Since 2007 the airborne data processing team within NEODAAS (previously operating as NERC Airborne Research Facility Data Analysis Node) have processed over 400 flights of data, enabling over a decade of world leading science and providing an archive of data which continue to be used for new research.

Pioneering software for processing full waveform LiDAR

NEODAAS began processing full waveform LiDAR data in 2010, at this time it was a very early technology with very limited software available to work with full waveform LiDAR files. The airborne processing team wrote and released software so researchers could work with the new technology.

Pushing instruments to understand forest fires in Canada

In 2018 NERC-ARF undertook a campaign to collect high quality airborne data over forest fires in Canada using hyperspectral instruments covering visible to thermal wavelengths. A key requirement of the study was to collect ######

Understanding driver of biodiversity in tropical forests
How so many plant species coexist in tropical forests, despite intense competition for resources, is an unresolved question in community ecology. The answer has far-reaching implications given the many links between biodiversity and ecosystem functioning. Imaging spectroscopy is emerging as a powerful tool to map tropical forest diversity but few studies have used the technique to test ecological theory.

In Bongalov et al., (2019) imaging spectrometer data collected from the NERC Specim Fenix instrument as part of a campaign in 2014 were used to develop a method to remotely map beta-diversity which correlated well with plot based measurements. The method allowed mapping beta-diversity for entire landscapes containing multiple forest types, something not possible with traditional field-plot based approaches.

Analysis of the remotely sensed beta-diversity map of Sepilok revealed forest-type-specific patterns of spatial autocorrelation in community composition spanning over kilometres – beyond the scales typically considered in field studies. The paper confirmed that that beta- diversity is structured by environmental factors, and that spatial autocorrelation in composition arises, in part, from the spatial organisation of the environment itself.

Key publications
Bongalov, B., Burslem, D. F. R. P., Jucker, T., Thompson, S. E. D., Rosindell, J., Swinfield, T., et al. (2019). Reconciling the contribution of environmental and stochastic structuring of tropical forest diversity through the lens of imaging spectroscopy. Ecology Letters, 10, 95–12.