Special Issue "Enhanced Modeling and Surveying Tools for Smart Cities"

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

Deadline for manuscript submissions: closed (30 April 2020).

Special Issue Editors

Dr. Lemonia Ragia
Website
Guest Editor
ATHENA Research & Innovation Center in Information Technologies, Artemidos 6 & Epidavrou 15124, Marousi, Athens, Greece
Interests: photogrammetry; computer vision; surveying; GIS; spatial analysis; virtual and augmented reality
Special Issues and Collections in MDPI journals
Dr. Cédric Grueau
Website
Guest Editor
Polytechnic Institute of Setúbal/IPS, Setúbal, Portugal
Interests: geographic information science; multiagent systems; model-driven development; social simulation; requirement engineering
Special Issues and Collections in MDPI journals
Prof. Dr. Robert Laurini
Website
Guest Editor

Special Issue Information

Dear Colleagues,

Smart cities generate a number of challenges regarding their modeling and operations and give rise to a host of exciting new problems. New urban environments and their associated road infrastructures need to be closely monitored. We have to upgrade our tools to meet new, demanding, dynamic conditions. This Special Issue includes selected papers from the 5th International Conference on Geographical Information Systems Theory, Applications, and Management held in Heraklion, Crete, Greece, May 2019. It presents a collection of papers that use modern technologies to address some of these new problems. The first papers propose tools for modeling the urban environment. The next papers propose ways to optimize travel time and find the best path. The following papers deal with two complimentary ways for positioning and georeferencing. Finally, two papers integrate different technologies for monitoring and accuracy assessment.

Dr. Lemonia Ragia
Prof. Cédric Grueau
Prof. Robert Laurini
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 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. 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 1000 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

  • smart cities
  • urban environment
  • road infrastructure
  • optimization of travel time
  • optimizing the best path
  • georeferencing
  • accuracy assessment

Published Papers (6 papers)

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Editorial

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Open AccessEditorial
Making Smart Cities Resilient to Climate Change by Mitigating Natural Hazard Impacts
ISPRS Int. J. Geo-Inf. 2020, 9(3), 153; https://doi.org/10.3390/ijgi9030153 - 08 Mar 2020
Abstract
Climate change is undoubtedly a big issue due to its devastating consequences. The enhanced resilience to natural hazards due to climate change belongs to the concept of smart cities. This Editorial proposes different uses of Geographic Information Systems to handle and disseminate data [...] Read more.
Climate change is undoubtedly a big issue due to its devastating consequences. The enhanced resilience to natural hazards due to climate change belongs to the concept of smart cities. This Editorial proposes different uses of Geographic Information Systems to handle and disseminate data for natural disasters. Data are gathered from various data sources and are processed and visualized in maps using apps. These apps are available through the Internet or mobile devices and can be used to inform and train the stakeholders of disaster-prone areas in order to mitigate the impacts of disasters. Full article
(This article belongs to the Special Issue Enhanced Modeling and Surveying Tools for Smart Cities)
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Research

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Open AccessArticle
Dynamic Floating Stations Model for Emergency Medical Services with a Consideration of Traffic Data
ISPRS Int. J. Geo-Inf. 2020, 9(5), 336; https://doi.org/10.3390/ijgi9050336 - 20 May 2020
Abstract
To equally distribute the workload and minimize the travel distance for fire departments, we developed a new dynamic floating stations model (DFSM) to target traffic-related emergency medical services (EMS) during peak hours. This study revealed that traffic-related EMS incidents have different characteristics to [...] Read more.
To equally distribute the workload and minimize the travel distance for fire departments, we developed a new dynamic floating stations model (DFSM) to target traffic-related emergency medical services (EMS) during peak hours. This study revealed that traffic-related EMS incidents have different characteristics to other EMS incidents. The number of floating stations was determined by the number of available ambulances at a given time. The optimum floating station location was identified by using the given capacity to establish the smallest service radius. In DFSM simulations using floating stations with a capacity of 100 and 150 EMS incidents, the result shows significant improvements in comparison to the current situation. Full article
(This article belongs to the Special Issue Enhanced Modeling and Surveying Tools for Smart Cities)
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Open AccessArticle
GNSS Positioning Using Mobile Devices with the Android Operating System
ISPRS Int. J. Geo-Inf. 2020, 9(4), 220; https://doi.org/10.3390/ijgi9040220 - 07 Apr 2020
Abstract
The access and the use of the global navigation satellite system (GNSS) pseudo-range and carrier-phase measurements mobile devices as smartphones and tablets with an Android operating system has transformed the concept of accurate positioning with mobile devices. In this work, the comparison of [...] Read more.
The access and the use of the global navigation satellite system (GNSS) pseudo-range and carrier-phase measurements mobile devices as smartphones and tablets with an Android operating system has transformed the concept of accurate positioning with mobile devices. In this work, the comparison of positioning performances obtained with a smartphone and an external mass-market GNSS receiver both in real-time and post-processing is made. Particular attention is also paid to accuracy and precision of positioning results, also analyzing the possibility of estimating the phase ambiguities as integer values (fixed positioning) that it is still challenging for mass-market devices. The precisions and accuracies obtained with the mass-market receiver were about 5 cm and 1 cm both for real-time and post-processing solutions, respectively, while those obtained with a smartphone were slightly worse (few meters in some cases) due to the noise of its measurements. Full article
(This article belongs to the Special Issue Enhanced Modeling and Surveying Tools for Smart Cities)
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Open AccessArticle
Accuracy Assessment of a UAV Block by Different Software Packages, Processing Schemes and Validation Strategies
ISPRS Int. J. Geo-Inf. 2020, 9(3), 164; https://doi.org/10.3390/ijgi9030164 - 11 Mar 2020
Cited by 2
Abstract
Unmanned aerial vehicle (UAV) systems are heavily adopted nowadays to collect high-resolution imagery with the purpose of documenting and mapping environment and cultural heritage. Such data are currently processed by programs based on the Structure from Motion (SfM) concept, coming from the computer [...] Read more.
Unmanned aerial vehicle (UAV) systems are heavily adopted nowadays to collect high-resolution imagery with the purpose of documenting and mapping environment and cultural heritage. Such data are currently processed by programs based on the Structure from Motion (SfM) concept, coming from the computer vision community, rather than from classical photogrammetry. It is interesting to check whether some widely accepted rules coming from old-fashioned photogrammetry still holds: the relation between accuracy and ground sampling distance (GSD), the ratio between the vertical and horizontal accuracy, accuracy estimated on ground control points (GCPs) vs. that estimated with check points (CPs) also in relation to their ratio and distribution. To face the envisaged aspects, the paper adopts a comparative approach, as several programs are used and numerous configurations considered. The paper illustrates the dataset adopted, the carefully tuned processing strategies and bundle block adjustment (BBA) results in terms of accuracy for both GCPs and CPs. Finally, a leave-one-out (LOO) cross-validation strategy is proposed to assess the accuracy for one of the proposed configurations. Some of the reported results were previously presented in the 5th GISTAM Conference. Full article
(This article belongs to the Special Issue Enhanced Modeling and Surveying Tools for Smart Cities)
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Open AccessArticle
Multi-Parameter Estimation of Average Speed in Road Networks Using Fuzzy Control
ISPRS Int. J. Geo-Inf. 2020, 9(1), 55; https://doi.org/10.3390/ijgi9010055 - 17 Jan 2020
Abstract
Average speed is crucial for calculating link travel time to find the fastest path in a road network. However, readily available data sources like OpenStreetMap (OSM) often lack information about the average speed of a road. However, OSM contains other road information which [...] Read more.
Average speed is crucial for calculating link travel time to find the fastest path in a road network. However, readily available data sources like OpenStreetMap (OSM) often lack information about the average speed of a road. However, OSM contains other road information which enables an estimation of average speed in rural regions. In this paper, we develop a Fuzzy Framework for Speed Estimation (Fuzzy-FSE) that employs fuzzy control to estimate average speed based on the parameters road class, road slope, road surface and link length. The OSM road network and, optionally, a digital elevation model (DEM) serve as free-to-use and worldwide available input data. The Fuzzy-FSE consists of two parts: (a) a rule and knowledge base which decides on the output membership functions and (b) multiple Fuzzy Control Systems which calculate the output average speeds. The Fuzzy-FSE is applied exemplary and evaluated for the BioBío and Maule region in central Chile and for the north of New South Wales in Australia. Results demonstrate that, even using only OSM data, the Fuzzy-FSE performs better than existing methods such as fixed speed profiles. Compared to these methods, the Fuzzy-FSE improves the speed estimation between 2% to 12%. In future work, we will investigate the potential of data-driven machine learning methods to estimate average speed. The applied datasets and the source code of the Fuzzy-FSE are available via GitHub. Full article
(This article belongs to the Special Issue Enhanced Modeling and Surveying Tools for Smart Cities)
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Open AccessArticle
The ε-Approximation of the Time-Dependent Shortest Path Problem Solution for All Departure Times
ISPRS Int. J. Geo-Inf. 2019, 8(12), 538; https://doi.org/10.3390/ijgi8120538 - 27 Nov 2019
Abstract
In this paper, the shortest paths search for all departure times (profile search) are discussed. This problem is called a time-dependent shortest path problem (TDSP) and is suitable for time-dependent travel-time analysis. Particularly, this paper deals with the ε-approximation of profile search [...] Read more.
In this paper, the shortest paths search for all departure times (profile search) are discussed. This problem is called a time-dependent shortest path problem (TDSP) and is suitable for time-dependent travel-time analysis. Particularly, this paper deals with the ε -approximation of profile search computation. The proposed algorithms are based on a label correcting modification of Dijkstra’s algorithm (LCA). The main idea of the algorithm is to simplify the arrival function after every relaxation step so that the maximum relative error is maintained. When the maximum relative error is 0.001, the proposed solution saves more than 97% of breakpoints and 80% of time compared to the exact version of LCA. Furthermore, the runtime can be improved by other 15% to 40% using heuristic splitting of the original departure time interval to several subintervals. The algorithms we developed can be used as a precomputation step in other routing algorithms or for some travel time analysis. Full article
(This article belongs to the Special Issue Enhanced Modeling and Surveying Tools for Smart Cities)
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