Geospatial Data Analysis - GIS Techniques: Studying geographic information system (GIS) techniques for analyzing and visualizing spatial data for various applications
Keywords:
Geospatial data analysis, GIS techniquesAbstract
Geospatial data analysis plays a crucial role in understanding spatial relationships, patterns, and trends across various domains. Geographic Information Systems (GIS) provide a powerful framework for processing, analyzing, and visualizing geospatial data. This paper explores the fundamental GIS techniques used in geospatial data analysis, highlighting their applications in different fields such as urban planning, environmental management, and disaster response. The paper discusses key GIS concepts, data types, analysis methods, and visualization techniques. Additionally, it examines the challenges and future directions of GIS in geospatial data analysis, emphasizing the importance of GIS in decision-making processes for sustainable development.
Downloads
References
Vemoori, Vamsi. "Transformative Impact of Advanced Driver-Assistance Systems (ADAS) on Modern Mobility: Leveraging Sensor Fusion for Enhanced Perception, Decision-Making, and Cybersecurity in Autonomous Vehicles." Journal of AI-Assisted Scientific Discovery 3.2 (2023): 17-61.
Ponnusamy, Sivakumar, and Dinesh Eswararaj. "Navigating the Modernization of Legacy Applications and Data: Effective Strategies and Best Practices." Asian Journal of Research in Computer Science 16.4 (2023): 239-256.
Pulimamidi, Rahul. "Emerging Technological Trends for Enhancing Healthcare Access in Remote Areas." Journal of Science & Technology 2.4 (2021): 53-62.
Tillu, Ravish, Muthukrishnan Muthusubramanian, and Vathsala Periyasamy. "From Data to Compliance: The Role of AI/ML in Optimizing Regulatory Reporting Processes." Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online) 2.3 (2023): 381-391.
K. Joel Prabhod, “ASSESSING THE ROLE OF MACHINE LEARNING AND COMPUTER VISION IN IMAGE PROCESSING,” International Journal of Innovative Research in Technology, vol. 8, no. 3, pp. 195–199, Aug. 2021, [Online]. Available: https://ijirt.org/Article?manuscript=152346
Tatineni, Sumanth. "Applying DevOps Practices for Quality and Reliability Improvement in Cloud-Based Systems." Technix international journal for engineering research (TIJER)10.11 (2023): 374-380.
Perumalsamy, Jegatheeswari, Bhavani Krothapalli, and Chandrashekar Althati. "Machine Learning Algorithms for Customer Segmentation and Personalized Marketing in Life Insurance: A Comprehensive Analysis." Journal of Artificial Intelligence Research 2.2 (2022): 83-123.
Venkatasubbu, Selvakumar, Subhan Baba Mohammed, and Monish Katari. "AI-Driven Storage Optimization in Embedded Systems: Techniques, Models, and Real-World Applications." Journal of Science & Technology 4.2 (2023): 25-64.
Devan, Munivel, Bhavani Krothapalli, and Lavanya Shanmugam. "Advanced Machine Learning Algorithms for Real-Time Fraud Detection in Investment Banking: A Comprehensive Framework." Cybersecurity and Network Defense Research 3.1 (2023): 57-94.
Keerthika, R., and Ms SS Abinayaa, eds. Algorithms of Intelligence: Exploring the World of Machine Learning. Inkbound Publishers, 2022.
Althati, Chandrashekar, Bhavani Krothapalli, and Bhargav Kumar Konidena. "Machine Learning Solutions for Data Migration to Cloud: Addressing Complexity, Security, and Performance." Australian Journal of Machine Learning Research & Applications 1.2 (2021): 38-79.
Pakalapati, Naveen, Bhargav Kumar Konidena, and Ikram Ahamed Mohamed. "Unlocking the Power of AI/ML in DevSecOps: Strategies and Best Practices." Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online) 2.2 (2023): 176-188.
Katari, Monish, Musarath Jahan Karamthulla, and Munivel Devan. "Enhancing Data Security in Autonomous Vehicle Communication Networks." Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online) 2.3 (2023): 496-521.
Krishnamoorthy, Gowrisankar, and Sai Mani Krishna Sistla. "Exploring Machine Learning Intrusion Detection: Addressing Security and Privacy Challenges in IoT-A Comprehensive Review." Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online) 2.2 (2023): 114-125.
Reddy, Sai Ganesh, et al. "Harnessing the Power of Generative Artificial Intelligence for Dynamic Content Personalization in Customer Relationship Management Systems: A Data-Driven Framework for Optimizing Customer Engagement and Experience." Journal of AI-Assisted Scientific Discovery 3.2 (2023): 379-395.
Prabhod, Kummaragunta Joel. "Advanced Machine Learning Techniques for Predictive Maintenance in Industrial IoT: Integrating Generative AI and Deep Learning for Real-Time Monitoring." Journal of AI-Assisted Scientific Discovery 1.1 (2021): 1-29.
Tembhekar, Prachi, Lavanya Shanmugam, and Munivel Devan. "Implementing Serverless Architecture: Discuss the practical aspects and challenges." Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online) 2.3 (2023): 560-580.
Devan, Munivel, Kumaran Thirunavukkarasu, and Lavanya Shanmugam. "Algorithmic Trading Strategies: Real-Time Data Analytics with Machine Learning." Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online) 2.3 (2023): 522-546.
Tatineni, Sumanth, and Karthik Allam. "Implementing AI-Enhanced Continuous Testing in DevOps Pipelines: Strategies for Automated Test Generation, Execution, and Analysis." Blockchain Technology and Distributed Systems 2.1 (2022): 46-81.
Sadhu, Ashok Kumar Reddy, and Amith Kumar Reddy. "A Comparative Analysis of Lightweight Cryptographic Protocols for Enhanced Communication Security in Resource-Constrained Internet of Things (IoT) Environments." African Journal of Artificial Intelligence and Sustainable Development 2.2 (2022): 121-142.
Makka, A. K. A. “Optimizing SAP Basis Administration for Advanced Computer Architectures and High-Performance Data Centers”. Journal of Science & Technology, vol. 1, no. 1, Oct. 2020, pp. 242-279, https://thesciencebrigade.com/jst/article/view/282.
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
License Terms
Ownership and Licensing:
Authors of research papers submitted to Distributed Learning and Broad Applications in Scientific Research retain the copyright of their work while granting the journal certain rights. Authors maintain ownership of the copyright and have granted the journal a right of first publication. Simultaneously, authors agree to license their research papers under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) License.
License Permissions:
Under the CC BY-NC-SA 4.0 License, others are permitted to share and adapt the work, as long as proper attribution is given to the authors and acknowledgement is made of the initial publication in the journal. This license allows for the broad dissemination and utilization of research papers.
Additional Distribution Arrangements:
Authors are free to enter into separate contractual arrangements for the non-exclusive distribution of the journal's published version of the work. This may include posting the work to institutional repositories, publishing it in journals or books, or other forms of dissemination. In such cases, authors are requested to acknowledge the initial publication of the work in this journal.
Online Posting:
Authors are encouraged to share their work online, including in institutional repositories, disciplinary repositories, or on their personal websites. This permission applies both prior to and during the submission process to the journal. Online sharing enhances the visibility and accessibility of the research papers.
Responsibility and Liability:
Authors are responsible for ensuring that their research papers do not infringe upon the copyright, privacy, or other rights of any third party. Scientific Research Canada disclaims any liability or responsibility for any copyright infringement or violation of third-party rights in the research papers.
If you have any questions or concerns regarding these license terms, please contact us at editor@dlabi.org.
