Satellite LiDAR for Vegetation Structure and Biomass Estimation: Advances with ICESat-2 and GEDI
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Forest Remote Sensing".
Deadline for manuscript submissions: 30 April 2026 | Viewed by 62
Special Issue Editors
Interests: vegetation remote sensing; spaceborne LiDAR; forest structure; land surface change
Interests: LiDAR remote sensing; ICESat-2; forest height mapping; DEM genaration
Special Issues, Collections and Topics in MDPI journals
Interests: spaceborne LiDAR for forest application; forest management; aboveground biomass
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Recent advances in spaceborne LiDAR missions, especially NASA’s ICESat-2 and GEDI, have revolutionized our ability to quantify vegetation structure, forest canopy height, and aboveground biomass at regional to global scales. These datasets enable unprecedented insights into forest carbon dynamics, biodiversity, and land–atmosphere interactions, particularly when integrated with passive optical and SAR data.
This Special Issue aims to bring together cutting-edge research leveraging ICESat-2 and GEDI data for vegetation remote sensing. We welcome studies that improve retrieval algorithms; develop data fusion techniques; validate canopy height and biomass products; and apply LiDAR observations to ecological monitoring, forest management, or climate modeling. The scope aligns closely with the Remote Sensing journal’s interests in novel sensing technologies, large-scale monitoring, and Earth system science.
Topics of interest include (but are not limited to) the following:
- Forest canopy height inversion from ICESat-2 or GEDI;
- Biomass estimation models using LiDAR and multisource data;
- LiDAR data fusion with Sentinel, Landsat, or SAR imagery;
- Machine learning applications for vegetation structure retrieval;
- Validation and uncertainty assessment of spaceborne LiDAR products;
- Long-term forest dynamics and disturbance detection;
- LiDAR applications in non-forest ecosystems (e.g., savannas or shrublands).
We encourage submissions of original research articles, technical notes, and reviews.
Dr. Aobo Liu
Dr. Xiaoxiao Zhu
Dr. Cangjiao Wang
Dr. Yating Chen
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
- ICESat-2
- GEDI
- forest canopy height
- aboveground biomass
- vegetation structure
- LiDAR remote sensing
- data fusion
- forest monitoring
- carbon mapping
- machine learning
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.
Further information on MDPI's Special Issue policies can be found here.
