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for Data Science in Earth Observation develops innovative methods for information extraction from remote sensing data in close cooperation with the Department EO Data Science of the Remote Sensing Technology
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in Earth Observation develops innovative methods for information extraction from remote sensing data in close cooperation with the Department EO Data Science of the Remote Sensing Technology Institute
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projects can be based around include remote sensing; role of invertebrate and vertebrate fauna in tree health; biology, ecology and management of pests, diseases and beneficial microorganisms; health
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radiative transfer modelling (2) explore the near-real time inversion of remote sensing of forest disturbances using emulation (3) use a library of digital twin forests to understand the uncertainties in
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uncertainties and biases in N flux monitoring, including proximal sensing, remote sensing, Eddy covariance and in-situ continuous sampling accompanied by traditional laboratory analyses. NitroScope will benefit
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measurement techniques to reduce uncertainties and biases in N flux monitoring, including proximal sensing, remote sensing, Eddy covariance and in-situ continuous sampling accompanied by traditional laboratory
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equipment. Traditionally, this has required separate, specialized wireless systems for communication, radar-based sensing, and localization—each relying on dedicated hardware. However, the emerging field
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imaging is one of the rapidly growing domains in remote sensing primarily due to the breadth of applications on a variety of areas, from plant disease detection to object tracking. For example
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. Louise Terryn. Job profile MSc degree (or equivalent) in a relevant field (Bio-Engineering, Forestry, Remote Sensing, Surveying, Physics, Geosciences, Environmental Sciences, Computer Science A passion for