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IJGI
Special Issues
Indoor Positioning and Mapping Based on 3D GIS
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Indoor Positioning and Mapping Based on 3D GIS

A special issue of ISPRS International Journal of Geo-Information (ISSN 2220-9964).

Deadline for manuscript submissions: closed (31 July 2021) | Viewed by 8750

Special Issue Editors

Dr. Ihab Hamzi Hijazi

E-Mail Website
Guest Editor
1. Urban Planning Engineering Department, An-Najah National University, Nablus P.O. Box 7, Palestine
2. Chair of Geoinformatics, TUM Department of Aerospace and Geodesy, Technical University of Munich, Munich, Germany
Interests: BIM/GIS integration; GIS for built environments; information architecture; urban dynamics
Special Issues, Collections and Topics in MDPI journals
Dr. Youness Dehbi

E-Mail Website
Guest Editor
Institute of Geodesy and Geoinformation, Arbeitsgruppe Geoinformation, University of Bonn, Meckenheimer Allee 172D, 53115 Bonn, Germany
Interests: urban reasoning & analytics; statistical relational learning; pattern recognition & machine learning for GIS

Special Issue Information

Dear Colleagues,

The advancement in computer hardware and software are extending the capabilities of GIS as a tool in analysis and visualization of indoor environment. Developing methods to describe the location inside building or defining the navigable space for pedestrian is of great importance. Moreover, providing a proper description for the position of utilities such as water network element or electrical network inside building is needed for maintenance or replacement, or to investigate the result of damage to the building structure on another utility network, or to estimate the effect of different maintenance operations in different locations along utilities service systems. Contemporary cartography provide techniques to represent landscape and treat building as black boxes.

This Special Issue is dedicated to explore current trends with regards to the technological, methodological, conceptual and social dimensions of indoor mapping. We call for original papers from researchers around the world, which focus on all topics involving the positing and mapping of the indoor environment.

Dr. Ihab Hamzi Hijazi
Dr. Youness Dehbi
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. ISPRS International Journal of Geo-Information is an international peer-reviewed open access monthly 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 1700 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.

Keywords

  • CityGML
  • IndoorGML
  • 3D GIS
  • indoor positing
  • indoor mapping
  • BIM

Published Papers (3 papers)

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Research

27 pages, 1025 KiB  
Article
Improving Room-Level Location for Indoor Trajectory Tracking with Low IPS Accuracy
by Taehoon Kim, Kyoung-Sook Kim and Ki-Joune Li
ISPRS Int. J. Geo-Inf. 2021, 10(9), 620; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10090620 - 16 Sep 2021
Cited by 1 | Viewed by 2562
Abstract
With the development of indoor positioning methods, such as Wi-Fi positioning, geomagnetic sensor positioning, Ultra-Wideband positioning, and pedestrian dead reckoning, the area of location-based services (LBS) is expanding from outdoor to indoor spaces. LBS refers to the geographic location information of moving objects [...] Read more.
With the development of indoor positioning methods, such as Wi-Fi positioning, geomagnetic sensor positioning, Ultra-Wideband positioning, and pedestrian dead reckoning, the area of location-based services (LBS) is expanding from outdoor to indoor spaces. LBS refers to the geographic location information of moving objects to provide the desired services. Most Wi-Fi-based indoor positioning methods provide two-dimensional (2D) or three-dimensional (3D) coordinates in 1–5 m of accuracy on average approximately. However, many applications of indoor LBS are targeted to specific spaces such as rooms, corridors, stairs, etc. Thus, they require determining a service space from a coordinate in indoor spaces. In this paper, we propose a map matching method to assign an indoor position to a unit space a subdivision of an indoor space, called USMM (Unit Space Map Matching). Map matching is a commonly used localization improvement method that utilizes spatial constraints. We consider the topological information between unit spaces and moving objects’ probabilistic properties, compared to existing room-level mappings based on sensor signals, especially received signal strength-based fingerprinting. The proposed method has the advantage of calculating the probability even if there is only one input trajectory. Last, we analyze the accuracy and performance of the proposed USMM methods by extensive experiments in real and synthetic environments. The experimental results show that our methods bring a significant improvement when the accuracy level of indoor positioning is low. In experiments, the room-level location accuracy improves by almost 30% and 23% with real and synthetic data, respectively. We conclude that USMM methods are helpful to correct valid room-level locations from given positioning locations. Full article
(This article belongs to the Special Issue Indoor Positioning and Mapping Based on 3D GIS)
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15 pages, 9410 KiB  
Article
Indoor Traveling Salesman Problem (ITSP) Path Planning
by Jinjin Yan, Sisi Zlatanova, Jinwoo (Brian) Lee and Qingxiang Liu
ISPRS Int. J. Geo-Inf. 2021, 10(9), 616; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10090616 - 16 Sep 2021
Cited by 9 | Viewed by 3216
Abstract
With the growing complexity of indoor living environments, people have an increasing demand for indoor navigation. Currently, navigation path options in indoor are monotonous as existing navigation systems commonly offer single-source shortest-distance or fastest paths. Such path options might be not always attractive. [...] Read more.
With the growing complexity of indoor living environments, people have an increasing demand for indoor navigation. Currently, navigation path options in indoor are monotonous as existing navigation systems commonly offer single-source shortest-distance or fastest paths. Such path options might be not always attractive. For instance, pedestrians in a shopping mall may be interested in a path that navigates through multiple places starting from and ending at the same location. Here, we name it as the indoor traveling salesman problem (ITSP) path. As its name implies, this path type is similar to the classical outdoor traveling salesman problem (TSP), namely, the shortest path that visits a number of places exactly once and returns to the original departure place. This paper presents a general solution to the ITSP path based on Dijkstra and branch and bound (B&B) algorithm. We demonstrate and validate the method by applying it to path planning in a large shopping mall with six floors, in which the QR (Quick Response) codes are assumed to be utilized as the indoor positioning approach. The results show that the presented solution can successfully compute the ITSP paths and their potentials to apply to other indoor navigation applications at museums or hospitals. Full article
(This article belongs to the Special Issue Indoor Positioning and Mapping Based on 3D GIS)
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19 pages, 5204 KiB  
Article
Visual Positioning in Indoor Environments Using RGB-D Images and Improved Vector of Local Aggregated Descriptors
by Longyu Zhang, Hao Xia, Qingjun Liu, Chunyang Wei, Dong Fu and Yanyou Qiao
ISPRS Int. J. Geo-Inf. 2021, 10(4), 195; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10040195 - 24 Mar 2021
Cited by 5 | Viewed by 2013
Abstract
Positioning information has become one of the most important information for processing and displaying on smart mobile devices. In this paper, we propose a visual positioning method using RGB-D image on smart mobile devices. Firstly, the pose of each image in the training [...] Read more.
Positioning information has become one of the most important information for processing and displaying on smart mobile devices. In this paper, we propose a visual positioning method using RGB-D image on smart mobile devices. Firstly, the pose of each image in the training set is calculated through feature extraction and description, image registration, and pose map optimization. Then, in the image retrieval stage, the training set and the query set are clustered to generate the vector of local aggregated descriptors (VLAD) description vector. In order to overcome the problem that the description vector loses the image color information and improve the retrieval accuracy under different lighting conditions, the opponent color information and depth information are added to the description vector for retrieval. Finally, using the point cloud corresponding to the retrieval result image and its pose, the pose of the retrieved image is calculated by perspective-n-point (PnP) method. The results of indoor scene positioning under different illumination conditions show that the proposed method not only improves the positioning accuracy compared with the original VLAD and ORB-SLAM2, but also has high computational efficiency. Full article
(This article belongs to the Special Issue Indoor Positioning and Mapping Based on 3D GIS)
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