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Land OA journal Special Issue "Time Series Analysis by Focusing on Climate-Land Interactions Variables"

Special Issue "Time Series Analysis by Focusing on Climate-Land Interactions Variables" Time series analysis is a statistical technique that deals with time series data or trend analysis. Accurate results of forecasting in time series modelling can be helpful for classification, regression, prediction, and also numerical computation. Notably, research on time series forecasting has led to advances in many statistical and numerical methods.

The machine learning approach is a robust tool for forecasting real-world problems, especially time-series-based problems such as land systems, climate variables, soil temperature, sediment, streamflow, reservoir inflow, etc. The application of machine learning in the time series analysis area has proven very useful in addressing the complexity of computation. The systematic use of machine learning with particular focus on deep learning is receiving much attention, as is time series analysis for modeling, classification, clustering, trend analysis and forecasting solutions in land studies.

In this Special Issue, we would like to encourage people to contribute their latest developments, ideas and review articles on climate–land-based time series forecasting and its applications. This Special Issue will focus on essential climate–land-based applications in the time series analysis sector. Topics include, but are not limited to, the following:

  • Time series forecasting for climate–land interactions;
  • Application of time series analysis in soil, sediment, and water systems;
  • Data mining methods in time series analysis for land management;
  • Climate–land-based time series forecasting and its applications;
  • Application of spatial–temporal statistical analysis in land cover studies;
  • Time series forecasting in renewable energy and its impact on land (wind power, solar radiation, and hydropower);
  • Applied new approaches for time series analysis in land systems science.

Keywords

  • climate–land
  • time series forecasting
  • land cover
  • land–energy prediction
  • machine learning
  • data mining in land management
  • A special issue of Land (ISSN 2073-445X).

    Deadline for manuscript submissions: 11 November 2021.

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