138 citations as recorded by crossref.

1. Image-based post-disaster inspection of reinforced concrete bridge systems using deep learning with Bayesian optimization X. Liang
2. Detection of Disaster-Affected Cultural Heritage Sites from Social Media Images Using Deep Learning Techniques P. Kumar et al.
3. Challenges and limitations of earthquake-induced building damage mapping techniques using remote sensing images-A systematic review S. Matin & B. Pradhan
4. Robotics in the Construction Sector: Trends, Advances, and Challenges Y. Liu et al.
5. A 3D Shape Descriptor Based on Contour Clusters for Damaged Roof Detection Using Airborne LiDAR Point Clouds M. He et al.
6. Monitoring hourly night-time light by an unmanned aerial vehicle and its implications to satellite remote sensing X. Li et al.
7. Geographic object-based image analysis (GEOBIA): emerging trends and future opportunities G. Chen et al.
8. Transferability of object-based image analysis approaches for landslide detection in the Himalaya Mountains of northern Pakistan A. Bacha et al.
9. In situ volcanic ash sampling and aerosol–gas analysis based on UAS technologies (AeroVolc) S. Thivet et al.
10. Rapid Identification of Post-Earthquake Collapsed Buildings via Multi-Scale Morphological Profiles With Multi-Structuring Elements B. Wang et al.
11. Use of UAV-based photogrammetry products for semi-automatic detection and classification of asphalt road damage in landslide-affected areas N. Nappo et al.
12. A Critical Review of Unmanned Aerial Vehicles (UAVs) Use in Architecture and Urbanism: Scientometric and Bibliometric Analysis M. Videras Rodríguez et al.
13. Evaluating fine tuned deep learning models for real-time earthquake damage assessment with drone-based images F. Kizilay et al.
14. Unmanned aerial vehicle inspection of the Placer River Trail Bridge through image-based 3D modelling A. Khaloo et al.
15. Multi-Resolution Feature Fusion for Image Classification of Building Damages with Convolutional Neural Networks D. Duarte et al.
16. An object detection approach for detecting damages in heritage sites using 3-D point clouds and 2-D visual data R. Pathak et al.
17. Remote Sensing-Based Proxies for Urban Disaster Risk Management and Resilience: A Review S. Ghaffarian et al.
18. Review article: the use of remotely piloted aircraft systems (RPASs) for natural hazards monitoring and management D. Giordan et al.
19. Identification of Forested Landslides Using LiDar Data, Object-based Image Analysis, and Machine Learning Algorithms X. Li et al.
20. Accuracy of Unmanned Aerial Systems Photogrammetry and Structure from Motion in Surveying and Mapping: A Review S. Deliry & U. Avdan
21. Damage Detection and Virtual Reconstruction of Built Heritage: An Approach Using High-Resolution Range and Intensity Data P. Tiwari et al.
22. Recent Advancements in AI-Enabled Smart Electronics Packaging for Structural Health Monitoring V. Sharma et al.
23. Accuracy Assessment and Optimization of the Photogrammetric Process Variables for 3D Mapping Using Unmanned Aerial Vehicle (Drones) A. Gond et al.
24. CNN-based segmentation frameworks for structural component and earthquake damage determinations using UAV images T. Saida et al.
25. Automated regional seismic damage assessment of buildings using an unmanned aerial vehicle and a convolutional neural network C. Xiong et al.
26. An Evaluation of UAV Path Following and Collision Avoidance Using NFMGOA Control Algorithm R. Thusoo et al.
27. Towards an Integrated Approach to Infrastructure Damage Assessment in the Aftermath of Natural Hazards M. Nepal et al.
28. Large-Scale Synthetic Urban Dataset for Aerial Scene Understanding Q. Gao et al.
29. Bayes risk-based mission planning of Unmanned Aerial Vehicles for autonomous damage inspection J. Zeng et al.
30. Automatic Detection of Earthquake-Damaged Buildings by Integrating UAV Oblique Photography and Infrared Thermal Imaging R. Zhang et al.
31. Remote sensing‐based mapping of structural building damage in the Ahr valley G. Samprogna Mohor et al.
32. Review of Automatic Feature Extraction from High-Resolution Optical Sensor Data for UAV-Based Cadastral Mapping S. Crommelinck et al.
33. An Exploratory Application of Low-Cost Drone Imagery and an Image Analysis Model to Evaluate Post-Disaster Recovery Progress for Planning Equitable Housing Recoveries Through Dynamic Funding Allocation D. Perrucci et al.
34. Automatic extraction of urban land information from unmanned aerial vehicle (UAV) data A. Shukla & K. Jain
35. Detection of damaged buildings after an earthquake with convolutional neural networks in conjunction with image segmentation R. Ünlü & R. Kiriş
36. A BIM-Based Method for Structural Stability Assessment and Emergency Repairs of Large-Panel Buildings Damaged by Military Actions and Explosions: Evidence from Ukraine P. Hryhorovskyi et al.
37. A Drone-Based Structure from Motion Survey, Topographic Data, and Terrestrial Laser Scanning Acquisitions for the Floodgate Gaps Deformation Monitoring of the Modulo Sperimentale Elettromeccanico System (Venice, Italy) M. Fabris & M. Monego
38. Remote Sensing of Wildland Fire-Induced Risk Assessment at the Community Level M. Ahmed et al.
39. Prediction of old goaf residual subsidence integrating EDS-InSAR with EsLSTM in the Loess Plateau, China F. Ma et al.
40. Big Data in Natural Disaster Management: A Review M. Yu et al.
41. A Review on UAV-Based Remote Sensing Technologies for Construction and Civil Applications S. Guan et al.
42. Post-Disaster Building Damage Assessment: Multi-Class Object Detection vs. Object Localization and Classification D. Hatić et al.
43. Rapid urban flood damage assessment using high resolution remote sensing data and an object-based approach S. Jiménez-Jiménez et al.
44. Photogrammetry in Documentation and Ambient Vibration Test of Historical Masonry Minarets K. Hacıefendioğlu & E. Maraş
45. Vector Field UAV Guidance for Path Following and Obstacle Avoidance with Minimal Deviation J. Wilhelm & G. Clem
46. Pose-graph optimization for efficient tie-point matching and 3D scene reconstruction from oblique UAV images Z. Xu et al.
47. How can Big Data and machine learning benefit environment and water management: a survey of methods, applications, and future directions A. Sun & B. Scanlon
48. Unmanned Aerial Vehicles for Search and Rescue: A Survey M. Lyu et al.
49. SAM-VQA: Supervised Attention-Based Visual Question Answering Model for Post-Disaster Damage Assessment on Remote Sensing Imagery A. Sarkar et al.
50. Identification of Structurally Damaged Areas in Airborne Oblique Images Using a Visual-Bag-of-Words Approach A. Vetrivel et al.
51. Territoires « cyclonés ». Les aléas cycloniques et leurs impacts F. Vinet & F. Leone
52. Light-Weight Semantic Segmentation Network for UAV Remote Sensing Images S. Liu et al.
53. UAV-Derived Himalayan Topography: Hazard Assessments and Comparison with Global DEM Products C. Watson et al.
54. Earthquake Damage Visualization (EDV) Technique for the Rapid Detection of Earthquake-Induced Damages Using SAR Data R. Sharma et al.
55. ReCRNet: a deep residual network for crack detection in historical buildings H. Reis & K. Khoshelham
56. Geoscientists in the Sky: Unmanned Aerial Vehicles Responding to Geohazards R. Antoine et al.
57. Planning remote sensing emergency services: Bridging the gap between remote sensing science and emergency practice in China X. Zheng et al.
58. Deep learning for automatic post-disaster debris identification for precise damage assessments using UAV footage G. Prakash et al.
59. Heuristics Based Optimization for Multidepot Drone Location and Routing Problem to Detect Post-Earthquake Damages N. Aydin et al.
60. Instance segmentation scheme for roofs in rural areas based on Mask R-CNN M. Amo-Boateng et al.
61. Automated surface damage detection and quantification in concrete structures using semantic point clouds L. Huang et al.
62. Airborne LiDAR for post-disaster recovery in Japan – lessons from coseismic landslides and lifeline impacts in the aftermath of the 1 January 2024 Noto Peninsula earthquake C. Gomez
63. Use of Multi-Temporal LiDAR Data to Extract Collapsed Buildings and to Monitor Their Removal Process after the 2016 Kumamoto Earthquake F. Yamazaki et al.
64. 无人机振动下惯性传感器辅助的图像运动去模糊 纪. Ji Yue et al.
65. A heterogenous-source geoinformation system to manage climate-induced modifications on the landscape for sustainable development L. Serra Bellini et al.
66. A method for using unmanned aerial vehicles for emergency investigation of single geo-hazards and sample applications of this method H. Huang et al.
67. Change detection in urban areas from remote sensing data: a multidimensional classification scheme H. Si Salah et al.
68. Veículos Aéreos Não Tripulados (VANT) para inspeção de manifestações patológicas em fachadas com revestimento cerâmico R. Ballesteros & A. Lordsleem Junior
69. Identification of Land Use Affected by Tidal Floods using Unmanned Aerial Vehicles in Coastal Medan City, North Sumatra, Indonesia A. Thoha et al.
70. Remote proximity monitoring between mobile construction resources using camera-mounted UAVs D. Kim et al.
71. Synergistic object-based multi-class feature extraction in urban landscape using airborne LiDAR data S. Jawak et al.
72. Assessment of GCP Number and Separation Distance for Small UAS Surveys with and without GNSS-PPK Positioning D. Bolkas
73. Processing Social Media Images by Combining Human and Machine Computing during Crises F. Alam et al.
74. Integrating UAV and Ground Panoramic Images for Point Cloud Analysis of Damaged Building J. Jhan et al.
75. Review of Remote Sensing Approaches and Soft Computing for Infrastructure Monitoring A. Kyriou et al.
76. 3D reconstruction of disaster scenes for urban search and rescue S. Verykokou et al.
77. Pre-disaster mapping with drones: an urban case study in Victoria, British Columbia, Canada M. Kucharczyk & C. Hugenholtz
78. Landslides Information Extraction Using Object-Oriented Image Analysis Paradigm Based on Deep Learning and Transfer Learning H. Lu et al.
79. Rapid Damage Assessment Following Natural Disasters through Information Integration Y. Chen & W. Ji
80. Integrating Machine Learning and Remote Sensing in Disaster Management: A Decadal Review of Post-Disaster Building Damage Assessment S. Al Shafian & D. Hu
81. Real-time bridge disaster management: Enabling technology and application framework H. Deng et al.
82. “Hurricaned” territories. Hurricane hazards and their impacts F. Vinet & F. Leone
83. Centimetre-range deformations of built environment revealed by drone-based photogrammetry S. Varbla et al.
84. Automated crack segmentation in close-range building façade inspection images using deep learning techniques K. Chen et al.
85. Unmanned Aerial Vehicle for Remote Sensing Applications—A Review H. Yao et al.
86. Post-Disaster Building Damage Detection from Earth Observation Imagery Using Unsupervised and Transferable Anomaly Detecting Generative Adversarial Networks S. Tilon et al.
87. Prediction analysis of landslide displacement trajectory based on the gradient descent method with multisource remote sensing observations J. Wang et al.
88. Drones—An Open Access Journal D. Gonzalez-Aguilera & P. Rodriguez-Gonzalvez
89. Active tectonics of the onshore Hengchun Fault using UAS DSM combined with ALOS PS-InSAR time series (Southern Taiwan) B. Deffontaines et al.
90. The effectiveness of an integrated BIM/UAV model in managing safety on construction sites S. Alizadehsalehi et al.
91. A multi-UAV cooperative route planning methodology for 3D fine-resolution building model reconstruction X. Zheng et al.
92. Integrated HBIM-GIS Models for Multi-Scale Seismic Vulnerability Assessment of Historical Buildings G. Sammartano et al.
93. Identification of Building Damage from UAV-Based Photogrammetric Point Clouds Using Supervoxel Segmentation and Latent Dirichlet Allocation Model C. Liu et al.
94. A Hybrid Improved Symbiotic Organisms Search and Sine–Cosine Particle Swarm Optimization Method for Drone 3D Path Planning T. Xiong et al.
95. UAV and GIS based rapid earthquake-induced building damage assessment and methodology for EMS-98 isoseismal map drawing: The June 12, 2017 Mw 6.3 Lesvos (Northeastern Aegean, Greece) earthquake S. Mavroulis et al.
96. Community-scale multi-level post-hurricane damage assessment of residential buildings using multi-temporal airborne LiDAR data Z. Zhou et al.
97. Utility Based Scheduling for Multi-UAV Search Systems in Disaster-Hit Areas K. Miyano et al.
98. Application of unmanned aerial vehicles in earth resources monitoring: focus on evaluating potentials for forest monitoring in Ethiopia H. Berie & I. Burud
99. Exploring Technological Alternatives to the Visual Inspection Method in the Built Environment L. Acosta et al.
100. UAV-Based Structural Damage Mapping: A Review N. Kerle et al.
101. GIS-Based Information System for Automated Building Façade Assessment Based on Unmanned Aerial Vehicles and Artificial Intelligence K. Chen et al.
102. Tsunami Damage Detection with Remote Sensing: A Review S. Koshimura et al.
103. Integrating Construction 4.0 Technologies: A Four-Layer Implementation Plan M. El Jazzar et al.
104. A review study on unmanned aerial vehicle and mobile robot technologies on damage inspection of reinforced concrete structures J. Wang & T. Ueda
105. Leveraging Digital Twins as a Common Operating Picture for Disaster Management: Case of Seismic Hazards M. Korkmaz et al.
106. 基于SBAS-InSAR技术的成汶高速汶川段滑坡易发区选线研究 P. Liu et al.
107. Exploring three pillars of construction robotics via dual-track quantitative analysis Y. Liu et al.
108. Cognitive Internet of Vehicles and disaster management: A proposed architecture and future direction A. Arooj et al.
109. Fusion of vertical and oblique images using Intra-Cluster-Classification for building damage assessment M. Kakooei & Y. Baleghi
110. Unmanned aircraft path planning for construction safety inspections L. Yu et al.
111. Concrete 3D Printing: Process Parameters for Process Control, Monitoring and Diagnosis in Automation and Construction T. Quah et al.
112. Multi-Class Concrete Defect Classification Using Guided Semantic–Spatial Fusion and Squeeze–Excitation Enhanced DenseNet Model A. Mayya & N. Alkayem
113. Mobile augmented reality in support of building damage and safety assessment W. Kim et al.
114. Usability of aerial video footage for 3-D scene reconstruction and structural damage assessment J. Cusicanqui et al.
115. Structural Building Damage Detection with Deep Learning: Assessment of a State-of-the-Art CNN in Operational Conditions F. Nex et al.
116. Deep learning-based 3D digital damage map of vertical-type tunnels using unmanned fusion data scanning K. Jang et al.
117. Applications of multirotor drone technologies in construction management Y. Li & C. Liu
118. Deep Neural Networks for Quantitative Damage Evaluation of Building Losses Using Aerial Oblique Images: Case Study on the Great Wall (China) Y. Gong et al.
119. Earthquake-induced building damage detection using the fusion of optical and radar data in intelligent systems M. Ghahrloo & M. Mokhtarzade
120. A literature review of next-generation smart sensing technology in structural health monitoring S. Sony et al.
121. Determining changes in building tilts based on UAV photogrammetry K. Strząbała et al.
122. Detection of seismic façade damages with multi-temporal oblique aerial imagery D. Duarte et al.
123. A Damage-Tolerant Task Assignment Algorithm for UAV Swarm in Confrontational Environments C. Chen et al.
124. UAV Bridge Inspection through Evaluated 3D Reconstructions S. Chen et al.
125. An Automatic Procedure for Early Disaster Change Mapping Based on Optical Remote Sensing Y. Ma et al.
126. NECTAR-An Agent-Based Dynamic Task Allocation Algorithm in the UAV Swarm C. Chen et al.
127. Application and Development of Autonomous Robots in Concrete Construction: Challenges and Opportunities S. Zhao et al.
128. Geomorphological evolution of landslides near an active normal fault in northern Taiwan, as revealed by lidar and unmanned aircraft system data K. Chang et al.
129. Visual monitoring of civil infrastructure systems via camera-equipped Unmanned Aerial Vehicles (UAVs): a review of related works Y. Ham et al.
130. Incidents1M: a Large-Scale Dataset of Images With Natural Disasters, Damage, and Incidents E. Weber et al.
131. Complete Coverage Path Planning for a Multi-UAV Response System in Post-Earthquake Assessment A. Nedjati et al.
132. Mapping vegetation biophysical and biochemical properties using unmanned aerial vehicles-acquired imagery B. Lu et al.
133. Fusion of satellite, aircraft, and UAV data for automatic disaster damage assessment M. Kakooei & Y. Baleghi
134. Data collection tools for post-disaster damage assessment of building and lifeline infrastructure systems J. Lozano & I. Tien
135. Semisupervised classification of hurricane damage from postevent aerial imagery using deep learning Y. Li et al.
136. Disaster damage detection through synergistic use of deep learning and 3D point cloud features derived from very high resolution oblique aerial images, and multiple-kernel-learning A. Vetrivel et al.
137. Automated engineering analysis of crack mechanisms on building façades using UAVs Y. Liu et al.
138. Yapay Zeka Kullanılarak Deprem Bölgelerinden Drone ile Alınan Görüntülerden Enkaz Tespitinin Gerçekleştirilmesi Ö. Picak & K. Sabancı