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Detection and Identification of Forest Cover Change

This special issue belongs to the section “Forest Inventory, Modeling and Remote Sensing“.

Special Issue Information

Dear Colleagues,

This Special Issue focuses on the detection and identification of forest cover dynamics, a relevant aspect of sustainable management and our understanding of climate and environmental change. This Special Issue will highlight recent advances in remote sensing methodologies and technologies, including the use of multispectral, hyperspectral, LiDAR and SAR data, as well as the application of machine learning and artificial intelligence techniques for spatio-temporal analysis.

We welcome the submission of articles that address the development of new algorithms for classification and change detection, as well as case studies that apply these techniques to different types of forests and geographical scales. The scope of this Special Issue includes, but is not limited to, monitoring deforestation, forest fragmentation, natural disturbances, agricultural expansion, forest restoration and the impacts of climate change on vegetation cover. We encourage the submission of original research articles, reviews and technical notes that contribute to the advancement of knowledge in the field.

Dr. Marcos Benedito Schimalski
Dr. Veraldo Liesenberg
Guest Editors

Dr. Rorai Pereira Martins-Neto
Guest Editor Assistant

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Forests is an international peer-reviewed open access monthly journal published by MDPI.

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

  • remote sensing
  • active sensors
  • passive sensors
  • monitoring
  • processing
  • extract
  • forest
  • machine learning

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Published Papers

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Forests - ISSN 1999-4907