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  1. Bivariate Time Series Analysis

    Analysis of bivariate time series is necessary for detecting teleconnections and reconstructing climate but it is almost always done in natural...
    Chapter 2023
  2. Analysis of Trivariate Time Series

    The trivariate case presents an important transfer to really multivariate time series. It includes frequency domain characteristics which have not...
    Chapter 2023
  3. Gap-filling missing data in time series using the correlation matrix method of multiple time series in Asadabad Plain, Iran

    Groundwater resources are crucial sources of water supply, and preserving the quality of these resources is an undeniable necessity. On the other...

    Hamed Nozari, Ali Vanaei, Fatemeh Faraji in Sustainable Water Resources Management
    Article 24 November 2023
  4. Analysis of Scalar Time Series

    The basics of theory of random processes including the concepts of stationarity, ergodicity, and linearity are given in simple form to help user to...
    Chapter 2023
  5. Practical Time Series Analysis in Natural Sciences



    This book presents an easy-to-use tool for time series analysis and allows the user to concentrate upon studying time series properties rather than...

    Victor Privalsky in Progress in Geophysics
    Book 2023
  6. Seasonal components in GPS displacement time series

    We present a simple method for identification of seasonal components in GPS displacement time series. The method considers two options for the...

    F. Alejandro Nava, Lenin Ávila-Barrientos in Acta Geophysica
    Article 12 December 2023
  7. Reconstruction of geodetic time series with missing data and time-varying seasonal signals using Gaussian process for machine learning

    Seasonal signals in satellite geodesy time series are mainly derived from a number of loading sources, such as atmospheric pressure and hydrological...

    Keke Xu, Shaobin Hu, ... Yifu Liu in GPS Solutions
    Article 29 February 2024
  8. Minimum-entropy velocity estimation from GPS position time series

    We propose a nonparametric minimum entropy method for estimating an optimal velocity from position time series, which may contain unknown noise, data...

    Jarir Saleh, Richard A. Bennett, Simon D. P. Williams in Journal of Geodesy
    Article 02 February 2024
  9. Causal inference for time series

    Many research questions in Earth and environmental sciences are inherently causal, requiring robust analyses to establish whether and how changes in...

    Jakob Runge, Andreas Gerhardus, ... Gustau Camps-Valls in Nature Reviews Earth & Environment
    Article 27 June 2023
  10. Identify Landslide Precursors from Time Series InSAR Results

    Landslides cause huge human and economic losses globally. Detecting landslide precursors is crucial for disaster prevention. The small baseline...

    Meng Liu, Wentao Yang, ... Peijun Shi in International Journal of Disaster Risk Science
    Article Open access 10 January 2024
  11. Strategies to remove hydrological effects in continuous gravity time series

    Multi-annual gravity time series offer a unique, noninvasive way to monitor mass redistributions within the Earth. However, for non-hydrological...

    Maxime Mouyen in Journal of Geodesy
    Article Open access 27 October 2023
  12. Moving Trend Analysis Methodology for Hydro-meteorology Time Series Dynamic Assessment

    In the last 30 years, there are many publications in the literature due to global warming and climate change impacts exhibiting non-stationary...

    Article Open access 15 May 2024
  13. Time Series Forecasting of Indian Coal Mines Fatal Accidents

    Abstract

    The present study analyzes the fatal accident occurrences of seventy years from 1951 to 2020 in Indian coal mines. The autoregressive...

    Abinash Mohanty, Devidas S. Nimaje in Journal of Mining Science
    Article 01 December 2023
  14. Time Series Analysis

    Abraão D. C. Nascimento in Encyclopedia of Mathematical Geosciences
    Reference work entry 2023
  15. Extended singular spectrum analysis for processing incomplete heterogeneous geodetic time series

    The singular spectrum analysis (SSA) is a powerful tool to de-noise the geodetic time series and extract geophysical signals of interest. However,...

    Kunpu Ji, Yunzhong Shen, ... Fengwei Wang in Journal of Geodesy
    Article 04 August 2023
  16. Modeling trends and periodic components in geodetic time series: a unified approach

    Geodetic time series are usually modeled with a deterministic approach that includes trend, annual, and semiannual periodic components having...

    Gaël Kermarrec, Federico Maddanu, ... Janusz Bogusz in Journal of Geodesy
    Article Open access 04 March 2024
  17. Neural network based system in evapotranspiration time series prediction

    Evapotranspiration is a very important process of the water cycle. Thus, the ability to model and understand evolution of this process is very...

    Predrag Popović, Milan Gocić, ... Slaviša Trajković in Earth Science Informatics
    Article 08 February 2023
  18. Time Series Analysis

    Time series analysis is used to investigate the temporal behavior of a variable x(t). Examples include investigations into long-term records of...
    Martin H. Trauth in Python Recipes for Earth Sciences
    Chapter 2022
  19. Time series modelling: applications for groundwater control in urban tunnelling

    Water ingress to tunnels may result in pore pressure drawdown and consolidation settlements in areas above tunnels founded on soft soil deposits,...

    Eivind Stein, Jenny Langford, Mats Kahlström in Bulletin of Engineering Geology and the Environment
    Article Open access 25 September 2023
  20. Anatomy of the spatiotemporally correlated noise in GNSS station position time series

    Global Navigation Satellite Systems (GNSS) enable the determination of station displacements, which are essential to understanding geophysical...

    Kevin Gobron, Paul Rebischung, ... Zuheir Altamimi in Journal of Geodesy
    Article 30 April 2024
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