Article
Green & Sustainable Science & Technology
Ziyu Zhao, Zhongke Feng, Jiali Liu, Yuan Wang
Summary: Forest resource inventory is essential for sustainable forest management. This study designed a multi-functional, high-precision, real-time tree-measuring instrument that integrates plot set-up, tree position measurement, DBH measurement, and tree height measurement. The results showed that the instrument has high measurement accuracy and efficiency, making it practical for forest inventory applications.
Article
Remote Sensing
Bruno Miguez Moreira, Gabriel Goyanes, Pedro Pina, Oleg Vassilev, Sandra Heleno
Summary: This study systematically evaluated the influence of survey design and computer processing choices on UAV-based photogrammetry retrieval of tree diameter at breast height. Using agricultural fields in Spain and woodlands in Bulgaria as study areas, the research demonstrated that careful methodology design can achieve highly accurate measurements of tree DBH using SfM techniques.
Article
Environmental Sciences
Amelia Holcomb, Linzhe Tong, Srinivasan Keshav
Summary: This paper presents an algorithm that uses a low-cost smartphone LiDAR sensor to automatically estimate the trunk diameter. The algorithm is implemented in a smartphone app and tested in different forests, showing accurate results and significant reduction in surveyor time.
Article
Forestry
Zhengnan Zhang, Tiejun Wang, Andrew K. Skidmore, Fuliang Cao, Guanghui She, Lin Cao
Summary: The diameter at breast height (DBH) is an important trait for studying plant ecology and biodiversity, as well as managing forests. Traditional ground-based approaches for measuring individual tree DBH over large areas are time-consuming and expensive. In this study, we propose an improved area-based approach using airborne LiDAR data to estimate plot-level DBH by utilizing the relationship between tree height and DBH. The results demonstrate the potential of using height-DBH relationships to improve the accuracy of estimating plot-level DBH from airborne LiDAR data.
Article
Forestry
Enrique Perez-Martin, Serafin Lopez-Cuervo Medina, Tomas Herrero-Tejedor, Miguel Angel Perez-Souza, Julian Aguirre de Mata, Alejandra Ezquerra-Canalejo
Summary: This study examines the performance of an MLS with SLAM technology for tree inventory compilation in a historic garden, and evaluates the accuracy of DBH estimates using three fitting algorithms. The Monte Carlo fitting algorithm showed the best results, accurately estimating the DBH of most trees in the study.
Article
Remote Sensing
Elizabeth M. Prior, Valerie A. Thomas, Randolph H. Wynne
Summary: This study compared canopy heights derived from NAIP DSMs and point clouds to those derived from lidar data, and found that the 90th percentiles of heights derived from the point clouds were better at estimating mean dominant height (MDH) than the comparatively coarse resolution DSM. The main limitation of the NAIP datasets was found to be shadowing caused by steep terrain. However, in closed-canopy temperate deciduous forests without shadowing, the mean dominant heights estimated using NAIP DSMs and point clouds are comparable to those estimated using lidar data.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2022)
Article
Environmental Sciences
Tianyu Hu, Xiliang Sun, Yanjun Su, Hongcan Guan, Qianhui Sun, Maggi Kelly, Qinghua Guo
Summary: A low-cost UAV lidar system was developed and demonstrated effectiveness in estimating forest inventory attributes comparable to high-end systems. This study provides guidance on selecting appropriate UAV lidar systems and flight specifications for forest research and management.
Article
Environmental Sciences
Yuanshuo Hao, Faris Rafi Almay Widagdo, Xin Liu, Ying Quan, Lihu Dong, Fengri Li
Summary: This study established DBH-UAVLS point cloud estimation models using UAV laser scanning technology, achieving lower RMSE values through NLME models, improving the transferability of DBH estimation, and providing a baseline for UAV small-scale forest inventories.
Article
Environmental Sciences
Benjamin T. Fraser, Russell G. Congalton
Summary: The research utilizes Unmanned Aerial Systems (UAS) and advanced image processing techniques to estimate tree diameters and various stand-level parameters in forests, with an average error reported. Stand-level parameters were either overestimated or underestimated, with a lesser overestimation for stands larger than 9 hectares. Random forest supervised classification achieved a promising overall accuracy of 85% in identifying large trees, offering local land managers opportunities for better understanding forested ecosystems. Future research on individual tree crown detection, especially for co-dominant or suppressed trees, will further enhance these efforts.
Article
Environmental Sciences
Gabriel Loureiro, Andre Dias, Alfredo Martins, Jose Almeida
Summary: The use and research of Unmanned Aerial Vehicles (UAVs) have been increasing due to their versatile applications in various operations. Safety issues and failures need to be taken into consideration, especially with the increasing presence of UAVs in airspace. Detecting a safe landing spot during operation is crucial for the UAV's successful mission completion.
Article
Environmental Sciences
Neal C. Swayze, Wade T. Tinkham, Jody C. Vogeler, Andrew T. Hudak
Summary: This study investigated the use of unmanned aerial system (UAS) imagery for modeling individual tree and stand-level metrics in dry conifer forests. It found that tree extraction accuracy was maximized for nadir crosshatch UAS flight designs, while extracted tree height accuracy was high for all UAS flight parameters. Additionally, stand density estimates were most accurate with off-nadir or crosshatch flight designs at lower altitudes.
REMOTE SENSING OF ENVIRONMENT
(2021)
Article
Environmental Sciences
Mitchel L. M. Rudge, Shaun R. Levick, Renee E. Bartolo, Peter D. Erskine
Summary: This study explores the potential of UAV-LS tree segmentation and allometric scaling methods to model the diameter distributions of savanna trees. By comparing field-surveyed data with UAV-LS data, significant differences were found between the modeled diameter distributions and field surveys, especially when smaller trees were excluded.
Article
Environmental Sciences
J. C. White, M. Woods, T. Krahn, C. Papasodoro, D. Belanger, C. Onafrychuk, I. Sinclair
Summary: This study assessed the absolute and relative accuracies of leaf-on and leaf-off SPL data acquired at different altitudes, and compared them with LML data, finding that the leaf-off SPL data were most accurate overall.
REMOTE SENSING OF ENVIRONMENT
(2021)
Article
Environmental Sciences
Yulin Gong, Xuejian Li, Huaqiang Du, Guomo Zhou, Fangjie Mao, Lv Zhou, Bo Zhang, Jie Xuan, Dien Zhu
Summary: The accurate classification of tree species is crucial for sustainable forest management and biodiversity monitoring. This study proposes a new intensity frequency feature for fine classification of eight tree species using UAV LiDAR. The results demonstrate that this new feature can serve as a comprehensive and effective intensity feature for tree species classification.
Article
Environmental Sciences
Tian Zhou, Renato Cesar dos Santos, Jidong Liu, Yi-Chun Lin, William Changhao Fei, Songlin Fei, Ayman Habib
Summary: LiDAR data plays a crucial role in forest inventory and management. This study compares three tree detection and localization approaches using LiDAR data from different platforms and with different characteristics. The results highlight the importance of considering data characteristics when selecting an appropriate method.
Article
Engineering, Electrical & Electronic
Fariborz Ghorbani, Hamid Ebadi, Amin Sedaghat, Norbert Pfeifer
Summary: This article proposes a new 3D local descriptor to reduce the effect of point displacement error in point cloud coarse registration. The approach includes an improved local reference frame, a new geometric arrangement, and the consideration of directional histograms as features. The results show high performance in challenging and noisy environments.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2022)
Article
Engineering, Electrical & Electronic
Agata Walicka, Norbert Pfeifer
Summary: This article proposes a method for instance segmentation of individual grains from a terrestrial laser scanning point cloud. The method includes a classification step using the random forest algorithm and a segmentation step using density and Euclidean distance. The experiments showed that the method accurately identifies grains and is robust to the shadowing effect.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2022)
Article
Geography, Physical
P. Glira, K. Oelsboeck, T. Kadiofsky, M. Schoerghuber, J. Weichselbaum, C. Zinner, L. Fel
Summary: Recent developments in rail vehicles have increased the demand for accurate and up-to-date 3D maps of rail track networks. This study presents a fully automatic photogrammetric method for reconstructing 3D rail track segments. The method utilizes images from a front-looking camera and observations from a low-cost GNSS receiver as data inputs, with optional inputs such as a rail track, a digital height model, and ground control points to improve accuracy. The method was applied to reconstruct a 13 km long tram line in Vienna, demonstrating its effectiveness.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2022)
Article
Environmental Sciences
Lei Xu, Jian Gong, Jiaming Na, Yuanwei Yang, Zhao Tan, Norbert Pfeifer, Shunyi Zheng
Summary: This study proposes a convergence diameter and radial dislocation detection method based on block-level fitting, which solves the accuracy degradation caused by the model error and point cloud incompletion. The experimental results showed that the method has good detection accuracy and is suitable for practical engineering applications.
Article
Environmental Sciences
Valeria-Ersilia Oniga, Ana-Ioana Breaban, Norbert Pfeifer, Maximilian Diac
Summary: The paper discusses a method for 3D building modeling based on oblique UAS images, using a low-cost drone to collect data over an urban area. The process includes various steps such as filtering ground points, classification, segmentation, plane creation, and 3D model reconstruction. The results show that the proposed pipeline is reliable, with a global accuracy of around 0.15 m for each modeled building.
Article
Environmental Sciences
Michael Lechner, Alena Dostalova, Markus Hollaus, Clement Atzberger, Markus Immitzer
Summary: Microwave and optical imaging methods provide complementary information for tree species classification. This study shows that using a high number of Sentinel-2 scenes can achieve a high overall classification accuracy, and the additional use of Sentinel-1 data can further improve the results, especially when only a single Sentinel-2 scene is available.
Article
Ecology
Jesper Erenskjold Moeslund, Kevin Kuhlmann Clausen, Lars Dalby, Camilla Flojgaard, Meelis Partel, Norbert Pfeifer, Markus Hollaus, Ane Kirstine Brunbjerg, Mat Disney, Jian Zhang
Summary: This study used a large plant dataset and lidar data to analyze the impact of habitat characteristics on plant dark diversity, and identified factors that should be considered by managers and policymakers in conservation and restoration projects.
REMOTE SENSING IN ECOLOGY AND CONSERVATION
(2023)
Review
Geography, Physical
Florian Poeppl, Hans Neuner, Gottfried Mandlburger, Norbert Pfeifer
Summary: Trajectory estimation is the task of obtaining position and orientation estimates by fusion of various sensor inputs. This paper provides a unified view of trajectory estimation with a focus on its role in kinematic mapping, specifically the integration of GNSS, INS, laser scanners, and cameras, along with a survey of related literature. Recent trends and challenges in trajectory estimation are identified and discussed.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2023)
Article
Environmental Sciences
Khrystyna Burshtynska, Svitlana Kokhan, Norbert Pfeifer, Maksym Halochkin, Iryna Zayats
Summary: In recent decades, floods in the Pre-Carpathian region of Ukraine have become more frequent, causing significant economic and environmental damage. This study aims to propose a methodology for hydrological modeling of riverbed sections with complex morphometric and hydrological characteristics. Using UAV imagery, a digital elevation model (DEM) is constructed, and factors such as cross-section distance and Manning coefficients are determined for accurate modeling. The research findings suggest that imaging during the leafless period is essential for achieving the required accuracy of the DEM.
Article
Geosciences, Multidisciplinary
Moritz Altmann, Katharina Ramskogler, Sebastian Mikolka-Floery, Madlene Pfeiffer, Florian Haas, Tobias Heckmann, Jakob Rom, Fabian Fleischer, Toni Himmelstoss, Norbert Pfeifer, Camillo Ressl, Erich Tasser, Michael Becht
Summary: Using digital monoplotting and historical terrestrial photographs, this study quantitatively analyzes surface changes of a Little Ice Age lateral moraine section over a 130-year period (1890-2020). The results show continuous expansion of the gully system and initial expansion of vegetation-covered areas until 1953, followed by a decrease due to large-scale erosion within the gully system. The study also concludes that land-cover development was influenced by temperature and precipitation changes.
Article
Environmental Sciences
Philipp Glira, Christoph Weidinger, Johannes Otepka-Schremmer, Camillo Ressl, Norbert Pfeifer, Michaela Haberler-Weber
Summary: Nonrigid registration is a significant challenge in point cloud processing with diverse applications. This paper presents a new method using piecewise tricubic polynomials to model nonrigid deformations, offering several advantages over existing methods.
Article
Imaging Science & Photographic Technology
Taskin Oezkan, Norbert Pfeifer, Gudrun Styhler-Aydin, Georg Hochreiner, Ulrike Herbig, Marina Doering-Williams
Summary: This paper presents a set of methods to improve the automation of parametric 3D modeling of historic roof structures using terrestrial laser scanning point clouds. By detecting and excluding roof cover points and splitting complex segments into linear sub-segments, the automation and completeness of the modeling process is increased.
JOURNAL OF IMAGING
(2022)
Article
Humanities, Multidisciplinary
Benjamin Wild, Geert J. J. Verhoeven, Martin Wieser, Camillo Ressl, Jona Schlegel, Stefan Wogrin, Johannes Otepka-Schremmer, Norbert Pfeifer
Summary: Contemporary graffiti are polarising, with differing opinions regarding whether they should be considered cultural heritage. However, for heritage professionals and academics who value these short-lived creations, digital documentation of graffiti can be seen as part of our legacy. AUTOGRAF is an automated tool developed within the INDIGO project that converts conventional graffiti photos into high-resolution, distortion-free, and georeferenced orthophotomaps, providing an improved method for digital preservation of graffiti.
Article
Geochemistry & Geophysics
Reuma Arav, Sagi Filin, Norbert Pfeifer
Summary: In this article, a context-aware subsampling approach is proposed to reduce the data load of less important regions while retaining high resolution of objects of interest. Visual saliency measures are used to identify regions that require detail preservation, and data reduction is only applied to nonsalient regions. A hierarchical data structure based on surface nature enables progressive subsampling, with retained representative points describing the underlying surface. The proposed model is demonstrated on datasets from different scanners, and results are compared with three common simplification approaches, showing a reduced point cloud similar to the original for ROI analysis regardless of the level of simplification.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
