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Tsunami Damage Detection with Remote Sensing: A Review

Shunichi Koshimura, Luis Moya, Erick Mas, Yanbing Bai
2020 Geosciences  
Tsunamis are rare events compared with the other natural disasters, but once it happens, it can be extremely devastating to the coastal communities.  ...  This paper provides a review of how remote sensing methods have developed to contribute to post-tsunami disaster response.  ...  E.M. is for tsunami damage interpretation, L.M. is for machine learning method, and Y.B. is for deep learning method. All authors have read and agreed to the published version of the manuscript.  ... 
doi:10.3390/geosciences10050177 fatcat:o6trnuw7efgvjp7zbnh3ev2nqm

Priority Analysis of Remote Sensing and Geospatial Information Techniques to Water-Related Disaster Damage Reduction for Inter-Korean Cooperation

Sunmin Lee, Sung-Hwan Park, Moung-Jin Lee, Taejung Song
2020 Journal of Sensors  
Water disaster satellites with high-resolution C band synthetic aperture radar are scheduled to be launched by South Korea.  ...  Especially, the use of radar images, such as C band images, has proven essential.  ...  In addition, in one case, disasters were evaluated by applying deep learning to satellite imagery [35] .  ... 
doi:10.1155/2020/8878888 fatcat:ew6kqeiulzg7jfrvtkkuwgw3g4

Using 3D Convolution and Multimodal Architecture For Earthquake Damage Detection Based on Satellite Imagery and Digital Urban Data

Takashi Miyamoto, Yudai Yamamoto
2021 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
In this work, a novel method for detecting damage to single buildings from a set of multi-temporal satellite images is developed by applying a recent machine learning approach.  ...  The damage detection system is designed as a deep learning model that uses multimodal data, consisting of optical satellite images and structural attributes.  ...  We express our sincere condolences to the victims of the earthquake and wish for a quick recovery and reconstruction of the affected area.  ... 
doi:10.1109/jstars.2021.3102701 fatcat:iz4katspnza2nom3ruw3byorki

SENSOR FUSION, GIS AND AI TECHNOLOGIES FOR DISASTER MANAGEMENT

H. Kemper, G. Kemper
2020 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
In all parts, spatial data is key in order to analyze existing structure, assist in risk assessment and update the information after a disaster incident.  ...  Emphasis is further driven to Machine Learning techniques adopted from Artificial Intelligence that improve algorithms for auto-detection and represent an important step forwards to an integrated system  ...  HOT initiative 4 ) After a disaster strikes a certain area satellite images are one of the first datasets that are available to the disaster response teams.  ... 
doi:10.5194/isprs-archives-xliii-b3-2020-1677-2020 fatcat:batjuyaxibaq3hrk3t364lo23i

USE OF MACHINE LEARNING TECHNIQUES FOR RAPID DETECTION, ASSESSMENT AND MAPPING THE IMPACT OF DISASTERS ON TRANSPORT INFRASTRUCTURE

P. M. Kikin, A. A. Kolesnikov, A. M. Portnov
2019 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
Change detection based on geospatial data before and after damage can make rapid and automatic assessment possible with reasonable accuracy and speed.  ...  Therefore, it is very important to quickly provide emergency services with necessary post-disaster maps, created on the principles of rapid mapping.  ...  The advances of machine learning technologies, together with satellite remote sensing data, have recently brought much attention to their applicability to damage recognition.  ... 
doi:10.5194/isprs-archives-xlii-3-w8-195-2019 fatcat:f4ur4rszx5hlhbp5bascixr32m

Detecting flooded areas with machine learning techniques: case study of the Selška Sora river flash flood in September 2007

Peter Lamovec, Tatjana Veljanovski, Matjaž Mikoš, Krištof Oštir
2013 Journal of Applied Remote Sensing  
Floods seem to appear with increased frequency from one year to another. They create great damage to property and in some cases even result in lost lives.  ...  Machine learning techniques can reduce the time necessary for flood mapping. We test various machine learning methods to find the one with the highest classification accuracy.  ...  Images were acquired within the frame of International Charter Space and Major Disaster, 6 which, in the event of any natural or manmade disaster, provides access to free satellite images and products  ... 
doi:10.1117/1.jrs.7.073564 fatcat:pwrgdbf6erg5notaq66pwdnszq

Automatic Post-Disaster Damage Mapping Using Deep-Learning Techniques for Change Detection: Case Study of the Tohoku Tsunami

Jérémie Sublime, Ekaterina Kalinicheva
2019 Remote Sensing  
images from areas struck by a disaster before and after it hits.  ...  In this paper, we present a state-of-the-art deep-learning approach for change detection applied to satellite images taken before and after the Tohoku tsunami of 2011.  ...  He came up with the subject on change detection with unsupervised techniques, as well as the application to the case study of the Tohoku tsunami.  ... 
doi:10.3390/rs11091123 fatcat:j2c4k7e5pbbtljuv4gnxjk3ona

SWC 2021 Solar Farm disaster Management_V6.pdf [article]

Shakthi Bharath K, Surender Rangaraju, Osama Isaac, Abhijit Ghosh, Phu Le Vo, Ramesh V, Arjun A, Kalai Arul S, Gowthama Krishna D
2022 figshare.com  
a combination of satellite images.  ...  In this paper, we propose a prediction model to analyze the effect of above mentioned extreme environmental factors and disasters on the productivity and efficiency of the solar farm output by utilizing  ...  Not but least, I would like to extend my special thanks to Arjun A, student of PSG Institute of Technology -Coimbatore for his effort and dedicated work.  ... 
doi:10.6084/m9.figshare.19285373.v1 fatcat:zoz354wanrbvjad3b6bhzgvsp4

Disaster Monitoring of Satellite Image Processing Using Progressive Image Classification

Romany F. Mansour, Eatedal Alabdulkreem
2023 Computer systems science and engineering  
Satellites are mostly used to detect disasters on Earth, and they have advantages in capturing Earth images.  ...  The PICA creates tailoring and adjustments obtained from satellite images before training and post-disaster aerial image data patches.  ...  Radar (SAR) satellite imagery was used to attempt to monitor the occurrence of natural disasters.  ... 
doi:10.32604/csse.2023.023307 fatcat:ba26d566ffhdxjqxjzzdeaxlf4

APPLICATIONS OF SENTINEL-1 SYNTHETIC APERTURE RADAR IMAGERY FOR FLOODS DAMAGE ASSESSMENT: A CASE STUDY OF NAKHON SI THAMMARAT, THAILAND

G. Dadhich, H. Miyazaki, M. Babel
2019 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
</strong> Flooding is one of the major disasters occurring in various parts of the world. Estimation of economic loss due to flood often becomes necessary for flood damage mitigation.  ...  Although, these impediments can be surpassed by using RADAR satellite imagery.  ...  The satellite images were acquired sequentially by satellite Sentinel 1A, before and after the flood took place.  ... 
doi:10.5194/isprs-archives-xlii-2-w13-1927-2019 fatcat:j7ypawxgwfcrfokomo2uvlgypi

Creating A Coefficient of Change in the Built Environment After a Natural Disaster [article]

Karla Saldana Ochoa
2021 arXiv   pre-print
The study utilizes the algorithm Seg-Net to perform semantic segmentation of the built environment from the satellite images in both instances (prior and post-natural disasters).  ...  Thanks to an automated crawler, aerial images from before and after a natural disaster of 50 epicenters worldwide were obtained from Google Earth, generating a 10,000 aerial image database with a spatial  ...  Acknowledgements The authors would like to thank the Reviewers and Editor for their helpful comments and constructive suggestions.  ... 
arXiv:2111.04462v2 fatcat:bwex36am35arra6yuf4xupymsm

D6.1 Conceptual framework for remote sensing-based CH monitoring

V. Karathanassi, A. Georgopoulos, A. Doulamis, Enriques Hermandez-Montes
2020 Zenodo  
In this deliverable, new state of the art methods are briefly described to document the main decisions on the advanced image processing and data analysis methods that will be developed and/or applied within  ...  Some products, such as 3D representation of the monuments, land deformation, etc., address the needs of routine monitoring, while some others address post-disaster requirements and are generated after  ...  Rapid damage mapping after a disaster is crucial and can provide a first damage assessment for the affected region.  ... 
doi:10.5281/zenodo.6352008 fatcat:nul4udvk35hupazeullordefxa

Big Data in Natural Disaster Management: A Review

Manzhu Yu, Chaowei Yang, Yun Li
2018 Geosciences  
The paper has presented the findings of several researchers on varied scientific and technological perspectives that have a bearing on the efficacy of big data in facilitating natural disaster management  ...  From this perspective, big data has radically changed the ways through which human societies adopt natural disaster management strategies to reduce human suffering and economic losses.  ...  These human-annotated features were then used to train a supervised machine learning system to learn to recognize such features in new unseen images.  ... 
doi:10.3390/geosciences8050165 fatcat:yucms6qo7nht5krjmnrwrkzy2y

The 2011 Tohoku Tsunami from the Sky: A Review on the Evolution of Artificial Intelligence Methods for Damage Assessment

Jérémie Sublime
2021 Geosciences  
that could help to better handle the aftermath of similar disasters in the future.  ...  However, this tsunami was also one of the first observed from the sky by modern satellites and aircrafts, thus providing a unique opportunity to exploit these data and train artificial intelligence methods  ...  Synthetic Aperture Radar Images as Source Data One solution to the problem of cloud occlusion and lighting issues faced by optical images is to use the SAR data acquired by satellites.  ... 
doi:10.3390/geosciences11030133 fatcat:q4e4d73xxff3bcxeiik5byqr7e

Monitoring Urban Deprived Areas with Remote Sensing and Machine Learning in Case of Disaster Recovery

Saman Ghaffarian, Sobhan Emtehani
2021 Climate  
images and machine learning methods.  ...  We produced the damage and recovery maps based on change analysis over the detected slum areas.  ...  Acknowledgments: The satellite images were provided by Digital Globe Foundation, which were granted for a project at ITC entitled "post-disaster recovery assessment using remote sensing image analysis  ... 
doi:10.3390/cli9040058 fatcat:fegud7pf5rcclkhq4ksefnwtvq
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