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Remote Sensing Advances in Spaceborne Laser Altimetry for High-Accuracy Elevation Modeling and Application

A Special Issue of Remote Sensing (ISSN 2072-4292) belonging to the section "Satellite Missions for Earth and Planetary Exploration".

Deadline for manuscript submissions: 15 December 2026 | Viewed by 1015

Editors

Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR 999077, China
Interests: satellite laser altimetry/space LiDAR data processing; validation of remote sensing data and products

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Guest Editor
College of Surveying and Geo-Informatics, Tongji University, 1239 Siping Rd., Shanghai 200092, China
Interests: satellite laser altimetry/space LiDAR data processing; validation of remote sensing data and products
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Spaceborne laser altimetry has significantly advanced the field of remote sensing by enabling the collection of accurate elevation information over large areas. This technology is not only pivotal for Earth observation, enabling detailed mapping of terrestrial topography, vegetation structure, ice sheets, and hydrological features, but also plays a crucial role in deep space exploration, such as planetary surface mapping and lunar or Martian terrain analysis. These advancements greatly contribute to our understanding of both Earth and other celestial bodies, supporting scientific research and informing decision-making in environmental management, resource exploration, and planetary science.

The aim of this Special Issue is to present recent developments and innovative research in spaceborne laser altimetry, with particular emphasis on high-precision elevation modeling and its practical uses. The theme is closely connected to the journal’s focus on satellite missions for Earth and planetary exploration, reflecting the growing importance of remote sensing technologies in both terrestrial and extraterrestrial contexts. By inviting contributions from researchers working in Earth sciences and planetary studies, we hope to encourage cross-disciplinary dialogue and showcase the diverse applications of laser altimetry in fields ranging from environmental monitoring to planetary geology.

We encourage submissions that focus on recent advances in the processing and application of spaceborne laser altimetry data for high-accuracy elevation modeling. Topics of particular interest include the development of improved algorithms for data processing, methods for calibration and validation of elevation products, and the integration of laser altimetry with complementary remote sensing data. We also welcome studies demonstrating the use of spaceborne laser altimetry in specific applications such as topographic mapping, forest structure assessment, ice sheet monitoring, and planetary or lunar surface analysis. Contributions presenting innovative approaches or comparative evaluations are especially encouraged.

Dr. Binbin Li
Prof. Dr. Huan Xie
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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized 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

  • spaceborne laser altimetry
  • high-accuracy elevation modeling
  • calibration and validation
  • multi-source data integration
  • sensor technology
  • planetary and asteroids mapping

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Published Papers (1 paper)

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Research

27 pages, 76472 KB  
Article
Mapping Submarine Sand Wave Bathymetry from Sentinel-2 Texture Using a Spatial-Sequential Deep Learning Model
by Chao Zhu, Chunfeng Li, Jieqiong Zhou, Wenyan Zhang, Mingwei Wang, Dineng Zhao, Xiaoming Qin, Peter Arlinghaus and Ziyin Wu
Remote Sens. 2026, 18(15), 2511; https://doi.org/10.3390/rs18152511 - 1 Aug 2026
Viewed by 346
Abstract
Submarine sand waves are widespread on shallow continental shelves. Their complex morphology and potential mobility create challenges for engineering surveys, navigation safety, and seabed stability assessment. Multibeam surveys provide accurate bathymetry but are costly and spatially limited, whereas satellite-based methods offer broader coverage [...] Read more.
Submarine sand waves are widespread on shallow continental shelves. Their complex morphology and potential mobility create challenges for engineering surveys, navigation safety, and seabed stability assessment. Multibeam surveys provide accurate bathymetry but are costly and spatially limited, whereas satellite-based methods offer broader coverage but remain challenging in complex sand wave fields. Here, we propose a spatial-sequential 2DCNN–LSTM model for retrieving submarine sand wave bathymetry from Sentinel-2 surface reflectance imagery. The model represents each target point as a sequence of local multispectral image patches, allowing convolutional layers to extract two-dimensional textural features and LSTM layers to learn profile-scale rhythmic continuity associated with sand wave morphology. The model was trained using multibeam bathymetry and applied to a large extrapolation area of approximately 4000 km2 on the Taiwan Banks. Evaluation on the large extrapolated area against in situ bathymetric data achieved a root mean square error (RMSE) of 3.78 m, a mean absolute error (MAE) of 2.99 m, and a mean relative error (MRE) of 9.1%. The results demonstrate that sand wave-induced optical textures can provide useful information for broad-scale bathymetric reconstruction, although model performance remains dependent on image texture visibility controlled by hydrodynamic, illumination, and atmospheric conditions. This framework offers a cost-effective approach for satellite-based monitoring of large submarine sand wave fields, providing a new perspective for engineering applications. Full article
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