RESEARCH ON SHAPE CHARACTERISTIC OF 3D MODELING SOFTWARE (SfM/MVS) IN UAV AERIAL IMAGES

Kitagawa, Etsuji; Muraki, Hirokazu; Yoshinaga, Kyouhei; Tsumura, Yakumi

doi:10.2208/jscejcei.74.ii_143

Cited by 3 publications

(5 citation statements)

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“…However, the estimated values of all SfM software tended to be underestimated compared to the measured values. In addition, the generated images were similar to the results of previous studies [31,[42][43][44]48], which used different SfM software. Therefore, although the SfM process was performed using different PCs, the results of this study show little influence.…”

Section: Discussionsupporting

confidence: 68%

“…In addition, PhotoScan was superior in terms of image processing while Pix4Dmapper was superior in terms of forest information estimation. The analysis of different SfM software packages in previous studies has shown that PhotoScan is superior for image generation [31,42,43,48]. In addition, Villanueva et al [44] found that the DSM obtained with Pix4Dmapper was slightly more accurate than that obtained with PhotoScan.…”

Section: Discussionmentioning

confidence: 99%

“…Sugai et al [38] verified the accuracy of photogrammetry using Pix4Dmapper, PhotoScan, and Smart3Dcapture, stating that the effects of the number of control points and the distribution of points on the analysis results differed depending on the software. Kitagawa [42] extracted features from two experiments, and compared their differences. PhotoScan produced a clearer image, but had weak displacement extraction, while Pix4Dmapper had a z-value fluctuation, but strong displacement extraction [42].…”

Section: Introductionmentioning

confidence: 99%

“…Kitagawa [42] extracted features from two experiments, and compared their differences. PhotoScan produced a clearer image, but had weak displacement extraction, while Pix4Dmapper had a z-value fluctuation, but strong displacement extraction [42]. Sona et al [43] processed images with Erdas-LPS, EyeDEA, PhotoScan, Pix4UAV, and PhotoModeler Scanner to evaluate their characteristics, capabilities, and weaknesses.…”

Section: Introductionmentioning

confidence: 99%

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Effects of Differences in Structure from Motion Software on Image Processing of Unmanned Aerial Vehicle Photography and Estimation of Crown Area and Tree Height in Forests

Kameyama

Sugiura

2021

Remote Sensing

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This study examines the effects of differences in structure from motion (SfM) software on image processing of aerial images by unmanned aerial vehicles (UAV) and the resulting estimations of tree height and tree crown area. There were 20 flight conditions for the UAV aerial images, which were a combination of five conditions for flight altitude, two conditions for overlap, and two conditions for side overlap. Images were then processed using three SfM programs (Terra Mapper, PhotoScan, and Pix4Dmapper). The tree height and tree crown area were determined, and the SfM programs were compared based on the estimations. The number of densified point clouds for PhotoScan (160 × 105 to 50 × 105) was large compared to the two other two SfM programs. The estimated values of crown area and tree height by each SfM were compared via Bonferroni multiple comparisons (statistical significance level set at p < 0.05). The estimated values of canopy area showed statistically significant differences (p < 0.05) in 14 flight conditions for Terra Mapper and PhotoScan, 16 flight conditions for Terra Mapper and Pix4Dmapper, and 11 flight conditions for PhotoScan and Pix4Dmappers. In addition, the estimated values of tree height showed statistically significant differences (p < 0.05) in 15 flight conditions for Terra Mapper and PhotoScan, 19 flight conditions for Terra Mapper and Pix4Dmapper, and 20 flight conditions for PhotoScan and Pix4Dmapper. The statistically significant difference (p < 0.05) between the estimated value and measured value of each SfM was confirmed under 18 conditions for Terra Mapper, 20 conditions for PhotoScan, and 13 conditions for Pix4D. Moreover, the RMSE and rRMSE values of the estimated tree height were 5–6 m and 20–28%, respectively. Although the estimation accuracy of any SfM was low, the estimated tree height by Pix4D in many flight conditions had smaller RMSE values than the other software. As statistically significant differences were found between the SfMs in many flight conditions, we conclude that there were differences in the estimates of crown area and tree height depending on the SfM used. In addition, Pix4Dmapper is suitable for estimating forest information, such as tree height, and PhotoScan is suitable for detailed monitoring of disaster areas.

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Section: Discussionsupporting

confidence: 68%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Effects of Differences in Structure from Motion Software on Image Processing of Unmanned Aerial Vehicle Photography and Estimation of Crown Area and Tree Height in Forests

Kameyama

Sugiura

2021

Remote Sensing

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“…Orthomosaics, DSMs, 3D models, mesh models, and point clouds were presented as the analysis results, and methods for setting and applying analysis methodologies were proposed [13][14][15][16][17][18][19]. Image mapping constructed topographic data using software, such as Pix4D Mapper, Photoscan, and ContextCapture, and presented the advantages and drawbacks of the analysis speed and measurement accuracy [15,[20][21][22]. In particular, PhotoScan has a high processing speed and work convenience, while Pix4D Mapper facilitates data extraction with high accuracy of the topographic data [23][24][25][26].…”

Section: Relative Workmentioning

confidence: 99%

A Study on the Determination Methods of Monitoring Point for Inundation Damage in Urban Area Using UAV and Hydrological Modeling

Song

Lee

Kang

et al. 2022

Water

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Recently, unmanned aerial vehicles (UAVs) have been used in various fields, such as military, logistics, transportation, construction, and agriculture, making it possible to apply the limited activities of humans to various and wide ranges. In addition, UAVs have been utilized to construct topographic data that are more precise than existing satellite images or cadastral maps. In this study, a monitoring point for preventing flood damage in an urban area was selected using a UAV. In addition, the topographic data were constructed using a UAV, and the flow of rainwater was examined using the watershed analysis in an urban area. An orthomosaic, a digital surface model (DSM), and a three-dimensional (3D) model were constructed for the topographic data, and a precision of 0.051 m based on the root mean square error (RMSE) was achieved through the observation of ground control points (GCPs). On the other hand, for the watershed analysis in the urban area, the point in which the flow of rainwater converged was analyzed by adjusting the thresholds. A monitoring point for preventing flood damage was proposed by examining the topographic characteristics of the target area related to the inflow of rainwater.

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Estimating Tree Height and Volume Using Unmanned Aerial Vehicle Photography and SfM Technology, with Verification of Result Accuracy

Kameyama

Sugiura

2020

Drones

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This study aimed to investigate the effects of differences in shooting and flight conditions for an unmanned aerial vehicle (UAV) on the processing method and estimated results of aerial images. Forest images were acquired under 80 different conditions, combining various aerial photography methods and flight conditions. We verified errors in values measured by the UAV and the measurement accuracy with respect to tree height and volume. Our results showed that aerial images could be processed under all the studied flight conditions. However, although tree height and crown were decipherable in the created 3D model in 64 conditions, they were undecipherable in 16. The standard deviation (SD) in crown area values for each target tree was 0.08 to 0.68 m2. UAV measurements of tree height tended to be lower than the actual values, and the RMSE (root mean square error) was high (5.2 to 7.1 m) through all the 64 modeled conditions. With the estimated volume being lower than the actual volume, the RMSE volume measurements for each flight condition were from 0.31 to 0.4 m3. Therefore, irrespective of flight conditions for UAV measurements, accuracy was low with respect to the actual values.

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RESEARCH ON SHAPE CHARACTERISTIC OF 3D MODELING SOFTWARE (SfM/MVS) IN UAV AERIAL IMAGES

Cited by 3 publications

References 0 publications

Effects of Differences in Structure from Motion Software on Image Processing of Unmanned Aerial Vehicle Photography and Estimation of Crown Area and Tree Height in Forests

Effects of Differences in Structure from Motion Software on Image Processing of Unmanned Aerial Vehicle Photography and Estimation of Crown Area and Tree Height in Forests

A Study on the Determination Methods of Monitoring Point for Inundation Damage in Urban Area Using UAV and Hydrological Modeling

Estimating Tree Height and Volume Using Unmanned Aerial Vehicle Photography and SfM Technology, with Verification of Result Accuracy

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