Special Issue "Editorial Board Members' Collection Series: Forest Remote Sensing"
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Remote Sensors".
Deadline for manuscript submissions: 15 June 2023 | Viewed by 1103
Special Issue Editors

Interests: forest remote sensing; geomatics; forest inventory; biodiversity; decision support systems
Special Issues, Collections and Topics in MDPI journals

Interests: geodesy; ground deformations; synthetic aperture radar (SAR); interferometry SAR (InSAR) techniques; phase unwrapping; multi-track; satellite constellations
Special Issues, Collections and Topics in MDPI journals
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
Manuscript Submission Information
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Keywords
- earth observation
- remote sensing
- forest monitoring
- ecological modeling