Article
Environmental Sciences
Federica Marotta, Simone Teruggi, Cristiana Achille, Giorgio Paolo Maria Vassena, Francesco Fassi
Summary: The paper discusses the creation process of a multi-source high-resolution Digital Terrain Model (DTM) in dense vegetated areas for landslide movement understanding. Challenges from the area's characteristics and processed data were faced, but it provided valuable testing opportunities for the technologies used through the complexity of the case study.
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)
Review
Environmental Sciences
Tasiyiwa Priscilla Muumbe, Jussi Baade, Jenia Singh, Christiane Schmullius, Christian Thau
Summary: Savannas are diverse ecosystems with complex vegetation, conventional methods may underestimate carbon storage potential. TLS technology shows promise in accurate vegetation parameter extraction, future research should focus on algorithm development and improvement.
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
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
Geography, Physical
Miguel Yermo, Francisco F. Rivera, Jose C. Cabaleiro, David L. Vilarino, Tomas F. Pena
Summary: This paper presents a fast algorithm for determining the least cost path in an Airborne Laser Scanning point cloud, which avoids the loss of information and precision caused by using a digital terrain model (DTM) in traditional methods.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2022)
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
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
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
Environmental Sciences
Yufu Zang, Fancong Meng, Roderik Lindenbergh, Linh Truong-Hong, Bijun Li
Summary: This paper presents a novel deep neural network-based localization method in urban environment, divided into place recognition and pose refinement. By extracting cylinder-like features to describe global features, estimating similarities using a probabilistic framework, and utilizing CNN for pose refinement, the system successfully achieves accurate localization in urban scenes.
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
Environmental Sciences
Gene Bailey, Yingkui Li, Nathan McKinney, Daniel Yoder, Wesley Wright, Robert Washington-Allen
Summary: This study presents a straightforward method, Las2DoD, to quantify surface change directly from point clouds. The method was applied to two case studies of erosion and showed higher accuracy in measuring sediment compared to other commonly used methods. Las2DoD is able to capture more low-magnitude changes and is particularly useful in cases where surface changes are small but contribute significantly to the total surface change.
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
Agronomy
Ahmed Kayad, Francelino A. Rodrigues Jr, Sergio Naranjo, Marco Sozzi, Francesco Pirotti, Francesco Marinello, Urs Schulthess, Pierre Defourny, Bruno Gerard, Marie Weiss
Summary: Mapping crop within-field yield variability provides essential information for precision agriculture applications. This study aimed to estimate maize biomass and grain yield using Leaf Area Index (LAI) retrieved from hyperspectral aerial images and compared it with simple vegetation index approaches. The PROSAIL model was used to retrieve LAI and estimate maize biomass and yield. Results showed that the NDRE method had the highest accuracy, and the late vegetative growth stage at V16 was the best stage for maize yield prediction.
FIELD CROPS RESEARCH
(2022)
Article
Remote Sensing
Kanan Akbar Hossain, Mauro Masiero, Francesco Pirotti
Summary: This study explored the land use and land cover change in Sundarbans, the world's largest mangrove forest, over a period of 45 years (1975-2020) using Landsat imagery. The results showed a decrease in dense forest cover and an increase in moderate and sparse forest, as well as a conversion of sparse forest to barren land. The presence of barren land and human settlements along the forest boundary was more common in the Indian part of Sundarbans.
EUROPEAN JOURNAL OF REMOTE SENSING
(2022)
Article
Environmental Sciences
Francesco Pirotti, Opeyemi Adedipe, Brigitte Leblon
Summary: This study investigates the sensitivity of Sentinel-1 C-band backscatter to the moisture content of tree canopies in a specific area in Portugal. The results show that the backscatter values are inversely correlated with the local incidence angle over canopies, and the correlation is stronger in wet scenarios. The backscatter values can discriminate between wet and dry forest environments, but are less sensitive to the transition between dry and extremely dry conditions. The study also finds that C-VH backscatter is more sensitive in capturing burnt canopies and can capture post-fire recovery after approximately 360 days.
Article
Environmental Sciences
Akbar Hossain Kanan, Francesco Pirotti, Mauro Masiero, Md Masudur Rahman
Summary: This study aims to analyze the potential impacts of sea level rise on dry land inundation in the Sundarbans area. The results show that under different scenarios of sea level rise, a significant amount of land in the Sundarbans could be flooded by 2100. While the direct impact of sea level rise on inundation is limited, indirect threats and human disturbances are expected to be major drivers of degradation in the Sundarbans by the end of the twenty-first century.
Article
Biodiversity Conservation
Michele Dalponte, Ruggero Cetto, Daniele Marinelli, Davide Andreatta, Cristina Salvadori, Francesco Pirotti, Lorenzo Frizzera, Damiano Gianelle
Summary: This study explores the spectral separability of different stages of spruce bark beetle infestation using Planet imagery at individual tree level. The results show that there are significant differences in spectral bands and indexes between healthy trees and those in the red-stage of infestation, as well as between healthy trees and those in the green-attack stage at the end of the summer.
ECOLOGICAL INDICATORS
(2023)
Article
Forestry
Federica Romagnoli, Alberto Cadei, Maximiliano Costa, Davide Marangon, Giacomo Pellegrini, Davide Nardi, Mauro Masiero, Laura Secco, Stefano Grigolato, Emanuele Lingua, Lorenzo Picco, Francesco Pirotti, Andrea Battisti, Tommaso Locatelli, Kristina Blennow, Barry Gardiner, Raffaele Cavalli
Summary: Windstorms have significant impacts on European forests, influencing various dimensions such as ecology, operations, geomorphology, economy, and socio-cultural aspects. However, current literature mainly focuses on specific aspects and lacks a comprehensive understanding. An interdisciplinary and systemic approach is needed to analyze and address the cascade effects and interconnections among these dimensions in post-windstorm dynamics.
FOREST ECOLOGY AND MANAGEMENT
(2023)
Article
Environmental Sciences
Shirong Cai, Kunlong Niu, Xiaolin Mu, Xiankun Yang, Francesco Pirotti
Summary: This study analyzed the spatiotemporal changes in extreme precipitation in the Pearl River Basin using the long-term APHRODITE dataset. The results showed an increasing trend in annual and seasonal precipitation, with different indices exhibiting different changes in different seasons and regions. The findings are important for flood mitigation, natural hazard control, and water resources management in the Pearl River Basin.
Proceedings Paper
Automation & Control Systems
Samuele Trestini, Francesco Morari, Francesco Pirotti, Daniela Anastasija Epstein, Simone Severini
2022 IEEE INTERNATIONAL WORKSHOP ON METROLOGY FOR AGRICULTURE AND FORESTRY (METROAGRIFOR)
(2022)
Article
Computer Science, Information Systems
Francesco Pirotti, Marco Piragnolo, Marika D'Agostini, Raffaele Cavalli
Summary: The post-pandemic era highlights the importance of physical and psychological well-being for reducing vulnerability. This study uses IoT sensors and drone technology to collect climate data in an urban garden, and generates thermal comfort maps.
Article
Geochemistry & Geophysics
Michele Gazzea, Lars Michael Kristensen, Francesco Pirotti, Eren Erman Ozguven, Reza Arghandeh
Summary: This article introduces a weakly supervised method based on deep learning for estimating tree species using remote-sensing technology in multiple study areas, and validates the effectiveness of the method.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Proceedings Paper
Geography, Physical
A. Masiero, P. Dabove, V Di Pietra, M. Piragnolo, A. Vettore, A. Guarnieri, C. Toth, V Gikas, H. Perakis, K-W Chiang, L. M. Ruotsalainen, S. Goel, J. Gabela
Summary: This paper investigates the potential of UWB and LiDAR for precise pedestrian positioning and tracking, especially in indoor environments. The results show that LiDAR-based approach outperforms UWB when there are no obstructions, but obstructions cause gaps in LiDAR-based tracking. Therefore, a combination of LiDAR and UWB can be used to reduce interruptions in positioning.
XXIV ISPRS CONGRESS IMAGING TODAY, FORESEEING TOMORROW, COMMISSION II
(2022)
Proceedings Paper
Geography, Physical
A. H. Kanan, F. Pirotti
Summary: This study compares the land use and land cover change between Bangladesh and Indian Sundarbans from 1975 to 2020 using Landsat satellite images. The findings show a decrease in dense forest cover and an increase in moderate forest cover in both Bangladesh and Indian Sundarbans over the past 45 years. The study also reveals an increase in water bodies in the region. The comparative assessment between these two countries can inform sustainable forest management and planning.
XXIV ISPRS CONGRESS: IMAGING TODAY, FORESEEING TOMORROW, COMMISSION III
(2022)
Proceedings Paper
Geography, Physical
E. Kutcharttl, J. Hernandez, P. Corvalan, A. Promis, F. Pirotti
Summary: Earth observation using remote sensing imagery is a fast method to determine alteration levels. In this study, 12 stands of Araucaria-Nothofagus forests in southern Chile were analyzed to represent four alteration levels. Different approaches were tested, and the results show that the maximum NDVI values can accurately distinguish between the four classes.
XXIV ISPRS CONGRESS: IMAGING TODAY, FORESEEING TOMORROW, COMMISSION III
(2022)
Proceedings Paper
Geography, Physical
F. Tonion, F. Pirotti
Summary: This study analyzed several aspects of NO2 data from S5P over the years 2019, 2020, and 2021. The results showed a correlation between ground measurements and S5P values, indicating that S5P imagery is a valid index for spatial distribution of NO2 concentration and air quality.
XXIV ISPRS CONGRESS: IMAGING TODAY, FORESEEING TOMORROW, COMMISSION III
(2022)
Proceedings Paper
Computer Science, Theory & Methods
Filippo Tonion, Francesco Pirotti
Summary: This study applies different AI techniques to process optical data and achieve multitemporal classification of fluvial geomorphic units. The results show that all tested AI methods are capable of accurate classification, with Random Forest obtaining the best performance.
GEOMATICS AND GEOSPATIAL TECHNOLOGIES, ASITA 2021
(2022)