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For people, place, prosperity and planet, we deliver impact with measurement science

Niall Origo

Niall Origo

Senior scientist

Biography

Niall Origo is a Senior Research Scientist in Earth Observation. His work focuses on the application of metrology, radiative transfer modelling and field instrumentation to the measurement of vegetation related biophysical variables.

Niall joined NPL in 2012 after completing the MSc Remote Sensing at University College London (UCL). He is currently finishing a PhD in Remote Sensing at UCL looking at the measurement and modelling of the fraction of absorbed photosynthetically active radiation (fAPAR).

Understanding the role of and changes in vegetation is critical for climate change, food security and disaster management applications. Niall’s work develops novel methods to understand the quality of the data feeding into these applications. Examples of work he leads includes the development and utilisation of virtual replicas of real vegetated field sites, establishment and maintenance of sensor networks for satellite validation, and the application of hyperspectral imaging from UAVs to retrieve satellite validation data.

Selected publications

Origo, N., Gorrono, J., Ryder, J., Nightingale, J., Bialek, A. (2020) Fiducial Reference Measurements for validation of Sentinel-2 and Proba-V surface reflectance products. Remote Sensing of Environment, 241:111690

Calders, K., Origo, N., Burt, A., Disney, M., Nightingale, J., Raumonen, P., Akerblom, M., Malhi, Y., Lewis, P. (2018) Realistic Forest Stand Reconstruction from Terrestrial LiDAR for Radiative Transfer Modelling. Remote Sensing, 18(6):1-15

Calders, K., Origo, N., Disney, M., Nightingale, J., Woodgate, W., Armston, J. and Lewis, P. (2018) Variability and bias in active and passive ground-based measurements of effective plant, wood and leaf area index. Agricultural and Forest Meteorology, 252:231-240.

Origo, N., Calders, K., Nightingale, J. and Disney, M. (2017) Influence of levelling technique on the retrieval of canopy structural parameters from digital hemispherical photography. Agricultural and Forest Meteorology, 237-238:143-149

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