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Journal articles on the topic 'Aerial photography in traffic engineering'

Author: Grafiati

Published: 4 June 2021

Last updated: 12 February 2022

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1

Ekstrand, S. "Close range forest defoliation effects of traffic emissions assessed using aerial photography." Science of The Total Environment 146-147 (May 1994): 149–55. http://dx.doi.org/10.1016/0048-9697(94)90231-3.

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2

Makigami, Yasuji, Hamao Sakamoto, and Masachika Hayashi. "An Analytical Method of Traffic Flow Using Aerial Photographs." Journal of Transportation Engineering 111, no. 4 (July 1985): 377–94. http://dx.doi.org/10.1061/(asce)0733-947x(1985)111:4(377).

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3

Dowling, Richard G., and Willis W. K. Cheng. "Evaluation of Speed Measurement and Prediction Techniques for Signalized Arterials." Transportation Research Record: Journal of the Transportation Research Board 1564, no. 1 (January 1996): 20–29. http://dx.doi.org/10.1177/0361198196156400103.

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The ability to accurately measure and predict the average speed of traffic for different facilities and conditions has become increasingly important with the implementation of the Environmental Protection Agency's Transportation Conformity Rule. Average speed is a vital input into motor vehicle emission rate models. Three speed measurement techniques (floating cars, loop detectors, and aerial photographs) and two average travel speed prediction techniques (the Highway Capacity Manual method for arterials and TRANSYT-7F for signalized arterials) are evaluated. These techniques are compared and evaluated against 4 hr of field data gathered for an 8-mi (13-km) section of Ventura Boulevard in Los Angeles, California. The mean speeds measured by floating cars and aerial photographs were in close agreement (within 6 percent of each other). Loop detectors generally produced mean speeds 22 percent higher than the floating car measurements, even after correcting for the differences between the space mean speeds measured by floating cars and the time mean speeds measured by the loops. TRANSYT-7F was able to predict the average travel speeds on the arterial within 3 percent of the floating car measurements and 5 percent of the aerial photograph measurements. The Highway Capacity Manual estimates were uniformly 18 percent lower than the measured floating car speeds. A correction to the method improved the estimates but tended to slightly over-compensate. The adjusted estimated speeds were 9 percent higher than the floating car speeds.

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4

Luo, Zhang, Wang, Wang, and Meng. "Traffic Patrolling Routing Problem with Drones in an Urban Road System." Sensors 19, no. 23 (November 25, 2019): 5164. http://dx.doi.org/10.3390/s19235164.

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The remarkable development of various sensor equipment and communication technologies has stimulated many application platforms of automation. A drone is a sensing platform with strong environmental adaptability and expandability, which is widely used in aerial photography, transmission line inspection, remote sensing mapping, auxiliary communication, traffic patrolling, and other fields. A drone is an effective supplement to the current patrolling business in road traffic patrolling with complex urban buildings and road conditions and a limited ground perspective. However, the limited endurance of patrol drones can be directly solved by vehicles that cooperate with drones on patrolling missions. In this paper, we first proposed and studied the traffic patrolling routing problem with drones (TPRP-D) in an urban road system. Considering road network equations and the heterogeneity of patrolling tasks in the actual patrolling process, we modeled the problem as a double-layer arc routing problem (DL-ARP). Based on graph theory and related research work, we present the mixed integer linear programming formulations and two-stage heuristic solution approaches to solve practical-sized problems. Through analysis of numerical experiments, the solution method proposed in this paper can quickly provide an optimal path planning scheme for different test sets, which can save 9%–16% of time compared with traditional vehicle patrol. At the same time, we analyze several relevant parameters of the patrol process to determine the effect of coordinated traffic patrol. Finally, a case study was completed to verify the practicability of the algorithm.

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5

Yoo, Sang-Lok, and Jong-Chul Jeong. "Safe Navigation Distance Between Marine Routes and Aquaculture Farms in South Korea Using Gaussian Mixture Model." Sensors 20, no. 5 (February 25, 2020): 1246. http://dx.doi.org/10.3390/s20051246.

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The purpose of this study was to determine the minimum separation distance between aquaculture farms and ship traffic to prevent damage to either the farms or the vessels. A high-risk area in South Korea was selected for the study by overlapping shipping routes with fisheries using satellite and aerial photographs. The annual frequency of damage was calculated based on a probability distribution applied to the sea area, and a safe distance between the aquaculture farms and the traffic was derived. The Kolmogorov–Smirnov (KS) test was conducted to determine whether the Gaussian mixture model (GMM) follows the data of this study. It was found that a safe distance of at least 1000 m is needed to avoid farm or vessel damage. Then, it is possible to prevent damage to vessel propellers and fisheries locating aquaculture farms at the minimum safe distance from the traffic routes. For protection and security of these structures, the installation of a set of wirelessly Internet of Underwater Things (IoUT) sensors that can transmit the farm location to the ship’s navigator were suggested.

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6

Hong, Tao, Qiye Yang, Peng Wang, Jinmeng Zhang, Wenbo Sun, Lei Tao, Chaoqun Fang, and Jihan Cao. "Multitarget Real-Time Tracking Algorithm for UAV IoT." Wireless Communications and Mobile Computing 2021 (August 24, 2021): 1–15. http://dx.doi.org/10.1155/2021/9999596.

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Unmanned aerial vehicles (UAVs) have increased the convenience of urban life. Representing the recent rapid development of drone technology, UAVs have been widely used in fifth-generation (5G) cellular networks and the Internet of Things (IoT), such as drone aerial photography, express drone delivery, and drone traffic supervision. However, owing to low altitude and low speed, drones can only limitedly monitor and detect small target objects, resulting in frequent intrusion and collision. Traditional methods of monitoring the safety of drones are mostly expensive and difficult to implement. In smart city construction, a large number of smart IoT cameras connected to 5G networks are installed in the city. Captured drone images are transmitted to the cloud via a high-speed and low-latency 5G network, and machine learning algorithms are used for target detection and tracking. In this study, we propose a method for real-time tracking of drone targets by using the existing monitoring network to obtain drone images in real time and employing deep learning methods by which drones in urban environments can be guided. To achieve real-time tracking of UAV targets, we employed the tracking-by-detection mode in machine learning, with the network-modified YOLOv3 (you only look once v3) as the target detector and Deep SORT as the target tracking correlation algorithm. We established a drone tracking dataset that contains four types of drones and 2800 pictures in different environments. The tracking model we trained achieved 94.4% tracking accuracy in real-time UAV target tracking and a tracking speed of 54 FPS. These results comprehensively demonstrate that our tracking model achieves high-precision real-time UAV target tracking at a reduced cost.

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7

Mehmood, Atif, and Said M. Easa. "Optimizing geometric design of roundabouts: multi-objective analysis." Canadian Journal of Civil Engineering 33, no. 1 (January 1, 2006): 29–40. http://dx.doi.org/10.1139/l05-078.

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The main objectives of roundabout design are to maximize traffic safety and operational efficiency. Traditionally, because of the complexity of the system and the multiple objectives involved, the design process is iterative and time-consuming. A minor change in the geometry can result in significant changes in the system performance (operation and safety). This paper presents an optimization model that directly provides the roundabout geometry that optimizes two objectives: design consistency and operational efficiency. Design consistency is represented by the mean difference in operating speeds for various conflicting vehicle paths and operational efficiency is represented by the average roundabout delay. Vehicle paths (through, right, and left) and roundabout delay are modeled for all roundabout approaches. The input geometric data to the model can be easily obtained from an aerial photograph of the selected site using a geographic information systems (GIS) software. The system performance is optimized subject to geometric and traffic constraints. The proposed model is applicable to single-lane roundabouts (urban and rural) with four legs intersecting at right angles. Application of the model to an actual proposed roundabout site is presented. This proposed approach provides the optimum solution directly and is also more efficient than the traditional iterative approach. Key words: geometric design, roundabouts, horizontal curve, radius, optimization, consistency, capacity, traffic delay.

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8

Coifman, Benjamin, Lizhe Li, and Wen Xiao. "Resurrecting the Lost Vehicle Trajectories of Treiterer and Myers with New Insights into a Controversial Hysteresis." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 20 (July 11, 2018): 25–38. http://dx.doi.org/10.1177/0361198118786473.

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The 1974 paper by Treiterer and Myers is a seminal work in traffic flow theory. This longevity is in part because of the impressive collection of manually extracted vehicle trajectories. To date, only a few studies have rivaled the scale of the empirical vehicle trajectory data used in Treiterer and Myers. Their data collection used high-speed aerial photography and manual data reduction to follow hundreds of vehicles. In spite of the Herculean collection effort, the trajectory data set was never released and has since been lost. Fortunately, the plots survive and the present work re-extracts the vehicle trajectory data from the time–space diagrams. The discussion places the value of the data in context and then uses the data to put an end to decades of misinterpretation that started with Treiterer himself. The central thesis of Treiterer and Myers generated considerable interest: a hysteresis whereby drivers exhibit different fundamental behavior depending on whether they are entering or exiting a disturbance. There has been extensive debate about the authors’ findings in the literature, but without the original data set any interpretation has required considerable speculation. With the resurrected trajectories, this work reexamines the vehicles underlying the hysteresis and finally quells the speculation. Rather than arising from car following behavior, it turns out that the enigmatic progression arose from a combination of lane change maneuvers and unremarkable transitions into or out of the congested regime. On publication, the re-extracted data from this paper will be released to the research community.

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9

Park, Bum-Jin, Taehyeong Kim, Inchul Yang, Jinnyung Heo, and Bongsoo Son. "A method for measuring accurate traffic density by aerial photography." Journal of Advanced Transportation 49, no. 4 (October 1, 2014): 568–80. http://dx.doi.org/10.1002/atr.1288.

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10

Mauelshagen, L. "LOW ALTITUDE AERIAL PHOTOGRAPHY." Photogrammetric Record 12, no. 68 (August 26, 2006): 239–41. http://dx.doi.org/10.1111/j.1477-9730.1986.tb00561.x.

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11

Rieke-Zapp, Dirk. "Small-Format Aerial Photography." Photogrammetric Record 26, no. 134 (June 2011): 277. http://dx.doi.org/10.1111/j.1477-9730.2011.00637_2.x.

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12

Massasati, Ahmad S. "Georeferencing Aerial Photography: Beginners Approach." Journal of Surveying Engineering 128, no. 4 (November 2002): 159–67. http://dx.doi.org/10.1061/(asce)0733-9453(2002)128:4(159).

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13

신민성 and Sanghoon Bae. "Use of Aerial Photography for Estimating Traffic Information by Vehicle Gap Distances." Journal of Transport Research 17, no. 2 (June 2010): 75–82. http://dx.doi.org/10.34143/jtr.2010.17.2.75.

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14

Sims, W. G., and M. L. Benson. "Mapping from Colour Aerial Photography." Photogrammetric Record 6, no. 33 (August 26, 2006): 321–24. http://dx.doi.org/10.1111/j.1477-9730.1969.tb00945.x.

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15

Woodrow, H. C. "Mapping from Colour Aerial Photography." Photogrammetric Record 6, no. 34 (August 26, 2006): 408. http://dx.doi.org/10.1111/j.1477-9730.1969.tb00959.x.

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16

Wallington, E. D. "Aerial photography and image interpretation." Photogrammetric Record 19, no. 108 (December 2004): 420–22. http://dx.doi.org/10.1111/j.0031-868x.2004.295_6.x.

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17

Robertson, V. C. "AERIAL PHOTOGRAPHY AND PROPER LAND UTILISATION." Photogrammetric Record 1, no. 6 (August 26, 2006): 5–12. http://dx.doi.org/10.1111/j.1477-9730.1955.tb01034.x.

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18

Welch, R., and J. Halliday. "IMAGE QUALITY CONTROLS FOR AERIAL PHOTOGRAPHY†." Photogrammetric Record 8, no. 45 (August 26, 2006): 317–25. http://dx.doi.org/10.1111/j.1477-9730.1975.tb00059.x.

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19

Matthews, M. C., and C. R. I. Clayton. "The Use of Oblique Aerial Photography to Investigate the Extent and Sequence of Landslipping at Stag Hill, Guildford, Surrey." Geological Society, London, Engineering Geology Special Publications 2, no. 1 (1986): 309–15. http://dx.doi.org/10.1144/gsl.1986.002.01.54.

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AbstractThe University of Surrey is situated on the northern slopes of Stag Hill, below Guildford Cathedral, which occupies the summit. During the investigation for the design of the University, it became apparent that the site was underlain by a large landslip, 500 m wide from east to west and extending 160 m from rear scarp to toe. Considerable effort was made to establish its geometry and extent (Skempton & Petley (1967), and Morgenstern & Tchalenko (1967)).In recent years it was realised that because the construction of the Cathedral extended over a long period of time, the likelihood of Stag Hill being covered by oblique aerial photography would be high. Some forty oblique aerial photographs, spanning the period 1949 to 1982, were collected and analysed together with vertical aerial photographs and topographic maps.Although the landslip is visible on vertical aerial photographs, individual elements are not easily identified. Using oblique photography, in particular that in which recognition of subdued topography has been enhanced by low sun angles, up to six phases of landslipping were identified.This paper uses this example to demonstrate the usefulness of aerial photography in site investigation and in particular the value of oblique photography, a topic which receives little attention in BS 5930:1981 considering how cost effective this tool can be.

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20

Schloesser, Donald W., Charles L. Brown, and Bruce A. Manny. "Use of Aerial Photography to Inventory Aquatic Vegetation." Journal of Aerospace Engineering 1, no. 3 (July 1988): 142–50. http://dx.doi.org/10.1061/(asce)0893-1321(1988)1:3(142).

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21

Hößler, Tom, and Tom Landgraf. "Automated Traffic Analysis in Aerial Images." International Journal on Smart Sensing and Intelligent Systems 7, no. 5 (2020): 1–5. http://dx.doi.org/10.21307/ijssis-2019-086.

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22

Wester-Ebbinghaus, W. "AERIAL PHOTOGRAPHY BY RADIO CONTROLLED MODEL HELICOPTER." Photogrammetric Record 10, no. 55 (August 26, 2006): 85–92. http://dx.doi.org/10.1111/j.1477-9730.1980.tb00006.x.

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23

Hiby, A. R., D. Thompson, and A. J. Ward. "CENSUS OF GREY SEALS BY AERIAL PHOTOGRAPHY." Photogrammetric Record 12, no. 71 (August 26, 2006): 589–94. http://dx.doi.org/10.1111/j.1477-9730.1988.tb00607.x.

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24

Ekin, Bill. "The Use of GPS for Low-Cost Aerial Block Photography." Journal of Navigation 48, no. 2 (May 1995): 239–48. http://dx.doi.org/10.1017/s0373463300012704.

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Flight trials using an inexpensive Garmin GPS receiver, Century 1 autopilot and a Cessna F172H aircraft to acquire block aerial photography are described. The performance of the whole system in the maintenance of constant sidelap and forward lap in block aerial vertical photography was good. However, the system was not good enough to manoeuvre the aircraft accurately on curved flight paths.

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25

Pisetskaya, Olga, Yanina Isayeva, and Maksim Goutsaki. "Application of Unmanned Flying Vehicle for Obtaining Digital Orthofotomaps." Baltic Surveying 11 (November 20, 2019): 60–69. http://dx.doi.org/10.22616/j.balticsurveying.2019.018.

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Nowadays, surveys using unmanned aerial vehicles is becoming popular. The resulting orthophotomap is the final product for creating digital plans and cardboard. The objectives of the study are to study the possibilities of obtaining orthophotomaps from survey materials using unmanned aerial vehicles based on the results of the experiment. The article describes various types of aerial photography. Some types of unmanned flying vehicles to conduct aerial photography for the purpose of monitoring, engineering surveys, inventory of agricultural land, and crop forecasts are considered. A description of aerial photography surveying is given on the example of the city of Dzerzhinsk, Minsk Region, which is performed taking into account the unmanned flying vehicles of GeoScan 201 and the Republican agricultural aero-geodesic unitary enterprise BelPSHAGI. A description of the GeoScan Planner software and basic pre-flight preparation is given. The stages of the preparatory work before the aerial photography, the creation of the planning and high-altitude geodetic justification, the implementation of aerial photography procedures, the steps of the aerial photograph anchorage procedure are considered. Agisoft Photoscan, which allows to get clouds of points, surfaces, 3D models and orthophotomaps using digital raster images are presented. The map of heights (DEM) of the terrain and the orthophotomap was made on the basis of a dense points cloud. According to the results of the research, a conclusion was made on the possibility of using aerial photography materials obtained using unmanned flying vehicles to get orthophotomaps of the required accuracy.

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Walstra, J., J. H. Chandler, N. Dixon, and T. A. Dijkstra. "Aerial photography and digital photogrammetry for landslide monitoring." Geological Society, London, Special Publications 283, no. 1 (2007): 53–63. http://dx.doi.org/10.1144/sp283.5.

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27

Amos, E. M., D. Blakeway, and C. D. Warren. "Remote Sensing Techniques in Civil Engineering Surveys." Geological Society, London, Engineering Geology Special Publications 2, no. 1 (1986): 119–24. http://dx.doi.org/10.1144/gsl.1986.002.01.26.

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AbstractThis paper outlines selected remote sensing techniques and their application to civil engineering surveys.In BS 5930, emphasis has been placed on the interpretation of black and white aerial photography to provide information. However, other techniques such as true colour and false colour infrared photography, thermal infrared, radar and landsat satellite imagery may be useful in appropriate applications.

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28

Chen, Shen-En, Corey Rice, Chuck Boyle, and Edd Hauser. "Small-Format Aerial Photography for Highway-Bridge Monitoring." Journal of Performance of Constructed Facilities 25, no. 2 (April 2011): 105–12. http://dx.doi.org/10.1061/(asce)cf.1943-5509.0000145.

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29

Bawden, M. P. "APPLICATIONS OF AERIAL PHOTOGRAPHY IN LAND SYSTEM MAPPING." Photogrammetric Record 5, no. 30 (August 26, 2006): 461–64. http://dx.doi.org/10.1111/j.1477-9730.1967.tb00897.x.

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30

Graham, R. W., and G. H. Tthomson. "CONSIDERATIONS OF SPECIFICATIONS FOR SMALL FORMAT AERIAL PHOTOGRAPHY." Photogrammetric Record 13, no. 74 (August 26, 2006): 225. http://dx.doi.org/10.1111/j.1477-9730.1989.tb00672.x.

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31

Marks, A. R. "AERIAL PHOTOGRAPHY FROM A TETHERED HELIUM FILLED BALLOON." Photogrammetric Record 13, no. 74 (August 26, 2006): 257–61. http://dx.doi.org/10.1111/j.1477-9730.1989.tb00677.x.

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32

Goba, N. L., and E. M. Senese. "THE STATUS OF SUPPLEMENTARY AERIAL PHOTOGRAPHY IN ONTARIO." Photogrammetric Record 14, no. 80 (August 26, 2006): 283–91. http://dx.doi.org/10.1111/j.1477-9730.1992.tb00253.x.

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33

Warner, W. S., and L. E. Blankenberg. "Bundle Adjustment For 35 mm Oblique Aerial Photography." Photogrammetric Record 15, no. 86 (October 1995): 217–24. http://dx.doi.org/10.1111/0031-868x.00027.

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34

Take, W. A., M. J. Chappel, R. W. I. Brachman, and R. K. Rowe. "Quantifying geomembrane wrinkles using aerial photography and digital image processing." Geosynthetics International 14, no. 4 (August 2007): 219–27. http://dx.doi.org/10.1680/gein.2007.14.4.219.

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35

Manning, J. H. "CIVIL ENGINEERING APPLICATIONS OF WARTIME RECONNAISSANCE AERIAL PHOTOGRAPHY AND RELATED MATERIAL." Photogrammetric Record 14, no. 80 (August 26, 2006): 219–26. http://dx.doi.org/10.1111/j.1477-9730.1992.tb00247.x.

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36

Weltman, Austin. "Assessing ground conditions of small sites by aerial infrared photography." Quarterly Journal of Engineering Geology and Hydrogeology 20, no. 2 (May 1987): 114–15. http://dx.doi.org/10.1144/gsl.qjeg.1987.020.02.01.

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37

Thomson, G. H. "EVALUATING IMAGE QUALITY OF SMALL FORMAT AERIAL PHOTOGRAPHY SYSTEMS." Photogrammetric Record 12, no. 71 (August 26, 2006): 595–603. http://dx.doi.org/10.1111/j.1477-9730.1988.tb00608.x.

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38

Davison, M. "HEIGHTING ACCURACY TEST FROM 1:2000 SCALE AERIAL PHOTOGRAPHY." Photogrammetric Record 14, no. 84 (October 1994): 922–25. http://dx.doi.org/10.1111/j.1477-9730.1994.tb00293.x.

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39

Huda, Feblil, Kaspul Anuar, Syafri Syafri, and Anita Susilawati. "PEMBUATAN PETA GEOSPASIAL MELALUI PEMETAAN UDARA PADA KELURAHAN BATU BERSURAT, KECAMATAN XIII KOTO KAMPAR, KABUPATEN KAMPAR, PROVINSI RIAU." Dinamisia : Jurnal Pengabdian Kepada Masyarakat 3, no. 1 (June 25, 2019): 76–83. http://dx.doi.org/10.31849/dinamisia.v3i1.2060.

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One of the most commonly used geospatial mapping methods is photogrammetry (aerial mapping). Photogrammetry is a method of mapping objects on the surface of the earth by using aerial photography as a medium. The aerial mapping process is carried out through cameras installed on Unmanned Aerial Vehicle (UAV). From the aerial photography, object interpretation and geometry measurements will be carried out to produce line maps, digital maps and photo maps. In general, photogrammetry is a mapping technology by utilizing aerial photography to be processed into a geo-spatial information system. Batu Bersurat Village is one of the villages located in Subdistrict XIII Koto Kampar, Kampar Regency, which did not have a geospatial information map. Community service team from the Mechanical Engineering Department of the University of Riau had a plan to carry out community service activities in Batu Besurat Village in the form of making geospatial information maps through aerial mapping. This aerial mapping activity was carried out by utilizing UAV with the type of fixed wing. In its implementation, the community service activities were planned to involve Mechanical Engineering students, university students of the University of Riau, village officials and the local community. It is expected that with this community service program, the geospatial information system map made by Batu Bersurat Village can be used in village spatial planning for agricultural land, residential land and validation of village boundaries.

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Liu, Hong, Mu Lin, and Luyan Deng. "UAV route planning for aerial photography under interval uncertainties." Optik 127, no. 20 (October 2016): 9695–700. http://dx.doi.org/10.1016/j.ijleo.2016.06.117.

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41

Li, Miao, Lu Zhen, Shuaian Wang, Wenya Lv, and Xiaobo Qu. "Unmanned aerial vehicle scheduling problem for traffic monitoring." Computers & Industrial Engineering 122 (August 2018): 15–23. http://dx.doi.org/10.1016/j.cie.2018.05.039.

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42

Taylor, Jessica K. D., Robert D. Kenney, Donald J. LeRoi, and Scott D. Kraus. "Automated Vertical Photography for Detecting Pelagic Species in Multitaxon Aerial Surveys." Marine Technology Society Journal 48, no. 1 (January 1, 2014): 36–48. http://dx.doi.org/10.4031/mtsj.48.1.9.

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AbstractMarine aerial surveys are designed to maximize the potential for detecting target species. Collecting data on different taxa from the same platform is economically advantageous but normally comes at the cost of compromising optimal taxon-specific scanning patterns and survey parameters, in particular altitude. Here, we describe simultaneous visual and photographic sampling methods as a proof of concept for detecting large whales and turtles from a single aircraft, despite very different sighting cues. Data were collected for fishing gear, fish, sharks, turtles, seals, dolphins, and whales using two observers and automated vertical photography. The photographic method documented an area directly beneath the aircraft that would otherwise have been obscured from observers. Preliminary density estimates were calculated for five species for which there were sufficient sample sizes from both methods after an initial year of data collection. The photographic method yielded significantly higher mean density estimates for loggerhead turtles, ocean sunfish, and blue sharks (p < 0.01), despite sampling a substantially smaller area than visual scanning (less than 11%). Density estimates from these two methods were not significantly different for leatherback turtles or basking sharks (p > 0.05), two of the largest species included in the analysis, which are relatively easy to detect by both methods. Although postflight manual processing of photographic data was extensive, this sampling method comes at no additional in-flight effort and obtains high-quality digital documentation of sightings on the trackline. Future directions for this project include automating photographic sighting detections, expanding the area covered by photography, and performing morphometric measurement assessments.

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43

Du, Yuchuan, Cong Zhao, Feng Li, and Xuefeng Yang. "An Open Data Platform for Traffic Parameters Measurement via Multirotor Unmanned Aerial Vehicles Video." Journal of Advanced Transportation 2017 (2017): 1–12. http://dx.doi.org/10.1155/2017/8324301.

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Multirotor unmanned aerial vehicle video observation can obtain accurate information about traffic flow of large areas over extended times. This paper aims to construct an open data test platform for updated traffic data accumulation and traffic simulation model verification by analyzing real time aerial video. Common calibration boards were used to calibrate internal camera parameters and image distortion correction was performed using a high-precision distortion model. To solve external parameters calibration problems, an existing algorithm was improved by adding two sets of orthogonal equations, achieving higher accuracy with only four calibrated points. A simplified algorithm is proposed to calibrate cameras by calculating the relationship between pixel and true length under the camera optical axis perpendicular to road conditions. Aerial video (160 min) from the Shanghai inner ring expressway was collected and real time traffic parameter values were obtained from analyzing and processing the aerial visual data containing spatial, time, velocity, and acceleration data. The results verify that the proposed platform provides a reasonable and objective approach to traffic simulation model verification and improvement. The proposed data platform also offers significant advantages over conventional methods that use historical and outdated data to run poorly calibrated traffic simulation models.

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44

Wang, Kaipeng, Zhijun Meng, and Zhe Wu. "Deep Learning-Based Ground Target Detection and Tracking for Aerial Photography from UAVs." Applied Sciences 11, no. 18 (September 11, 2021): 8434. http://dx.doi.org/10.3390/app11188434.

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Target detection and tracking can be widely used in military and civilian scenarios. Unmanned aerial vehicles (UAVs) have high maneuverability and strong concealment, thus they are very suitable for using as a platform for ground target detection and tracking. Most of the existing target detection and tracking algorithms are aimed at conventional targets. Because of the small scale and the incomplete details of the targets in the aerial image, it is difficult to apply the conventional algorithms to aerial photography from UAVs. This paper proposes a ground target image detection and tracking algorithm applied to UAVs using a revised deep learning technology. Aiming at the characteristics of ground targets in aerial images, target detection algorithms and target tracking algorithms are improved. The target detection algorithm is improved to detect small targets on the ground. The target tracking algorithm is designed to recover the target after the target is lost. The target detection and tracking algorithm is verified on the aerial dataset.

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Tian, Dehong, Jianmin He, Jie Qi, and Haixin Sun. "Research on the Modeling and Simulation of Optimal Dynamic Aerial Ammunition Scheduling and Transportation." Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 36, no. 6 (December 2018): 1236–42. http://dx.doi.org/10.1051/jnwpu/20183661236.

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To optimize the aerial ammunition scheduling and transportation, both the synergy among all departments of aerial ammunition support system and uncertain factors, such as traffic and attack situations, are taken into consideration in the model. The traffic and attack situations of roads are quantified as crossing time through the model so that the optimization can be simplified into multi-source shortest path problem. Then the optimal transport path of aerial ammunition and combination of storages can be determined by the improved Floyd-Warshall algorithm. Simulation result shows that the dynamic aerial ammunition scheduling and transportation model proposed in this paper is more suitable than traditional model in changing the decision according to the real-time fighting, so as to provide more reliable guarantee of troops.

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Mastelic, Toni, Josip Lorincz, Ivan Ivandic, and Matea Boban. "Aerial Imagery Based on Commercial Flights as Remote Sensing Platform." Sensors 20, no. 6 (March 17, 2020): 1658. http://dx.doi.org/10.3390/s20061658.

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Remote sensing is commonly performed via airborne platforms such as satellites, specialized aircraft, and unmanned aerial systems (UASs), which perform airborne photography using mounted cameras. However, they are limited by their coverage (UASs), irregular flyover frequency (aircraft), and/or low spatial resolution (satellites) due to their high altitude. In this paper, we examine the utilization of commercial flights as an airborne platform for remote sensing. Namely, we simulate a situation where all aircraft on commercial flights are equipped with a mounted camera used for airborne photography. The simulation is used to estimate coverage, the temporal and spatial resolution of aerial imagery acquired this way, as well as the storage capacity required for storing all imagery data. The results show that Europe is 83.28 percent covered with an average of one aerial photography every half an hour and a ground sampling distance of 0.96 meters per pixel. Capturing such imagery results in 20 million images or four petabytes of image data per day. More detailed results are given in the paper for separate countries/territories in Europe, individual commercial airlines and alliances, as well as three different cameras.

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Pérez, Juan Antonio, Francisco Manuel Bascon, and María Cristina Charro. "Photogrammetric Usage of 1956-57 Usaf Aerial Photography of Spain." Photogrammetric Record 29, no. 145 (February 27, 2014): 108–24. http://dx.doi.org/10.1111/phor.12048.

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Spencer, R. D. "FILM TRIALS OF AERIAL PHOTOGRAPHY FOR FORESTRY IN VICTORIA, AUSTRALIA." Photogrammetric Record 9, no. 51 (August 26, 2006): 391–403. http://dx.doi.org/10.1111/j.1477-9730.1978.tb00431.x.

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Cox, R. C. A. "THE BENEFITS OF FORWARD MOTION COMPENSATION FOR AERIAL SURVEY PHOTOGRAPHY." Photogrammetric Record 14, no. 79 (August 26, 2006): 5–17. http://dx.doi.org/10.1111/j.1477-9730.1992.tb00204.x.

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Dando, R. C. A. "ROYAL PHOTOGRAPHIC SOCIETY ACTIVITIES IN AERIAL PHOTOGRAPHY AND REMOTE SENSING." Photogrammetric Record 14, no. 79 (August 26, 2006): 129–30. http://dx.doi.org/10.1111/j.1477-9730.1992.tb00212.x.

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