Long-Term Monitoring and Driving Forces of Forest Cover
A special issue of Forests (ISSN 1999-4907). This special issue belongs to the section "Forest Operations and Engineering".
Deadline for manuscript submissions: 31 March 2026 | Viewed by 620
Special Issue Editors
Interests: eco-environment monitoring and assessment; coordination analysis; spatial analysis; sustainable development
Special Issues, Collections and Topics in MDPI journals
Interests: climate change; land use; remote sensing; land degradation; natural hazards
Special Issues, Collections and Topics in MDPI journals
Interests: remote sensing; ecosystem services; ecological security; landscape; soil
Interests: disaster monitoring; disaster reduction
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Forests are the largest terrestrial ecosystem on Earth, which play a vital role in conserving water resources, regulating the climate, purifying the air, preventing wind erosion and sand drift, and protecting biodiversity. However, in recent years, the rapid decline in global forest cover has attracted widespread attention. Therefore, quickly and accurately determining the area and coverage of forests is of great significance for better realizing their ecological, social, and economic value.
With the continuous increase in remote sensing satellites and the gradual enrichment of satellite data, the long-term monitoring of forest cover has become available in recent years. However, as a type of big data, wide and long-term monitoring of forest cover still remains a challenge. Different from traditional remote sensing classification methods, machine learning has advantages in terms of big data processing and its calculation capabilities, which have been widely used in numerous fields. Hence, these recent advanced monitoring methods and analysis methods are our motivation to organize this Special Issue to welcome colleagues to share their work on forest cover monitoring and driving force analyses with advanced methods.
This Special Issue is dedicated to advances in long-term forest cover monitoring and driving force analysis. Articles should include aspects of forest cover monitoring, driving forces of forest change, and forest cover change. Techniques and methods from machine learning are welcome. Generally, manuscripts demonstrating novel applications of these techniques to forest cover would be appropriate for this Special Issue.
Potential topics include, but are not limited to, the following:
- Forest cover monitoring;
- Driving forces of forest change;
- Forest cover change;
- Machine learning;
Dr. Jianwan Ji
Prof. Dr. Bing Guo
Dr. Eshetu Shifaw
Dr. Rui Zhang
Guest Editors
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 100 words) can be sent to the Editorial Office for announcement on this website.
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
- forest cover monitoring
- driving forces of forest change
- forest cover change
- long-term monitoring
- remote sensing
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