Takeo Shibata
Takeo Shibata is an independent researcher and systems engineer with more than 30 years of experience in software and information systems development. He studied geophysics at Tohoku University and the University of California, Berkeley, and has maintained a long-standing interest in GIS, remote sensing, and Earth-related data analysis.
Alongside his professional work in the food distribution industry, he continues to explore the intersection of AI, geospatial technologies, and practical applications. He has presented topics related to AI and GIS at academic and technical communities, primarily in Japan and occasionally in the United States. His current interests include applying Python-based geospatial workflows and satellite data to real-world environmental and agricultural problems.
Sessions
This lightning talk presents a Python-based workflow for monitoring drought-related conditions in California rice-growing regions using public GIS datasets and satellite-derived environmental indicators.
This lightning talk introduces an early-stage approach to rice supply forecasting by combining rice-field polygon data, public statistics, and satellite-derived indicators such as vegetation and photosynthetic activity metrics.
Inspired by Sacramento rice production, this talk presents a Python workflow integrating public GIS data and satellite-derived indicators for reproducible geospatial analysis and environmental monitoring.