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UAV in Smart City and Smart Region

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

Deadline for manuscript submissions: closed (30 April 2021) | Viewed by 39476

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Special Issue Editors

Dr. Michal Kačmařík

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Guest Editor

Department of Geoinformatics, VŠB – Technical University of Ostrava, 17. listopadu 2172/15, 70800 Ostrava, Czech Republic
Interests: satellite positioning and navigation; GNSS meteorology; location-based services; spatial data collection; remote sensing; unmanned air vehicles; natural hazards
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Prof. Dr. Fabio Remondino

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Guest Editor

3D Optical Metrology (3DOM) Unit, Bruno Kessler Foundation (FBK), 38123 Trento, Italy
Interests: photogrammetry; laser scanning; optical metrology; 3D; AI; quality control
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Dr. Eija Honkavaara

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Guest Editor

Finnish Geospatial Research Institute FGI, National Land Survey of Finland, Geodeetinrinne 2, FI-02430 Masala, Finland
Interests: photogrammetry; hyperspectral imaging; UAV; calibration; SLAM; machine learning
Special Issues, Collections and Topics in MDPI journals

Dr. Václav Šafář

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Guest Editor

Research Institute of Geodesy, Topography and Cartography, v.v.i, Ústecká 98, 250 66 Zdiby, Czech Republic
Interests: photogrammetry; UAV; archive aerial images; BIM; precision farming; remote sensing

Special Issue Information

Dear Colleagues,

The fast increase in the utilization of unmanned air vehicles (UAVs) and development of Smart Cities/Regions are opening new possibilities and challenges in providing and utilization of up-to-date information about various spatial features and phenomena shaping our world. Such information needs to be provided from variable locations, sometimes with a short time latency or with a high update rate and practically always at the lowest possible costs. In all these factors, UAVs can excel as they have proven to be an effective tool for a variety of mapping and monitoring purposes. In addition to that, many UAV applications not targeting spatial data collection are already in operational use or under development.

This Special Issue, which stems from the conference “GIS Ostrava 2020: UAV in Smart City and Smart Region”, welcomes but is not limited to contributions in the following topics:

Image orientation and accurate georeferencing;
Simultaneous localization and mapping (SLAM);
Integration of UAV data with other data sources;
Current trends in data processing;
2D mapping;
3D mapping;
Civil security, emergency management, search and rescue operations, situation awareness;
Natural hazards monitoring;
Precision farming with UAVs;
Environmental mapping and monitoring with UAVs;
Change detection in urban and natural environments;
Infrastructure and building inspection with UAVs and BIM;
Collaborative UAVs and swarm UAVs;
Autonomous operation, unmanned traffic management;
UAV regulations.

Assoc. Prof. Michal Kačmařík
Prof. Fabio Remondino
Dr. Eija Honkavaara
Dr. Václav Šafář
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 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

unmanned air vehicles
smart city
smart region
mapping and visualization
3D modeling
autonomous systems
change detection
inspection and monitoring
precision farming
UAV regulations

Published Papers (8 papers)

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Research

21 pages, 2658 KiB

Open AccessArticle

Modeling and Performance Optimization of Unmanned Aerial Vehicle Channels in Urban Emergency Management

by Bing Han, Danyang Qin, Ping Zheng, Lin Ma and Merhawit Berhane Teklu

ISPRS Int. J. Geo-Inf. 2021, 10(7), 478; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10070478 - 11 Jul 2021

Cited by 5 | Viewed by 2526

Abstract

With the development of smart cities, the use of unmanned aerial vehicles (UAVs) for interactive information exchange between air and ground can provide effective support for the deployment of emergency work. However, the existing UAV air-to-ground channels often use a single channel model. Considering that the density and distribution of obstructions on information transmission paths at different heights are different, only using a single channel model greatly affects the reliability of communications. Aiming at addressing the different channel characteristics of air-to-ground channels at different heights, a height-based adaptive SUUL-SULA channel model is proposed in this paper. Firstly, in the ultra-low altitude environment, the influence of large-scale fading and small-scale fading on the envelope of the received signal is discussed based on the classic LOO model, and the probability density function and bit error rate model of the received signal are derived. Secondly, a SULA channel model based on Jakes’ model is proposed in the low-altitude environment. The uniform circular array beamforming technology is adopted to realize the design of the Doppler frequency shift compensation algorithm. Finally, the simulation results show that the SUUL-SULA model effectively reduces the bit error rate of the system and improves the reliability of communication. Therefore, this model can provide effective physical support for the application of UAV in smart city emergency management. Full article

(This article belongs to the Special Issue UAV in Smart City and Smart Region)

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23 pages, 2109 KiB

Open AccessArticle

Joint Optimization on Trajectory, Cache Placement, and Transmission Power for Minimum Mission Time in UAV-Aided Wireless Networks

by Tingting Lan, Danyang Qin and Guanyu Sun

ISPRS Int. J. Geo-Inf. 2021, 10(7), 426; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10070426 - 23 Jun 2021

Cited by 6 | Viewed by 1831

Abstract

In recent years, due to the strong mobility, easy deployment, and low cost of unmanned aerial vehicles (UAV), great interest has arisen in utilizing UAVs to assist in wireless communication, especially for on-demand deployment in emergency situations and temporary events. However, UAVs can only provide users with data transmission services through wireless backhaul links established with a ground base station, and the limited capacity of the wireless backhaul link would limit the transmission speed of UAVs. Therefore, this paper designed a UAV-assisted wireless communication system that used cache technology and realized the transmission of multi-user data by using the mobility of UAVs and wireless cache technology. Considering the limited storage space and energy of UAVs, the joint optimization problem of the UAV’s trajectory, cache placement, and transmission power was established to minimize the mission time of the UAV. Since this problem was a non-convex problem, it was decomposed into three sub-problems: trajectory optimization, cache placement optimization, and power allocation optimization. An iterative algorithm based on the successive convex approximation and alternate optimization techniques was proposed to solve these three optimization problems. Finally, in the power allocation optimization, the proposed algorithm was improved by changing the optimization objective function. Numerical results showed that the algorithm had good performance and could effectively reduce the task completion time of the UAV. Full article

(This article belongs to the Special Issue UAV in Smart City and Smart Region)

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19 pages, 66437 KiB

Open AccessArticle

The Use of UAV in Cadastral Mapping of the Czech Republic

by Václav Šafář, Markéta Potůčková, Jakub Karas, Jan Tlustý, Eva Štefanová, Marián Jančovič and Drahomíra Cígler Žofková

ISPRS Int. J. Geo-Inf. 2021, 10(6), 380; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10060380 - 03 Jun 2021

Cited by 10 | Viewed by 4403

Abstract

The main challenge in the renewal and updating of the Cadastre of Real Estate of the Czech Republic is to achieve maximum efficiency but to retain the required accuracy of all points in the register. The paper discusses the possibility of using UAV photogrammetry and laser scanning for cadastral mapping in the Czech Republic. Point clouds from images and laser scans together with orthoimages were derived over twelve test areas. Control and check points were measured using geodetic methods (RTK-GNSS and total stations). The accuracy of the detailed survey based on UAV technologies was checked on hundreds of points, mainly building corners and fence foundations. The results show that the required accuracy of 0.14 m was achieved on more than 80% and 98% of points in the case of the image point clouds and orthoimages and the case of the LiDAR point cloud, respectively. Nevertheless, the methods lack completeness of the performed survey that must be supplied by geodetic measurements. The paper also provides a comparison of the costs connected to traditional and UAV-based cadastral mapping, and it addresses the necessary changes in the organisational and technological processes in order to utilise the UAV based technologies. Full article

(This article belongs to the Special Issue UAV in Smart City and Smart Region)

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27 pages, 7739 KiB

Open AccessArticle

Autonomous Flight Trajectory Control System for Drones in Smart City Traffic Management

by Dinh Dung Nguyen, Jozsef Rohacs and Daniel Rohacs

ISPRS Int. J. Geo-Inf. 2021, 10(5), 338; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10050338 - 17 May 2021

Cited by 33 | Viewed by 11582

Abstract

With the exponential growth of numerous drone operations ranging from infrastructure monitoring to even package delivery services, the integration of UAS in the smart city transportation systems is an actual task that requires radically new, sustainable (safe, secure, with minimum environmental impact and life cycle cost) solutions. The primary objective of this proposed option is the definition of routes as desired and commanded trajectories and their autonomous execution. The airspace structure and fixed routes are given in the global GPS reference system with supporting GIS mapping. The concept application requires a series of further studies and solutions as drone trajectory (or corridor) following by an autonomous trajectory tracking control system, coupled with autonomous conflict detection, resolution, safe drone following, and formation flight options. The second part of the paper introduces such possible models and shows some results of their verification tests. Drones will be connected with the agency, designed trajectories to support them with factual information on trajectories and corridors. While the agency will use trajectory elements to design fixed or desired trajectories, drones may use the conventional GPS, infrared, acoustic, and visual sensors for positioning and advanced navigation. The accuracy can be improved by unique markers integrated into the infrastructure. Full article

(This article belongs to the Special Issue UAV in Smart City and Smart Region)

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15 pages, 4427 KiB

Open AccessArticle

Aerial Bombing Crater Identification: Exploitation of Precise Digital Terrain Models

by Martin Dolejš, Jan Pacina, Martin Veselý and Dominik Brétt

ISPRS Int. J. Geo-Inf. 2020, 9(12), 713; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9120713 - 01 Dec 2020

Cited by 14 | Viewed by 3578

Abstract

Places of past conflicts and persistent objects that reflect such events often attract the attention of archaeological prospection which facilitates the construction of conflict narratives. Field prospection as a precise method for localization of aerial bombing craters (as an example of such persistent features) is a highly time- and resource-consuming task. Therefore, methods for automatic identification of such features are evolving. We present a comparison of three methods for possible automatic crater detection based on (a) extraterrestrial crater detection algorithms, (b) geomorphology-based edge extraction, and (c) image pattern recognition via a state-of-the-art convolutional neural network (CNN). All methods were preliminarily tested on a case study of eight Second World War (WWII) aerial bombing crater sites in NW Czechia via Airborne Laser Scanned LiDAR-derived digital terrain models with different spatial resolutions. We found that extraterrestrial crater detection algorithms and geomorphology-based edge extraction methods yield worse results given the standard indices of precision and recall. By comparison, the CNN method utilized for a particular task achieved satisfying results, predominantly with 0.5 m/px resolution (which is often available at the country level) of the input raster. Nevertheless, overall performance with this resolution varies significantly among the sites. Therefore, the quality and readability of the input data are crucial factors for the successful acquisition of precise ordinance location identification. Full article

(This article belongs to the Special Issue UAV in Smart City and Smart Region)

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19 pages, 13149 KiB

Open AccessEditor’s ChoiceArticle

Flight Planning for LiDAR-Based UAS Mapping Applications

by Bashar Alsadik and Fabio Remondino

ISPRS Int. J. Geo-Inf. 2020, 9(6), 378; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9060378 - 08 Jun 2020

Cited by 18 | Viewed by 6947

Abstract

In the last two decades, unmanned aircraft systems (UAS) were successfully used in different environments for diverse applications like territorial mapping, heritage 3D documentation, as built surveys, construction monitoring, solar panel placement and assessment, road inspections, etc. These applications were correlated to the onboard sensors like RGB cameras, multi-spectral cameras, thermal sensors, panoramic cameras, or LiDARs. According to the different onboard sensors, a different mission plan is required to satisfy the characteristics of the sensor and the project aims. For UAS LiDAR-based mapping missions, requirements for the flight planning are different with respect to conventional UAS image-based flight plans because of different reasons related to the LiDAR scanning mechanism, scanning range, output scanning rate, field of view (FOV), rotation speed, etc. Although flight planning for image-based UAS missions is a well-known and solved problem, flight planning for a LiDAR-based UAS mapping is still an open research topic that needs further investigations. The article presents the developments of a LiDAR-based UAS flight planning tool, tested with simulations in real scenarios. The flight planning simulations considered an UAS platform equipped, alternatively, with three low-cost multi-beam LiDARs, namely Quanergy M8, Velodyne VLP-16, and the Ouster OS-1-16. The specific characteristics of the three sensors were used to plan flights and acquired dense point clouds. Comparisons and analyses of the results showed clear relationships between point density, flying speeds, and flying heights. Full article

(This article belongs to the Special Issue UAV in Smart City and Smart Region)

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Graphical abstract

21 pages, 12625 KiB

Open AccessArticle

Visual Exposure of Rock Outcrops in the Context of a Forest Disease Outbreak Simulation Based on a Canopy Height Model and Spectral Information Acquired by an Unmanned Aerial Vehicle

by Marie Balková, Aleš Bajer, Zdeněk Patočka and Tomáš Mikita

ISPRS Int. J. Geo-Inf. 2020, 9(5), 325; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9050325 - 15 May 2020

Cited by 12 | Viewed by 3261

Abstract

This research was focused on the study of visual exposure evolution in the locality of the Drátenická skála nature monument (in the Czech Republic) and the surrounding forest complex in terms of history and through modelling for further possible stand development. The local forests underwent conversion from a natural fir-beech composition to an intensive spruce monoculture with few insect pests or windbreak events to an actual bark beetle infestation. Historic maps, landscape paintings, photographs, and orthophotos served as the basic materials for the illustration of the past situation. Further development was modelled using canopy height models and spectral properties captured by unmanned aerial vehicles (UAVs). As an example, the possible situation of total mortality among coniferous spruce trees after a bark beetle outbreak was modelled. Other options and a practical use of such preprocessed data are, for example, a model for opening and transforming the stands around the rock as one of the ongoing outcrop management trends in the protected landscape area (PLA) of Žďárské vrchy. Full article

(This article belongs to the Special Issue UAV in Smart City and Smart Region)

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14 pages, 3166 KiB

Open AccessEditor’s ChoiceArticle

Multisensorial Close-Range Sensing Generates Benefits for Characterization of Managed Scots Pine (Pinus sylvestris L.) Stands

by Tuomas Yrttimaa, Ninni Saarinen, Ville Kankare, Niko Viljanen, Jari Hynynen, Saija Huuskonen, Markus Holopainen, Juha Hyyppä, Eija Honkavaara and Mikko Vastaranta

ISPRS Int. J. Geo-Inf. 2020, 9(5), 309; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9050309 - 07 May 2020

Cited by 16 | Viewed by 3479

Abstract

Terrestrial laser scanning (TLS) provides a detailed three-dimensional representation of surrounding forest structures. However, due to close-range hemispherical scanning geometry, the ability of TLS technique to comprehensively characterize all trees, and especially upper parts of forest canopy, is often limited. In this study, we investigated how much forest characterization capacity can be improved in managed Scots pine (Pinus sylvestris L.) stands if TLS point clouds are complemented with photogrammetric point clouds acquired from above the canopy using unmanned aerial vehicle (UAV). In this multisensorial (TLS+UAV) close-range sensing approach, the used UAV point cloud data were considered especially suitable for characterizing the vertical forest structure and improvements were obtained in estimation accuracy of tree height as well as plot-level basal-area weighted mean height (H_g) and mean stem volume (V_mean). Most notably, the root-mean-square-error (RMSE) in H_g improved from 0.8 to 0.58 m and the bias improved from −0.75 to −0.45 m with the multisensorial close-range sensing approach. However, in managed Scots pine stands, the mere TLS also captured the upper parts of the forest canopy rather well. Both approaches were capable of deriving stem number, basal area, V_mean, H_g, and basal area-weighted mean diameter with the relative RMSE less than 5.5% for all the sample plots. Although the multisensorial close-range sensing approach mainly enhanced the characterization of the forest vertical structure in single-species, single-layer forest conditions, representation of more complex forest structures may benefit more from point clouds collected with sensors of different measurement geometries. Full article

(This article belongs to the Special Issue UAV in Smart City and Smart Region)

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