Article
Construction & Building Technology
Mert Oytun, Guzide Atasoy
Summary: This study investigates the measurement accuracy of TLS in crack analysis for different building materials and proposes boundary ranges for different scan settings. The findings provide practical contributions to the use of TLS for crack identification.
AUTOMATION IN CONSTRUCTION
(2022)
Article
Environmental Sciences
Andrea Jalandoni, W. Ross Winans, Mark D. Willis
Summary: Terrestrial laser scanning intensity values can reveal hidden painted rock art behind graffiti and moss, providing archaeologists with a new tool for detecting obscured rock art in limestone caves. This method can assist in the interpretation of black painted rock art, which is common globally.
Article
Geography, Physical
Xufei Wang, Zexin Yang, Xiaojun Cheng, Jantien Stoter, Wenbing Xu, Zhenlun Wu, Liangliang Nan
Summary: In this research, an automatic, robust, and efficient method for registering forest point clouds is proposed. The approach locates tree stems and matches them based on their relative spatial relationship to determine the registration transformation. The algorithm requires no extra tree attributes and can align point clouds of large forest environments. Additionally, a new benchmark dataset is introduced for the development and evaluation of forest point cloud registration methods.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2023)
Article
Forestry
ChiUng Ko, JooWon Lee, Donggeun Kim, JinTaek Kang
Summary: This study assessed the feasibility of using LiDAR devices for obtaining digital forest resource information. The findings showed that the BPLS and TLS methods had high accuracy for estimating height and DBH in most sample plots, but the BPLS underestimated height more in a sloped plot. However, the BPLS had a higher efficiency compared to the TLS method.
Article
Environmental Sciences
Lidu Zhao, Xiaping Ma, Zhongfu Xiang, Shuangcheng Zhang, Chuan Hu, Yin Zhou, Guicheng Chen
Summary: The extraction of landslide deformation using terrestrial laser scanning has many important applications. This study proposes a method to extract landslide deformations from TLS data by eliminating edge drift and using weighted least squares regularization solution. Experimental results show that the proposed method outperforms existing methods in landslide deformation extraction.
Article
Forestry
Timo P. Pitkanen, Tuula Piri, Aleksi Lehtonen, Mikko Peltoniemi
Summary: The study demonstrated the applicability of TLS point cloud data in detecting structural differences between healthy and diseased trees infected by Heterobasidion annosum. Diseased trees were found to have a more swollen butt and point accumulations at greater heights, but there was no statistically significant difference in crown occupancy compared to healthy trees. Up to 85% classification accuracy of the infection status was achieved based on the calculated features.
FOREST ECOLOGY AND MANAGEMENT
(2021)
Article
Engineering, Multidisciplinary
Michalina Wojtkowska, Michal Kedzierski, Paulina Delis
Summary: This study discusses the use of artificial neural networks and point clouds to calculate displacements of cultural heritage structures. The model trained on a laboratory dataset was able to determine displacements of the building facade with a relative accuracy of 3% and a success rate of 85%. Deformations derived from digital surface models generated from point clouds had a relative accuracy of 7%, while values determined by image-based close-range photogrammetry methods were 35%. An innovative aspect is the use of neural networks to determine deformations based on sub-models generated from the point cloud, along with a supervised-trained high accuracy predictive model. The practical significance lies in creating an end-to-end solution that can automatically detect and estimate the value of deformation, providing a major advantage over other methods.
Article
Forestry
Cornelis Stal, Jeffrey Verbeurgt, Lars De Sloover, Alain De Wulf
Summary: Sustainable forest management depends on accurate estimation of tree parameters, particularly the DBH for volume and mass extraction. This study showed that HMTLS is a useful alternative technique for precisely and efficiently calculating DBH, with comparable parameters to STLS and ALS data sets but significantly reduced acquisition time.
JOURNAL OF FORESTRY RESEARCH
(2021)
Article
Remote Sensing
Maolin Chen, Long Xiao, Zehui Jin, Jianping Pan, Fengyun Mu, Feifei Tang
Summary: Terrestrial laser scanning (TLS) is utilized in forest inventory, but it requires registering multiple scans into a uniform coordinate system. This study proposes a registration method for forest TLS data using a smartphone to obtain auxiliary information. The method measures the scanner position and initial scanning direction using a smartphone and uses them to calculate coarse transformation parameters. Fine registration is conducted by constructing transformation parameters based on the coarse registration result and evaluating them using stem positions as input.
REMOTE SENSING LETTERS
(2023)
Article
Geochemistry & Geophysics
Yuanzhi Cai, Lei Fan, Peter M. Atkinson, Cheng Zhang
Summary: This research proposes a novel image enhancement method to reveal the local geometric characteristics of point cloud data in images. The method explores various feature channel combinations and achieves improved semantic segmentation accuracy. Experimental results on the Semantic3D benchmark demonstrate the superiority of this image-based approach.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Engineering, Civil
Hyungjoon Seo
Summary: This paper used terrestrial laser scanning to monitor the global behavior of a large retaining structure and found a significant increase in differential tilt angles at the bottom of concrete panels adjacent to the tunnel every year. The differential tilt angle of one concrete panel with large differences affects the tilt angles of others, as they are linked together.
JOURNAL OF CIVIL STRUCTURAL HEALTH MONITORING
(2021)
Article
Environmental Sciences
Maolin Chen, Xinyi Zhang, Cuicui Ji, Jianping Pan, Fengyun Mu
Summary: In this paper, a density-adaptive feature extraction method is proposed for point cloud classification. It addresses the issue of unknown angular resolution by introducing a method called neighborhood analysis of randomly picked points (NARP) for angular resolution estimation. The proposed method also includes the use of relative projection density, a grid feature, to mitigate the impact of density variation. Experimental results demonstrate the effectiveness and stability of the proposed method, especially for small-size objects. The relative projection density outperforms traditional projection density in classification performance.
Article
Humanities, Multidisciplinary
Ming Guo, Mengxi Sun, Deng Pan, Guoli Wang, Yuquan Zhou, Bingnan Yan, Zexin Fu
Summary: This article evaluates the feasibility of combining portable 3D LiDAR scanning and UAV photogrammetry for the monitoring and restoration of wooden pagodas. By acquiring the exterior picture using a UAV and the inside point cloud using a LiDAR scanner, a complete and accurate point cloud of the pagoda is obtained. The research provides theoretical and methodological support for the digital protection of architectural heritage and GIS data modeling.
Article
Engineering, Environmental
David Clemens -Sewall, Matthew Parno, Don Perovich, Chris Polashenski, Ian A. Raphael
Summary: The study introduces FlakeOut, a filter designed specifically to filter wind-blown snowflakes from TLS data, with a low false positive rate making it suitable for applications requiring quantitative measurements of the snow surface.
COLD REGIONS SCIENCE AND TECHNOLOGY
(2022)
Article
Geochemistry & Geophysics
Mohammad Pashaei, Michael J. Starek, Craig L. Glennie, Jacob Berryhill
Summary: Information derived from full-waveform (FW) lidar data is relevant for point cloud analysis. Traditionally, waveform attributes are obtained through fitting the echo waveform with a parametric function. However, it is challenging for some systems to describe the system response using a simple parametric function. This study explores the direct exploitation of multireturn waveform signals for point cloud classification in a built environment. The classification performance of calibrated waveform attributes and deep learning-based FW data classification technique is compared, showing that the latter contains higher information content.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2023)
Article
Environmental Sciences
Adolfo Molada-Tebar, Angel Marques-Mateu, Jose Luis Lerma, Stephen Westland
Article
Computer Science, Artificial Intelligence
Gabriel Riutort-Mayol, Virgilio Gomez-Rubio, Angel Marques-Mateu, Jose Luis Lerma, Antonio Lopez-Quilez
IET IMAGE PROCESSING
(2020)
Article
Geography, Physical
Ines Barbero-Garcia, Jose Luis Lerma, Gaspar Mora-Navarro
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2020)
Article
Archaeology
Berta Carrion-Ruiz, Gabriel Riutort-Mayol, Adolfo Molada-Tebar, Jose L. Lerma, Valentin Villaverde
Summary: Rock art documentation is a complex task that requires a complete, rigorous, and exhaustive approach to enable stakeholders to preserve archaeological sites under constant deterioration. Prehistoric pigments used in paintings are highly light sensitive, and microfading spectrometry is a suitable technique for determining the light-stability of these pigments in a non-destructive manner. The evaluation of color changes and chromatic differences through spectral data can help establish future conservation actions for archaeological sites.
JOURNAL OF CULTURAL HERITAGE
(2021)
Article
Chemistry, Multidisciplinary
Miriam Cabrelles, Jose Luis Lerma, Valentin Villaverde
APPLIED SCIENCES-BASEL
(2020)
Article
Chemistry, Multidisciplinary
Francesco Di Stefano, Miriam Cabrelles, Luis Garcia-Asenjo, Jose Luis Lerma, Eva Savina Malinverni, Sergio Baselga, Pascual Garrigues, Roberto Pierdicca
APPLIED SCIENCES-BASEL
(2020)
Article
Mathematics
Gabriel Riutort-Mayol, Virgilio Gomez-Rubio, Jose Luis Lerma, Julio M. del Hoyo-Melendez
Article
Engineering, Multidisciplinary
Ines Barbero-Garcia, Roberto Pierdicca, Marina Paolanti, Andrea Felicetti, Jose Luis Lerma
Summary: This study integrates target-based close-range photogrammetry with facial landmark machine learning detection to develop an automatic, smartphone-based tool that provides 3D information of the head and face. This methodology opens a new path for the effective integration of machine learning and photogrammetry in medicine, particularly for overall head analysis.
Article
Multidisciplinary Sciences
Jonas Grieb, Ines Barbero-Garcia, Jose Luis Lerma
Summary: This study proposes a new method for identifying deformational plagiocephaly using spherical harmonics to extract features from the head models and measure deformity. Compared to traditional anthropometric indexes, this method shows better results in the detection of DP.
SCIENTIFIC REPORTS
(2022)
Article
Computer Science, Information Systems
Angel Collado, Gaspar Mora-Navarro, Veronica Heras, Jose Luis Lerma
Summary: The main objective of this article is to develop a web-based cultural heritage management system in Canton Nabon, Ecuador, using new web technologies and geomatics knowledge. The system will provide a web-based geoportal accessible to the whole society, allowing users to consult geolocalised heritage information on a virtual map and view 3D geovisualization in an interactive web viewer.
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
(2022)
Article
Medicine, Legal
Thomas Fischer, Martina Marchetti-Deschmann, Ana Cristina Assis, Michal Levin Elad, Manuel Algarra, Marko Barac, Iva Bogdanovic Radovic, Flavio Cicconi, Britt Claes, Nunzianda Frascione, Sony George, Alexandra Guedes, Cameron Heaton, Ron Heeren, Violeta Lazic, Jose Luis Lerma, Maria del Valle Martinez de Yuso Garcia, Martin Nosko, John O'Hara, Ilze Oshina, Antonio Palucci, Aleksandra Pawlaczyk, Aistyna Zelena Pospiskova, Marcel de Puit, Ksenija Radodic, Mara Repele, Mimoza Ristova, Francesco Saverio Romolo, Ivo Safarik, Zdravko Siketic, Janis Spigulis, Malgorzata Iwona Szynkowska-Jozwik, Andrei Tsiatsiuyeu, Joanna Vella, Lorna Dawson, Stefan Roediger, Simona Francese
Summary: This study investigated the feasibility of using different imaging methods for forgery detection through simulating a forensic scenario. The results showed that correct forensic statements can only be achieved by the complementary application of different methods.
Article
Environmental Sciences
Alba Nely Arevalo-Verjel, Jose Luis Lerma, Juan F. Prieto, Juan Pedro Carbonell-Rivera, Jose Fernandez
Summary: UAV-DAP has great potential for high-precision photogrammetry due to its low cost and ability to generate high-density point clouds. This research explores different scenarios to analyze the accuracy of this technique and identifies the best parameters for improved results.
Article
Environmental Sciences
Giacomo Patrucco, Antonio Gomez, Ali Adineh, Max Rahrig, Jose Luis Lerma
Summary: This study illustrates how combining different geomatics techniques can efficiently support historical analyses for studying heritage buildings. It also proposes a strategy for generating HBIM models starting from the integration of 3D thermal investigations and historical sources.
Article
Chemistry, Multidisciplinary
Sergio Baselga, Gaspar Mora-Navarro, Jose Luis Lerma
Summary: This paper presents a research on the accuracy assessment of a smartphone-based photogrammetric solution (PhotoMeDAS) for cranial diagnosis using 3D head models. The study demonstrates the propagation of measurement uncertainty to cranial deformation indices. The PhotoMeDAS solution provides accurate and reliable measurements, making it a recommended tool for doctors to establish comprehensive cranial deformation indices during medical diagnosis.
APPLIED SCIENCES-BASEL
(2022)
Article
Chemistry, Analytical
Max Rahrig, Miguel angel Herrero Cortell, Jose Luis Lerma
Summary: This paper presents a workflow for using non-invasive multispectral imaging techniques, ranging from UV to NIR, to investigate wall paintings. It discusses different methods for image analysis and visualization, including combining spectral bands in hybrid false-color images and applying NDVI/NDPI and PCA for image analysis. The aim is to generate a high-resolution photogrammetric image set that provides information on underdrawings, material differences, damages, painting techniques, and conservation measures. The image data are superimposed with pixel accuracy in a GIS for further analysis and annotation of findings. The research is carried out on an early Spanish Renaissance wall painting in the Cathedral of Valencia.