Evaluation of UAV Photogrammetric Accuracy for Mapping and Earthworks Computations

GEOMATICA ◽  
2014 ◽  
Vol 68 (4) ◽  
pp. 309-317 ◽  
Author(s):  
Chris Cryderman ◽  
S. Bill Mah ◽  
Aaron Shufletoski
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Confidence Level ◽  
Geometric Analysis ◽  
Weather Conditions ◽  
Ground Control ◽  
Surface Models ◽  
Aerial Vehicle ◽  
Survey Results

This study quantifies the accuracies achieved and tests the validity of an in-house developed Unmanned Aerial Vehicle (UAV) system employed in a stockpile volumetric survey. UAV photogrammetric results are compared with conventional GNSS survey results. To test the repeatability of the UAV system, multiple flights were flown over the same stockpile using different GNSS ground control, at different times and weather conditions. Positional accuracies of UAV photogrammetric results were found to be very similar to those from GNSS RTK survey, at the scale of photography flown. UAV stockpile volume results agreed with those from GNSS within 3 755 m3 (0.7%) on a 530 255 m3 pile. Stockpile volume comparisons between subsequent UAV surface models agreed within 877 m3 (0.2%) on the same pile. Geometric analysis of independent UAV photogrammetric models over the same area indicated that they could be considered the same at a 95% confidence level. We conclude that the UAV photogrammetric approach is, at the very least, equivalent in accuracy to GNSS RTK surveys at the scale of photography observed. The accuracy of the UAV photogrammetric surveys were sufficient for 1:200 scale mapping and 0.145 m contours. The UAV photogrammetric approach also provided greater detail, resulting in more representative models of the measured surfaces.

scholarly journals Ground Control Point-Free Unmanned Aerial Vehicle-Based Photogrammetry for Volume Estimation of Stockpiles Carried on Barges

Sensors ◽  
2019 ◽  
Vol 19 (16) ◽  
pp. 3534 ◽  
Author(s):  
Haiqing He ◽  
Ting Chen ◽  
Huaien Zeng ◽  
Shengxiang Huang
Keyword(s):  
Free Surface ◽  
Unmanned Aerial Vehicle ◽  
Control Point ◽  
Dynamic Environment ◽  
Measurement Unit ◽  
Ground Control ◽  
Ground Control Point ◽  
Surface Models ◽  
Aerial Vehicle ◽  
Uav Images

In this study, an approach using ground control point-free unmanned aerial vehicle (UAV)-based photogrammetry is proposed to estimate the volume of stockpiles carried on barges in a dynamic environment. Compared with similar studies regarding UAVs, an indirect absolute orientation based on the geometry of the vessel is used to establish a custom-built framework that can provide a unified reference instead of prerequisite ground control points (GCPs). To ensure sufficient overlap and reduce manual intervention, the stereo images are extracted from a UAV video for aerial triangulation. The region of interest is defined to exclude the area of water in all UAV images using a simple linear iterative clustering algorithm, which segments the UAV images into superpixels and helps to improve the accuracy of image matching. Structure-from-motion is used to recover three-dimensional geometry from the overlapping images without assistance of exterior parameters obtained from the airborne global positioning system and inertial measurement unit. Then, the semi-global matching algorithm is used to generate stockpile-covered and stockpile-free surface models. These models are oriented into a custom-built framework established by the known distance, such as the length and width of the vessel, and they do not require GCPs for coordinate transformation. Lastly, the volume of a stockpile is estimated by multiplying the height difference between the stockpile-covered and stockpile-free surface models by the size of the grid that is defined using the resolution of these models. Results show that a relatively small deviation of approximately ±2% between the volume estimated by UAV photogrammetry and the volume calculated by traditional manual measurement was obtained. Therefore, the proposed approach can be considered the better solution for the volume measurement of stockpiles carried on barges in a dynamic environment because UAV-based photogrammetry not only attains superior density and spatial object accuracy but also remarkably reduces data collection time.

scholarly journals Pemanfaatan Metode Fotogrametri untuk Pengukuran Garis Pantai dan Identifikasi Objek-Objek Tematik dengan Menggunakan Wahana Uav (Unmanned Aerial Vehicle) (Studi Kasus Pengukuran Garis Pantai di Pangkalan TNI AL Pondok Dayung

2020 ◽  
Vol 5 (1) ◽  
pp. 71-84
Author(s):  
Adhyta Harfan ◽  
Dipo Yudhatama ◽  
Imam Bachrodin
Keyword(s):  
Real Time ◽  
Unmanned Aerial Vehicle ◽  
Control Point ◽  
Ground Control ◽  
Ground Control Point ◽  
Real Time Kinematic ◽  
Aerial Vehicle

Metode Fotogrametri telah banyak digunakan dalam survei dan pemetaan. Seiring dengan kemajuan ilmu pengetahuan dan teknologi, metode fotogrametri saat ini berbasiskan pesawat tanpa awak atau yang lebih dikenal dengan UAV (Unmanned Aerial Vehicle). Kelebihan metode fotogrametri berbasiskan UAV untuk pengukuran garis pantai adalah memiliki resolusi spasial yang sangat tinggi dan dapat menjagkau daerah-daerah yang sulit dan berbahaya. Di samping itu juga dapat memberikan data foto udara terkini dengan sekala detail. Dalam penelitian ini membandingkan ketelitian horisontal antara hasil pengukuran garis pantai menggunakan metode fotogrametri berbasiskan UAV secara rektifikasi dengan GCP (Ground Control Point) maupun secara PPK (Post Processed Kinematic) dengan pengukuran garis pantai metode GNSS RTK (Real Time Kinematic). Hasil perhitungan ketelitian horisontal mengacu pada standar publikasi IHO S-44 tentang pengukuran garis pantai. Pemotretan dilakukan dengan ketinggian terbang 180 m, dengan tampalan depan dan samping 80%. Hasil perhitungan ketelitian horisontal foto udara terektifikasi 5 GCP, foto udara PPK dan foto udara PPK terektifikasi 1 GCP terhadap pengukuran garis pantai dengan metode GNSS RTK diperoleh nilai standar deviasi (σ) dan 95% selang kepercayaan (CI95%) masing-masing sebagai berikut: σ5gcp=10,989 cm dengan CI95% 16.8 cm < μ < 21.2 cm , σppk=26,066 cm dengan CI95% 26.5 cm < μ < 37 cm dan σppk1gcp=10,378 cm dengan CI95% 15.6 cm < μ < 19.8 cm. Kemudian terdapat 10 objek tematik berdasarkan Peta Laut Nomor 1 yang dapat diinterpretasi pada hasil orthomosaic foto udara.

scholarly journals Aplikasi UAV (Unmanned Aerial Vehicle) untuk Monitoring Zona Pantai

2021 ◽  
Vol 2 (9) ◽  
pp. 1663-1681
Author(s):  
Dio Mega Putri ◽  
Ahmad Perwira Mulia
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Control Point ◽  
Data Monitoring ◽  
Ground Control ◽  
Ground Control Point ◽  
Area Survey ◽  
Aerial Vehicle

Salah satu fungsi manajemen zona pantai adalah untuk menjaga kestabilan pantai sehingga sangat memerlukan data monitoring zona pantai. Namun, data monitoring dan penelitian tentang kondisi zona pantai dan perubahan garis pantai masih sedikit. Pesatnya perkembangan teknologi mengakibatkan pekerjaan survei dan pemetaan zona pantai kini dapat dilakukan dengan mudah, yaitu dengan menggunakan teknologi UAV. Penelitian ini bertujuan untuk menganalisis kondisi zona pantai berdasarkan ortofoto yang diambil oleh UAV yang dikontrol dengan menggunakan GPS Geodetik di lapangan dan menguraikan tahapan pembentukan fotogrametri dengan UAV hingga menghasilkan gambar ortofoto yang terkoreksi. Metodologi yang diterapkan dalam penelitian ini terdiri dari prasurvei, survei lapangan dan pasca survei. Tahapan awal penelitian meliputi persiapan teknis dan non teknis, pengamatan area survey dan melakukan studi referensi. Tahapan survei lapangan dilakukan untuk mengumpulkan data primer berupa hasil pengukuran Ground Control Point (GCP) dan pengambilan mosaik foto udara menggunakan UAV/Drone, mengambil foto dokumentasi lapangan, serta memenuhi kebutuhan survei lainnya. Tahapan pasca survei merupakan kegiatan pengolahan data foto udara serta pengolahan foto dokumentasi. Nilai ketentuan ketelitian geometri berdasarkan kelas (CE90 dan LE90) termasuk ke dalam kelas 1. Berdasarkan hasil perhitungan selisih jarak beberapa objek di foto pada komputer dan jarak sebenarnya di lapangan, diperoleh rata-rata persentase akurasi sebesar 97%. Hal tersebut menandakan bahwa pengukuran menggunakan UAV memiliki akurasi yang tinggi. UAV merupakan alat yang ideal untuk survei dan pemetaan zona pantai serta masalah pantai lainnya.

scholarly journals Synthesis of algorithm of unmanned aerial vehicle detection by acoustic noise

Doklady BGUIR ◽  
2021 ◽  
Vol 19 (2) ◽  
pp. 65-73
Author(s):  
A. D. Puzanau ◽  
D. S. Nefedov
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Acoustic Noise ◽  
Signal To Noise Ratio ◽  
Weather Conditions ◽  
Wind Noise ◽  
Detection Range ◽  
Detection Systems ◽  
A Value ◽  
Coherent Accumulation ◽  
Aerial Vehicle

 The algorithm of detection of acoustic noise provided by an unmanned aerial vehicle (UAV) in the noise background due to wind is synthesized in the article. Creation of the algorithm has been carried out using the Neyman – Pearson lemma. The algorithm assumes a combination of the stages of wind noise coherent compensation and coherent accumulation of UAV’s acoustic noise sound pressure impulses. The coherent accumulation time matches doubled time of fluctuation correlation resulted by experimental research of acoustic noise of different types of  UAVs. Efficiency of the developed algorithm of UAV detection depends on flight velocity, foreshortening, amount of blades and rotor turnovers of UAV as well as weather conditions. For the probability of a false alarm value of 10–4, the probability of correct UAV detection value of 0.9 is provided wherein signal-to-noise ratio has a value of 8 dB. These indicators correspond the detection range of 200 to 300 meters. The obtained results allow discussions about perspective of acoustic UAVs detection systems adaptation. 

scholarly journals UAVC: A New Method for Correcting Lidar Overlap Factors Based on Unmanned Aerial Vehicle Vertical Detection

2021 ◽  
Vol 12 (1) ◽  
pp. 184
Author(s):  
Ming Zhao ◽  
Zhiyuan Fang ◽  
Hao Yang ◽  
Liangliang Cheng ◽  
Jianfeng Chen ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Extinction Coefficient ◽  
Weather Conditions ◽  
Lidar Signal ◽  
Aerial Vehicle ◽  
Changing Trend ◽  
Overlap Factor ◽  
The Vertical Distribution ◽  
Matter Concentration ◽  
Mie Lidar

A method to calibrate the overlap factor of Lidar is proposed, named unmanned aerial vehicle correction (UAVC), which uses unmanned aerial vehicles (UAVs) to detect the vertical distribution of particle concentrations. The conversion relationship between the particulate matter concentration and the aerosol extinction coefficient is inverted by the high-altitude coincidence of the vertical detection profiles of the UAV and Lidar. Using this conversion relationship, the Lidar signal without the influence of the overlap factor can be inverted. Then, the overlap factor profile is obtained by comparing the signal with the original Lidar signal. A 355 nm Raman-Mie Lidar and UAV were used to measure overlap factors under different weather conditions. After comparison with the Raman method, it is found that the overlap factors calculated by the two methods are in good agreement. The changing trend of the extinction coefficient at each height is relatively consistent, after comparing the inversion result of the corrected Lidar signal with the ground data. The results show that after the continuously measured Lidar signal is corrected by the overlap factor measured by this method, low-altitude aerosol information can be effectively obtained.

Recommendations for UAV Pre-Flight Preparation

2020 ◽  
Vol 67 (1) ◽  
pp. 93-98 ◽  
Author(s):  
Rashid K. Kurbanov ◽  
Olga M. Zakharova
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Unmanned Aerial Vehicle ◽  
Visual Inspection ◽  
Weather Conditions ◽  
Aerial Vehicles ◽  
Safety Research ◽  
Aerial Vehicle ◽  
Test Flight ◽  
And Storage ◽  
Measuring Unit

The current level of technical development and accessibility allows to consider unmanned aerial vehicles as a reliable tool for operational monitoring of agricultural territories. Drones are able to observe territories that are inaccessible to helicopters and small aircrafts. The use of drones is associated with certain risks that affect flight safety. (Research purpose) To make recommendations on the preflight preparation of unmanned aerial vehicles. (Materials and methods) The authors used scientific literature, survey materials of domestic and foreign authors, websites of UAV manufacturers. (Results and discussion) The authors examined the issues of a drone registration, key parameters that influence data collection and ensure safe monitoring: operation and storage of drone batteries, visual inspection of a drone, sensors calibration, setting the “return home” point and checking the signal GPS/GLONASS communication quality, test flight, restricted areas and weather conditions. (Conclusions) It was established that UAV pre-flight preparation was an important stage in monitoring agricultural fields, which included a number of operations that were carried out with the aim of ensuring the safety of the operator and the unmanned aerial vehicle, as well as to obtain high-quality aerial photography materials. The authors determined that an unmanned aerial vehicle weighing from 250 grams to 30 kilograms was a object to be registered. They identified the need for specialized software, compliance with the rules of operation and storage of batteries, a thorough visual inspection of the drone, calibration of the compass; checking the setting of the return point to the beginning of the route, the GPS/GLONASS signal level, conducting a test flight, monitoring the readings of the inertial measuring unit and weather conditions, checking the zone of prohibited flights.

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