Some of those information will include more details on the property as well as time related information on the price (changes).

    This is a somehow related articles about the real estate prices in Ontario: http://www.canadianbusiness.com/blogs-and-comment/check-out-this-heat-map-of-toronto-real-estate-prices/

    I am also inspired by this dataset which was provided for King County https://www.kaggle.com/harlfoxem/housesalesprediction

  2. H

    Heat Maps Software Report

    • datainsightsmarket.com
    doc, pdf, ppt
    Updated Jun 6, 2025
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    Data Insights Market (2025). Heat Maps Software Report [Dataset]. https://www.datainsightsmarket.com/reports/heat-maps-software-1970952
    Explore at:
    pdf, doc, pptAvailable download formats
    Dataset updated
    Jun 6, 2025
    Dataset authored and provided by
    Data Insights Market
    License

    https://www.datainsightsmarket.com/privacy-policyhttps://www.datainsightsmarket.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The heat map software market is experiencing robust growth, driven by the increasing need for businesses to understand user behavior and optimize website and application design for enhanced user experience (UX). The market, estimated at $2 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $6 billion by 2033. This growth is fueled by several key factors. Firstly, the rising adoption of digital platforms across various industries necessitates effective UX optimization, making heat map software an indispensable tool for businesses aiming to boost conversion rates and customer satisfaction. Secondly, advancements in technology, such as AI-powered analytics and integration with other marketing tools, are enhancing the capabilities and accessibility of heat map solutions. Finally, the growing emphasis on data-driven decision-making within organizations further propels the market's expansion. The competitive landscape is characterized by a blend of established players and emerging startups, fostering innovation and driving down prices. While increased competition could pose a challenge, the overall market outlook remains highly positive, with continued growth anticipated across various regions and segments. Despite its promising trajectory, the market faces some restraints. The relatively high cost of advanced heat map software may limit adoption for smaller businesses with tighter budgets. Furthermore, the complexity of analyzing and interpreting heat map data may require specialized expertise, posing a barrier for some users. However, the ongoing development of user-friendly interfaces and affordable solutions is gradually mitigating these challenges. Segmentation within the market is evolving, with distinct solutions emerging for specific industries and applications, catering to niche needs. The market is segmented by deployment (cloud, on-premise), pricing model (subscription, one-time purchase) and industry (e-commerce, gaming, education, etc). Key players like Hotjar, Smartlook, and others are actively innovating to expand their offerings and remain competitive in this dynamic market.

  3. Heatmap and Session Recording Software Market Report | Global Forecast From...

    • dataintelo.com
    csv, pdf, pptx
    Updated Dec 3, 2024
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    Dataintelo (2024). Heatmap and Session Recording Software Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/global-heatmap-and-session-recording-software-market
    Explore at:
    csv, pptx, pdfAvailable download formats
    Dataset updated
    Dec 3, 2024
    Dataset authored and provided by
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Heatmap and Session Recording Software Market Outlook



    The global heatmap and session recording software market is projected to expand significantly from its 2023 valuation of approximately $1.2 billion to an estimated market size of $3.5 billion by 2032, reflecting a robust compound annual growth rate (CAGR) of 12.3%. This substantial growth can be attributed to several factors, including the increasing demand for enhanced user experience analytics and the rising adoption of digital transformation across various sectors. The market is also being propelled by the need for businesses to understand customer behavior more deeply, optimize conversion rates, and improve overall customer satisfaction in an increasingly competitive digital landscape.



    One of the primary growth factors for the heatmap and session recording software market is the burgeoning emphasis on user experience (UX) optimization. As businesses strive to create more interactive and personalized digital interfaces, there is an escalating need for tools that can provide actionable insights into user interactions and preferences. These software solutions enable companies to visualize user engagement through heatmaps and session replays, thereby facilitating data-driven decisions to enhance website and application designs. Furthermore, the integration of artificial intelligence and machine learning algorithms into these tools is enhancing their capability to offer predictive analytics, making them indispensable for businesses aiming to stay ahead of consumer expectations.



    Another significant driver of market growth is the increasing focus on conversion rate optimization (CRO). With e-commerce and online services proliferating, businesses are under constant pressure to maximize their conversion rates from web traffic. Heatmap and session recording software offer invaluable insights into user journey bottlenecks and friction points that may hinder conversion. By identifying these inefficiencies, businesses can implement targeted strategies to streamline the conversion funnel, ultimately leading to increased sales and customer retention. This trend is being further fueled by the competitive e-commerce landscape, where the ability to convert visitors into customers can provide a decisive edge.



    Moreover, the necessity for comprehensive customer behavior analysis is catalyzing the market's expansion. Organizations are increasingly aware of the importance of understanding the nuances of customer interactions to tailor their offerings and marketing strategies effectively. Heatmap and session recording tools provide detailed analytics on user behavior patterns, preferences, and feedback, enabling businesses to make informed decisions and improve customer engagement. In an era where customer-centric approaches are key to success, the ability to analyze and act upon user data has become a critical component of business strategy, thereby driving demand for these software solutions.



    Regionally, the North American market currently leads in terms of adoption and innovation in heatmap and session recording software, driven by the region's advanced technological infrastructure and high concentration of digital businesses. Europe follows closely, with many countries emphasizing data-driven approaches to enhance digital experiences. Meanwhile, the Asia Pacific region is anticipated to witness the highest growth rate during the forecast period, attributable to the rapid digitalization and increasing online presence of businesses. These dynamics, coupled with growing internet penetration and smartphone adoption, are fostering a fertile environment for the expansion of heatmap and session recording solutions in the Asia Pacific region.



    Component Analysis



    The heatmap and session recording software market is segmented into software and services, each playing a crucial role in the overall ecosystem. The software component comprises various tools that enable the tracking and visualization of user interactions across digital platforms. These tools are continuously evolving, incorporating advanced features such as AI-driven insights and predictive analytics, providing businesses with a comprehensive understanding of user behavior. This segment is witnessing significant innovations aimed at enhancing user interface and experience, reflecting the increasing demand for sophisticated analytics capabilities among businesses seeking to optimize their digital presence.



    With the growing complexity of digital platforms and the need for seamless integration across various business functions, the services component is gaining increase

  4. H

    Heatmap Tools Report

    • archivemarketresearch.com
    doc, pdf, ppt
    Updated Feb 24, 2025
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    Archive Market Research (2025). Heatmap Tools Report [Dataset]. https://www.archivemarketresearch.com/reports/heatmap-tools-45318
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    pdf, doc, pptAvailable download formats
    Dataset updated
    Feb 24, 2025
    Dataset authored and provided by
    Archive Market Research
    License

    https://www.archivemarketresearch.com/privacy-policyhttps://www.archivemarketresearch.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The global heatmap tools market size was valued at USD 476.2 million in 2022 and is projected to grow from USD 555.4 million in 2023 to USD 1,267.9 million by 2030, exhibiting a CAGR of 11.2% during the forecast period. Heatmaps are visual representations of data that use color-coding to provide a quick and easy way to identify patterns and trends. Heatmap tools allow users to create heatmaps from a variety of data sources, including website analytics, user behavior data, and sales data. The market for heatmap tools is driven by several factors, including the increasing adoption of digital marketing, the growing need for customer insights, and the need to improve website usability. In addition, the advent of cloud-based heatmap tools has made it easier and more affordable for businesses to use these tools. Key players in the heatmap tools market include Contentsquare, Hotjar, Smartlook, Mouseflow, and FullStory. These players offer a wide range of features and capabilities, including session recording, click tracking, scroll tracking, and heatmaps. They also offer a variety of pricing plans to suit the needs of different businesses.

  5. H

    Heatmap Software Tool Report

    • marketresearchforecast.com
    doc, pdf, ppt
    Updated May 19, 2025
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    Market Research Forecast (2025). Heatmap Software Tool Report [Dataset]. https://www.marketresearchforecast.com/reports/heatmap-software-tool-539770
    Explore at:
    ppt, pdf, docAvailable download formats
    Dataset updated
    May 19, 2025
    Dataset authored and provided by
    Market Research Forecast
    License

    https://www.marketresearchforecast.com/privacy-policyhttps://www.marketresearchforecast.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The global heatmap software market is experiencing robust growth, driven by the increasing adoption of data-driven decision-making across various industries. Businesses are leveraging heatmaps to understand user behavior on websites and applications, optimize user experience (UX), improve conversion rates, and enhance overall digital performance. The market's expansion is fueled by the rising popularity of website analytics, A/B testing, and user experience (UX) optimization strategies. The cloud-based segment dominates the market due to its scalability, accessibility, and cost-effectiveness. Large enterprises represent a significant portion of the market due to their higher budgets and complex website structures requiring sophisticated analytics. However, the on-premises segment continues to hold relevance for organizations with stringent data security and compliance requirements. Competition is intense, with established players like Hotjar and Mouseflow alongside newer entrants continually innovating to offer enhanced features and functionalities. The market is expected to see continued growth, driven by technological advancements in AI-powered analytics and the increasing adoption of heatmap tools across mobile applications. Geographic distribution shows North America and Europe holding significant market share, reflecting the high level of digital maturity and adoption of analytics tools in these regions. However, the Asia-Pacific region exhibits strong growth potential, driven by rapid digital transformation and rising internet penetration. Challenges for market growth include the complexity of implementing and interpreting heatmap data, the need for specialized expertise, and the potential for data privacy concerns. Despite these challenges, the market is anticipated to maintain a healthy compound annual growth rate (CAGR), indicating a promising outlook for businesses offering heatmap software solutions and services. Future growth will be significantly shaped by the integration of heatmaps with other analytics tools and the development of more sophisticated and user-friendly interfaces.

  6. H

    Heatmap software Report

    • datainsightsmarket.com
    doc, pdf, ppt
    Updated May 12, 2025
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    Data Insights Market (2025). Heatmap software Report [Dataset]. https://www.datainsightsmarket.com/reports/heatmap-software-1396250
    Explore at:
    pdf, doc, pptAvailable download formats
    Dataset updated
    May 12, 2025
    Dataset authored and provided by
    Data Insights Market
    License

    https://www.datainsightsmarket.com/privacy-policyhttps://www.datainsightsmarket.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The heatmap software market is experiencing robust growth, driven by increasing demand for user experience (UX) optimization and website analytics across diverse business sectors. The market, estimated at $2 billion in 2025, is projected to expand significantly over the next decade, fueled by a compound annual growth rate (CAGR) of 15%, reaching approximately $6 billion by 2033. This growth is primarily attributed to the rising adoption of digital technologies, the growing emphasis on data-driven decision-making, and the need for businesses to enhance website usability and conversion rates. The segmentation reveals a strong preference for cloud-based solutions, with the Standard and Senior tiers ($79 and $419 per user/month respectively) showcasing higher adoption rates within large enterprises focused on in-depth user behavior analysis. Smaller businesses, while adopting heatmap tools, generally opt for the Basic plan ($17 per user/month) due to budget constraints. The competitive landscape is fiercely competitive, with a range of players offering varying levels of functionality and pricing. The market is characterized by both established analytics providers and specialized heatmap software vendors, creating a dynamic environment where innovation and feature differentiation are key success factors. Geographical distribution shows North America and Europe as leading markets, accounting for a combined market share exceeding 60%. However, rapid digitalization in Asia-Pacific and other emerging regions is driving substantial growth potential. Continued technological advancements, such as the integration of AI and machine learning for predictive analytics, will further shape the market’s trajectory. Challenges remain in areas such as data privacy concerns and the need for user-friendly interfaces to broaden adoption across all user segments. Future growth hinges on the ability of vendors to address these challenges while constantly innovating to meet evolving business requirements and user expectations. The market presents attractive opportunities for companies focusing on integration with other marketing and analytics platforms, providing a holistic view of user behavior for improved decision-making.

  7. Heatmap software Market Report | Global Forecast From 2025 To 2033

    • dataintelo.com
    csv, pdf, pptx
    Updated Sep 22, 2024
    + more versions
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    Dataintelo (2024). Heatmap software Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/global-heatmap-software-market
    Explore at:
    pptx, csv, pdfAvailable download formats
    Dataset updated
    Sep 22, 2024
    Dataset authored and provided by
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Heatmap Software Market Outlook



    The global market size of heatmap software is estimated to grow from USD 1.2 billion in 2023 to USD 3.5 billion by 2032, at a CAGR of 12.5% during the forecast period. The growth of the heatmap software market is primarily driven by the increasing need for businesses to analyze consumer behavior and optimize user experience, along with the growing adoption of data-driven decision-making processes across various industries.



    The rising need for businesses to understand their customers' online behaviors and interactions has significantly contributed to the growth of the heatmap software market. With the digital footprint expanding rapidly, organizations are increasingly leveraging heatmap software to visualize user interactions on websites and applications, thus enabling them to optimize the user experience. This, in turn, helps in enhancing customer satisfaction and boosting conversion rates. The shift towards data-driven decision-making is another crucial factor propelling market growth, as heatmap software provides valuable insights into user behavior without relying solely on traditional analytics.



    Another significant growth factor for the heatmap software market is the increasing adoption of e-commerce platforms and online retailing. With the surge in online shopping, retailers are focusing on improving the online shopping experience to attract and retain customers. Heatmap software plays a pivotal role in this by helping retailers understand user behavior, identify areas of improvement, and make informed decisions to enhance website performance. Additionally, the integration of advanced technologies such as artificial intelligence and machine learning into heatmap software is expected to further drive market growth by providing more accurate and comprehensive insights.



    The growing emphasis on user experience (UX) analytics is also fueling the demand for heatmap software. Organizations across various industries are recognizing the importance of delivering a seamless and intuitive user experience to stay competitive. Heatmap software enables businesses to identify pain points, track user engagement, and optimize website layouts and content accordingly. This focus on UX analytics is particularly prominent in sectors such as retail, e-commerce, healthcare, and BFSI, where user experience directly impacts customer satisfaction and business success.



    Regionally, North America is expected to dominate the heatmap software market, followed by Europe and Asia Pacific. The strong presence of key market players, coupled with the high adoption rate of advanced technologies, positions North America as a leading region. Europe is anticipated to witness substantial growth due to the increasing focus on digital transformation and user experience optimization. Asia Pacific is projected to experience the highest CAGR during the forecast period, driven by the rapid growth of the e-commerce sector and the rising awareness of the benefits of heatmap software among businesses in emerging economies.



    Component Analysis



    The heatmap software market is segmented into software and services based on components. The software segment holds the largest share in the market, primarily due to the widespread adoption of heatmap tools by businesses seeking to analyze and optimize user interactions on their digital platforms. Heatmap software provides visual representations of user activity, highlighting areas with the highest engagement and identifying potential issues in the user journey. This valuable insight enables organizations to make data-driven decisions to enhance user experience and increase conversion rates.



    The services segment, although smaller compared to the software segment, is expected to witness significant growth during the forecast period. This growth can be attributed to the increasing demand for professional services such as implementation, training, and consulting. As businesses adopt heatmap software, they often require expert assistance to integrate these tools seamlessly into their existing systems and maximize their benefits. Service providers play a crucial role in helping organizations understand and utilize heatmap data effectively, ensuring they can make informed decisions to improve their digital platforms.



    Furthermore, the services segment includes ongoing support and maintenance, which are essential for ensuring the continuous and efficient operation of heatmap software. Regular updates, troubleshooting, and customer support services are vital for organizations to address any issues promp

  8. u

    House Sales in Ontario - Catalogue - Canadian Urban Data Catalogue (CUDC)

    • data.urbandatacentre.ca
    • beta.data.urbandatacentre.ca
    Updated Mar 20, 2023
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    (2023). House Sales in Ontario - Catalogue - Canadian Urban Data Catalogue (CUDC) [Dataset]. https://data.urbandatacentre.ca/dataset/house-sales-in-ontario
    Explore at:
    Dataset updated
    Mar 20, 2023
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    Ontario
    Description

    This dataset includes the listing prices for the sale of properties (mostly houses) in Ontario. They are obtained for a short period of time in July 2016 and include the following fields: Price in dollars Address of the property Latitude and Longitude of the address obtained by using Google Geocoding service Area Name of the property obtained by using Google Geocoding service This dataset will provide a good starting point for analyzing the inflated housing market in Canada although it does not include time related information. Initially, it is intended to draw an enhanced interactive heatmap of the house prices for different neighborhoods (areas) However, if there is enough interest, there will be more information added as newer versions to this dataset. Some of those information will include more details on the property as well as time related information on the price (changes). This is a somehow related articles about the real estate prices in Ontario: http://www.canadianbusiness.com/blogs-and-comment/check-out-this-heat-map-of-toronto-real-estate-prices/ I am also inspired by this dataset which was provided for King County https://www.kaggle.com/harlfoxem/housesalesprediction

  9. Quantum-AI Fraud Heatmap Market Research Report 2033

    • growthmarketreports.com
    csv, pdf, pptx
    Updated Jun 28, 2025
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    Growth Market Reports (2025). Quantum-AI Fraud Heatmap Market Research Report 2033 [Dataset]. https://growthmarketreports.com/report/quantum-ai-fraud-heatmap-market
    Explore at:
    pptx, pdf, csvAvailable download formats
    Dataset updated
    Jun 28, 2025
    Dataset authored and provided by
    Growth Market Reports
    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Quantum-AI Fraud Heatmap Market Outlook



    According to our latest research, the global Quantum-AI Fraud Heatmap market size reached USD 2.18 billion in 2024, reflecting the growing integration of advanced quantum and artificial intelligence technologies in anti-fraud solutions. The market is expanding at a robust CAGR of 27.5% and is forecasted to reach USD 18.19 billion by 2033. This remarkable growth is primarily driven by escalating cyber threats, the proliferation of digital transactions, and the urgent need for real-time fraud detection across industries.




    The primary growth factor for the Quantum-AI Fraud Heatmap market is the exponential rise in sophisticated cyberattacks targeting financial, healthcare, and government sectors. As digital transformation accelerates, businesses are increasingly vulnerable to complex fraud schemes that traditional detection systems struggle to identify. Quantum-AI Fraud Heatmap solutions leverage the combined power of quantum computing and AI-driven analytics, enabling organizations to detect anomalies and fraudulent patterns in real-time with unprecedented accuracy. The surge in online banking, digital payments, and e-commerce transactions further amplifies the demand for advanced fraud detection systems, as enterprises seek to safeguard sensitive customer data and maintain regulatory compliance. The integration of machine learning algorithms with quantum processing capabilities allows these solutions to analyze vast datasets rapidly, delivering actionable insights that are vital for preempting fraud in today’s dynamic threat landscape.




    Another significant driver is the increasing regulatory pressure on organizations to implement robust fraud prevention measures. Governments and regulatory bodies worldwide are enacting stringent compliance mandates, such as GDPR, PCI DSS, and CCPA, to protect consumer data and ensure transparency in financial transactions. Quantum-AI Fraud Heatmap platforms are becoming indispensable tools for enterprises striving to meet these regulatory requirements, as they offer real-time monitoring, automated reporting, and advanced risk assessment features. The ability of these solutions to adapt to evolving fraud tactics and provide continuous protection has made them a preferred choice among leading banks, insurance companies, and e-commerce platforms. Additionally, the growing awareness of the financial and reputational risks associated with data breaches is prompting organizations to invest heavily in next-generation fraud detection technologies.




    The rapid adoption of cloud computing and the proliferation of Internet of Things (IoT) devices are also fueling the Quantum-AI Fraud Heatmap market’s expansion. Cloud-based deployment models offer scalability, flexibility, and cost-efficiency, making them attractive to organizations of all sizes. The integration of fraud heatmap solutions with IoT networks enables real-time monitoring of transactional data across multiple endpoints, enhancing the ability to detect and mitigate threats instantly. Furthermore, advancements in quantum encryption and AI-powered behavioral analytics are enabling enterprises to stay ahead of cybercriminals by identifying subtle deviations from normal user behavior. This technological synergy is expected to drive continuous innovation in the market, creating new opportunities for solution providers and end-users alike.




    Regionally, North America dominates the Quantum-AI Fraud Heatmap market, accounting for the largest revenue share in 2024, followed by Europe and Asia Pacific. The region’s leadership can be attributed to the presence of major technology vendors, high digital adoption rates, and a mature regulatory environment. However, Asia Pacific is anticipated to witness the fastest growth during the forecast period, driven by rapid digitalization, increasing cyber threats, and the rising adoption of advanced fraud detection solutions across emerging economies such as China, India, and Singapore. Latin America, the Middle East, and Africa are also experiencing steady growth, supported by government initiatives to strengthen cybersecurity infrastructure and the expansion of digital financial services.



  10. H

    Heat Map Camera Report

    • promarketreports.com
    doc, pdf, ppt
    Updated May 3, 2025
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    Pro Market Reports (2025). Heat Map Camera Report [Dataset]. https://www.promarketreports.com/reports/heat-map-camera-224860
    Explore at:
    ppt, pdf, docAvailable download formats
    Dataset updated
    May 3, 2025
    Dataset authored and provided by
    Pro Market Reports
    License

    https://www.promarketreports.com/privacy-policyhttps://www.promarketreports.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The global heat map camera market is experiencing robust growth, driven by increasing demand across diverse sectors. While precise figures for market size and CAGR aren't provided, leveraging industry knowledge and recognizing the strong adoption in sectors like automotive, building inspection, and security, we can reasonably estimate the 2025 market size to be around $2.5 billion, exhibiting a Compound Annual Growth Rate (CAGR) of approximately 12% during the forecast period (2025-2033). This growth is propelled by several key factors: the increasing affordability of thermal imaging technology, advancements leading to higher resolution and improved sensitivity in heat map cameras, and expanding applications in various industries. For instance, the integration of heat map cameras in drones for aerial surveillance and precision agriculture is a rapidly growing trend. Furthermore, stringent safety regulations and the rising need for predictive maintenance in industrial settings are fueling the adoption of these cameras for condition monitoring and early fault detection. The market segmentation reveals significant opportunities across various wavelength types (short-wave, mid-wave, and long-wave) and applications (aerial, marine, and land-based). While long-wave infrared cameras currently dominate due to their cost-effectiveness, the demand for higher-resolution mid-wave and short-wave infrared cameras is increasing in niche applications requiring greater precision. Geographically, North America and Europe are currently major markets, but the Asia-Pacific region, particularly China and India, are showing significant growth potential owing to rapid industrialization and infrastructure development. However, factors like high initial investment costs and the need for specialized expertise in operation and maintenance can act as restraints to market expansion. The competitive landscape is relatively fragmented, with key players including Hangzhou Hikvision, FLIR, and others continuously innovating to improve product features and expand their market reach. The future growth trajectory of the heat map camera market looks promising, driven by technological innovation and expanding application areas.

  11. Heatmap for patients with different severity with odds ratios of resource...

    • plos.figshare.com
    xls
    Updated Jun 11, 2023
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    Dorine Borensztajn; Joany M. Zachariasse; Susanne Greber-Platzer; Claudio F. Alves; Paulo Freitas; Frank J. Smit; Johan van der Lei; Ewout W. Steyerberg; Ian Maconochie; Henriëtte A. Moll (2023). Heatmap for patients with different severity with odds ratios of resource use, corrected for patient characteristics#. [Dataset]. http://doi.org/10.1371/journal.pone.0251046.t003
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 11, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Dorine Borensztajn; Joany M. Zachariasse; Susanne Greber-Platzer; Claudio F. Alves; Paulo Freitas; Frank J. Smit; Johan van der Lei; Ewout W. Steyerberg; Ian Maconochie; Henriëtte A. Moll
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Heatmap for patients with different severity with odds ratios of resource use, corrected for patient characteristics#.

  12. f

    Appendix C. Heat map of feeding trial growth rates and the general...

    • wiley.figshare.com
    html
    Updated May 31, 2023
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    George Livingston; Yuexin Jiang; Jeremy W. Fox; Mathew A. Leibold (2023). Appendix C. Heat map of feeding trial growth rates and the general experimental food web. [Dataset]. http://doi.org/10.6084/m9.figshare.3558228.v1
    Explore at:
    htmlAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    Wiley
    Authors
    George Livingston; Yuexin Jiang; Jeremy W. Fox; Mathew A. Leibold
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Heat map of feeding trial growth rates and the general experimental food web.

  13. f

    Heatmap for different ages with odds ratios of resource use, corrected for...

    • figshare.com
    xls
    Updated Jun 10, 2023
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    Dorine Borensztajn; Joany M. Zachariasse; Susanne Greber-Platzer; Claudio F. Alves; Paulo Freitas; Frank J. Smit; Johan van der Lei; Ewout W. Steyerberg; Ian Maconochie; Henriëtte A. Moll (2023). Heatmap for different ages with odds ratios of resource use, corrected for patient characteristics#. [Dataset]. http://doi.org/10.1371/journal.pone.0251046.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 10, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Dorine Borensztajn; Joany M. Zachariasse; Susanne Greber-Platzer; Claudio F. Alves; Paulo Freitas; Frank J. Smit; Johan van der Lei; Ewout W. Steyerberg; Ian Maconochie; Henriëtte A. Moll
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Heatmap for different ages with odds ratios of resource use, corrected for patient characteristics#.

  14. Heat map of standardised admission rates per hospital: All children*.

    • plos.figshare.com
    xls
    Updated Jun 2, 2023
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    Dorine M. Borensztajn; Nienke N. Hagedoorn; Irene Rivero Calle; Ian K. Maconochie; Ulrich von Both; Enitan D. Carrol; Juan Emmanuel Dewez; Marieke Emonts; Michiel van der Flier; Ronald de Groot; Jethro Herberg; Benno Kohlmaier; Emma Lim; Federico Martinon-Torres; Daan Nieboer; Ruud G. Nijman; Marko Pokorn; Franc Strle; Maria Tsolia; Clementien Vermont; Shunmay Yeung; Dace Zavadska; Werner Zenz; Michael Levin; Henriette A. Moll (2023). Heat map of standardised admission rates per hospital: All children*. [Dataset]. http://doi.org/10.1371/journal.pone.0244810.t004
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    xlsAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Dorine M. Borensztajn; Nienke N. Hagedoorn; Irene Rivero Calle; Ian K. Maconochie; Ulrich von Both; Enitan D. Carrol; Juan Emmanuel Dewez; Marieke Emonts; Michiel van der Flier; Ronald de Groot; Jethro Herberg; Benno Kohlmaier; Emma Lim; Federico Martinon-Torres; Daan Nieboer; Ruud G. Nijman; Marko Pokorn; Franc Strle; Maria Tsolia; Clementien Vermont; Shunmay Yeung; Dace Zavadska; Werner Zenz; Michael Levin; Henriette A. Moll
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Heat map of standardised admission rates per hospital: All children*.

  15. Heat map of standardised any admission rates per hospital for different...

    • plos.figshare.com
    xls
    Updated Jun 1, 2023
    + more versions
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    Dorine M. Borensztajn; Nienke N. Hagedoorn; Irene Rivero Calle; Ian K. Maconochie; Ulrich von Both; Enitan D. Carrol; Juan Emmanuel Dewez; Marieke Emonts; Michiel van der Flier; Ronald de Groot; Jethro Herberg; Benno Kohlmaier; Emma Lim; Federico Martinon-Torres; Daan Nieboer; Ruud G. Nijman; Marko Pokorn; Franc Strle; Maria Tsolia; Clementien Vermont; Shunmay Yeung; Dace Zavadska; Werner Zenz; Michael Levin; Henriette A. Moll (2023). Heat map of standardised any admission rates per hospital for different patient groups: Final diagnosis*. [Dataset]. http://doi.org/10.1371/journal.pone.0244810.t006
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Dorine M. Borensztajn; Nienke N. Hagedoorn; Irene Rivero Calle; Ian K. Maconochie; Ulrich von Both; Enitan D. Carrol; Juan Emmanuel Dewez; Marieke Emonts; Michiel van der Flier; Ronald de Groot; Jethro Herberg; Benno Kohlmaier; Emma Lim; Federico Martinon-Torres; Daan Nieboer; Ruud G. Nijman; Marko Pokorn; Franc Strle; Maria Tsolia; Clementien Vermont; Shunmay Yeung; Dace Zavadska; Werner Zenz; Michael Levin; Henriette A. Moll
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Heat map of standardised any admission rates per hospital for different patient groups: Final diagnosis*.

  16. Heat map of standardised any admission rates per hospital for different age...

    • plos.figshare.com
    xls
    Updated Jun 4, 2023
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    Dorine M. Borensztajn; Nienke N. Hagedoorn; Irene Rivero Calle; Ian K. Maconochie; Ulrich von Both; Enitan D. Carrol; Juan Emmanuel Dewez; Marieke Emonts; Michiel van der Flier; Ronald de Groot; Jethro Herberg; Benno Kohlmaier; Emma Lim; Federico Martinon-Torres; Daan Nieboer; Ruud G. Nijman; Marko Pokorn; Franc Strle; Maria Tsolia; Clementien Vermont; Shunmay Yeung; Dace Zavadska; Werner Zenz; Michael Levin; Henriette A. Moll (2023). Heat map of standardised any admission rates per hospital for different age groups*. [Dataset]. http://doi.org/10.1371/journal.pone.0244810.t007
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 4, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Dorine M. Borensztajn; Nienke N. Hagedoorn; Irene Rivero Calle; Ian K. Maconochie; Ulrich von Both; Enitan D. Carrol; Juan Emmanuel Dewez; Marieke Emonts; Michiel van der Flier; Ronald de Groot; Jethro Herberg; Benno Kohlmaier; Emma Lim; Federico Martinon-Torres; Daan Nieboer; Ruud G. Nijman; Marko Pokorn; Franc Strle; Maria Tsolia; Clementien Vermont; Shunmay Yeung; Dace Zavadska; Werner Zenz; Michael Levin; Henriette A. Moll
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Heat map of standardised any admission rates per hospital for different age groups*.

  17. b

    Data from: Kansrijke gebieden voor de aanleg van een warmtenet - diverse...

    • ldf.belgif.be
    Updated Apr 1, 2016
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    (2016). Kansrijke gebieden voor de aanleg van een warmtenet - diverse varianten (2012) [Dataset]. https://ldf.belgif.be/datagovbe?subject=https%3A%2F%2Fmetadata.omgeving.vlaanderen.be%2Fsrv%2Fresources%2Fdatasets%2F792b3f01-2566-4c52-8e61-d480d72f202a
    Explore at:
    Dataset updated
    Apr 1, 2016
    Variables measured
    http://publications.europa.eu/resource/authority/data-theme/ENER, http://publications.europa.eu/resource/authority/data-theme/REGI, http://publications.europa.eu/resource/authority/data-theme/TECH
    Description

    La « Heat Map Flanders » a été commandée par l'Agence flamande de l'énergie pour mettre en œuvre la directive 2012/27/UE relative à l'efficacité énergétique. Les principaux produits sont des cartes avec la demande et l'offre de chaleur pour la situation actuelle (2012) et une carte avec des zones prometteuses pour la récupération de chaleur et les réseaux de chaleur à l'avenir, à la fois pour le territoire de la Flandre. L'étude a été réalisée par VITO en collaboration avec les gestionnaires de réseau de distribution Eandis et Infrax. Vous pouvez consulter le rapport d’accompagnement à l’adresse suivante: www.energysparen.be/carte thermique. -- Dans le cadre de la carte thermique de Flandre, il a été examiné, pour chaque cellule de grille de 1200 x 1200 m en Flandre, s'il s'agit d'une zone prometteuse (économiquement intéressante ou présentant des avantages supérieurs aux coûts) pour l'investissement dans un réseau de chaleur basé sur la chaleur résiduelle ou sur la chaleur provenant d'une nouvelle cogénération à haut rendement. Pour plus d'informations générales, voir le rapport. -- Cette section contient quatre couches cartographiques: Titre (1): Utilisation de la chaleur résiduelle dans la même cellule de grille. Nom de la couche (1):er_kb_net_lok_1200m Description (1): Dans cette analyse coûts-avantages, le potentiel économique d'un réseau de chaleur local a été étudié à l'intérieur de chaque cellule de grille avec de la chaleur résiduelle disponible. Les calculs tiennent compte des mécanismes de soutien du gouvernement flamand («aide à l’investissement pour la chaleur résiduelle»). L'analyse a lieu à une résolution de 1200 x 1200 m et est basée sur l'état en 2012. Titre (2): Si la chaleur résiduelle est transportée vers les cellules voisines. Nom de couche (2):er_kb_net_nab_1200m Description (2): Pour chaque cellule de grille ayant une demande de chaleur, un calcul coûts-avantages est effectué sur la base de la chaleur résiduelle disponible dans les cellules de grille voisines, la cellule de grille dite «source de chaleur». La prise en compte du transport de la chaleur résiduelle vers la cellule du réseau entraîne des coûts supplémentaires. Cela suppose un approvisionnement direct de la cellule de grille en cours d'évaluation. Les calculs tiennent compte des mécanismes de soutien du gouvernement flamand («aide à l’investissement pour la chaleur résiduelle»). L'analyse a lieu à une résolution de 1200 x 1200 m et est basée sur l'état en 2012. Titre (3): Lorsque la chaleur résiduelle est extraite d’une cellule voisine, avec une valeur pour la chaleur résiduelle de 25 EUR/MWh. Nom de couche (3):er_kb_net_comb_max_wrw_1200m Description (3): Pour chaque cellule de grille ayant une demande de chaleur, un calcul coûts-avantages est effectué sur la base de la chaleur résiduelle disponible dans les cellules de grille voisines, la cellule de grille dite «source de chaleur». La prise en compte du transport de la chaleur résiduelle vers la cellule du réseau entraîne des coûts supplémentaires. Cette fois, d'éventuelles économies d'échelle seront prises en compte si les cellules de grille intermédiaires procèdent elles-mêmes à la construction d'un réseau de chaleur. Les calculs tiennent compte des mécanismes de soutien du gouvernement flamand («aide à l’investissement pour la chaleur résiduelle»). Il s'agit d'une variante de la carte «Zones prospères pour la construction d'un réseau de chaleur dans lequel la chaleur résiduelle n'est pas obtenue directement à partir de la source, mais via une cellule voisine, avec une valeur de chaleur résiduelle de 0 EUR/MWh.» L'analyse a lieu à une résolution de 1200 x 1200 m et est basée sur l'état en 2012. Titre (4): Avec la cogénération comme source de chaleur, scénario de bas prix du carburant. Nom de la couche (4):er_kb_net_wkk_min_bp_1200m Description (4): Pour chaque cellule de réseau, un calcul coûts-avantages est effectué pour l'installation d'une nouvelle cogénération centrale (turbine à gaz) qui fournit sa chaleur dans la même cellule de réseau à l'aide d'un réseau de chaleur. Les certificats de cogénération sont pris en compte dans les calculs. Dans ce scénario, les prix du carburant seront réduits. L'effet sur les avantages peut être comparé à la carte « Avec la cogénération comme source de chaleur ». L'analyse a lieu à une résolution de 1200 x 1200 m et est basée sur l'état en 2012.

  18. f

    Additional file 7 of How are nature-based solutions contributing to priority...

    • springernature.figshare.com
    xlsx
    Updated Jul 25, 2023
    + more versions
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    Jan Dick; Jonathan Carruthers-Jones; Steve Carver; Anne J. Dobel; James D. Miller (2023). Additional file 7 of How are nature-based solutions contributing to priority societal challenges surrounding human well-being in the United Kingdom: a systematic map [Dataset]. http://doi.org/10.6084/m9.figshare.13120822.v1
    Explore at:
    xlsxAvailable download formats
    Dataset updated
    Jul 25, 2023
    Dataset provided by
    figshare
    Authors
    Jan Dick; Jonathan Carruthers-Jones; Steve Carver; Anne J. Dobel; James D. Miller
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    United Kingdom
    Description

    Additional file 7. Heatmap references.

  19. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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Mahdy Nabaee (2016). House Sales in Ontario [Dataset]. https://www.kaggle.com/mnabaee/ontarioproperties/activity
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House Sales in Ontario

Draw an enhanced heatmap of House Prices

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CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
Oct 7, 2016
Dataset provided by
Kaggle
Authors
Mahdy Nabaee
License

https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

Area covered
Ontario
Description

This dataset includes the listing prices for the sale of properties (mostly houses) in Ontario. They are obtained for a short period of time in July 2016 and include the following fields: - Price in dollars - Address of the property - Latitude and Longitude of the address obtained by using Google Geocoding service - Area Name of the property obtained by using Google Geocoding service

This dataset will provide a good starting point for analyzing the inflated housing market in Canada although it does not include time related information. Initially, it is intended to draw an enhanced interactive heatmap of the house prices for different neighborhoods (areas)

However, if there is enough interest, there will be more information added as newer versions to this dataset. Some of those information will include more details on the property as well as time related information on the price (changes).

This is a somehow related articles about the real estate prices in Ontario: http://www.canadianbusiness.com/blogs-and-comment/check-out-this-heat-map-of-toronto-real-estate-prices/

I am also inspired by this dataset which was provided for King County https://www.kaggle.com/harlfoxem/housesalesprediction

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