Erick Mas
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View article: Integrating GAN-Generated SAR and Optical Imagery for Building Damage Mapping
Integrating GAN-Generated SAR and Optical Imagery for Building Damage Mapping Open
Reliable assessment of building damage is essential for effective disaster management. Synthetic Aperture Radar (SAR) has become a valuable tool for damage detection, as it operates independently of the daylight and weather conditions. How…
View article: Assessing the Demographical Dynamics of Evacuations During Flood Hazard Using Mobile Spatial Statistics
Assessing the Demographical Dynamics of Evacuations During Flood Hazard Using Mobile Spatial Statistics Open
This study proposes a method to quantitatively assess evacuation demographics during regional floods using Mobile Spatial Statistics (MSSs). It focuses on Koriyama City, affected by Typhoon Hagibis in 2019, as well as Yamagata City, which …
View article: Accurate flood extent mapping in suburban areas using a single SAR image: FFT-based artifact removal approach
Accurate flood extent mapping in suburban areas using a single SAR image: FFT-based artifact removal approach Open
Rapid and reliable flood inundation mapping is essential for disaster response. While multi-temporal SAR analysis is widely used, suitable pre-event imagery is often unavailable in real disaster scenarios. This study proposes a method for …
View article: ABIC-based joint inversion using tsunami, GNSS and SAR data: finite fault model of the 2024 Noto Peninsula earthquake, Japan
ABIC-based joint inversion using tsunami, GNSS and SAR data: finite fault model of the 2024 Noto Peninsula earthquake, Japan Open
SUMMARY Nowadays, many joint inversions are carried out to understand the earthquake source process. In the joint inversion analysis, we have to determine the relative weights among different data sets in addition to the regularization ter…
View article: The 2024 Noto Peninsula earthquake building damage dataset: multi-source visual assessment
The 2024 Noto Peninsula earthquake building damage dataset: multi-source visual assessment Open
We present a building damage dataset following the 2024 Noto Peninsula earthquake. The database was compiled from freely available, multi-source, remote sensing data, verified through opt-in crowd-sourced information. The dataset consists …
View article: The 2024 Noto Peninsula earthquake building damage dataset: Multi-source visual assessment
The 2024 Noto Peninsula earthquake building damage dataset: Multi-source visual assessment Open
We present a building damage dataset following the 2024 Noto Peninsula Earthquake. The database was compiled from freely available, multi-source, remote sensing data, verified through opt-in crowd-sourced information. The dataset consists …
View article: Tsunami pedestrian evacuation simulation for Camaná, Peru: Perspectives for improving evacuation performance
Tsunami pedestrian evacuation simulation for Camaná, Peru: Perspectives for improving evacuation performance Open
Optimizing pedestrian evacuation in the face of a tsunami remains a critical challenge for safeguarding human lives. Agent-based models combined with reinforcement learning techniques offer a powerful framework to simulate complex evacuati…
View article: Multiple hazards and population change in Japan’s Suzu City after the 2024 Noto Peninsula Earthquake
Multiple hazards and population change in Japan’s Suzu City after the 2024 Noto Peninsula Earthquake Open
The earthquake that struck Japan’s Noto Peninsula on January 1, 2024, caused extensive damage, leading to the first major tsunami warning since the 2011 Tohoku earthquake. It remains unclear where people moved immediately after the earthqu…
View article: Streamlining Forest Wildfire Surveillance: AI-Enhanced UAVs Utilizing the FLAME Aerial Video Dataset for Lightweight and Efficient Monitoring
Streamlining Forest Wildfire Surveillance: AI-Enhanced UAVs Utilizing the FLAME Aerial Video Dataset for Lightweight and Efficient Monitoring Open
In recent years, unmanned aerial vehicles (UAVs) have played an increasingly crucial role in supporting disaster emergency response efforts by analyzing aerial images. While current deep-learning models focus on improving accuracy, they of…
View article: Feasibility of anomalous event detection based on Mobile Spatial Statistics: A study of six cases in Japan
Feasibility of anomalous event detection based on Mobile Spatial Statistics: A study of six cases in Japan Open
One of the primary goals of disaster risk management is to minimize the loss of life in the event of a disaster. To reduce the number of victims in disasters is important to know the amount of exposed population to a hazard. Similarly, pop…
View article: A Study on Digital Model for Decision-Making in Crisis Response
A Study on Digital Model for Decision-Making in Crisis Response Open
In this paper, we propose a digital model to run an evacuation simulation that reflects the road network blockage caused by the landslide and river flooding damage in Marumori-machi, Miyagi Prefecture, which was severely damaged by Typhoon…
View article: Towards Efficient Disaster Response via Cost-effective Unbiased Class Rate Estimation through Neyman Allocation Stratified Sampling Active Learning
Towards Efficient Disaster Response via Cost-effective Unbiased Class Rate Estimation through Neyman Allocation Stratified Sampling Active Learning Open
With the rapid development of earth observation technology, we have entered an era of massively available satellite remote-sensing data. However, a large amount of satellite remote sensing data lacks a label or the label cost is too high t…
View article: Understanding Tsunami Evacuation via a Social Force Model While Considering Stress Levels Using Agent-Based Modelling
Understanding Tsunami Evacuation via a Social Force Model While Considering Stress Levels Using Agent-Based Modelling Open
Given massive events, such as demonstrations in coastal cities exposed to tsunamigenic earthquakes, it is essential to explore pedestrian motion methods to help at-risk coastal communities and stakeholders understand the current issues the…
View article: Flood Data Analysis on SpaceNet 8 Using Apache Sedona
Flood Data Analysis on SpaceNet 8 Using Apache Sedona Open
With the escalating frequency of floods posing persistent threats to human life and property, satellite remote sensing has emerged as an indispensable tool for monitoring flood hazards. SpaceNet8 offers a unique opportunity to leverage cut…
View article: Fault Model of the 2024 Noto Peninsula Earthquake Based on Aftershock, Tsunami, and GNSS Data
Fault Model of the 2024 Noto Peninsula Earthquake Based on Aftershock, Tsunami, and GNSS Data Open
On January 1, 2024, at 16:10 (local time), a magnitude (Mw) 7.5 earthquake occurred on the Noto Peninsula, Japan. Japan Meteorological Agency seismic intensity scale of 7 was observed and a tsunami warning was issued for a wide area along …
View article: The Impact of the 2024 Noto Peninsula Earthquake Tsunami
The Impact of the 2024 Noto Peninsula Earthquake Tsunami Open
The tsunami generated by the Mw7.6 earthquake of Noto Peninsula, Japan left widespread impact. We analyzed multi-modal information and data to elucidate its impact.We modeled the tsunami propagation and inundation with multiple tsunami sou…
View article: The 2004 Noto Peninsula Earthquake Tsunami - It's Generation, Propagation, Inundation, and Impact
The 2004 Noto Peninsula Earthquake Tsunami - It's Generation, Propagation, Inundation, and Impact Open
The tsunami was generated by the Mw7.6 Noto Peninsula Earthquake and left widespread impact. After the event occurred, we modeled the tsunami propagation and coastal inundation with various tsunami source models and discussed its propagati…
View article: Tsunami Digital Twin – Concept, Progress, and Application to the 2024 Noto Peninsula Earthquake Tsunami Disaster, Japan
Tsunami Digital Twin – Concept, Progress, and Application to the 2024 Noto Peninsula Earthquake Tsunami Disaster, Japan Open
The digital twin is recognized as digital copies of the physical world's objects stored in digital(cyber) space and utilized to simulate the sequences and consequences of target phenomena. Users can fully view the target through real-time …
View article: Exploring the Feasibility of Ray Tracing SAR Simulation on Building Damage Assessment
Exploring the Feasibility of Ray Tracing SAR Simulation on Building Damage Assessment Open
Synthetic aperture radar (SAR) imagery is indispensable for acquiring a comprehensive, large-scale topographical perspective of the Earth's surface, facilitating the evaluation of diverse scenarios spanning various events. However, integra…
View article: Evaluation of Deep Learning Models for Building Damage Mapping in Emergency Response Settings
Evaluation of Deep Learning Models for Building Damage Mapping in Emergency Response Settings Open
Integrated with remote sensing technology, deep learning has been increasingly used for rapid damage assessment. Despite reportedly having high accuracy, the approach requires numerous samples to maintain its performance. However, in the e…
View article: Estimation of the Seismic Source of the 1974 Lima Peru Earthquake and Tsunami (Mw 8.1)
Estimation of the Seismic Source of the 1974 Lima Peru Earthquake and Tsunami (Mw 8.1) Open
In this investigation, we have conducted a long period teleseismic and tsunami waveform inversion to obtain the slip distribution of the 1974 Lima-Perú earthquake occurred in the central region of Peru. According to teleseismic inversion, …
View article: TSUNAMI EVACUATION IN A MASSIVE CROWD EVENT USING AN AGENT-BASED MODEL
TSUNAMI EVACUATION IN A MASSIVE CROWD EVENT USING AN AGENT-BASED MODEL Open
Under emergencies, individuals tend to move faster than during normal conditions, i.e., evacuation vs non-evacuation scenarios (Helbing et al., 2000; Cornes et al., 2019; Chen et al., 2018). Evacuations because of false alarms, terrorist a…
View article: Beyond tsunami fragility functions: experimental assessment for building damage estimation
Beyond tsunami fragility functions: experimental assessment for building damage estimation Open
Tsunami fragility functions (TFF) are statistical models that relate a tsunami intensity measure to a given building damage state, expressed as cumulative probability. Advances in computational and data retrieval speeds, coupled with novel…
View article: Digital twin computing for enhancing resilience of disaster response system
Digital twin computing for enhancing resilience of disaster response system Open
Digital twin is now recognized as digital copies of physical world's objects stored in digital space and utilized to simulate the sequences and consequences of target phenomena. By incorporating physical world’s data into the digital…