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A precise location in aerial surveying can only be achieved using Ground Control Points GCPs. At least three point should be used and as the number increases the model will be more precise in X, Y and Z positions for a certain extent. The distribution of the GCPs also affect the precision of the 3D model resulted from the aerial imaging. This study aims to find the optimum number and distribution of the GCPs to achieve the minimal error in points location. 1.5 km2 of longitudinal area was imaged with a commercial UAV named DJI Mavic 2 pro with at nadir camera orientation at height of 100 m above the ground. A total of 1515 images were taken with average ground sampling distance (GSD) of 2.3 cm. Deferential Global Positioning System DGPS Leica GS 15 receiver were used to observe the 62 ground control points with PPK fashion. The project area was divided into two regions the first region has a parallel distribution of GCPs and the second region has a zigzag distribution. The images were processed using Pix4Dmapper and Agisoft Metashape software by applying a bundle adjustment process with an incremental number of GCPs starting with 3 and finishes with 26 for each distribution pattern, the remaining points were used as a check points to determine the precision of the model at each trial. The resulted coordinates of check points were compared with the coordinates observed with the DGPS. The comparison depicts the optimum number of GCPs required for the best location precision and the best distribution pattern.
A precise location in aerial surveying can only be achieved using Ground Control Points GCPs. At least three point should be used and as the number increases the model will be more precise in X, Y and Z positions for a certain extent. The distribution of the GCPs also affect the precision of the 3D model resulted from the aerial imaging. This study aims to find the optimum number and distribution of the GCPs to achieve the minimal error in points location. 1.5 km2 of longitudinal area was imaged with a commercial UAV named DJI Mavic 2 pro with at nadir camera orientation at height of 100 m above the ground. A total of 1515 images were taken with average ground sampling distance (GSD) of 2.3 cm. Deferential Global Positioning System DGPS Leica GS 15 receiver were used to observe the 62 ground control points with PPK fashion. The project area was divided into two regions the first region has a parallel distribution of GCPs and the second region has a zigzag distribution. The images were processed using Pix4Dmapper and Agisoft Metashape software by applying a bundle adjustment process with an incremental number of GCPs starting with 3 and finishes with 26 for each distribution pattern, the remaining points were used as a check points to determine the precision of the model at each trial. The resulted coordinates of check points were compared with the coordinates observed with the DGPS. The comparison depicts the optimum number of GCPs required for the best location precision and the best distribution pattern.
Ground Control Points GCPs are the only way to obtain accurate positions in aerial surveys. At least three points should be utilized, and the model will get increasingly accurate in X, Y, and Z coordinates as the number rises. The accuracy of the 3D model created from aerial photography is also affected by the arrangement of GCPs. The goal of this research is to determine the optimal number and arrangement of GCPs in order to obtain the lowest possible error in point positioning. A conventional UAV called DJI Mavic 2 pro was used to photograph one and a half square kilometer site at an elevation equal to hundred meters from earth’s surface with nadir camera configuration. GSD (ground sampling distance) of 2.3 centimeters was used to collect 1515 pictures. 62 GCPs were observed in PPK (Post Processing kinematic) method using a DGPS (differential global positioning system) receiver GS 15 from Leica. The study area was split into two areas, one with a straight arrangement of GCPs and the other with a diagonal arrangement of GCPs. The pictures were processed using 3Dsurvey and 3DF Zephyr software utilizing a full bundle adjustment procedure with increasing GCPs number beginning with three GCPs and ending with twenty-six GCPs for both arrangement layout, with the other points serving as check points for the model’s accuracy at each attempt. The check point coordinates obtained were compared to the DGPS coordinates. The result indicates the optimal GCP number needed for the most accurate position and spread layout. That the minimum gap between adjacent GCPs ought to be not over than 100 meters and spread homogenously.
Terrestrial laser scanning is a potential emerging technology increasingly used in several applications, including reverse engineering, digital reconstruction, deformation monitoring, forensic crime scene preservation, and construction (AEC) applications. The data tolerance accepted in these applications ranges from tens of millimeters (e.g., historical monument digitization) to tens of micrometers (e.g., industrial high-precision manufacturing and assembling). Instrument mechanism, atmospheric conditions, object surface characteristics, and scan geometry are the four main factors that affect the laser point clouds produced by the Time of Flight (TOF) 3D laser scanner. Consequently, research groups worldwide have put a significant effort into modeling the sources of TOF-TLS errors and design-specific performance evaluation methodologies. This paper investigated the influence of scanning geometry parameterized by incidence angle and the range on the quality of TOF-TLS data in industrial sites. The quality of an indoor sample dataset of an industrial case study was studied and assessed. The results showed that the incidence angle and range parameters substantially impacted the quality of the TOF-TLS data. The suggested methodology can accurately correct the laser data to eliminate the incidence angle and range effects. A revised and optimized point cloud dataset was reconstructed by utilizing these features in conjunction with the approximated quality of the individual points. Furthermore, when assessing the quality of individual point clouds, the accuracy validation obtained through the RMSE value was 3 mm based on ground-truth reference points. On the other hand, the standard deviation values computed through the Multi-Scale Model-to-model cloud (M3C2) analysis were revealed to reach 1mm, which shows better performance results than the Cloud-to-Cloud (C2C) and Cloud-to-Model (C2M) comparison analysis. However, the proposed method may result in the elimination of several significant laser points. These points of high incidence angle values are not eliminated in every instance. The effect of scanning geometry, represented by the angle of incidence with the normalized intensity of the scanning points, should be studied intensively in future studies. ABSTRAK: Terestrial pengimbas laser adalah teknologi yang berpotensi besar dalam pelbagai aplikasi, termasuk kejuruteraan balikan, rekonstruksi digital, pengawasan perubahan bentuk, pemeliharaan tempat kejadian jenayah forensik, dan aplikasi konstruksi (AEC). Penerimaan data toleransi dalam aplikasi ini adalah dalam julat lingkungan beberapa milimeter (cth: digitalisasi monumen sejarah) sehingga beberapa mikrometer (cth: industri pembuatan berkejituan tinggi dan pemasangan). Mekanisme alatan, keadaan atmosfera, ciri-ciri permukaan objek, dan geometri pengimbas adalah empat faktor utama yang memberi kesan terhadap gumpalan asap titik laser terhasil daripada masa terbang (TOF) 3D pengimbas laser. Oleh itu, kumpulan pengkaji sedunia telah berusaha bersungguh-sungguh dalam pemodelan sumber ralat TOF-TLS dan mereka kaedah penilaian prestasi reka bentuk tertentu. Kajian ini dipengaruhi oleh geometri pengimbas berparameter sudut tuju dan julat kualiti data TOF-TLS dalam kawasan industri. Kualiti sampel set data dalam bangunan menggunakan kajian pembelajaran industri telah diteliti dan dinilai. Dapatan kajian menunjukkan sudut tuju dan julat parameter sangat mempengaruhi kualiti data TOF-TLS. Kaedah yang dicadangkan ini dapat memperbetulkan arah secara tepat iaitu kesan pengurangan sudut tuju dan julat. Set data rawak titik yang diubah dan dioptimumkan telah dibina semula dengan menggunakan ciri-ciri ini bersempena kualiti anggaran titik-titik individu. Tambahan, apabila menaksir kualiti titik rawak individu, pengesahan ketepatan yang diperoleh melalui nilai RMSE dijumpai sebanyak 3 mm berdasarkan titik-titik panduan kesahihan bumi. Di samping itu, nilai sisihan piawai yang dikira melalui analisis Model-ke-model Skala-Pelbagai Rawak (M3C2) didapati mencapai 1 mm, di mana menunjukkan dapatan prestasi lebih baik berbanding analisis Rawak-ke-rawak (C2C) dan Rawak-ke-Model (C2M) secara bandingan. Walau bagaimanapun, kaedah yang dicadangkan ini mungkin menyebabkan penyisihan beberapa titik laser penting. Titik-titik ini yang mempunyai nilai sudut tuju yang tinggi adalah tidak disisihkan pada setiap masa. Kesan pengimbas geometri, merupakan sudut tuju dengan keamatan ternormal titik-titik pengimbas, perlu dikaji dengan lebih lanjut pada masa depan.
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