The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Digital Archiving Policy
  • Promote your Publication
  • Metadata Harvesting (OAI2)

IJACSA

  • About the Journal
  • Call for Papers
  • Editorial Board
  • Author Guidelines
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Fees/ APC
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Proposals
  • Guest Editors
  • SUSAI-EE 2025
  • ICONS-BA 2025
  • IoT-BLOCK 2025

Future of Information and Communication Conference (FICC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Editorial Board
  • Guidelines
  • Submit
  • Current Issue
  • Archives
  • Indexing
  • Fees
  • Reviewers
  • Subscribe

DOI: 10.14569/IJACSA.2022.0130743
PDF

Novel Approach for Spatiotemporal Weather Data Analysis

Author 1: Radhika T V
Author 2: K C Gouda
Author 3: S Sathish Kumar

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 13 Issue 7, 2022.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: Massive volumes of multidimensional array-based spatiotemporal data are generated by climate observations and model simulations. The growth in climate data leads to new opportunities for climate studies at multiple spatial and temporal scales. Managing, analyzing and processing of big climate data is considered to be challenging because of huge data volume. In this work multidimensional climate data such as precipitation and temperature are processed and analyzed in the Spark MapReduce Platform, since Spark platform is computationally more efficient than Hadoop-MapReduce Platform of same configuration. In temporal scale monthly and seasonal analysis of climate data has been carried out to understand the regional climate. The prediction of Rainfall on monthly and seasonal time scales is very much important for planning and devising agricultural strategies and disaster management, etc. As the prediction of climate state is very challenging, in this study an attempt is being made for the prediction of the rainfall using the time series analysis in the same framework. As a test case the time series approach such as Auto Regression Integrated Moving Average (ARIMA) has been used for the prediction of rainfall. The proposed approach is evaluated and found to be accurate in the analysis and prediction of climate data and this will surely guide for the researcher for better understanding of the climate and its application to multiple sectors.

Keywords: Spatiotemporal; big climate data; spark; ARIMA

Radhika T V, K C Gouda and S Sathish Kumar, “Novel Approach for Spatiotemporal Weather Data Analysis” International Journal of Advanced Computer Science and Applications(IJACSA), 13(7), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0130743

@article{V2022,
title = {Novel Approach for Spatiotemporal Weather Data Analysis},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0130743},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0130743},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {7},
author = {Radhika T V and K C Gouda and S Sathish Kumar}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

IJACSA

Upcoming Conferences

IntelliSys 2025

28-29 August 2025

  • Amsterdam, The Netherlands

Future Technologies Conference 2025

6-7 November 2025

  • Munich, Germany

Healthcare Conference 2026

21-22 May 2026

  • Amsterdam, The Netherlands

Computing Conference 2026

9-10 July 2026

  • London, United Kingdom

IntelliSys 2026

3-4 September 2026

  • Amsterdam, The Netherlands

Computer Vision Conference 2026

15-16 October 2026

  • Berlin, Germany
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference
  • Communication Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© The Science and Information (SAI) Organization Limited. All rights reserved. Registered in England and Wales. Company Number 8933205. thesai.org