Advances in Remote Sensing and GIS Utilization in Monitoring of Forest Ecosystems
A special issue of Forests (ISSN 1999-4907). This special issue belongs to the section "Forest Inventory, Modeling and Remote Sensing".
Deadline for manuscript submissions: 31 October 2025 | Viewed by 1394
Special Issue Editors
Interests: optical remote sensing; time series analysis; forest management; dendrochronology
Interests: GIS; remote sensing; water science; meteorology; climatology; environment; digital cartography; atmosphere; statistics; numerical analysis
Special Issues, Collections and Topics in MDPI journals
Interests: low-carbon design and planning; territorial spatial carbon metabolism; land heat island (LHI); urban carbon pool engineering technology
Interests: land use/land cover (LULC) mapping; forests; classification development and comparison; geographic object-based image analysis; natural disasters; UAS; ecosystem services
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Global forests lost 28.3 million hectares in 2023 and continue to be threatened by substantial natural and human disturbances. In the temporal dimension (recent decades or even recent centuries), we could witness the spatial–temporal forest change that includes carbon storage change, forest landscape change, and forest diversity change and explore its possible drivers. In the spatial dimension, we expect to detect extreme events (deforestation, forest fire, forest insects, forest drought, and other forest disturbances) and collect new forest ecological data (tree canopy height, forest aboveground biomass, and forest soil biochemistry) for management and planning. Remote sensing (RS) and geographic information systems (GISs) are cost-effective tools to monitor forest change in the long term and detect extreme events on a large spatial scale, which could be very helpful for forest management and planning. Novel applications with remote sensing and GIS could be entire new methods such as advanced techniques (deep learning or machine learning) or high-quality sensors. They could also be updated versions of classical techniques/sensor applications.
In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:
- Forest cover or diversity change detection;
- Forest disturbances (fire, insect, drought and others);
- Forest carbon sequestration;
- Environmental impact assessment;
- Forest dynamics (biomass, humidity, temperature and soil);
- Forest policy and management with remote sensing or GIS;
- Dendrochronology with remote sensing or GIS.
Dr. Hang Li
Dr. Aleksandar Dj Valjarević
Dr. Menglin Qin
Prof. Dr. Giorgos Mallinis
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
- remote sensing
- GIS
- forest management
- change detection
- forest disturbances
- carbon sequestration
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