The candidate must have a background in Geomatics with a strong interest in image analysis, OR a background in computer vision with a strong interest in 3D spatial information. In both cases, the candidate should have good programming skills, competence in 3D modelling and spatial analysis, understanding of machine learning, and fascination for Earth science applications.
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Many Earth observation platforms (drones, micro-satellites) have become inexpensive, recording massive amounts of data via thermal, colour, infrared, and radar cameras for different applications, such as urban planning, vegetation dynamics monitoring, and natural hazard monitoring. Living in the age of big remote sensing data, currently we face challenges in managing, processing, and efficiently exploiting these data for socio-economic and environmental applications. This project will develop novel 3D data fusion modelling using voxels for context-based, automated information processing and extraction from large databases of disparate remote sensing imagery to bring new perspectives on phenomenon understanding and prediction.
Biological, Earth & Environmental Sciences