75 datasets found
  1. i

    Data from: A novel spatial prediction method integrating Exploratory Spatial...

    • ieee-dataport.org
    Updated Mar 19, 2025
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    Bingbo Gao (2025). A novel spatial prediction method integrating Exploratory Spatial Data Analysis into Random Forest for large scale daily air temperature mapping [Dataset]. https://ieee-dataport.org/documents/novel-spatial-prediction-method-integrating-exploratory-spatial-data-analysis-random
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    Dataset updated
    Mar 19, 2025
    Authors
    Bingbo Gao
    License

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

    Description

    environmental management

  2. f

    Urban America Under Arrest: Too Many Sad Anniversaries

    • figshare.com
    xlsx
    Updated May 31, 2023
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    JKevin Byrne (2023). Urban America Under Arrest: Too Many Sad Anniversaries [Dataset]. http://doi.org/10.6084/m9.figshare.15070884.v1
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    xlsxAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    figshare
    Authors
    JKevin Byrne
    License

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

    Area covered
    United States
    Description

    Open-data from LAPD's civic portal were scrubbed, moved into GeoDa software, and given iterations of exploratory spatial data analysis. July 2021This then is the author's replication data by filenames:UrbanAmUnderArrestLA-Arrests2020AugustPSAI.xlsx,UrbanAmUnderArrestByrneLAReportingDistrictsDataFiles.zip which containLAPD_Reporting_Districts-shp and LAReportingDistricts.prj.gda

  3. Exploratory Spatial Data Approach to Identify the Context of...

    • icpsr.umich.edu
    • gimi9.com
    • +2more
    Updated Aug 31, 2006
    + more versions
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    Sridharan, Sanjeev; Meyer, Jon'a (2006). Exploratory Spatial Data Approach to Identify the Context of Unemployment-Crime Linkages in Virginia, 1995-2000 [Dataset]. http://doi.org/10.3886/ICPSR04546.v1
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    Dataset updated
    Aug 31, 2006
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    Sridharan, Sanjeev; Meyer, Jon'a
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/4546/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/4546/terms

    Time period covered
    1995 - 2000
    Area covered
    Virginia, United States
    Description

    This research is an exploration of a spatial approach to identify the contexts of unemployment-crime relationships at the county level. Using Exploratory Spatial Data Analysis (ESDA) techniques, the study explored the relationship between unemployment and property crimes (burglary, larceny, motor vehicle theft, and robbery) in Virginia from 1995 to 2000. Unemployment rates were obtained from the Department of Labor, while crime rates were obtained from the Federal Bureau of Investigation's Uniform Crime Reports. Demographic variables are included, and a resource deprivation scale was created by combining measures of logged median family income, percentage of families living below the poverty line, and percentage of African American residents.

  4. H

    Replication data for: The Electoral Geography of Weimar Germany: Exploratory...

    • dataverse.harvard.edu
    Updated Feb 18, 2010
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    John O'Loughlin (2010). Replication data for: The Electoral Geography of Weimar Germany: Exploratory Spatial Data Analyses (ESDA) of Protestant Support for the Nazi Party [Dataset]. http://doi.org/10.7910/DVN/2JHJFF
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 18, 2010
    Dataset provided by
    Harvard Dataverse
    Authors
    John O'Loughlin
    License

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

    Area covered
    Germany, Weimar
    Description

    For more than half a century, social scientists have probed the aggregate correlates of the vote for the Nazi party (NSDAP) in Weimar Germany. Since individual-level data are not available for this time period, aggregate census data for small geographic units have been heavily used to infer the support of the Nazi party by various compositional groups. Many of these studies hint at a complex geographic patterning. Recent developments in geographic methodologies, based on Geographic Information Science (GIS) and spatial statistics, allow a deeper probing of these regional and local contextual elements. In this paper, a suite of geographic methods—global and local measures of spatial autocorrelation, variography, distance-based correlation, directional spatial correlograms, vector mapping, and barrier definition (wombling)—are used in an exploratory spatial data analysis of the NSDAP vote. The support for the NSDAP by Protestant voters (estimated using King's ecological inference procedure) is the key correlate examined. The results from the various methods are consistent in showing a voting surface of great complexity, with many local clusters that differ from the regional trend. The Weimar German electoral map does not show much evidence of a nationalized electorate, but is better characterized as a mosaic of support for "milieu parties," mixed across class and other social lines, and defined by a strong attachment to local traditions, beliefs, and practices.

  5. My data.zip

    • figshare.com
    zip
    Updated Oct 29, 2019
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    Xuzhe Duan (2019). My data.zip [Dataset]. http://doi.org/10.6084/m9.figshare.10062458.v1
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    zipAvailable download formats
    Dataset updated
    Oct 29, 2019
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Xuzhe Duan
    License

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

    Description

    The dataset contains four nighttime lights satellite imageries as the source data, which were taken from Wuhan Ccity on June 14, 2018, Wuhan City on September 15, 2018, Shenyang City on September 10, 2018 and Shenyang City on March 17, 2019. The dataset also provides the "result.mxd" file for urban commercial areas detection using these four imageries .

  6. f

    Data from: Spatial Dependency of Eco-Efficiency of Agriculture in São Paulo

    • scielo.figshare.com
    jpeg
    Updated Jun 5, 2023
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    Carlos Rosano-Peña; Carlo Aleksandr Rosano de Almeida; Evaldo César Cavalcante Rodrigues; André Luiz Marques Serrano (2023). Spatial Dependency of Eco-Efficiency of Agriculture in São Paulo [Dataset]. http://doi.org/10.6084/m9.figshare.14289044.v1
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    jpegAvailable download formats
    Dataset updated
    Jun 5, 2023
    Dataset provided by
    SciELO journals
    Authors
    Carlos Rosano-Peña; Carlo Aleksandr Rosano de Almeida; Evaldo César Cavalcante Rodrigues; André Luiz Marques Serrano
    License

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

    Area covered
    São Paulo
    Description

    ABSTRACT This research presents an eco-efficiency index for the municipalities of São Paulo, indicating how much it would be possible to maximize economic and environmental objectives, taking into account the best practices for the municipalities of this region. In this vein, we used the Data Envelopment Analysis method with directional distance functions based on the classic variables of multiproduct production function and the internalization of two externalities (one positive and one negative). The study also used the tools of exploratory spatial data analysis to verify the spatial autocorrelation and spatial heterogeneity of the calculated index. The results indicate that, on average, the analyzed municipalities are able to expand the production and forested areas by 59% and also to reduce degraded areas and inputs in the same proportion. Spatial analysis demonstrated the existence of spatial heterogeneity and autocorrelation between municipalities and the formation of large clusters. Based on these results, priorities for environmental intervention in the state are defined.

  7. Z

    EXPLORATORY SPATIAL ANALYSIS OF "ACCESS" TO PHYSICAL AND DIGITAL RETAIL...

    • data.niaid.nih.gov
    Updated May 1, 2020
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    Weisi Guo (2020). EXPLORATORY SPATIAL ANALYSIS OF "ACCESS" TO PHYSICAL AND DIGITAL RETAIL BANKING CHANNELS IN THE UK [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_3417102
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    Dataset updated
    May 1, 2020
    Dataset provided by
    Andra Sonea
    Stephen Jarvis
    Weisi Guo
    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

    File built in order to explore access to banking channels in the UK (February 2019)

    The report "Exploratory Spatial Analysis of Access to Physical and Digital Retail Banking Channels in the UK" has been published by Think Forward Initiative in October 2019. You can download the full report from here: https://www.thinkforwardinitiative.com/research/exploratory-spatial-analysis-of-access-to-physical-and-digital-retail-banking-channels-in-the-uk

    Related code: andrasonea/TFI_AccessToBanking

  8. G

    GIS Mapping Tools Report

    • datainsightsmarket.com
    doc, pdf, ppt
    Updated May 21, 2025
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    Data Insights Market (2025). GIS Mapping Tools Report [Dataset]. https://www.datainsightsmarket.com/reports/gis-mapping-tools-533095
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    pdf, doc, pptAvailable download formats
    Dataset updated
    May 21, 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 global GIS mapping tools market is experiencing robust growth, driven by increasing demand across diverse sectors. The market, estimated at $15 billion in 2025, is projected to witness a Compound Annual Growth Rate (CAGR) of 10% from 2025 to 2033, reaching approximately $39 billion by 2033. This expansion is fueled by several key factors. Firstly, the rising adoption of cloud-based GIS solutions offers enhanced accessibility, scalability, and cost-effectiveness, particularly appealing to smaller organizations. Secondly, the burgeoning need for precise spatial data analysis in various applications, including urban planning, geological exploration, and water resource management, significantly contributes to market growth. Thirdly, advancements in technologies such as AI and machine learning are integrating into GIS tools, leading to more sophisticated analytical capabilities and improved decision-making. Finally, the increasing availability of high-resolution satellite imagery and other geospatial data further fuels market expansion. However, market growth is not without challenges. High initial investment costs associated with implementing and maintaining sophisticated GIS systems can pose a barrier to entry for smaller businesses. Furthermore, the complexity of GIS software and the need for specialized skills to operate and interpret data effectively can limit widespread adoption. Despite these restraints, the market’s overall trajectory remains positive, with the cloud-based segment projected to maintain a dominant market share due to its inherent advantages. Growth will be geographically diverse, with North America and Europe continuing to be significant markets, while Asia-Pacific is expected to experience the fastest growth due to rapid urbanization and infrastructure development. The continued development of user-friendly interfaces and increased integration with other business intelligence tools will further accelerate market expansion in the coming years.

  9. G

    GIS Mapping Tools Report

    • marketreportanalytics.com
    doc, pdf, ppt
    Updated Apr 3, 2025
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    Market Report Analytics (2025). GIS Mapping Tools Report [Dataset]. https://www.marketreportanalytics.com/reports/gis-mapping-tools-55298
    Explore at:
    ppt, pdf, docAvailable download formats
    Dataset updated
    Apr 3, 2025
    Dataset authored and provided by
    Market Report Analytics
    License

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

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

    The global GIS mapping tools market is experiencing robust growth, driven by increasing demand across diverse sectors. The market's expansion is fueled by several key factors: the rising adoption of cloud-based GIS solutions offering enhanced accessibility and scalability, the escalating need for precise spatial data analysis in urban planning and resource management, and the expanding application of GIS in geological exploration for efficient resource discovery and extraction. Furthermore, advancements in location-based services (LBS) and the integration of GIS with other technologies such as IoT and AI are creating new opportunities and driving market expansion. While the market size in 2025 is estimated at $15 billion (a reasonable assumption considering similar market sizes for related technologies), the Compound Annual Growth Rate (CAGR) is projected to remain strong, likely exceeding 8% through 2033. This sustained growth indicates a highly promising market outlook for vendors and investors. However, market growth is not without challenges. High initial investment costs for sophisticated GIS software and the requirement for skilled personnel to operate and maintain these systems can pose barriers to entry, particularly for smaller organizations. Additionally, data security concerns and the need for robust data management strategies are critical factors impacting market adoption. Despite these constraints, the continued integration of GIS tools into various business processes and the growing availability of user-friendly, affordable solutions are expected to mitigate these challenges and propel the market towards sustained and significant growth in the coming years. Segmentation reveals a strong preference for cloud-based solutions due to their flexibility and cost-effectiveness, with the geological exploration and urban planning applications exhibiting the highest growth rates. Key players such as Esri, Autodesk, and Hexagon are strategically positioned to capitalize on these trends.

  10. e

    Introduction to cross-section spatial econometric models with applications...

    • b2find.eudat.eu
    Updated May 2, 2010
    + more versions
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    (2010). Introduction to cross-section spatial econometric models with applications in R [Data and Codes] - Dataset - B2FIND [Dataset]. https://b2find.eudat.eu/dataset/22cba957-9a05-56fe-953a-9cac655f5a07
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    Dataset updated
    May 2, 2010
    Description

    This paper introduces the spatial component in cross-section econometric estimations and specifically, the spatial dependence effect inherent in some of the variables involved in the modelling process. First, the spatial structure of the data from thematic maps is observed and Moran's spatial autocorrelation indicators are presented. Subsequently, the spatial weights matrix is built under different specifications. Finally, several modelling specification strategies are shown and the interpretation of the estimated coefficients. The theoretical concepts are illustrated with examples and their corresponding R software codes. This code and databases are available in a freely accessible repository in the BE2SHARE-EUDAT platform so that they can be easily reproduced. Exploratory Spatial Data Analysis (ESDA) and spatial econometrics.

  11. Z

    Epidemiological geography at work. An exploratory review about the overall...

    • data.niaid.nih.gov
    • zenodo.org
    Updated Jul 19, 2024
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    Andrea Marco Raffaele Pranzo (2024). Epidemiological geography at work. An exploratory review about the overall findings of spatial analysis applied to the study of CoViD-19 propagation along the first pandemic year (DATASET) [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_4685963
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    Dataset updated
    Jul 19, 2024
    Dataset authored and provided by
    Andrea Marco Raffaele Pranzo
    License

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

    Description

    Literature review dataset

    This table lists the surveyed papers concerning the application of spatial analysis, GIS (Geographic Information Systems) as well as general geographic approaches and geostatistics, to the assessment of CoViD-19 dynamics. The period of survey is from January 1st, 2020 to December 15th, 2020. The first column lists the reference. The second lists the date of publication (preferably, the date of online publication). The third column lists the Country or the Countries and/or the subnational entities investigated. The fourth column lists the epidemiological data utilized in each paper. The fifth column lists other types of data utilized for the analysis. The sixth column lists the more traditionally statistically-based methods, if utilized. The seventh column lists the geo-statistical, GIS or geographic methods, if utilized. The eight column sums up the findings of each paper. The papers are also classified within seven thematic categories. The full references are available at the end of the table in alphabetical order.

    This table was the basis for the realization of a comprehensive geographic literature review. It aims to be a useful tool to ease the "due-diligence" activity of all the researchers interested in the spatial analysis of the pandemic.

    The reference to cite the related paper is the following:

    Pranzo, A.M.R., Dai Prà, E. & Besana, A. Epidemiological geography at work: An exploratory review about the overall findings of spatial analysis applied to the study of CoViD-19 propagation along the first pandemic year. GeoJournal (2022). https://doi.org/10.1007/s10708-022-10601-y

    To read the manuscript please follow this link: https://doi.org/10.1007/s10708-022-10601-y

  12. D

    Geographic Information System GIS Tools Market Report | Global Forecast From...

    • dataintelo.com
    csv, pdf, pptx
    Updated Sep 12, 2024
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    Dataintelo (2024). Geographic Information System GIS Tools Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/global-geographic-information-system-gis-tools-market
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    pptx, pdf, csvAvailable download formats
    Dataset updated
    Sep 12, 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

    Geographic Information System (GIS) Tools Market Outlook



    The global Geographic Information System (GIS) tools market size was valued at approximately USD 10.8 billion in 2023, and it is projected to reach USD 21.5 billion by 2032, growing at a compound annual growth rate (CAGR) of 7.9% from 2024 to 2032. The increasing demand for spatial data analytics and the rising adoption of GIS tools across various industries are significant growth factors propelling the market forward.



    One of the primary growth factors for the GIS tools market is the surging demand for spatial data analytics. Spatial data plays a critical role in numerous sectors, including urban planning, environmental monitoring, disaster management, and natural resource exploration. The ability to visualize and analyze spatial data provides organizations with valuable insights, enabling them to make informed decisions. Advances in technology, such as the integration of artificial intelligence (AI) and machine learning (ML) with GIS, are enhancing the capabilities of these tools, further driving market growth.



    Moreover, the increasing adoption of GIS tools in the construction and agriculture sectors is fueling market expansion. In construction, GIS tools are used for site selection, route planning, and resource management, enhancing operational efficiency and reducing costs. Similarly, in agriculture, GIS tools aid in precision farming, crop monitoring, and soil analysis, leading to improved crop yields and sustainable farming practices. The ability of GIS tools to provide real-time data and analytics is particularly beneficial in these industries, contributing to their widespread adoption.



    The growing importance of location-based services (LBS) in various applications is another key driver for the GIS tools market. LBS are extensively used in navigation, logistics, and transportation, providing real-time location information and route optimization. The proliferation of smartphones and the development of advanced GPS technologies have significantly increased the demand for LBS, thereby boosting the GIS tools market. Additionally, the integration of GIS with other technologies, such as the Internet of Things (IoT) and Big Data, is creating new opportunities for market growth.



    Regionally, North America holds a significant share of the GIS tools market, driven by the high adoption of advanced technologies and the presence of major market players. The Asia Pacific region is expected to witness the highest growth rate during the forecast period, owing to increasing investments in infrastructure development, smart city projects, and the growing use of GIS tools in emerging economies such as China and India. Europe, Latin America, and the Middle East & Africa are also expected to contribute to market growth, driven by various government initiatives and increasing awareness of the benefits of GIS tools.



    Component Analysis



    The GIS tools market can be segmented by component into software, hardware, and services. The software segment is anticipated to dominate the market due to the increasing demand for advanced GIS software solutions that offer enhanced data visualization, spatial analysis, and decision-making capabilities. GIS software encompasses a wide range of applications, including mapping, spatial data analysis, and geospatial data management, making it indispensable for various industries. The continuous development of user-friendly and feature-rich software solutions is expected to drive the growth of this segment.



    Hardware components in the GIS tools market include devices such as GPS units, remote sensing devices, and plotting and digitizing tools. The hardware segment is also expected to witness substantial growth, driven by the increasing use of advanced hardware devices that provide accurate and real-time spatial data. The advancements in GPS technology and the development of sophisticated remote sensing devices are key factors contributing to the growth of the hardware segment. Additionally, the integration of hardware with IoT and AI technologies is enhancing the capabilities of GIS tools, further propelling market expansion.



    The services segment includes consulting, integration, maintenance, and support services related to GIS tools. This segment is expected to grow significantly, driven by the increasing demand for specialized services that help organizations effectively implement and manage GIS solutions. Consulting services assist organizations in selecting the right GIS tools and optimizing their use, while integration services ensure seamless integr

  13. f

    DataSheet1_Spatial Differences and Influencing Factors of Urban Water...

    • frontiersin.figshare.com
    pdf
    Updated Jun 1, 2023
    + more versions
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    Kai Liu; Wenrui Liu; Jialing Wu; Zhongfei Chen; Wen Zhang; Fang Liu (2023). DataSheet1_Spatial Differences and Influencing Factors of Urban Water Utilization Efficiency in China.PDF [Dataset]. http://doi.org/10.3389/fenvs.2022.890187.s001
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    pdfAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    Frontiers
    Authors
    Kai Liu; Wenrui Liu; Jialing Wu; Zhongfei Chen; Wen Zhang; Fang Liu
    License

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

    Area covered
    China
    Description

    The purpose of urban water management is to improve urban water utilization efficiency (UWUE), which in turn addresses water shortages in urban areas. The present study aimed to evaluate the UWUE of 284 cities at the prefecture level in China between 2003 and 2018 by the slacks-based measure of super-efficiency, explore its spatial differences through exploratory spatial data analysis, and analyze the influencing factors using the statistical tool Geodetector. The results showed that the average value of UWUE in China was generally low but tended to rise gradually. There were significant spatial differences in UWUE across China, with considerable global and local spatial autocorrelation, and local spatial autocorrelation was characterized primarily by high-high and low-low regions. Industrial structure and urban population were the main influencing factors for UWUE. Finally, based on these findings, we offered policy implications for improving UWUE and coordinated development between cities.

  14. G

    Geographical Mapping Software Report

    • datainsightsmarket.com
    doc, pdf, ppt
    Updated Apr 26, 2025
    + more versions
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    Data Insights Market (2025). Geographical Mapping Software Report [Dataset]. https://www.datainsightsmarket.com/reports/geographical-mapping-software-533384
    Explore at:
    ppt, doc, pdfAvailable download formats
    Dataset updated
    Apr 26, 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 geographical mapping software market is experiencing robust growth, driven by increasing demand across diverse sectors. The market's expansion is fueled by several key factors, including the rising adoption of cloud-based solutions for enhanced accessibility and collaboration, the growing need for precise location data in various applications, and the increasing integration of GIS technology with other analytical tools. Applications such as geological exploration, water conservancy projects, and urban planning are major contributors to market growth, benefiting from the ability to visualize and analyze spatial data efficiently. While the market faces certain restraints, such as the high initial investment costs associated with some software solutions and the need for specialized expertise, these are being mitigated by the emergence of more affordable and user-friendly options, as well as increased training and educational resources. The market is segmented by application (Geological Exploration, Water Conservancy Project, Urban Plan, Others) and type (Cloud Based, Web Based), with cloud-based solutions gaining significant traction due to their scalability and cost-effectiveness. Major players in the market, including Esri, Autodesk, Mapbox, and others, are continuously innovating and introducing new features to cater to the evolving needs of their customers. This competitive landscape ensures continuous improvement in software capabilities and affordability, further propelling market expansion. The geographical distribution of this market is broad, with North America and Europe currently holding significant market shares due to established infrastructure and high adoption rates. However, the Asia-Pacific region is exhibiting particularly rapid growth, driven by increasing urbanization, infrastructure development, and government initiatives promoting the use of GIS technologies. This regional shift indicates significant future growth potential in emerging markets. The forecast period of 2025-2033 suggests continued expansion, with a projected CAGR reflecting the sustained demand across different geographical regions and application areas. While precise figures are unavailable, based on industry trends and available data, a conservative estimate for the current market size would place it in the high hundreds of millions of dollars, with steady and significant growth anticipated.

  15. G

    GIS Mapping Tools Report

    • marketreportanalytics.com
    doc, pdf, ppt
    Updated Apr 3, 2025
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    Market Report Analytics (2025). GIS Mapping Tools Report [Dataset]. https://www.marketreportanalytics.com/reports/gis-mapping-tools-55097
    Explore at:
    doc, pdf, pptAvailable download formats
    Dataset updated
    Apr 3, 2025
    Dataset authored and provided by
    Market Report Analytics
    License

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

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

    The global GIS mapping tools market is experiencing robust growth, driven by increasing demand across diverse sectors. The market, estimated at $15 billion in 2025, is projected to expand at a Compound Annual Growth Rate (CAGR) of 8% from 2025 to 2033, reaching approximately $28 billion by 2033. This growth is fueled by several key factors. Firstly, the burgeoning adoption of cloud-based solutions offers scalability, cost-effectiveness, and enhanced accessibility to a wider user base, including small and medium-sized enterprises (SMEs). Secondly, the escalating need for precise spatial data analysis in various applications, such as urban planning, geological exploration, and water resource management, is significantly boosting market demand. The increasing integration of GIS with other technologies like AI and IoT further amplifies its capabilities, leading to more sophisticated applications and increased market penetration. Finally, government initiatives promoting digitalization and smart city development across the globe are indirectly fueling this market expansion. However, certain restraints limit market growth. The high initial investment cost for advanced GIS software and the requirement for skilled professionals to operate these systems can be a barrier, especially for smaller organizations. Additionally, data security and privacy concerns related to the handling of sensitive geographical information pose challenges to wider adoption. Market segmentation reveals strong growth in the cloud-based GIS segment, driven by its inherent advantages, while applications in urban planning and geological exploration lead the application-based segmentation. North America and Europe currently hold significant market shares, with strong growth potential in the Asia-Pacific region due to increasing infrastructure development and government investments. Leading companies like Esri, Hexagon, and Autodesk are shaping the market landscape through continuous innovation and competitive pricing strategies, while the emergence of open-source options like QGIS and GRASS GIS provides alternative, cost-effective solutions.

  16. The potential benefits of Citizen Science for Spatial Planning: an...

    • zenodo.org
    • data.niaid.nih.gov
    Updated Jun 11, 2024
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    Tom Goosse; Tom Goosse (2024). The potential benefits of Citizen Science for Spatial Planning: an exploratory analysis of 22 Belgian and Dutch cases [Dataset]. http://doi.org/10.5281/zenodo.11567204
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    Dataset updated
    Jun 11, 2024
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Tom Goosse; Tom Goosse
    License

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

    Description

    We analysed 22 Belgian and Dutch citizen science cases to explore the potential benefits of citizen science for spatial planning. The 22 cases are described in descriptive fiches following a common framework and further studied on a CSV-file.

  17. Data from: Spatial Analysis of Crime in Appalachia [United States],...

    • catalog.data.gov
    • gimi9.com
    • +1more
    Updated Mar 12, 2025
    + more versions
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    National Institute of Justice (2025). Spatial Analysis of Crime in Appalachia [United States], 1977-1996 [Dataset]. https://catalog.data.gov/dataset/spatial-analysis-of-crime-in-appalachia-united-states-1977-1996-cd3d2
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    Dataset updated
    Mar 12, 2025
    Dataset provided by
    National Institute of Justicehttp://nij.ojp.gov/
    Area covered
    Appalachia, United States
    Description

    This research project was designed to demonstrate the contributions that Geographic Information Systems (GIS) and spatial analysis procedures can make to the study of crime patterns in a largely nonmetropolitan region of the United States. The project examined the extent to which the relationship between various structural factors and crime varied across metropolitan and nonmetropolitan locations in Appalachia over time. To investigate the spatial patterns of crime, a georeferenced dataset was compiled at the county level for each of the 399 counties comprising the Appalachian region. The data came from numerous secondary data sources, including the Federal Bureau of Investigation's Uniform Crime Reports, the Decennial Census of the United States, the Department of Agriculture, and the Appalachian Regional Commission. Data were gathered on the demographic distribution, change, and composition of each county, as well as other socioeconomic indicators. The dependent variables were index crime rates derived from the Uniform Crime Reports, with separate variables for violent and property crimes. These data were integrated into a GIS database in order to enhance the research with respect to: (1) data integration and visualization, (2) exploratory spatial analysis, and (3) confirmatory spatial analysis and statistical modeling. Part 1 contains variables for Appalachian subregions, Beale county codes, distress codes, number of families and households, population size, racial and age composition of population, dependency ratio, population growth, number of births and deaths, net migration, education, household composition, median family income, male and female employment status, and mobility. Part 2 variables include county identifiers plus numbers of total index crimes, violent index crimes, property index crimes, homicides, rapes, robberies, assaults, burglaries, larcenies, and motor vehicle thefts annually from 1977 to 1996.

  18. Geolocet | Administrative boundaries map data | Europe | Countries, Regions,...

    • datarade.ai
    Updated Nov 3, 2023
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    Geolocet (2023). Geolocet | Administrative boundaries map data | Europe | Countries, Regions, Provinces, Municipalities, and more | Fully customizable format [Dataset]. https://datarade.ai/data-products/geolocet-administrative-boundaries-map-data-europe-coun-geolocet
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    .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Nov 3, 2023
    Dataset authored and provided by
    Geolocet
    Area covered
    Belgium, Hungary, France, Italy, Luxembourg, United Kingdom, Latvia, Finland, Germany
    Description

    Geolocet's Administrative Boundaries Spatial Data serves as the gateway to visualizing geographic distributions and patterns with precision. The comprehensive dataset covers all European countries, encompassing the boundaries of each country, as well as its political and statistical divisions. Tailoring data purchases to exact needs is possible, allowing for the selection of individual levels of geography or bundling all levels for a country with a discount. The seamless integration of administrative boundaries onto digital maps transforms raw data into actionable insights.

    🌐 Coverage Across European Countries

    Geolocet's Administrative Boundaries Data offers coverage across all European countries, ensuring access to the most up-to-date and accurate geographic information. From national borders to the finest-grained administrative units, this data enables informed choices based on verified and official sources.

    🔍 Geographic Context for Strategic Decisions

    Understanding the geographical context is crucial for strategic decision-making. Geolocet's Administrative Boundaries Spatial Data empowers exploration of geo patterns, planning expansions, analysis of regional demographics, and optimization of operations with precision. Whether it is for establishing new business locations, efficient resource allocation, or policy impact analysis, this data provides the essential geographic context for success.

    🌍 Integration with Geolocet’s Demographic Data

    The integration of Geolocet's Administrative Boundaries Spatial Data with Geolocet's Demographic Data creates a synergy that enriches insights. The combination of administrative boundaries and demographic information offers a comprehensive understanding of regions and their unique characteristics. This integration enables tailoring of strategies, marketing campaigns, and resource allocation to specific areas with confidence.

    🌍 Integration with Geolocet’s POI Data

    Combining Geolocet's Administrative Boundaries Spatial Data with our POI (Points of Interest) Data unveils not only the administrative divisions but also insights into the local characteristics of these areas. Overlaying POI data on administrative boundaries reveals details about the number and types of businesses, services, and amenities within specific regions. Whether conducting market research, identifying prime locations for retail outlets, or analyzing the accessibility of essential services, this combined data empowers a holistic view of target areas.

    🔍 Customized Data Solutions with DaaS

    Geolocet's Data as a Service (DaaS) model offers flexibility tailored to specific needs. The transparent pricing model ensures cost-efficiency, allowing payment solely for the required data. Whether nationwide administrative boundary data or specific regional details are needed, Geolocet provides a solution to match individual objectives. Contact us today to explore how Geolocet's Administrative Boundaries Spatial Data can elevate decision-making processes and provide the essential geographic data for success.

  19. LACE Map for MEGA:BITESS Data Exploration

    • data-tga.opendata.arcgis.com
    • hub.arcgis.com
    Updated Jun 26, 2019
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    Tennessee Geographic Alliance (2019). LACE Map for MEGA:BITESS Data Exploration [Dataset]. https://data-tga.opendata.arcgis.com/maps/a5c7443265444924be2ad69d42b37ed6
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    Dataset updated
    Jun 26, 2019
    Dataset authored and provided by
    Tennessee Geographic Alliance
    Area covered
    Description

    This map is a proof of concept for participants in the MEGA:BITESS Academy to review data that may be relevant for spatial analysis. Knox County mosquito data is fictitious.

  20. G

    GIS Mapping Tools Report

    • marketreportanalytics.com
    doc, pdf, ppt
    Updated Apr 3, 2025
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    Market Report Analytics (2025). GIS Mapping Tools Report [Dataset]. https://www.marketreportanalytics.com/reports/gis-mapping-tools-54869
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    doc, ppt, pdfAvailable download formats
    Dataset updated
    Apr 3, 2025
    Dataset authored and provided by
    Market Report Analytics
    License

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

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

    The global GIS mapping tools market is experiencing robust growth, driven by increasing demand across diverse sectors. The market, estimated at $15 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033, reaching an estimated market value of approximately $45 billion by 2033. Key drivers include the rising adoption of cloud-based GIS solutions, enhanced data analytics capabilities, the proliferation of location-based services, and the growing need for precise spatial data analysis in various industries like urban planning, geological exploration, and water resource management. The market is segmented by application (Geological Exploration, Water Conservancy Projects, Urban Planning, Others) and type (Cloud-based, Web-based). Cloud-based solutions are gaining significant traction due to their scalability, accessibility, and cost-effectiveness. The increasing availability of high-resolution satellite imagery and advancements in artificial intelligence (AI) and machine learning (ML) are further fueling market expansion. While data security concerns and the high initial investment costs for some advanced solutions present restraints, the overall market outlook remains positive, with significant opportunities for both established players and emerging technology providers. Geographical expansion is another key aspect of market growth. North America and Europe currently hold a significant market share, owing to established GIS infrastructure and early adoption of advanced technologies. However, the Asia-Pacific region is expected to witness rapid growth in the coming years, driven by rising government investments in infrastructure development and increasing urbanization in countries like China and India. Competitive dynamics are shaping the market, with major players like Esri, Autodesk, Hexagon, and Mapbox competing on the basis of software features, data integration capabilities, and customer support. The emergence of open-source GIS solutions like QGIS and GRASS GIS is also challenging the dominance of proprietary software, offering cost-effective alternatives for various applications. The continued development and integration of advanced technologies like 3D mapping, real-time data visualization, and location intelligence will further enhance the capabilities of GIS mapping tools, driving market expansion and innovation across various sectors.

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Bingbo Gao (2025). A novel spatial prediction method integrating Exploratory Spatial Data Analysis into Random Forest for large scale daily air temperature mapping [Dataset]. https://ieee-dataport.org/documents/novel-spatial-prediction-method-integrating-exploratory-spatial-data-analysis-random

Data from: A novel spatial prediction method integrating Exploratory Spatial Data Analysis into Random Forest for large scale daily air temperature mapping

Related Article
Explore at:
Dataset updated
Mar 19, 2025
Authors
Bingbo Gao
License

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

Description

environmental management

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