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Editorial Board Members' Collection Series: Forest Remote Sensing

This special issue belongs to the section “Remote Sensors“.

Special Issue Information

Dear Colleagues,

Remote sensing has been used in a diverse range of fields, such as forest monitoring and ecology, supporting management applications from mapping spatio-temporal forest dynamics (compositions and structures), to the estimation of forest variables or their integration into modeling systems. Technological development, integration and adoption in forestry continues to grow; therefore, the application of advanced forest remote sensing technology has become the current focus in the research into the development of forest observation and information systems.

The aim of this Special Issue is to present the new research and developments in the field. We invite original contributions that demonstrate the current research trends. The topics of this Special Issue may include the following:

  • Hydroclimatic and ecological models and simulations driven by satellite data in forests;
  • Integration of EO data with in situ field observations;
  • Monitoring and spatial estimation of ecosystem services (carbon, biodiversity, landscape, soil protection, etc.);
  • Development of new methods for the processing and analysis of EO data;
  • Applications of Earth observation techniques for monitoring forest disturbances and dynamics;
  • Applications of remote sensing to support sustainable forest resource management;
  • Big data processing for large-scale relevant EO data analysis;
  • Artificial Intelligence frameworks for the extraction of valuable signals for disaster risk management and forecasting in forestry using large sets of EO data.

Prof. Dr. Gherardo Chirici 
Dr. Antonio Pepe
Guest Editors

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • earth observation
  • remote sensing
  • forest monitoring
  • ecological modeling

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Sensors - ISSN 1424-8220