Special Issue "3D Modelling from Point Cloud: Algorithms and Methods"
Deadline for manuscript submissions: closed (31 March 2021).
Interests: geodetic analysis techniques; adjustment theory; mathematical statistics; parameter estimation; hypothesis testing; geostatistics; engineering mathematics
Interests: geodetic data analysis; filtering in state space; Monte Carlo methods; Bayesian data analysis; deformation analysis; engineering geodesy; laser scanning
Point clouds can be obtained by different kinds of laser-, radar-, as well as camera-based techniques, and can serve as a data basis, possibly alongside complementary data, to infer geometrical models of the surveyed objects. This Special Issue focusses on algorithms and methods related to 3D models, defined as mathematical representations of surfaces of objects in three-dimensional Euclidean space. Although the methodology and software for the processing of remotely sensed point clouds has matured considerably throughout the last decade, numerous challenges remain, related, for example, to:
- Difficult measurement environments;
- The fusion of heterogeneous data;
- Large-scale 3D point clouds;
- Accommodation of outliers;
- Spatio-temporal correlations;
- High-accuracy modeling; and
- Modeling of new or complex kinds of phenomena/objects
We therefore welcome novel algorithms and methods
- That take special data characteristics such as outliers, data gaps, stochastic properties, correlations, systematic errors, heterogeneity, or multiplicity of the data sources into account.
- Which utilize approaches from disciplines such as geoinformatics, geoinformation systems, photogrammetry, remote sensing, computer vision, geodesy, applied mathematics, statistics, and artificial intelligence.
- For surface reconstruction, pattern recognition, image classification and segmentation, crowd sourcing, feature extraction, SAR interferometry, etc.
- Solve a real-world problem in a scientific application such as urban GIS, 3D city models, cultural heritage documentation, landslide modelling, investigation of land subsidence phenomena, biomass estimation, determination of spatiotemporal patterns in the Earth sciences, building information modelling, classification, change detection, deformation analysis, georeferencing and localization approaches (e.g., simultaneous localization and mapping, SLAM) from point clouds by means of, for example, filtering in state space algorithms.
Dr. Boris Kargoll
Dr. Hamza Alkhatib
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 papers will be 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 2500 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
- 3D modelling
- laser scanning
- radar interferometry
- filtering in state space
- robust parameter estimation