New Perspectives on 3D Point Cloud (Third Edition)

Dear Colleagues,

Research about 3D point cloud processing and its application areas are expanding not only for geospatial analysis but also in civil engineering and manufacturing, transport and city planning, construction, geology, ecology, forestry, mechanical engineering, and so on. The topics are expanding towards the possibility of classification, shape detection, and data extraction via automated procedures. The process of semantic segmentation and feature extraction can be used for preservation, the prediction of events, climate control, and as a basis for decision making and analysis. Pattern recognition is a hot topic in autonomous vehicles and inspections.

This is a hot topic in research due to its innovation possibilities and multiple potential application fields, not to mention the problems that have not yet found a definitive solution (Poux, F., 2019). Furthermore, the possibility of using and developing open-source applications for data management and processing makes this topic a key area in the research.

This Special Issue will collect original papers regarding the innovative processing and applications of 3D point clouds acquired from remote sensing sensors in different and new areas of research (i.e., forest, environment, cultural heritage, geology, maritime, architecture, climate analysis, and city modeling research). Great importance will be given to new, innovative research regarding open-source solutions, as well as the creation and definition of automated/semi-automated procedures to collect, post-process, classify, and use 3D point clouds.

Topics should be strictly related to the aims of the Remote Sensing journal, with data results from different sensors of 3D reality-based surveys.

The papers suitable for this Special Issue must emphasize new perspectives and innovative methods on 3D point cloud acquisition, analysis, and post-processing, focusing on data extraction, semantic feature extraction, machine and deep learning algorithms, AI, the use of segmented point clouds for HBIM and BIM, and automated and semi-automated procedures. Importance should also be given to multi-temporal point clouds and the characterization of object dynamics.

Dr. Sara Barsanti
Guest Editor

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.

• point cloud acquisition (laser scanner, mono/stereo vision, panoramas, phone cameras, aerial and satellite images, indoor and narrow spaces)
• deep learning for segmentation/semantic representation and processing
• AI/ML/DL for point cloud processing and pattern recognition
• NErF
• monocular depth estimation for 3D point cloud reconstruction
• voxel creation
• denoising point clouds
• data extraction/data analysis/point cloud registration/multi-temporal point clouds
• change detection
• from 2D images to 3D Point Clouds with GANs and LLMs

• New Perspectives on 3D Point Cloud in Remote Sensing (9 articles)
• New Perspectives on 3D Point Cloud II in Remote Sensing (10 articles)