Remote Sensing Techniques for 3D Reconstruction and Multimodal Structural Analysis

Dear Colleagues,

3D reconstruction plays a critical role in modern remote sensing by enabling the detailed representation of terrain, urban environments, and complex structures for various engineering applications, including infrastructure assessment, digital twins, and large-scale structural analysis. Advances in remote sensing technologies, such as synthetic aperture radar (SAR), LiDAR, multispectral, hyperspectral, and high-resolution optical sensors, have significantly expanded the capabilities for capturing geometric and spectral information for 3D modeling.

However, the complexity of multimodal data integration, including varying resolutions, sensor types, and noise characteristics, presents ongoing challenges in achieving accurate, scalable, and efficient 3D reconstruction. The growing interest in machine learning, particularly physics-informed models and deep learning architectures, offers promising directions for improving data fusion and structural interpretation from diverse remote sensing datasets.

This Special Issue aims to provide a dedicated platform for the latest research efforts focused on developing and applying remote sensing methodologies for 3D reconstruction and structural analysis, highlighting both theoretical advancements and practical implementations across various engineering fields.

The primary goal of this Special Issue is to explore state-of-the-art methodologies and technologies that enhance 3D reconstruction and structural analysis using remote sensing data. This focus aligns closely with Remote Sensing’s scope by emphasizing:

The development of innovative image processing techniques for remote sensing datasets.

The fusion and analysis of multimodal remote sensing data for 3D structural modeling.

Remote sensing applications in engineering contexts include infrastructure assessment, resource exploration, and digital elevation modeling.

Suggested themes and article types for submission:

Multimodal Data Fusion for Structural Analysis.

Fusion of SAR, LiDAR, multispectral, and hyperspectral data for 3D modeling.

Cross-modal feature alignment and data normalization strategies.

Physics-informed and deep learning-based fusion models for remote sensing.

Image Processing Techniques for Structural Analysis.

SAR despeckling and structural deformation analysis.

Hyperspectral and multispectral image analysis for material classification.

LiDAR point cloud segmentation and classification for structural assessment.

Engineering Applications.

Urban modeling and smart city infrastructure monitoring.

Structural health monitoring and deformation detection in civil engineering.

Large-scale terrain analysis and digital twins for construction projects.

Automated surveying and resource exploration using 3D remote sensing.

3D Surface Reconstruction Techniques.

Digital elevation modeling generation and refinement using SAR and LiDAR data.

Multi-view and photometric stereo methods for large-scale 3D modeling.

Surface normal estimation and point cloud generation from multispectral and RGB imagery.

Dr. Yakun Ju
Dr. Jianyuan Sun
Dr. Cong Zhang
Dr. Feng Gao
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.

• 3D surface reconstruction in remote sensing
• multimodal remote sensing data fusion
• synthetic aperture radar (SAR) imaging
• LiDAR point cloud processing
• hyperspectral and multispectral imaging
• remote sensing for structural analysis
• photogrammetry and remote sensing techniques