3D Reconstruction Based on Remote Sensing Imagery and Lidar Point Cloud

Dear Colleagues,

Remote sensing data-based 3D reconstruction is a very important research topic. It involves the fields of remote sensing, photogrammetry, computer vision, graphics, and machine learning. 3D reconstruction through remote sensing data is of great significance in environmental understanding, autonomous driving, visual perception, object recognition, robotic navigation, 3D modeling, and other fields and will also bring wide applications to urban planning, vision-based navigation, industries such as industrial manufacturing and intelligent control, education, healthcare, and entertainment.

Although 3D reconstruction has been studied for decades, it is still a challenge. The challenges come from i) datasets: in recent years, sensor platforms have become more and more flexible, and datasets from complex scenes are available; ii) methods: there are new capabilities and opportunities in data fusion/integration methods; in addition, in recent years, deep learning methods have become more and more popular, and the automation level has increased; and iii) applications: in recent years, many new applications have emerged, such as digital twins for smart cities, simulations for training and education, virtual reality for healthcare, and so on. The evolution in datasets, methods, and applications requires updated technologies to serve the needs of society.

We would like to invite you to submit articles on your recent research linked to the title of this Special Issue, which is “3D Reconstruction Based on Remote Sensing Imagery and LiDAR Point Cloud”. Contributions may focus on (but not be limited to) the following topics:

• 3D reconstruction from remote sensing images (satellite/aerial images, UAV images, terrestrial images/close range images);
• 3D reconstruction from point cloud, including indoor and outdoor;
• 3D reconstruction from a single image;
• 3D reconstruction from multiview images;
• 3D reconstruction from multimodality data;
• 3D reconstruction from multitemporal data;
• 3D reconstruction from crowdsources;
• 3D reconstruction from videos;
• 3D reconstruction for robotic mapping;
• 3D reconstruction for digital twins;
• 3D reconstruction for AR and VR;
• 3D reconstruction for archeology;
• 3D reconstruction for gaming.

Dr. Lingli Zhu
Prof. Dr. Jonathan Li
Prof. Sylvie Daniel
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-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.