Jumpei Takami

Jumpei Takami

Jumpei Takami is a specialist in remote sensing and geographic information systems (GIS), with a strong foundation in civil engineering and advanced data analytics. He holds a Master of Science in Civil Engineering from the University of Washington, United States, where he developed his expertise in applying satellite-based technologies to environmental monitoring. With over ten years of combined academic and professional experience, Mr. Takami has contributed to international projects that utilize satellite remote sensing to address hazards such as landslides, flooding, drought, and land subsidence. He has also supported forest monitoring initiatives, including canopy height and above-ground biomass estimation.

In recent years, Mr. Takami has shown strong interest in emerging technologies such as artificial intelligence (AI) and digital twins. He has applied machine learning techniques—including Spatially Variant Apodization (SVA) for SAR image enhancement, Histogram-Based Gradient Boosting Classifier (HBGC) for landslide detection, and convolutional neural networks (CNNs) for forest structure analysis. Inspired by the growing role of digital twin platforms in climate resilience, he has also explored their potential to integrate satellite data with simulation models for risk forecasting and urban planning in vulnerable regions. Looking ahead, Mr. Takami is committed to advancing the integration of AI and digital twin technologies with Earth observation to support sustainable disaster management and climate adaptation, particularly in low-resource and high-risk settings.

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  • Organization
    United Nations Office for Outer Space Affairs (UNOOSA)
  • Profession
    Associate Expert in Remote Sensing for Disaster Management, UN-SPIDER Program
Related sessions
In personAI and environmentAI and cities 
8 July 2025
14:00 - 17:15
EST - New York
CST - Beijing
PST - Los Angeles
AWST - Perth, Australia
In an era where climate change, urbanization, and population growth...