Exploring the integration of big data analytics in landscape visualization and interaction design (2024)

research-article

Free Access

  • Authors:
  • Xiaoqing Yang https://ror.org/04mw2ty13College of Art and Design, Anhui Institute of Information Technology, 241199, Wuhu, Anhui, China

    https://ror.org/04mw2ty13College of Art and Design, Anhui Institute of Information Technology, 241199, Wuhu, Anhui, China

    Search about this author

    ,
  • Roopesh Sitharan https://ror.org/04zrbnc33Faculty of Creative Multimedia, Multimedia University, 63100, Selangor, Malaysia

    https://ror.org/04zrbnc33Faculty of Creative Multimedia, Multimedia University, 63100, Selangor, Malaysia

    Search about this author

    ,
  • Elyna Amir Sharji https://ror.org/04zrbnc33Faculty of Creative Multimedia, Multimedia University, 63100, Selangor, Malaysia

    https://ror.org/04zrbnc33Faculty of Creative Multimedia, Multimedia University, 63100, Selangor, Malaysia

    Search about this author

    ,
  • He Feng https://ror.org/007cx7r28College of Arts and Education, Chizhou University, 247000, Chizhou, Anhui, China

    https://ror.org/007cx7r28College of Arts and Education, Chizhou University, 247000, Chizhou, Anhui, China

    Search about this author

Soft Computing - A Fusion of Foundations, Methodologies and ApplicationsVolume 28Issue 3Feb 2024pp 1971–1988https://doi.org/10.1007/s00500-023-09570-2

Published:08 January 2024Publication History

  • 0citation
  • 0
  • Downloads

Metrics

Total Citations0Total Downloads0

Last 12 Months0

Last 6 weeks0

Soft Computing - A Fusion of Foundations, Methodologies and Applications

Volume 28, Issue 3

PreviousArticleNextArticle

Exploring the integration of big data analytics in landscape visualization and interaction design (2)

Skip Abstract Section

Abstract

Abstract

The exponential growth of urban data presents significant challenges in efficiently analyzing and gaining actionable insights for urban planning and design. This paper proposes a big data analytics framework using MapReduce-based parallel FP-growth (MP-PFP) algorithm leveraging tools like Hadoop, MapReduce, and distributed crawlers to uncover patterns and trends from large-scale, heterogeneous urban datasets. A key contribution is the integration of diverse data types, from socio-economic datasets to environmental parameters, into a consistent analysis framework. The methodology employs frequent pattern mining algorithms on a scalable analytics platform to process behavior data and derive planning directives. Additionally, data visualization and parametric analysis techniques transform raw statistics into interactive 3D landscape representations that expose environmental site attributes. Specifically, the MapReduce capabilities enable distributed parallel processing of vast urban data volumes, ensuring speed and efficiency. The data visualization module creates immersive VR representations of urban landscapes, allowing interactive modifications. Advanced simulation techniques are incorporated to model the impact of planning directives on multiple landscape attributes. The framework is designed as a scalable, customizable solution that can integrate diverse urban data sources with customizable analytics, modeling and visualization modules through APIs. Comparative evaluations demonstrate a classification accuracy improvement from 68 to 93% over prevailing approaches. The framework has proven superior in data integration, real-time responsiveness, and accurately modeling the dynamic complexities of urban landscapes. The quantifiable simulations empower designers to make more informed planning decisions aligned with community needs. Despite ongoing data accuracy and privacy concerns, the methodology shows promising capabilities in harnessing urban big data to drive intelligent, sustainable urban development through its integration of data-driven insights, computational analysis, and interactive visualization. It brings impactful innovations to the future of urban informatics and planning.

References

  1. Abawajy JComprehensive analysis of big data variety landscapeInt J Parallel Emerg Distrib Syst2015301514333372610.1080/17445760.2014.925548Google ScholarExploring the integration of big data analytics in landscape visualization and interaction design (3)Digital Library
  2. Abbas RGu NImproving deep learning-based image super-resolution with residual learning and perceptual loss using SRGAN modelSoft Comput20232721160411605710.1007/s00500-023-09126-4Google ScholarExploring the integration of big data analytics in landscape visualization and interaction design (5)Digital Library
  3. Ali MYin BBilal Het al.Advanced efficient strategy for detection of dark objects based on spiking network with multi-box detectionMultimed Tools Appl202310.1007/s11042-023-16852-2Google ScholarExploring the integration of big data analytics in landscape visualization and interaction design (7)Cross Ref
  4. Andronie MLăzăroiu GIatagan MHurloiu IŞtefănescu RDijmărescu ADijmărescu IBig data management algorithms, deep learning-based object detection technologies, and geospatial simulation and sensor fusion tools in the internet of robotic thingsISPRS Int J Geo Inf20231223510.3390/ijgi12020035Google ScholarExploring the integration of big data analytics in landscape visualization and interaction design (9)Cross Ref
  5. Aslam MSL2–L∞ control for delayed singular markov switch system with nonlinear actuator faultsInt J Fuzzy Syst20212372297230810.1007/s40815-021-01102-0Google ScholarExploring the integration of big data analytics in landscape visualization and interaction design (11)Cross Ref
  6. Awaysheh FMAladwan MNAlazab MAlawadi SCabaleiro JCPena TFSecurity by design for big data frameworks over cloud computingIEEE Trans Eng Manag20216963676369310.1109/TEM.2020.3045661Google ScholarExploring the integration of big data analytics in landscape visualization and interaction design (13)Cross Ref
  7. Awaysheh FMAlazab MGarg SNiyato DVerikoukis CBig data resource management & networks: taxonomy, survey, and future directionsIEEE Commun Surv Tutor20212342098213010.1109/COMST.2021.3094993Google ScholarExploring the integration of big data analytics in landscape visualization and interaction design (15)Cross Ref
  8. Berglund EZMonroe JGAhmed INoghabaei MDo JPesantez JEKhaksarFasaee MABardaka EHan KProestos GTLevis JSmart infrastructure: a vision for the role of the civil engineering profession in smart citiesJ Infrastruct Syst20202620312000110.1061/(ASCE)IS.1943-555X.0000549Google ScholarExploring the integration of big data analytics in landscape visualization and interaction design (17)Cross Ref
  9. Chen ZObserver-based dissipative output feedback control for network T-S fuzzy systems under time delays with mismatch premiseNonlinear Dyn2019952923294110.1007/s11071-018-4732-xGoogle ScholarExploring the integration of big data analytics in landscape visualization and interaction design (19)Cross Ref
  10. Chen JVisual design of landscape architecture based on high-density three-dimensional internet of thingsComplexity2021202111210.1155/2021/2574025Google ScholarExploring the integration of big data analytics in landscape visualization and interaction design (21)Digital Library
  11. Dai XHou JLi QUllah RNi ZLiu YReliable control design for composite-driven scheme based on delay networked T-S fuzzy systemInt J Robust Nonlinear Control202030416221642408539310.1002/rnc.4839Google ScholarExploring the integration of big data analytics in landscape visualization and interaction design (23)Cross Ref
  12. Dou HLiu YChen Set al.A hybrid CEEMD-GMM scheme for enhancing the detection of traffic flow on highwaysSoft Comput202327163731638810.1007/s00500-023-09164-yGoogle ScholarExploring the integration of big data analytics in landscape visualization and interaction design (25)Digital Library
  13. Fialová JBamwesigye DŁukaszkiewicz JFortuna-Antoszkiewicz BSmart cities landscape and urban planning for sustainability in Brno CityLand202110887010.3390/land10080870Google ScholarExploring the integration of big data analytics in landscape visualization and interaction design (27)Cross Ref
  14. Gui Z, Wang Y, Li F, Tian S, Peng D, Cui Z (2020) High performance spatiotemporal visual analytics technologies and its applications in big socioeconomic data analysis. In: Spatial synthesis: computational social science and humanities, pp 221–255Google ScholarExploring the integration of big data analytics in landscape visualization and interaction design (29)
  15. Guo STang JLiu HGu XStudy on landscape architecture model design based on big data intelligenceBig Data Res20212510.1016/j.bdr.2021.100219Google ScholarExploring the integration of big data analytics in landscape visualization and interaction design (30)Digital Library
  16. Hassan MAwan FMNaz AdeAndrés-Galiana EJAlvarez OCernea AFernández-Brillet LFernández-Martínez JLKloczkowski AInnovations in genomics and big data analytics for personalized medicine and health care: a reviewInt J Mol Sci2022239464510.3390/ijms23094645Google ScholarExploring the integration of big data analytics in landscape visualization and interaction design (32)Cross Ref
  17. Hernández-de-Menéndez MMorales-Menendez REscobar CARamírez Mendoza RALearning analytics: state of the artInt J Interact Design Manuf (IJIDeM)20221631209123010.1007/s12008-022-00930-0Google ScholarExploring the integration of big data analytics in landscape visualization and interaction design (34)Cross Ref
  18. Huang YZhang YResearch on digital application of lighting design in public space based on cloud computing and data miningWirel Commun Mob Comput20212021112Google ScholarExploring the integration of big data analytics in landscape visualization and interaction design (36)
  19. Iqbal MJ, Farhan M, Ullah F, Srivastava G, Jabbar S (2023) Intelligent multimedia content delivery in 5G/6G networks: a reinforcement learning approach. In: Transactions on emerging telecommunications technologies, p e4842Google ScholarExploring the integration of big data analytics in landscape visualization and interaction design (37)
  20. Ismail A, Mutalib S, Haron H (2023) Data science technology course: the design, assessment and computing environment perspectives. In: Education and information technologies, pp 1–26Google ScholarExploring the integration of big data analytics in landscape visualization and interaction design (38)
  21. Karimi YHaghiKashani MAkbari MMahdipour ELeveraging big data in smart cities: a systematic reviewConcurr Comput Pract Exp2021332110.1002/cpe.6379Google ScholarExploring the integration of big data analytics in landscape visualization and interaction design (39)Cross Ref
  22. Li QHou JFault detection for asynchronous T-S fuzzy networked Markov jump systems with new event-triggered schemeIET Control Theory Appl2021151114611473458335110.1049/cth2.12136Google ScholarExploring the integration of big data analytics in landscape visualization and interaction design (41)Cross Ref
  23. Li XZhang DZheng YHong WWang WXia JLv ZEvolutionary computation-based machine learning for smart city high-dimensional big data analyticsAppl Soft Comput202313310.1016/j.asoc.2022.109955Google ScholarExploring the integration of big data analytics in landscape visualization and interaction design (43)Digital Library
  24. Litimein H, Huang ZY, Aslam MS (2023) Circular formation control with collision avoidance based on probabilistic position. Intell Autom Soft Comput 37(1)Google ScholarExploring the integration of big data analytics in landscape visualization and interaction design (45)
  25. Lovett AAppleton KWarren-Kretzschmar BVon Haaren CUsing 3D visualization methods in landscape planning: an evaluation of options and practical issuesLandsc Urban Plan2015142859410.1016/j.landurbplan.2015.02.021Google ScholarExploring the integration of big data analytics in landscape visualization and interaction design (46)Cross Ref
  26. Mathrani SLai XBig data analytic framework for organizational leverageAppl Sci2021115234010.3390/app11052340Google ScholarExploring the integration of big data analytics in landscape visualization and interaction design (48)Cross Ref
  27. Mortaheb RJankowski PSmart city re-imagined: city planning and GeoAI in the age of big dataJ Urban Manag202312141510.1016/j.jum.2022.08.001Google ScholarExploring the integration of big data analytics in landscape visualization and interaction design (50)Cross Ref
  28. Muhammad SAQaisar IMajid AShamrooz SAdaptive event-triggered robust H∞ control for Takagi–Sugeno fuzzy networked Markov jump systems with time-varying delayAsian J Control2023251213228456232910.1002/asjc.2762Google ScholarExploring the integration of big data analytics in landscape visualization and interaction design (52)Cross Ref
  29. Qaisar IMajid ARamaraj PDesign of sliding mode controller for sensor/actuator fault with unknown input observer for satellite control systemSoft Comput20212524149931500310.1007/s00500-021-06420-xGoogle ScholarExploring the integration of big data analytics in landscape visualization and interaction design (54)Digital Library
  30. Saçak BBozkurt AWagner ELearning design versus instructional design: a bibliometric study through data visualization approachesEduc Sci2022121175210.3390/educsci12110752Google ScholarExploring the integration of big data analytics in landscape visualization and interaction design (56)Cross Ref
  31. Sadhu APeplinski JEMohammadkhorasani AMoreu FA review of data management and visualization techniques for structural health monitoring using BIM and virtual or augmented realityJ Struct Eng202314910312200610.1061/(ASCE)ST.1943-541X.0003498Google ScholarExploring the integration of big data analytics in landscape visualization and interaction design (58)Cross Ref
  32. Shamrooz MA, Zhenhua MA (2023) Output regulation for time–delayed Takagi–Sugeno fuzzy model with networked control system. Hacettepe J Math Stat 1–21Google ScholarExploring the integration of big data analytics in landscape visualization and interaction design (60)
  33. Ullah RDai XSheng AEvent-triggered scheme for fault detection and isolation of non-linear system with time-varying delayIET Control Theory Appl2020141624292438441797310.1049/iet-cta.2018.5469Google ScholarExploring the integration of big data analytics in landscape visualization and interaction design (61)Cross Ref
  34. Ullah RLi YAslam MSSheng AEvent-triggered dissipative observer-based control for delay dependent T-S fuzzy singular systemsIEEE Access2020813427613428910.1109/ACCESS.2020.3011281Google ScholarExploring the integration of big data analytics in landscape visualization and interaction design (63)Cross Ref
  35. Vischioni CBove FMandreoli FMartoglia RPisi VTaccioli CVisual exploratory data analysis for copy number variation studies in biomedical researchBig Data Res20222710.1016/j.bdr.2021.100298Google ScholarExploring the integration of big data analytics in landscape visualization and interaction design (65)Digital Library
  36. Wu HLi GVisual communication design elements of internet of things based on cloud computing applied in graffiti art schemaSoft Comput2020248077808610.1007/s00500-019-04171-4Google ScholarExploring the integration of big data analytics in landscape visualization and interaction design (67)Digital Library
  37. Wu QLi XWang Ket al.Regional feature fusion for on-road detection of objects using camera and 3D-LiDAR in high-speed autonomous vehiclesSoft Comput202327181951821310.1007/s00500-023-09278-3Google ScholarExploring the integration of big data analytics in landscape visualization and interaction design (69)Digital Library
  38. Zhang CZeng WLiu LUrbanVR: An immersive analytics system for context-aware urban designComput Graph20219912813810.1016/j.cag.2021.07.006Google ScholarExploring the integration of big data analytics in landscape visualization and interaction design (71)Digital Library
  39. Zhenhua MUllah RLi YSheng AMajid AStability and admissibility analysis of T-S descriptive systems and its applicationsSoft Comput202226157159716610.1007/s00500-022-07323-1Google ScholarExploring the integration of big data analytics in landscape visualization and interaction design (73)Digital Library

Cited By

View all

Exploring the integration of big data analytics in landscape visualization and interaction design (75)

    Index Terms

    1. Exploring the integration of big data analytics in landscape visualization and interaction design
      1. Computing methodologies

        1. Human-centered computing

          1. Visualization

            1. Visualization application domains

          2. Information systems

            1. Information systems applications

              1. Spatial-temporal systems

          Index terms have been assigned to the content through auto-classification.

          Recommendations

          • Big Data Management: Advanced Issues and Approaches

            The objective of this article is to provide the advanced issues and approaches of big data management. The literature review indicates the overview of big data management; the aspects of Big Data Analytics BDA; the importance of big data management; the ...

            Read More

          • Energy-efficient hadoop for big data analytics and computing: A systematic review and research insights

            Abstract

            As the demands for big data analytics keep growing rapidly in scientific applications and online services, MapReduce and its open-source implementation Hadoop gained popularity in both academia and enterprises. Hadoop provides a highly feasible ...

            Highlights

            • This paper presents the new viewpoints/insights in improving the energy efficiency of Hadoop.
            • Present valuable and feasible solutions towards improving the energy efficiency of Hadoop.
            • Propose five categories of optimizing the ...

            Read More

          • Responsible Big Data Analytics for E-Business Services

            ICBDR '21: Proceedings of the 5th International Conference on Big Data Research

            This paper examines responsible big data analytics for e-business services and looks at how to use responsible big data analytics to obtain responsible e-business services. It addresses why responsibility matters to big data analytics and e-business ...

            Read More

          Login options

          Check if you have access through your login credentials or your institution to get full access on this article.

          Sign in

          Full Access

          Get this Article

          • Information
          • Contributors
          • Published in

            Exploring the integration of big data analytics in landscape visualization and interaction design (76)

            Soft Computing - A Fusion of Foundations, Methodologies and Applications Volume 28, Issue 3

            Feb 2024

            909 pages

            ISSN:1432-7643

            EISSN:1433-7479

            Issue’s Table of Contents

            © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

            Sponsors

              In-Cooperation

                Publisher

                Springer-Verlag

                Berlin, Heidelberg

                Publication History

                • Published: 8 January 2024
                • Accepted: 8 December 2023

                Author Tags

                • Big data analytics
                • Landscape design
                • Data visualization
                • Urban planning
                • Hadoop
                • MapReduce

                Qualifiers

                • research-article

                Conference

                Funding Sources

                • Exploring the integration of big data analytics in landscape visualization and interaction design (77)

                  Other Metrics

                  View Article Metrics

                • Bibliometrics
                • Citations0
                • Article Metrics

                  • Total Citations

                    View Citations
                  • Total Downloads

                  • Downloads (Last 12 months)0
                  • Downloads (Last 6 weeks)0

                  Other Metrics

                  View Author Metrics

                • Cited By

                  This publication has not been cited yet

                Digital Edition

                View this article in digital edition.

                View Digital Edition

                • Figures
                • Other

                  Close Figure Viewer

                  Browse AllReturn

                  Caption

                  View Issue’s Table of Contents

                  Export Citations

                    Exploring the integration of big data analytics in landscape visualization and interaction design (2024)

                    References

                    Top Articles
                    Latest Posts
                    Article information

                    Author: Madonna Wisozk

                    Last Updated:

                    Views: 6118

                    Rating: 4.8 / 5 (68 voted)

                    Reviews: 83% of readers found this page helpful

                    Author information

                    Name: Madonna Wisozk

                    Birthday: 2001-02-23

                    Address: 656 Gerhold Summit, Sidneyberg, FL 78179-2512

                    Phone: +6742282696652

                    Job: Customer Banking Liaison

                    Hobby: Flower arranging, Yo-yoing, Tai chi, Rowing, Macrame, Urban exploration, Knife making

                    Introduction: My name is Madonna Wisozk, I am a attractive, healthy, thoughtful, faithful, open, vivacious, zany person who loves writing and wants to share my knowledge and understanding with you.