Personal Remote Sensing and Advanced 3D Reconstruction in Geology: Data Acquisition, Processing and Interpretation

Dear Colleagues,

The field of geosciences is undergoing a significant transformation with the rapid development of three-dimensional (3D) reconstruction technologies. Techniques such as LiDAR, radar interferometry and photogrammetry using SfM-MVS, NeRF and 3D GS now enable the creation of high-fidelity digital twins of geological features, ranging from microscopic mineral structures to vast landscapes. These detailed 3D models have evolved beyond simple visualization tools, becoming essential for quantitative analysis. However, realizing the full potential of these technologies requires a seamless and integrated workflow—from precise data acquisition and advanced processing to meaningful geological interpretation. This end-to-end pipeline is crucial for transforming complex 3D data into actionable geological insights and informed decision-making.

This Special Issue aims to gather cutting-edge research that bridges the gap between 3D data acquisition and geological interpretation. We seek to showcase innovative methodologies and practical applications that advance the entire workflow, emphasizing not only the generation of 3D models but also their geological relevance and analytical value. This theme aligns closely with the scope of Remote Sensing, as it encompasses the full spectrum of remote sensing technologies—from platforms and sensors for data collection to novel algorithms for processing and interpreting geospatial data. Contributions to this Special Issue will highlight the critical role of remote sensing in advancing modern, data-driven geology, supporting the journal's mission to publish impactful research on the development and application of remote sensing technologies.

We invite the submission of high-quality original research articles and comprehensive reviews with focuses including, but not limited to, the following topics:

• Novel Data Acquisition: Advances in Personal Remote Sensing (PRS) platforms refer to the use of lightweight, affordable and portable sensors operated by an individual or small team. These systems are a move away from relying solely on satellite or manned aircraft data. UAVs and terrestrial, airborne or backpack-mounted LiDAR/SLAM systems are especially relevant, and sensor technologies for efficient and accurate 3D data capture in challenging geological environments are also regarded as a key topic.
• Advanced Processing Algorithms: Innovative methods for point cloud and mesh processing, including registration, denoising, segmentation, classification, feature extraction tailored to geological data and fusion of hyperspectral remote sensing data with 3D models.
• Automated Interpretation and AI: Machine learning, deep learning and computer vision applications in the automated mapping and analysis of geological structures (e.g., faults, folds, joints), stratigraphy and landforms.
• Multi-Scale and Multi-Source Data Fusion: Integration of 3D models with geophysical, geochemical and borehole data to create comprehensive and multi-faceted geological models.
• Quantitative Applications: Case studies demonstrating the use of 3D reconstruction in structural geology, geomorphology, engineering geology, hydrogeology and resource exploration, with an emphasis on extracting measurable parameters and supporting geological analysis.

Prof. Dr. Ran Wang
Prof. Dr. Huihui Feng
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.

• 3D reconstruction
• photogrammetry and remote sensing
• LiDAR
• point cloud processing
• digital outcrop model
• geomorphology
• artificial intelligence
• geological interpretation
• hyperspectral
• data fusion