Applications and Potential of UAV Photogrammetric Survey

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

Deadline for manuscript submissions: closed (15 December 2018) | Viewed by 45037

Special Issue Editor

Chair for Geodesy and Geoinformatics, Faculty for Agriculture and Environmental Sciences, Rostock University, Rostock, Germany
Interests: precision agriculture; remote sensing; phenology; photogrammetry
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue is devoted to the applications and potentials of UAS photogrammetric surveys. Unmanned aerial systems (UAS) have torpedoed into Earth sciences and photogrammetry during last few years. They give an enormous potential and freedom to scientists of different fields. In addition to science, UAS photogrammetry is commonly used in practice and the use of drones has become a common procedure in many environmental applications.

The Special Issue aims for papers showing the progress in key areas of UAS photogrammetry, such as real-time photogrammetry, applications of new sensors, such as LiDAR and hyperspectral scanners, oblique photogrammetry, large scale thematic remote sensing and environmental mapping. Typical papers are expected to address the following UAS photogrammtry topics:

  • online or real-time UAS-photogrammetry
  • Proposal of novel path planning methods for obstacle free navigation, for real scenarios, indoor and outdoor applications.
  • Sensor and data fusion for the integration of UAS imagery with satellite, aerial or terrestrial data, integration of heterogeneous data captured by UAS
  • Efficient corridor mapping and BVLOS applications
  • Innovative applications for monitoring, tracking and change detection in cadaster and surveying, rapid mapping, urban monitoring, disaster prevention, industrial plant inspection, search and rescue, multi-temporal analyses, precision farming, forestry, etc.

Dr.-Ing. Görres Grenzdörffer
Guest Editor

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Keywords

  • UAS Photogrammetry
  • Digital true orthophotos
  • Dense image matching and surface reconstruction
  • Corridor mapping
  • Oblique images
  • Hyperspectral and Lidar
  • Standardisation, Regulation, BVLOS
  • Obstacles, sense and avoid

Published Papers (9 papers)

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Research

18 pages, 8525 KiB  
Article
Enhanced Drone Navigation in GNSS Denied Environment Using VDM and Hall Effect Sensor
by Shady Zahran, Adel Moussa and Naser El-Sheimy
ISPRS Int. J. Geo-Inf. 2019, 8(4), 169; https://doi.org/10.3390/ijgi8040169 - 02 Apr 2019
Cited by 8 | Viewed by 5036
Abstract
The last decade has witnessed a wide spread of small drones in many civil and military applications. With the massive advancement in the manufacture of small and lightweight Inertial Navigation System (INS), navigation in challenging environments became feasible. Navigation of these small drones [...] Read more.
The last decade has witnessed a wide spread of small drones in many civil and military applications. With the massive advancement in the manufacture of small and lightweight Inertial Navigation System (INS), navigation in challenging environments became feasible. Navigation of these small drones mainly depends on the integration of Global Navigation Satellite Systems (GNSS) and INS. However, the navigation performance of these small drones deteriorates quickly when the GNSS signals are lost, due to accumulated errors of the low-cost INS that is typically used in these drones. During GNSS signal outages, another aiding sensor is required to bound the drift exhibited by the INS. Before adding any additional sensor on-board the drones, there are some limitations that must be taken into considerations. These limitations include limited availability of power, space, weight, and size. This paper presents a novel unconventional method, to enhance the navigation of autonomous drones in GNSS denied environment, through a new utilization of hall effect sensor to act as flying odometer “Air-Odo” and vehicle dynamic model (VDM) for heading estimation. The proposed approach enhances the navigational solution by estimating the unmanned aerial vehicle (UAV) velocity, and heading and fusing these measurements in the Extended Kalman Filter (EKF) of the integrated system. Full article
(This article belongs to the Special Issue Applications and Potential of UAV Photogrammetric Survey)
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26 pages, 8805 KiB  
Article
Accuracy Analysis of a 3D Model of Excavation, Created from Images Acquired with an Action Camera from Low Altitudes
by Damian Wierzbicki and Marcin Nienaltowski
ISPRS Int. J. Geo-Inf. 2019, 8(2), 83; https://doi.org/10.3390/ijgi8020083 - 13 Feb 2019
Cited by 12 | Viewed by 4099
Abstract
In the last few years, Unmanned Aerial Vehicles (UAVs) equipped with compact digital cameras, have become a cheap and efficient alternative to classic aerial photogrammetry and close-range photogrammetry. Low-altitude photogrammetry has great potential not only in the development of orthophoto maps but is [...] Read more.
In the last few years, Unmanned Aerial Vehicles (UAVs) equipped with compact digital cameras, have become a cheap and efficient alternative to classic aerial photogrammetry and close-range photogrammetry. Low-altitude photogrammetry has great potential not only in the development of orthophoto maps but is also increasingly used in surveying and rapid mapping. This paper presents a practical aspect of the application of the custom homemade low-cost UAV, equipped with an action camera, to obtain images from low altitudes and develop a digital elevation model of the excavation. The conducted analyses examine the possibilities of using low-cost UAVs to deliver useful photogrammetric products. The experiments were carried out on a closed excavation in the town of Mince (north-eastern Poland). The flight over the examined area was carried out autonomously. A photogrammetric network was designed, and the reference areas in the mine were measured using the Global Navigation Satellite System-Real Time Kinematic (GNSS-RTK) method to perform accuracy analyses of the excavation 3D model. Representation of the created numerical terrain model was a dense point cloud. The average height difference between the generated dense point cloud and the reference model was within the range of 0.01–0.13 m. The difference between the volume of the excavation measured by the GNSS kinematic method and the volume measured on the basis of a dense point cloud was less than 1%. The obtained results show that the application of the low-cost UAV equipped with an action camera with a wide-angle lens, allows for obtaining high-accuracy images comparable to classic, compact digital cameras. Full article
(This article belongs to the Special Issue Applications and Potential of UAV Photogrammetric Survey)
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26 pages, 13980 KiB  
Article
Identifying Asphalt Pavement Distress Using UAV LiDAR Point Cloud Data and Random Forest Classification
by Zhiqiang Li, Chengqi Cheng, Mei-Po Kwan, Xiaochong Tong and Shaohong Tian
ISPRS Int. J. Geo-Inf. 2019, 8(1), 39; https://doi.org/10.3390/ijgi8010039 - 16 Jan 2019
Cited by 35 | Viewed by 6968 | Retraction
Abstract
Asphalt pavement ages and incurs various distresses due to natural and human factors. Thus, it is crucial to rapidly and accurately extract different types of pavement distress to effectively monitor road health status. In this study, we explored the feasibility of pavement distress [...] Read more.
Asphalt pavement ages and incurs various distresses due to natural and human factors. Thus, it is crucial to rapidly and accurately extract different types of pavement distress to effectively monitor road health status. In this study, we explored the feasibility of pavement distress identification using low-altitude unmanned aerial vehicle light detection and ranging (UAV LiDAR) and random forest classification (RFC) for a section of an asphalt road that is located in the suburb of Shihezi City in Xinjiang Province of China. After a spectral and spatial feature analysis of pavement distress, a total of 48 multidimensional and multiscale features were extracted based on the strength of the point cloud elevations and reflection intensities. Subsequently, we extracted the pavement distresses from the multifeature dataset by utilizing the RFC method. The overall accuracy of the distress identification was 92.3%, and the kappa coefficient was 0.902. When compared with the maximum likelihood classification (MLC) and support vector machine (SVM), the RFC had a higher accuracy, which confirms its robustness and applicability to multisample and high-dimensional data classification. Furthermore, the method achieved an overall accuracy of 95.86% with a validation dataset. This result indicates the validity and stability of our method, which highway maintenance agencies can use to evaluate road health conditions and implement maintenance. Full article
(This article belongs to the Special Issue Applications and Potential of UAV Photogrammetric Survey)
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22 pages, 7552 KiB  
Article
Application of UAV Photogrammetry in Displacement Measurement of the Soil Nail Walls Using Local Features and CPDA Method
by Farid Esmaeili, Hamid Ebadi, Mohammad Saadatseresht and Farzin Kalantary
ISPRS Int. J. Geo-Inf. 2019, 8(1), 25; https://doi.org/10.3390/ijgi8010025 - 11 Jan 2019
Cited by 8 | Viewed by 3768
Abstract
The high cost of land across urban areas has made the excavation a typical practice to construct multiple underground stories. Various methods have been used to restrain the excavated walls and keep them from a possible collapse, including nailing and anchorage. The excavated [...] Read more.
The high cost of land across urban areas has made the excavation a typical practice to construct multiple underground stories. Various methods have been used to restrain the excavated walls and keep them from a possible collapse, including nailing and anchorage. The excavated wall monitoring, especially during the drilling and restraining operations, is necessary for preventing the risk of such incidents as an excavated wall collapse. In the present research, an unmanned aerial vehicle (UAV) photogrammetry-based algorithm was proposed for accurate, fast and low-cost monitoring of excavated walls. Different stages of the proposed methodology included design of the UAV photogrammetry network for optimal imaging, local feature extraction from the acquired images, a special optimal matching method and finally, displacement estimation through a combined adjustment method. Results of implementations showed that, using the proposed methodology, one can achieve a precision of ±7 mm in positioning local features on the excavated walls. Moreover, the wall displacement could be measured at an accuracy of ±1 cm. Having high flexibility, easy implementation, low cost and fast pace; the proposed methodology provides an appropriate alternative to micro-geodesic procedures and the use of instrumentations for excavated wall displacement monitoring. Full article
(This article belongs to the Special Issue Applications and Potential of UAV Photogrammetric Survey)
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16 pages, 7477 KiB  
Article
Investigating the Utility Potential of Low-Cost Unmanned Aerial Vehicles in the Temporal Monitoring of a Landfill
by Abdullah Harun Incekara, Ahmet Delen, Dursun Zafer Seker and Cigdem Goksel
ISPRS Int. J. Geo-Inf. 2019, 8(1), 22; https://doi.org/10.3390/ijgi8010022 - 11 Jan 2019
Cited by 19 | Viewed by 3913
Abstract
The collection of solid waste is a challenging issue, especially in highly urbanized areas. In developing countries, landfilling is currently the preferred method for disposing of solid waste, but each landfill has a limited lifecycle. Therefore, changes in the amount of stored waste [...] Read more.
The collection of solid waste is a challenging issue, especially in highly urbanized areas. In developing countries, landfilling is currently the preferred method for disposing of solid waste, but each landfill has a limited lifecycle. Therefore, changes in the amount of stored waste should be monitored for the sustainable management of such areas. In this study, volumetric changes in a landfill were examined using a low-cost unmanned aerial vehicle (UAV). Aerial photographs obtained from five different flights, covering approximately two years, were used in the volume calculations. Values representing the amount of remaining space between the solid waste and a reference plane were determined using digital elevation models, which were produced based on the structure from motion (SfM) approach. The obtained results and potential of UAVs in the photogrammetric survey of a landfill were further evaluated and interpreted by considering other possible techniques, ongoing progress, and the information existing in an environmental impact assessment report. As a result of the study, it was proved that SfM carried out using a low-cost UAV has a high potential for use in the reconstruction of a landfill. Outcomes were obtained over a short period, without the need for direct contact with the solid waste, making the UAV preferable for use in planning and decision-making studies. Full article
(This article belongs to the Special Issue Applications and Potential of UAV Photogrammetric Survey)
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23 pages, 10554 KiB  
Article
Real-Time Efficient Exploration in Unknown Dynamic Environments Using MAVs
by Haytham Mohamed, Adel Moussa, Mohamed Elhabiby and Naser El-Sheimy
ISPRS Int. J. Geo-Inf. 2018, 7(11), 450; https://doi.org/10.3390/ijgi7110450 - 18 Nov 2018
Viewed by 2634
Abstract
Micro aerial vehicles (MAVs) have been acknowledged as an influential technology for indoor search and rescue operations. The time constraint is a crucial factor in most search and rescue operations. The employed MAVs in indoor environments are characterized by short endurance flight time [...] Read more.
Micro aerial vehicles (MAVs) have been acknowledged as an influential technology for indoor search and rescue operations. The time constraint is a crucial factor in most search and rescue operations. The employed MAVs in indoor environments are characterized by short endurance flight time and limited payload weights. Hence, adding more batteries to extend the flight time is practically not feasible. Typically, most of the indoor missions’ environments might not be accessed and remain unknown. Working in such environments requires effective exploration and information gathering to save time and maximize the coverage area. Furthermore, due to the dynamism of such environments, choosing the least risky trajectory is an important task. This paper proposes a real-time active exploration technique which is capable of efficiently generating paths that minimize the vehicle’s risk and maximize the coverage area. Furthermore, it accomplishes real-time monitoring of sudden changes in the estimated map, due to the dynamic objects, by reevaluating at real-time the destination and trajectory to minimize the risk on the chosen path and simultaneously preserving the maximization of the coverage area. Ultimately, recording the implemented trajectory of the vehicle also assists in time-saving as the vehicle depends on this trajectory during the exit process. The performance of the technique is studied under static and dynamic environments and is also compared with different algorithms. Full article
(This article belongs to the Special Issue Applications and Potential of UAV Photogrammetric Survey)
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15 pages, 10573 KiB  
Article
Generating a High-Precision True Digital Orthophoto Map Based on UAV Images
by Yu Liu, Xinqi Zheng, Gang Ai, Yi Zhang and Yuqiang Zuo
ISPRS Int. J. Geo-Inf. 2018, 7(9), 333; https://doi.org/10.3390/ijgi7090333 - 21 Aug 2018
Cited by 41 | Viewed by 8177
Abstract
Unmanned aerial vehicle (UAV) low-altitude remote sensing technology has recently been adopted in China. However, mapping accuracy and production processes of true digital orthophoto maps (TDOMs) generated by UAV images require further improvement. In this study, ground control points were distributed and images [...] Read more.
Unmanned aerial vehicle (UAV) low-altitude remote sensing technology has recently been adopted in China. However, mapping accuracy and production processes of true digital orthophoto maps (TDOMs) generated by UAV images require further improvement. In this study, ground control points were distributed and images were collected using a multi-rotor UAV and professional camera, at a flight height of 160 m above the ground and a designed ground sample distance (GSD) of 0.016 m. A structure from motion (SfM), revised digital surface model (DSM) and multi-view image texture compensation workflow were outlined to generate a high-precision TDOM. We then used randomly distributed checkpoints on the TDOM to verify its precision. The horizontal accuracy of the generated TDOM was 0.0365 m, the vertical accuracy was 0.0323 m, and the GSD was 0.0166 m. Tilt and shadowed areas of the TDOM were eliminated so that buildings maintained vertical viewing angles. This workflow produced a TDOM accuracy within 0.05 m, and provided an effective method for identifying rural homesteads, as well as land planning and design. Full article
(This article belongs to the Special Issue Applications and Potential of UAV Photogrammetric Survey)
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19 pages, 5265 KiB  
Article
Use of Unmanned Aerial Vehicles (UAVs) for Updating Farmland Cadastral Data in Areas Subject to Landslides
by Edyta Puniach, Agnieszka Bieda, Paweł Ćwiąkała, Anita Kwartnik-Pruc and Piotr Parzych
ISPRS Int. J. Geo-Inf. 2018, 7(8), 331; https://doi.org/10.3390/ijgi7080331 - 19 Aug 2018
Cited by 31 | Viewed by 4876
Abstract
The purpose of this study was to verify the applicability of unmanned aerial vehicles (UAVs) to update cadastral records in areas affected by landslides. Its authors intended to compare the accuracy of coordinates determined using different UAV data processing methods for points which [...] Read more.
The purpose of this study was to verify the applicability of unmanned aerial vehicles (UAVs) to update cadastral records in areas affected by landslides. Its authors intended to compare the accuracy of coordinates determined using different UAV data processing methods for points which form the framework of a cadastral database, and to find out whether products obtained as a result of such UAV data processing are sufficient to define the extent of changes in the cadastral objects. To achieve this, an experiment was designed to take place at the site of a landslide. The entire photogrammetry mission was planned to cover an area of more than 70 ha. Given the steep grade of the site, the UAV was flown over each line at a different, individually preset altitude, such as to ensure consistent mean shooting distance (height above ground level), and thus, appropriate ground sample distance (GSD; pixel size). The results were analyzed in four variants, differing from each other in terms of the number of control points used and the method of their measurement. This allowed identification of the factors that affect surveying accuracy and the indication of the cadastral data updatable based on an UAV photogrammetric survey. Full article
(This article belongs to the Special Issue Applications and Potential of UAV Photogrammetric Survey)
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18 pages, 12636 KiB  
Article
Improving Tree Species Classification Using UAS Multispectral Images and Texture Measures
by Rossana Gini, Giovanna Sona, Giulia Ronchetti, Daniele Passoni and Livio Pinto
ISPRS Int. J. Geo-Inf. 2018, 7(8), 315; https://doi.org/10.3390/ijgi7080315 - 03 Aug 2018
Cited by 49 | Viewed by 4277
Abstract
This paper focuses on the use of ultra-high resolution Unmanned Aircraft Systems (UAS) imagery to classify tree species. Multispectral surveys were performed on a plant nursery to produce Digital Surface Models and orthophotos with ground sample distance equal to 0.01 m. Different combinations [...] Read more.
This paper focuses on the use of ultra-high resolution Unmanned Aircraft Systems (UAS) imagery to classify tree species. Multispectral surveys were performed on a plant nursery to produce Digital Surface Models and orthophotos with ground sample distance equal to 0.01 m. Different combinations of multispectral images, multi-temporal data, and texture measures were employed to improve classification. The Grey Level Co-occurrence Matrix was used to generate texture images with different window sizes and procedures for optimal texture features and window size selection were investigated. The study evaluates how methods used in Remote Sensing could be applied on ultra-high resolution UAS images. Combinations of original and derived bands were classified with the Maximum Likelihood algorithm, and Principal Component Analysis was conducted in order to understand the correlation between bands. The study proves that the use of texture features produces a significant increase of the Overall Accuracy, whose values change from 58% to 78% or 87%, depending on components reduction. The improvement given by the introduction of texture measures is highlighted even in terms of User’s and Producer’s Accuracy. For classification purposes, the inclusion of texture can compensate for difficulties of performing multi-temporal surveys. Full article
(This article belongs to the Special Issue Applications and Potential of UAV Photogrammetric Survey)
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