Perspectives of Remote Sensing to Assess Forest Structure and Diversity
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Forest Remote Sensing".
Deadline for manuscript submissions: 31 March 2026 | Viewed by 111
Special Issue Editors
Interests: vegetation remote sensing; carbon sink monitoring; radiation transfer modeling; surveying; LiDAR
Interests: airborne hyperspectral data; forest remote sensing; BRDF correction; forest disturbance; tree species mapping
Interests: forest remote sensing; tree species mapping; multimodal feature fusion; deep learning model; vegetation phenology
Special Issue Information
Dear Colleagues,
Assessing forest structure and biodiversity is essential for effective conservation, land management, and climate change mitigation. Remote sensing technologies have greatly advanced our capacity to collect data on forest ecosystems, offering efficient and non-invasive methods to monitor forest health, composition, and diversity across vast and often inaccessible areas. This Special Issue aims to explore the potential of advanced remote sensing techniques—such as satellite imagery, UAV-based sensors, hyperspectral LiDAR, and the fusion of multi-platform remote sensing data—for assessing forest structure and species diversity across varied ecosystems and geographic regions.
The integration of remote sensing with cutting-edge analytical approaches, including deep learning, machine learning, and 3D radiative transfer models, has opened new possibilities for forest monitoring. These innovations enable highly accurate mapping of forest biomass, canopy structure, and vegetation types, providing deeper insights into the complexities of forest ecosystems. Understanding the variability in forest structure and biodiversity is critical for addressing global challenges such as biodiversity loss, deforestation, and climate change. This Special Issue will highlight the latest research and methodologies in remote sensing, underscoring the role of these technologies in advancing forest management, conservation strategies, and our overall understanding of forest dynamics.
We invite contributions of original research, reviews, and case studies that highlight the role of remote sensing in assessing forest structure and biodiversity, and that propose new tools and techniques to improve forest monitoring.
Dr. Jun Geng
Dr. Wen Jia
Dr. Kaijian Xu
Dr. Hailan Jiang
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. Remote Sensing is an international peer-reviewed open access semimonthly 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 2700 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 structure
- biodiversity
- LiDAR
- satellite observation
- UAV
- vegetation remote sensing.
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