Dear Colleagues,

Remote sensing has long served as a cornerstone for monitoring, studying, and understanding our dynamic planet in disciplines such as geophysics, optical physics, and geospatial science. Leveraging cutting-edge techniques like LiDAR and photogrammetry, we can now generate detailed 2D/3D maps for supporting diverse applications, from environmental charting to powering digital twin and smart city initiatives. Beyond traditional mapping, these methods also play a critical role in addressing global challenges such as climate change, rapid urbanization, and environmental preservation. Recent advancements have seen the integration of remote sensing with advanced machine and deep learning algorithms, including convolutional neural networks, transformers, and Neural Radiance Fields (NeRF). These innovations have significantly enhanced our capacity to interpret remote sensing data. As the field of remote sensing continues to evolve, we anticipate advancements in both data processing and sensor technologies. These developments will further push the boundaries of remote sensing for achieving more precise and comprehensive 2D/3D mapping techniques.

This Special Issue aims to explore the latest research advancements in remote sensing for 2D/3D mapping. We emphasize both the methodological and algorithmic innovations as well as the broad application of remote sensing-based 2D/3D mapping techniques. This covers a spectrum of applications such as transportation planning, environmental modeling and analysis, property management, cultural heritage preservation, urban planning and design, and precision agriculture.

This Special Issue welcomes contributions centered on data acquisition, processing, analysis, and interpretation within the domain of 2D/3D mapping via remote sensing. We invite both original research articles and comprehensive reviews, covering areas such as, but not limited to:

• Advances in mapping methodologies and algorithmic techniques, like LiDAR scanning, photogrammetry reconstruction, point cloud processing, and Neural Radiance Field;
• Examination of remote sensing data sourced from different sensors, such as satellite and airborne imagery, as well as LiDAR and Radar point clouds;
• Exploration of emerging mapping platforms, like UAVs and mobile mapping systems;
• Incorporation of machine learning and deep learning methodologies into remote sensing mapping;
• Application of remote sensing-driven mapping in applications such as digital twins, transportation planning, environmental modeling, precision farming, etc.;
• Application of night-time lights for mapping urban structure and dynamics.

Dr. Fangning He
Dr. Hongzhou Yang
Dr. Shengjun Tang
Dr. Ding Ma
Prof. Dr. Ayman F. Habib
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.

• remote sensing
• mapping
• 3D reconstruction
• deep learning
• geoscience
• GIS
• satellite imagery
• UAV
• photogrammetry
• point cloud processing
• neural radiance field