Integrated use of unmanned aerial vehicle photogrammetry and terrestrial laser scanning to support archaeological analysis: The Acropolis of Selinunte case (Sicily, Italy)

2020 ◽  
Author(s):  
Antonio Costanzo ◽  
Antonino Pisciotta ◽  
Maria Ilaria Pannaccione Apa ◽  
Simona Bongiovanni ◽  
Patrizia Capizzi ◽  
...  
2019 ◽  
Vol 8 (2) ◽  
pp. 53 ◽  
Author(s):  
Young Jo ◽  
Seonghyuk Hong

Three-dimensional digital technology is important in the maintenance and monitoring of cultural heritage sites. This study focuses on using a combination of terrestrial laser scanning and unmanned aerial vehicle (UAV) photogrammetry to establish a three-dimensional model and the associated digital documentation of the Magoksa Temple, Republic of Korea. Herein, terrestrial laser scanning and UAV photogrammetry was used to acquire the perpendicular geometry of the buildings and sites, where UAV photogrammetry yielded higher planar data acquisition rate in upper zones, such as the roof of a building, than terrestrial laser scanning. On comparing the two technologies’ accuracy based on their ground control points, laser scanning was observed to provide higher positional accuracy than photogrammetry. The overall discrepancy between the two technologies was found to be sufficient for the generation of convergent data. Thus, the terrestrial laser scanning and UAV photogrammetry data were aligned and merged post conversion into compatible extensions. A three-dimensional (3D) model, with planar and perpendicular geometries, based on the hybrid data-point cloud was developed. This study demonstrates the potential for using the integration of terrestrial laser scanning and UAV photogrammetry in 3D digital documentation and spatial analysis of cultural heritage sites.


Author(s):  
Y. H. Jo ◽  
J.Y. Kim

Three-dimensional digital documentation is an important technique for the maintenance and monitoring of cultural heritage sites. This study focuses on the three-dimensional digital documentation of the Magoksa Temple, Republic of Korea, using a combination of terrestrial laser scanning and unmanned aerial vehicle (UAV) photogrammetry. Terrestrial laser scanning mostly acquired the vertical geometry of the buildings. In addition, the digital orthoimage produced by UAV photogrammetry had higher horizontal data acquisition rate than that produced by terrestrial laser scanning. Thus, the scanning and UAV photogrammetry were merged by matching 20 corresponding points and an absolute coordinate system was established using seven ground control points. The final, complete threedimensional shape had perfect horizontal and vertical geometries. This study demonstrates the potential of integrating terrestrial laser scanning and UAV photogrammetry for three-dimensional digital documentation. This new technique is expected to contribute to the three-dimensional digital documentation and spatial analysis of cultural heritage sites.


Author(s):  
N. Ridzuan ◽  
U. Ujang ◽  
S. Azri ◽  
T. L. Choon

Abstract. Air pollution is a global event that can harm the environment and people. It is recommended that effective management be implemented to allow for the sustainable development of a specific area. The 3D building model is employed in the study to support air pollution modelling for this purpose. A proper mode of data acquisition is required to produce the building model. Many data acquisition (Terrestrial Laser Scanning and Unmanned Aerial Vehicle) approaches can be utilized, but the most appropriate one for the use in outdoor air pollution is needed. This is because it can assist in providing precise data for the modelling of a 3D building while maintaining the shape and geometry of the real-world structure. The accurate data can support modelling of surrounding air pollution concerning wind data and surrounding conditions, where different generated structures can influence the flow of the pollutants. The suitable model can be determined by using suitability analysis and with the implementation of Computational Fluid Dynamics (CFD) simulation. However, from these, no specific technique is chosen because the generated models presented incomplete model. Hence, it is suggested to combine both techniques to acquire building data as the missing surfaces from each technique can be completed by another technique. Thus, this study provides a good reference for responsible agencies or researchers in selecting the best technique for modelling the building model in air pollution-related studies.


2020 ◽  
Vol 40 (5) ◽  
pp. 675-685 ◽  
Author(s):  
Cezary Specht ◽  
Pawel S. Dabrowski ◽  
Mariusz Specht

Abstract In 2011, a yacht marina was built in Sopot (the largest holiday resort in Poland), which initiated the formation of a local shallowing of the bottom related to the tombolo effect. The building of the marina led to disturbances in the transmission of bottom deposits along the coast, which resulted from waves and the shift of the beach coastline by approx. 50 m towards the sea. Its effects include progressive morphological changes in the shore and the sea bottom, which will lead to the formation of a peninsula between the shore and the marina in the future. This paper presents the results of a comparative analysis of the accuracy of 3D modelling of the tombolo phenomenon in the onshore part of the beach using both point clouds obtained by terrestrial laser scanning methods and photogrammetric methods based on unmanned aerial vehicle photographs. The methods subjected to assessment include both those for land modelling and for determining the coastline course and its changes. The analysis results prove the existence of sub-metre differences in the imaged relief and the coastline course, which were demonstrated using an analysis of land cross-sections. The possibilities and limitations of both methods are demonstrated as well.


2021 ◽  
Vol 13 (15) ◽  
pp. 2885
Author(s):  
Mei Li ◽  
Zengyuan Li ◽  
Qingwang Liu ◽  
Erxue Chen

Plantation forests play a critical role in forest products and ecosystems. Unmanned aerial vehicle (UAV) remote sensing has become a promising technology in forest related applications. The stand heights will reflect the growth and competition of individual trees in plantation. UAV laser scanning (ULS) and UAV stereo photogrammetry (USP) can both be used to estimate stand heights using different algorithms. Thus, this study aimed to deeply explore the variations of four kinds of stand heights including mean height, Lorey’s height, dominated height, and median height of coniferous plantations using different models based on ULS and USP data. In addition, the impacts of thinned point density of 30 pts to 10 pts, 5 pts, 1 pts, and 0.8 pts/m2 were also analyzed. Forest stand heights were estimated from ULS and USP data metrics by linear regression and the prediction accuracy was assessed by 10-fold cross validation. The results showed that the prediction accuracy of the stand heights using metrics from USP was basically as good as that of ULS. Lorey’s height had the highest prediction accuracy, followed by dominated height, mean height, and median height. The correlation between height percentiles metrics from ULS and USP increased with the increased height. Different stand heights had their corresponding best height percentiles as variables based on stand height characteristics. Furthermore, canopy height model (CHM)-based metrics performed slightly better than normalized point cloud (NPC)-based metrics. The USP was not able to extract exact terrain information in a continuous coniferous plantation for forest canopy cover (CC) over 0.49. The combination of USP and terrain from ULS can be used to estimate forest stand heights with high accuracy. In addition, the estimation accuracy of each forest stand height was slightly affected by point density, which can also be ignored.


2020 ◽  
Vol 50 (10) ◽  
pp. 1012-1024
Author(s):  
Meimei Wang ◽  
Jiayuan Lin

Individual tree height (ITH) is one of the most important vertical structure parameters of a forest. Field measurement and laser scanning are very expensive for large forests. In this paper, we propose a cost-effective method to acquire ITHs in a forest using the optical overlapping images captured by an unmanned aerial vehicle (UAV). The data sets, including a point cloud, a digital surface model (DSM), and a digital orthorectified map (DOM), were produced from the UAV imagery. The canopy height model (CHM) was obtained by subtracting the digital elevation model (DEM) from the DSM removed of low vegetation. Object-based image analysis was used to extract individual tree crowns (ITCs) from the DOM, and ITHs were initially extracted by overlaying ITC outlines on the CHM. As the extracted ITHs were generally slightly shorter than the measured ITHs, a linear relationship was established between them. The final ITHs of the test site were retrieved by inputting extracted ITHs into the linear regression model. As a result, the coefficient of determination (R2), the root mean square error (RMSE), the mean absolute error (MAE), and the mean relative error (MRE) of the retrieved ITHs against the measured ITHs were 0.92, 1.08 m, 0.76 m, and 0.08, respectively.


2014 ◽  
Vol 67 (1) ◽  
Author(s):  
Norashikin M. Thamrin ◽  
Norhashim Mohd. Arshad ◽  
Ramli Adnan ◽  
Rosidah Sam ◽  
Noorfazdli Abd. Razak ◽  
...  

In Simultaneous Localization and Mapping (SLAM) technique, recognizing and marking the landmarks in the environment is very important. Therefore, in a commercial farm, rows of trees, borderline of rows as well as the trees and other features are mostly used by the researchers in realizing the automation process in this field. In this paper, the detection of the tree based on its diameter is focused. There are few techniques available in determining the size of the tree trunk inclusive of the laser scanning method as well as image-based measurements. However, those techniques require heavy computations and equipments which become constraints in a lightweight unmanned aerial vehicle implementation. Therefore, in this paper, the detection of an object by using a single and multiple infrared sensors on a non-stationary automated vehicle platform is discussed. The experiments were executed on different size of objects in order to investigate the effectiveness of this proposed method. This work is initially tested on the ground, based in the lab environment by using an omni directional vehicle which later will be adapted on a small-scale unmanned aerial vehicle implementation for tree diameter estimation in the agriculture farm.  In the current study, comparing multiple sensors with single sensor orientation showed that the average percentage of the pass rate in the pole recognition for the former is relatively more accurate than the latter with 93.2 percent and 74.2 percent, respectively. 


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