Satellite LiDAR for Vegetation Structure and Biomass Estimation: Advances with ICESat-2 and GEDI

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

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