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Emanuel Castillo Cardona

Emanuel Castillo Cardona

Geospatial Data Scientist

Engineering / Architecture

Kingston, Ontario

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About Emanuel Castillo Cardona:

I am a Master of Science graduate in Geological Sciences from Queen's university, with a strong focus on geospatial data science and environmental applications. My background combines geomorphology, natural hazards, and climate research with hands-on experience in remote sensing, GIS, and data-driven modeling.

I enjoy working at the intersection of geoscience and technology—using tools like Python, R, and advanced GIS platforms to transform complex spatial data into insights that support risk assessment and decision-making. My experience includes analyzing satellite imagery, UAV and LiDAR data, and climate datasets to model terrain dynamics and hazard susceptibility.

I am motivated by projects that connect data science with real-world challenges, especially those related to sustainable urban growth, climate adaptation, and natural hazard risk reduction. I thrive in collaborative environments and bring strong problem-solving, communication, and technical skills to every project I take on.

Experience

Graduate-level training in geological sciences with a specialization in geospatial data science and applied research on geomorphology, natural hazards, and climate challenges. Skilled in remote sensing, GIS, and spatial modeling, with hands-on experience analyzing multi-source geospatial datasets (satellite imagery, UAV photogrammetry, LiDAR, DEMs). Proficient in Python, R, and GIS platforms (ArcGIS, QGIS, GRASS GIS) for data processing, automation, and visualization. Experienced in integrating climate and environmental data to support hazard assessment, risk mapping, and decision-making. Strong background in interdisciplinary collaboration, scientific communication, and translating complex data into actionable insights.

Education

Master of Science (M.Sc.) in Geological Sciences – Queen's University, Canada

Specialized in geospatial data science, geomorphology, and natural hazards

Thesis research applied remote sensing (UAV-SfM, LiDAR, satellite imagery) and GIS-based modeling to assess rockfall hazards in complex mountainous terrain

Gained expertise in Python, R, and spatial analysis tools for environmental and climate-related applications

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