Multi-Source Data Application for Forestry Conservation
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 May 2026 | Viewed by 1269
Special Issue Editors
2. Key Laboratory of Biodiversity Conservation of National Forestry and Grassland Administration, Beijing 100091, China
Interests: forest monitoring; landscape dynamics; remote sensing; ecosystem service
Interests: LiDAR remote sensing; 3D point cloud analysis; forest inventory
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Forest and vegetation resource surveys are essential for sustainable ecosystem management, biodiversity conservation, and climate change mitigation. They provide fundamental data to support effective policy-making, ecological restoration, and environmental protection. Traditional ground-based surveys are often labor-intensive and costly, especially in remote or topographically complex regions. The rapid development of remote sensing technologies, such as satellite imagery, unmanned aerial vehicles (UAVs), and airborne LiDAR, has created new opportunities for ecological monitoring and resource assessment. These technologies enable the acquisition of multi-resolution, timely, and cost-effective spatial information, supporting precise vegetation mapping, forestry conservation, and ecological assessment.
This Special Issue, “Multi-Source Data Application for Forestry Conservation”, seeks to advance research on remotely sensed data in forestry application and ecological conservation strategies. Potential topics include, but are not limited to, the following: (i) filtering and processing methods for UAV-LiDAR and UAV imagery in various landscapes; (ii) forest monitoring, vegetation classification, and tree species identification; (iii) biomass modeling, carbon storage estimation, NDVI- and EVI-based vegetation indices, wildfire detection, illegal logging detection, and dynamic change detection; (iv) resource surveying, biodiversity assessment, and ecological restoration; and (v) conservation and management strategies in urban green spaces, forest parks, protected areas, or national parks. By sharing innovative approaches and case studies, this Special Issue aims to highlight the latest advances in remote sensing technology, fostering a deeper understanding of its potential to support sustainable forestry practices and ecological conservation initiatives worldwide.
Dr. Sisi Yu
Prof. Dr. Zhenyang Hui
Dr. Xiao Wang
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
- vegetation index
- remote sensing
- greenness
- spatiotemporal dynamic
- ecological conservation
- environmental assessment
- forestry management
- forestry application
- multi-source data
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