Special Issue "UAV in Smart City and Smart Region"

Special Issue Editors

Dr. Michal Kačmařík
Website
Guest Editor
Department of Geoinformatics, VŠB – Technical University of Ostrava, 17. listopadu 2172/15, Ostrava, 70800, Czech Republic
Interests: satellite positioning and navigation; GNSS meteorology; location-based services; spatial data collection; remote sensing; unmanned air vehicles; natural hazards
Special Issues and Collections in MDPI journals
Dr. Eija Honkavaara
Website
Guest Editor
Finnish Geospatial Research Institute FGI, National Land Survey of Finland, Geodeetinrinne 2, Masala, FI-02430, Finland
Interests: photogrammetry; hyperspectral imaging; UAV; calibration; SLAM; machine learning
Special Issues and Collections in MDPI journals
Dr. Václav Šafář
Website
Guest Editor
Research Institute of Geodesy, Topography and Cartography, v.v.i, Ústecká 98, Zdiby, 250 66, 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 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

  • 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 (3 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Open AccessArticle
Flight Planning for LiDAR-Based UAS Mapping Applications
ISPRS Int. J. Geo-Inf. 2020, 9(6), 378; https://doi.org/10.3390/ijgi9060378 - 08 Jun 2020
Cited by 1
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 [...] Read more.
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)
Show Figures

Graphical abstract

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
ISPRS Int. J. Geo-Inf. 2020, 9(5), 325; https://doi.org/10.3390/ijgi9050325 - 15 May 2020
Cited by 1
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 [...] Read more.
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)
Show Figures

Figure 1

Open AccessEditor’s ChoiceArticle
Multisensorial Close-Range Sensing Generates Benefits for Characterization of Managed Scots Pine (Pinus sylvestris L.) Stands
ISPRS Int. J. Geo-Inf. 2020, 9(5), 309; https://doi.org/10.3390/ijgi9050309 - 07 May 2020
Cited by 3
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, [...] Read more.
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 (Hg) and mean stem volume (Vmean). Most notably, the root-mean-square-error (RMSE) in Hg 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, Vmean, Hg, 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)
Show Figures

Figure 1

Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: Use of UAV in Cadastral Mapping of the Czech Republic
Authors: V.Šafář, M.Potůčková, J.Karas, J.Tlustý, E.Štefanová, M.Jančovič, D. Cígler Žofková
Affiliation: 1. VSB - Technical University of Ostrava, Faculty of Mining and Geology, Department of Geodesy and Mine Surveying, Ostrava-Poruba, 708 00, 17. listopadu 2172/15, Czech Republic 2. Charles University, Faculty of Science, Department of Applied Geoinformatics and Cartography, 128 43, Albertov 6, Prague 2, Czech Republic 3. Upvision Ltd., 158 00, Klikatá 18, Praha 5 – Jinonice, Czech Republic 4. Cadastral Office for the region Plzeň, Radobyčická 2465/12, 30100, Jižní Předměstí Plzeň, Czech Republic 5. Czech technical university in Prague, Faculty of Civil Engineering, Department of Building Structures, 166 29, Thákurova 7, Praha 6, Czech Republic Correspondence to: V.Šafář1 ([email protected])
Abstract: The main challenge in the new mapping and updating the cadastre of the Czech Republic is to achieve maximum efficiency but to retain the required accuracy of 0.14m in position of all points in the register. The article discusses possibility of using UAV photogrammetry and laser scanning for cadastral mapping of the Czech Republic. Point clouds from images and laser scans together with orthoimages were acquired over seven test areas. Control and check points were measured by geodetic methods (GNSS-RTK, total stations). The accuracy of detailed survey based on UAV technologies was checked on a thousand of points, namely building corners and points on fences. The results show that the required accuracy of 0.14m was achieved on more that 80% of points in the case of the image point clouds and orthoimages and on 98% in the case of LiDAR point cloud, respectively. The paper also describes changes in the organization and technological processes of the applied mapping methods and provides a comparison of their costs.

Back to TopTop