Ryohei Kametaka

Tohoku University, PhD in Engineering

Apr. 2023 - Mar. 2026

• Conducted research at the International Research Institute of Disaster Science

• Researched methods for estimating flood inundation damage to farmlands and buildings using a single SAR image

Tokyo University of Marine Science and Technology, MA in Engineering

Apr. 2013 - Mar. 2015

• Conducted research at the Atmospheric and Environmental Physics Laboratory

• Compared optical properties and radiative fluxes dependent on particle shapes in cirrus clouds.

Tokyo University of Marine Science and Technology, BA in Engineering

Mar. 2009 - Feb. 2013

• Studied primarily mechanical and electrical/electronic engineering; conducted numerical simulations using Fortran for the graduation thesis.

• Gained hands-on experience in the operation and maintenance of marine engines through practical training.

GPA: 3.85

NV5 Geospatial Solutions, Inc.

Jun. 2017 - Ongoing

Sales Engineer

• We provide licenses for ENVI and IDL, which are essential tools for satellite imagery analysis and high-performance scientific computing.

• As a Sales Engineer, I am responsible for the entire customer lifecycle—from pre-sales consulting to post-sales technical support. I also lead regular training workshops for our users. Additionally, I apply my expertise in ENVI and IDL to design and implement systems specifically for optical and SAR (Synthetic Aperture Radar) data analysis.

• As natural disasters such as earthquakes and extreme rainfall become more frequent and severe globally, rapid and accurate damage assessment is vital for saving lives and streamlining recovery efforts. While optical imagery from satellites and UAVs provides intuitive situational awareness, it is often hampered by cloud cover and nighttime conditions. Consequently, Synthetic Aperture Radar (SAR) has gained significant attention as an all-weather, day-and-night observation tool, particularly for flood monitoring.

• During my doctoral studies, I focused on Inundated Area Extraction from Single-Event SAR Imagery during Heavy Rain Disasters. While previous studies have demonstrated the effectiveness of “Coherence” in assessing damage, this approach often fails in emergency scenarios—such as those involving JAXA’s ALOS series—due to the lack of pre-event archive data acquired under identical observation geometries. To address this gap, I developed a methodology integrating sub-aperture decomposition and hotspot analysis. This approach achieved a maximum improvement of approximately 20% in detection accuracy for both agricultural fields and urban structures, compared to conventional binary classification methods for flood estimation.

• Part of this research has been published in the International Journal of Applied Earth Observation and Geoinformation, and my full doctoral dissertation is available via the Tohoku University Online Academic Repository (TOUR). Furthermore, the source code implemented in my dissertation is publicly available on GitHub under the MIT License. My expertise lies in disaster-time damage estimation using SAR imagery, and I remain actively engaged in the latest advancements in satellite remote sensing applied to a broad range of natural disasters, including seismic events.

• Kametaka, R., Adriano, B., Mas, E., & Koshimura, S. (2025). “Accurate flood extent mapping in suburban areas using a single SAR image: FFT-based artifact removal approach”, International Journal of Applied Earth Observation and Geoinformation, 144, Article 104941. https://doi.org/10.1016/j.jag.2025.104941

• Ryohei Kametaka, “Enhancing Flood Mapping Accuracy from a Single SAR Image through Sub-Aperture-Based and Statistical Approaches”, Tohoku University, 2026.