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

Deadline for manuscript submissions: closed (31 October 2021) | Viewed by 45726

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Special Issue Editors

Dr. Panagiotis Partsinevelos

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Senselab Research, School of Mineral Resources Engineering, Technical University of Crete, 73100 Chania, Greece
Interests: unmanned aerial systems; tangible GIS; GNSS-denied environments; remote sensing
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Dr. Filiberto Chiabrando

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Department of Architecture and Design, Polytechnic University of Turin, I-10125 Torino, Italy
Interests: uncrewed aerial vehicle; photogrammetry; laser scanning; 3D reconstruction; rapid mapping; 3D modeling; 360° cameras; GIS and remote sensing; sensor integration
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Dr. Fabio Giulio Tonolo

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Department of Architecture and Design, Polytechnic University of Turin, 10125 Torino, Italy
Interests: geomatics; satellite remote sensing; unmanned aerial systems; GIS
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Dr. Kevin W. Franke

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Guest Editor

Department of Civil and Environmental Engineering, Brigham Young University, Provo, UT 84602, USA
Interests: remote sensing; earthquake engineering; UAV

Special Issue Information

Dear Colleagues,

Unmanned aerial systems (UAS) have become increasingly popular in a variety of geospatial applications. Academia and the global market are overwhelmed with often repetitive and simplistic UAS solutions, even though there are many unresolved research issues that need to be dealt with before we can fully unleash their potential. The research community should take action in establishing “smart”, autonomous, and disruptive implementations. UAS and Geoinformatics can benefit mutually from their integration. Towards this end, this Special Issue is devoted to UAS research in terms of novel platforms, embedded systems, new sensors (such as novel LiDAR and hyperspectral scanners), algorithms, real-time and on-board processing, decision making through AI and deep learning, real-time image processing, pattern recognition, fleet management, collaborative robotic systems, internet of drones, 3D reconstruction optimization, oblique photogrammetry, added value in GIS applications, navigation in GPS-denied environments, autonomous navigation, and horizontal and domain specific custom-made systems. Applications span a wide spectrum, including the environment, mapping, the Earth system, disaster management, satellite remote sensing integration, large scale thematic remote sensing, transportation, agriculture, inspection, dynamic environments, search and rescue, cultural heritage, human migration, geotechnical applications, geology, infrastructure, security, business, etc. Disruptive methodologies, review papers, best practice studies, and novel applications will be appreciated.

Dr. Panagiotis Partsinevelos
Dr. Filiberto Chiabrando
Dr. Fabio Giulio Tonolo
Dr. Kevin W. Franke
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

autonomous systems
mapping and visualization
decision making systems
on-board, real time processing
GPS-denied environments
navigation optimization
3D modeling
AI
collaborative and fleet systems

Published Papers (11 papers)

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Research

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24 pages, 6293 KiB

Open AccessArticle

FC-RRT*: An Improved Path Planning Algorithm for UAV in 3D Complex Environment

by Yicong Guo, Xiaoxiong Liu, Xuhang Liu, Yue Yang and Weiguo Zhang

ISPRS Int. J. Geo-Inf. 2022, 11(2), 112; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi11020112 - 05 Feb 2022

Cited by 16 | Viewed by 4042

Abstract

In complex environments, path planning is the key for unmanned aerial vehicles (UAVs) to perform military missions autonomously. This paper proposes a novel algorithm called flight cost-based Rapidly-exploring Random Tree star (FC-RRT*) extending the standard Rapidly-exploring Random Tree star (RRT*) to deal with the safety requirements and flight constraints of UAVs in a complex 3D environment. First, a flight cost function that includes threat strength and path length was designed to comprehensively evaluate the connection between two path nodes. Second, in order to solve the UAV path planning problem from the front-end, the flight cost function and flight constraints were used to inspire the expansion of new nodes. Third, the designed cost function was used to guide the update of the parent node to allow the algorithm to consider both the threat and the length of the path when generating the path. The simulation and comparison results show that FC-RRT* effectively overcomes the shortcomings of standard RRT*. FC-RRT* is able to plan an optimal path that significantly improves path safety as well as maintains has the shortest distance while satisfying flight constraints in the complex environment. This paper has application value in UAV 3D global path planning. Full article

(This article belongs to the Special Issue Unmanned Aerial Systems and Geoinformatics)

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17 pages, 12485 KiB

Open AccessArticle

Potential Use of Drone Ultra-High-Definition Videos for Detailed 3D City Modeling

by Bashar Alsadik and Yousif Hussein Khalaf

ISPRS Int. J. Geo-Inf. 2022, 11(1), 34; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi11010034 - 03 Jan 2022

Cited by 4 | Viewed by 3164

Abstract

Ongoing developments in video resolution either using consumer-grade or professional cameras has opened opportunities for different applications such as in sports events broadcasting and digital cinematography. In the field of geoinformation science and photogrammetry, image-based 3D city modeling is expected to benefit from this technology development. Highly detailed 3D point clouds with low noise are expected to be produced when using ultra high definition UHD videos (e.g., 4K, 8K). Furthermore, a greater benefit is expected when the UHD videos are captured from the air by consumer-grade or professional drones. To the best of our knowledge, no studies have been published to quantify the expected outputs when using UHD cameras in terms of 3D modeling and point cloud density. In this paper, a quantification is shown about the expected point clouds and orthophotos qualities when using UHD videos from consumer-grade drones and a review of which applications they can be applied in. The results show that an improvement in 3D models of ≅65% relative accuracy and ≅90% in point density can be attained when using 8K video frames compared with HD video frames which will open a wide range of applications and business cases in the near future. Full article

(This article belongs to the Special Issue Unmanned Aerial Systems and Geoinformatics)

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24 pages, 36795 KiB

Open AccessArticle

Efficient and High Path Quality Autonomous Exploration and Trajectory Planning of UAV in an Unknown Environment

by Leyang Zhao, Li Yan, Xiao Hu, Jinbiao Yuan and Zhenbao Liu

ISPRS Int. J. Geo-Inf. 2021, 10(10), 631; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10100631 - 22 Sep 2021

Cited by 9 | Viewed by 2566

Abstract

The ability of an autonomous Unmanned Aerial Vehicle (UAV) in an unknown environment is a prerequisite for its execution of complex tasks and is the main research direction in related fields. The autonomous navigation of UAVs in unknown environments requires solving the problem of autonomous exploration of the surrounding environment and path planning, which determines whether the drones can complete mission-based flights safely and efficiently. Existing UAV autonomous flight systems hardly perform well in terms of efficient exploration and flight trajectory quality. This paper establishes an integrated solution for autonomous exploration and path planning. In terms of autonomous exploration, frontier-based and sampling-based exploration strategies are integrated to achieve fast and effective exploration performance. In the study of path planning in complex environments, an advanced Rapidly Exploring Random Tree (RRT) algorithm combining the adaptive weights and dynamic step size is proposed, which effectively solves the problem of balancing flight time and trajectory quality. Then, this paper uses the Hermite difference polynomial to optimization the trajectory generated by the RRT algorithm. We named proposed UAV autonomous flight system as Frontier and Sampling-based Exploration and Advanced RRT Planner system (FSEPlanner). Simulation performs in both apartment and maze environment, and results show that the proposed FSEPlanner algorithm achieves greatly improved time consumption and path distances, and the smoothed path is more in line with the actual flight needs of a UAV. Full article

(This article belongs to the Special Issue Unmanned Aerial Systems and Geoinformatics)

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29 pages, 7202 KiB

Open AccessArticle

Autonomous Obstacle Avoidance Algorithm for Unmanned Surface Vehicles Based on an Improved Velocity Obstacle Method

by Jia Ren, Jing Zhang and Yani Cui

ISPRS Int. J. Geo-Inf. 2021, 10(9), 618; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10090618 - 16 Sep 2021

Cited by 17 | Viewed by 3811

Abstract

Focusing on the collision avoidance problem for Unmanned Surface Vehicles (USVs) in the scenario of multi-vessel encounters, a USV autonomous obstacle avoidance algorithm based on the improved velocity obstacle method is proposed. The algorithm is composed of two parts: a multi-vessel encounter collision detection model and a path re-planning algorithm. The multi-vessel encounter collision detection model draws on the idea of the velocity obstacle method through the integration of characteristics such as the USV dynamic model in the marine environment, the encountering vessel motion model, and the International Regulations for Preventing Collisions at Sea (COLREGS) to obtain the velocity obstacle region in the scenario of USV and multi-vessel encounters. On this basis, two constraint conditions for the motion state space of USV obstacle avoidance behavior and the velocity obstacle region are added to the dynamic window algorithm to complete a USV collision risk assessment and generate a collision avoidance strategy set. The path re-planning algorithm is based on the premise of the minimum resource cost and uses an improved particle swarm algorithm to obtain the optimal USV control strategy in the collision avoidance strategy set and complete USV path re-planning. Simulation results show that the algorithm can enable USVs to safely evade multiple short-range dynamic targets under COLREGS. Full article

(This article belongs to the Special Issue Unmanned Aerial Systems and Geoinformatics)

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19 pages, 7707 KiB

Open AccessArticle

DEM-Based UAV Flight Planning for 3D Mapping of Geosites: The Case of Olympus Tectonic Window, Lesvos, Greece

by Ermioni-Eirini Papadopoulou, Christos Vasilakos, Nikolaos Zouros and Nikolaos Soulakellis

ISPRS Int. J. Geo-Inf. 2021, 10(8), 535; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10080535 - 09 Aug 2021

Cited by 7 | Viewed by 2616

Abstract

Geosites are an important part of geoheritage, thus their detailed mapping is crucial for their management, protection and promotion processes. However, there is no specific approach to three-dimensional (3D) mapping of geosites and a full investigation is required, considering the current advances in the science of Geoinformatics and the need for setting up an integrated system that will suggest a suitable way of mapping areas of geological significance. The main purpose of this study is to explore new approaches to the 3D mapping of geosites, where the unmanned aerial vehicles’ (UAVs) flight planning is based on the digital elevation model (DEM). The case study that is being examined is the tectonic window of Mount Olympus, located in the southeast of Lesvos island, Greece. In this paper, a methodology has been developed to create flight plans for geosite 3D mapping. This methodology consists of three main stages: (a) flight planning based on SRTM-DEM, (b) data acquisition and image-based 3D modelling, and (c) comparison (flight plans and results). A semi-automated algorithm was developed for designing the flights, taking into account the topography of the mapped area (slope, aspect, elevation) and the final cartographic derivatives. The flight plans were compared with each other in levels of data collection, flight characteristics and their results. The results of this study are dense point clouds, DEMs and orthophotomaps. The algorithms that have been used for the comparison of point clouds were (I) surface density, (II) number of neighbours (NN), and (III) roughness and surface profile. The conclusion drawn from this study is that the DEM is a valuable source of information that can be used in designing flight plans specially shaped on the topography of each geosite. Full article

(This article belongs to the Special Issue Unmanned Aerial Systems and Geoinformatics)

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24 pages, 4331 KiB

Open AccessArticle

Boosting the Timeliness of UAV Large Scale Mapping. Direct Georeferencing Approaches: Operational Strategies and Best Practices

by Lorenzo Teppati Losè, Filiberto Chiabrando and Fabio Giulio Tonolo

ISPRS Int. J. Geo-Inf. 2020, 9(10), 578; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9100578 - 30 Sep 2020

Cited by 31 | Viewed by 5210

Abstract

The use of unmanned aerial vehicles (UAVs) is nowadays a standard approach in several application fields. Researches connected with these systems cover several topics and the evolution of these platforms and their applications are rapidly growing. Despite the high level of automatization reached nowadays, there is still a phase of the overall UAVs’ photogrammetric pipeline that requires a high effort in terms of time and resources (i.e., the georeferencing phase). However, thanks to the availability of survey-grade GNSS (Global Navigation Satellite System) receivers embedded in the aerial platforms, it is possible to also enhance this phase of the processing by adopting direct georeferencing approaches (i.e., without using any ground control point and exploiting real time kinematic (RTK) positioning). This work investigates the possibilities offered by a multirotor commercial system equipped with a RTK-enabled GNSS receiver, focusing on the accuracy of the georeferencing phase. Several tests were performed in an ad-hoc case study exploiting different georeferencing solutions and assessing the 3D positional accuracies, thanks to a network of control points. The best approaches to be adopted in the field according to accuracy requirements of the final map products were identified and operational guidelines proposed accordingly. Full article

(This article belongs to the Special Issue Unmanned Aerial Systems and Geoinformatics)

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17 pages, 3129 KiB

Open AccessFeature PaperArticle

Automated Geolocation in Urban Environments Using a Simple Camera-Equipped Unmanned Aerial Vehicle: A Rapid Mapping Surveying Alternative?

by Dimitrios Trigkakis, George Petrakis, Achilleas Tripolitsiotis and Panagiotis Partsinevelos

ISPRS Int. J. Geo-Inf. 2020, 9(7), 425; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9070425 - 30 Jun 2020

Cited by 4 | Viewed by 2824

Abstract

GNSS positioning accuracy can be degraded in areas where the surrounding object geometry and morphology interacts with the GNSS signals. Specifically, urban environments pose challenges to precise GNSS positioning because of signal interference or interruptions. Also, non-GNSS surveying methods, including total stations and laser scanners, involve time consuming practices in the field and costly equipment. The present study proposes the use of an Unmanned Aerial Vehicle (UAV) for autonomous rapid mapping that resolves the problem of localization for the drone itself by acquiring location information of characteristic points on the ground in a local coordinate system using simultaneous localization and mapping (SLAM) and vision algorithms. A common UAV equipped with a camera and at least a single known point, are enough to produce a local map of the scene and to estimate the relative coordinates of pre-defined ground points along with an additional arbitrary point cloud. The resulting point cloud is readily measurable for extracting and interpreting geometric information from the area of interest. Under two novel optimization procedures performing line and plane alignment of the UAV-camera-measured point geometries, a set of experiments determines that the localization of a visual point in distances reaching 15 m from the origin, delivered a level of accuracy under 50 cm. Thus, a simple UAV with an optical sensor and a visual marker, prove quite promising and cost-effective for rapid mapping and point localization in an unknown environment. Full article

(This article belongs to the Special Issue Unmanned Aerial Systems and Geoinformatics)

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14 pages, 5809 KiB

Open AccessArticle

Village-Level Homestead and Building Floor Area Estimates Based on UAV Imagery and U-Net Algorithm

by Xueyan Zhang

ISPRS Int. J. Geo-Inf. 2020, 9(6), 403; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9060403 - 20 Jun 2020

Cited by 7 | Viewed by 2484

Abstract

China’s rural population has declined markedly with the acceleration of urbanization and industrialization, but the area under rural homesteads has continued to expand. Proper rural land use and management require large-scale, efficient, and low-cost rural residential surveys; however, such surveys are time-consuming and difficult to accomplish. Unmanned aerial vehicle (UAV) technology coupled with a deep learning architecture and 3D modelling can provide a potential alternative to traditional surveys for gathering rural homestead information. In this study, a method to estimate the village-level homestead area, a 3D-based building height model (BHM), and the number of building floors based on UAV imagery and the U-net algorithm was developed, and the respective estimation accuracies were found to be 0.92, 0.99, and 0.89. This method is rapid and inexpensive compared to the traditional time-consuming and costly household surveys, and, thus, it is of great significance to the ongoing use and management of rural homestead information, especially with regards to the confirmation of homestead property rights in China. Further, the proposed combination of UAV imagery and U-net technology may have a broader application in rural household surveys, as it can provide more information for decision-makers to grasp the current state of the rural socio-economic environment. Full article

(This article belongs to the Special Issue Unmanned Aerial Systems and Geoinformatics)

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22 pages, 8382 KiB

Open AccessArticle

Mission Flight Planning of RPAS for Photogrammetric Studies in Complex Scenes

by José Miguel Gómez-López, José Luis Pérez-García, Antonio Tomás Mozas-Calvache and Jorge Delgado-García

ISPRS Int. J. Geo-Inf. 2020, 9(6), 392; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9060392 - 16 Jun 2020

Cited by 15 | Viewed by 4256

Abstract

This study describes a new approach to Remotely Piloted Aerial Systems (RPAS) photogrammetric mission flight planning. In this context, we have identified different issues appearing in complex scenes or difficulties caused by the project requirements in order to establish those functions or tools useful for resolving them. This approach includes the improvement of some common photogrammetric flight operations and the proposal of new flight schemas for some scenarios and practical cases. Some examples of these specific schemas are the combined flight (which includes characteristics of a classical block flight and a corridor flight in only one mission) and a polygon extrusion mode to be used for buildings and vertical objects, according to the International Committee of Architectural Photogrammetry (CIPA) recommendations. In all cases, it is very important to allow a detailed control of the flight and image parameters, such as the ground sample distance (GSD) variation, scale, footprints, coverage, and overlaps, according to the Digital Elevation Models (DEMs) available for the area. In addition, the application could be useful for quality control of other flights (or flight planning). All these new functions and improvements have been implemented in a software developed in order to make RPAS photogrammetric mission planning easier. The inclusion of new flight typologies supposes a novelty with respect to other available applications. The application has been tested using several cases including different types of flights. The results obtained in the quality parameters of flights (coverage and GSD variation) have demonstrated the viability of our new approach in supporting other photogrammetric procedures. Full article

(This article belongs to the Special Issue Unmanned Aerial Systems and Geoinformatics)

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23 pages, 12438 KiB

Open AccessArticle

Spoofing Detection of Civilian UAVs Using Visual Odometry

by Masood Varshosaz, Alireza Afary, Barat Mojaradi, Mohammad Saadatseresht and Ebadat Ghanbari Parmehr

ISPRS Int. J. Geo-Inf. 2020, 9(1), 6; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9010006 - 19 Dec 2019

Cited by 34 | Viewed by 3575

Abstract

Spoofing of Unmanned Aerial Vehicles (UAV) is generally carried out through spoofing of the UAV’s Global Positioning System (GPS) receiver. This paper presents a vision-based UAV spoofing detection method that utilizes Visual Odometry (VO). This method is independent of the other complementary sensors and any knowledge or archived map and datasets. The proposed method is based on the comparison of relative sub-trajectory of the UAV from VO, with its absolute replica from GPS within a moving window along the flight path. The comparison is done using three dissimilarity measures including (1) Sum of Euclidian Distances between Corresponding Points (SEDCP), (2) angle distance and (3) taxicab distance between the Histogram of Oriented Displacements (HOD) of these sub-trajectories. This method can determine the time and location of UAV spoofing and bounds the drift error of VO. It can be used without any restriction in the usage environment and can be implemented in real-time applications. This method is evaluated on four UAV spoofing scenarios. The results indicate that this method is effective in the detection of UAV spoofing due to the Sophisticated Receiver-Based (SRB) GPS spoofing. This method can detect UAV spoofing in the long-range UAV flights when the changes in UAV flight direction is larger than 3° and in the incremental UAV spoofing with the redirection rate of 1°. Additionally, using SEDCP, the spoofing of the UAV, when there is no redirection and only the velocity of the UAV is changed, can be detected. The results show that SEDCP is more effective in the detection of UAV spoofing and fake GPS positions. Full article

(This article belongs to the Special Issue Unmanned Aerial Systems and Geoinformatics)

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Review

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27 pages, 4573 KiB

Open AccessReview

Digital Terrain Models Generated with Low-Cost UAV Photogrammetry: Methodology and Accuracy

by Sergio Iván Jiménez-Jiménez, Waldo Ojeda-Bustamante, Mariana de Jesús Marcial-Pablo and Juan Enciso

ISPRS Int. J. Geo-Inf. 2021, 10(5), 285; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10050285 - 29 Apr 2021

Cited by 73 | Viewed by 8730

Abstract

Digital terrain model (DTM) generation is essential to recreating terrain morphology once the external elements are removed. Traditional survey methods are still used to collect accurate geographic data on the land surface. Given the emergence of unmanned aerial vehicles (UAVs) equipped with low-cost digital cameras and better photogrammetric methods for digital mapping, efficient approaches are necessary to allow rapid land surveys with high accuracy. This paper provides a review, complemented with the authors’ experience, regarding the UAV photogrammetric process and field survey parameters for DTM generation using popular commercial photogrammetric software to process images obtained with fixed-wing or multicopter UAVs. We analyzed the quality and accuracy of the DTMs based on four categories: (i) the UAV system (UAV platforms and camera); (ii) flight planning and image acquisition (flight altitude, image overlap, UAV speed, orientation of the flight line, camera configuration, and georeferencing); (iii) photogrammetric DTM generation (software, image alignment, dense point cloud generation, and ground filtering); (iv) geomorphology and land use/cover. For flat terrain, UAV photogrammetry provided a horizontal root mean square error (RMSE) between 1 to 3 × the ground sample distance (GSD) and a vertical RMSE between 1 to 4.5 × GSD, and, for complex topography, a horizontal RMSE between 1 to 7 × GSD and a vertical RMSE between 1.5 to 5 × GSD. Finally, we stress that UAV photogrammetry can provide DTMs with high accuracy when the photogrammetric process variables are optimized. Full article

(This article belongs to the Special Issue Unmanned Aerial Systems and Geoinformatics)

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