Article
Environmental Sciences
Daniele Ventura, Francesca Napoleone, Silvia Cannucci, Samuel Alleaume, Emiliana Valentini, Edoardo Casoli, Sabina Burrascano
Summary: This study used a low-cost unmanned aerial vehicle (UAV) and Structure from Motion (SfM) photogrammetry to capture high-resolution RGB imagery of semi-natural grasslands. Image classification through Object-Based Image Analysis (OBIA) allowed for accurate identification of three grassland types. The use of orthomosaics, digital elevation models (DEMs), and canopy height models (CHMs) achieved high classification accuracies and provided valuable information on vegetation cover and terrain characteristics.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2022)
Article
Environmental Sciences
Aris Thomasberger, Mette Moller Nielsen, Mogens Rene Flindt, Satish Pawar, Niels Svane
Summary: This study investigates the performance of five machine learning algorithms for the object-based classification of submerged seagrasses from UAS-derived imagery. The results show that the Bayes classifier performs well in favorable environmental conditions, while the DT and RT classifiers perform better on low-altitude images. The kNN classifier performs poorly in all scenarios, while the SVM classifier is the most sensitive to hyperparameter tuning but achieves the highest accuracies most often. These findings can help in selecting the appropriate classifier and optimizing hyperparameter settings.
Article
Remote Sensing
Yahya Zefri, Imane Sebari, Hicham Hajji, Ghassane Aniba
Summary: The increasing adoption of photovoltaic technology necessitates efficient and large-scale deployment-ready inspection solutions. In this study, a robust and versatile deep learning model is developed for the classification of defect-related patterns on PV modules.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2022)
Article
Ecology
Christian John, Fraser Shilling, Eric Post
Summary: The 'drpToolkit' is an open-source Python package that automates the workflow of data management, image alignment and data extraction from time-series image sets, improving the spatial consistency and accuracy of ecological data. It simplifies the process of converting raw imagery to ecological data and facilitates cross-study comparisons of phenology to improve understanding of ecological response to climate change.
METHODS IN ECOLOGY AND EVOLUTION
(2022)
Article
Forestry
Joshua Carpenter, Daniel Rentauskas, Nikhil Makkar, Jinha Jung, Songlin Fei
Summary: Field-based forest inventory plots are crucial for forest studies, providing valuable information about forests. They are now used for validation and training data in forest feature extraction and machine learning algorithms. However, the uncertainty in plot location measurements has undermined their usefulness. A method for accurately measuring plot center coordinates using low-cost targets and orthoimagery has improved the accuracy by an order of magnitude.
JOURNAL OF FORESTRY
(2023)
Article
Environmental Sciences
Vasilis Psiroukis, George Papadopoulos, Aikaterini Kasimati, Nikos Tsoulias, Spyros Fountas
Summary: Investigating the use of data-processing pipeline with UAS-derived visible-spectrum vegetation indices and photogrammetric products for estimating cotton plant height, this study found that vegetation indices, especially GCC and NExG, had high correlations with cotton height in the earlier growth stages, exceeding 0.70, while vegetation cover showed a consistent trend throughout the season and exceeded 0.90 at the beginning of the season.
Article
Agriculture, Multidisciplinary
Rong Huang, Wei Yao, Zhong Xu, Lin Cao, Xin Shen
Summary: Forest land plays a crucial role in the global environment and human livelihood. This study combines unmanned aircraft systems and LiDAR to estimate aboveground biomass in a plateau mountainous forest reserve. By using digital aerial photogrammetry and LiDAR, an accurate and cost-effective canopy height model and biomass estimation can be obtained. The results show the potential of utilizing this synergistic approach for large-scale biomass mapping.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2022)
Article
Agronomy
Leon Hinrich Oehme, Alice-Jacqueline Reineke, Thea Mi Weiss, Tobias Wuerschum, Xiongkui He, Joachim Mueller
Summary: This study utilized digital surface models created from RGB-images captured by a UAV to estimate the plant height of 400 maize genotypes. The results showed that the UAV-based estimation was most accurate between 39 to 68 days after sowing.
Article
Geochemistry & Geophysics
Hao Wang, Xiaolei Lv, Shuo Li
Summary: This study proposes a novel algorithm for building change detection that can process images from different perspectives and utilizes cross-temporal stereo matching to correct elevation errors in the existing DSM. This improves the accuracy and completeness of building change detection.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2023)
Article
Remote Sensing
Holger Heisig, Jean-Luc Simmen
Summary: The study presents a highly automated photogrammetric workflow for orientation of archival aerial imagery, which has been successfully applied to process a complete coverage of AAI over Switzerland with satisfying accuracies. The proposed workflow is at least five times more efficient in terms of human working time compared to classical workflows, while requiring very moderate computational resources.
PFG-JOURNAL OF PHOTOGRAMMETRY REMOTE SENSING AND GEOINFORMATION SCIENCE
(2021)
Article
Environmental Sciences
Peimin Chen, Huabing Huang, Jinying Liu, Jie Wang, Chong Liu, Ning Zhang, Mo Su, Dongjie Zhang
Summary: This study developed an effective method for estimating high-resolution building heights using Chinese GaoFen-7 imagery, which showed great potential and advantages in reducing manual workload.
REMOTE SENSING OF ENVIRONMENT
(2023)
Review
Environmental Sciences
Dingkun Hu, Jennifer Minner
Summary: This study conducts a systematic literature review to identify current gaps in the research on the application of drones and 3D modeling in urban planning and historic preservation. The findings reveal five research shortcomings and discuss possible countermeasures and future prospects.
Article
Geography, Physical
Kathrin Maier, Andrea Nascetti, Ward van Pelt, Gunhild Rosqvist
Summary: This study proposes a novel method to determine the spatial distribution of snow depth in challenging alpine terrains using a combination of a multispectral camera and a UAV. The method enables fast, reliable, and affordable measurement of high-resolution 3D snow-covered surface models. The experiments suggest that the red components in the electromagnetic spectrum are crucial in photogrammetric processing, and applying Principal Component Analysis can reduce processing times and computational resources.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2022)
Article
Forestry
Facundo Pessacg, Francisco Gomez-Fernandez, Matias Nitsche, Nicolas Chamo, Sebastian Torrella, Ruben Ginzburg, Pablo De Cristoforis
Summary: Forestry aerial photogrammetry using Unmanned Aerial Systems (UAS) helps bridge the gap between detailed fieldwork and broad-range satellite imagery-based analysis. However, optical sensors face limitations in collecting and classifying ground points in woodlands. This study proposes a novel method to generate accurate Digital Terrain Models (DTMs) in forested environments and develops a realistic simulator for controlled experimentation.
Article
Construction & Building Technology
Qintao Hu, Liangli Zhen, Yao Mao, Xi Zhou, Guozhong Zhou
Summary: A new method called Deep Automatic Building Extraction Network (DABE-Net) is proposed, which constructs building-blocks using squeeze-and excitation (SE) operations and the residual recurrent convolutional neural network (RRCNN), and introduces an attention mechanism to improve segmentation accuracy. In addition, a multi-scale segmentation loss function is developed to handle small buildings.
AUTOMATION IN CONSTRUCTION
(2021)
Article
Computer Science, Information Systems
Stephan Nebiker, Stefan Cavegn, Benjamin Loesch
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
(2015)
Article
Remote Sensing
Stefan Cavegn, Stephan Nebiker
PHOTOGRAMMETRIE FERNERKUNDUNG GEOINFORMATION
(2012)
Article
Remote Sensing
Eric Kenneth Matti, Stephan Nebiker
PHOTOGRAMMETRIE FERNERKUNDUNG GEOINFORMATION
(2014)
Article
Environmental Sciences
Stephan Nebiker, Jonas Meyer, Stefan Blaser, Manuela Ammann, Severin Rhyner
Summary: The successful application of low-cost 3D cameras with artificial intelligence technology in outdoor mobile mapping can be used for mapping, asset inventory, and change detection tasks in smart cities. The research demonstrates that the latest generation of low-cost 3D cameras are suitable for real-world outdoor applications with supported ranges, depth measurement accuracy, and robustness under varying lighting conditions.
Proceedings Paper
Geography, Physical
W. Wahbeh, G. Mueller, M. Ammann, S. Nebiker
Summary: This paper presents an image-based method for creating large-scale and complex mesh models of urban environments. By combining street-level mobile mapping system images and aerial imagery from UAVs, and using dense multi-view image matching, a successful reconstruction of an area was achieved.
XXIV ISPRS CONGRESS IMAGING TODAY, FORESEEING TOMORROW, COMMISSION II
(2022)
Proceedings Paper
Geography, Physical
J. Meyer, S. Blaser, S. Nebiker
Summary: This paper presents an edge-based hardware and software framework for 3D detection and mapping of parked vehicles. By investigating different detection methods and retraining the object detector, the system achieves high precision and recall rates. The software is also evaluated in terms of processing speed and data volume.
XXIV ISPRS CONGRESS CONGRESS IMAGING TODAY, FORESEEING TOMORROW, COMMISSION I
(2022)
Proceedings Paper
Geography, Physical
S. Blaser, S. Cavegn, S. Nebiker
ISPRS TC I MID-TERM SYMPOSIUM INNOVATIVE SENSING - FROM SENSORS TO METHODS AND APPLICATIONS
(2018)
Proceedings Paper
Remote Sensing
S. Cavegn, S. Nebiker, N. Haala
XXIII ISPRS CONGRESS, COMMISSION I
(2016)
Article
Remote Sensing
Stephan Nebiker, Natalie Lack
GIM INTERNATIONAL-THE WORLDWIDE MAGAZINE FOR GEOMATICS
(2016)
Proceedings Paper
Geography, Physical
S. Cavegn, N. Haala, S. Nebiker, M. Rothermel, T. Zwoelfer
ISPRS GEOSPATIAL WEEK 2015
(2015)
Proceedings Paper
Geography, Physical
M. Christen, S. Nebiker
ISPRS GEOSPATIAL WEEK 2015
(2015)
Proceedings Paper
Geography, Physical
Hannes Eugster, Fabian Huber, Stephan Nebiker, Antonio Gisi
XXII ISPRS CONGRESS, TECHNICAL COMMISSION I
(2012)
Proceedings Paper
Geography, Physical
S. Cavegn, S. Nebiker
XXII ISPRS CONGRESS, TECHNICAL COMMISSION IV
(2012)
Proceedings Paper
Geography, Physical
J. Burkhard, S. Cavegn, A. Barmettler, S. Nebiker
XXII ISPRS CONGRESS, TECHNICAL COMMISSION V
(2012)