Remote sensing has transformed the monitoring of life on Earth by revealing spatial and
temporal dimensions of biological diversity through structural, compositional and functional …

Abstract Machine learning approaches are increasingly used to extract patterns and insights
from the ever-increasing stream of geospatial data, but current approaches may not be …

Hyperspectral remote sensing technology has advanced significantly in the past two
decades. Current sensors onboard airborne and spaceborne platforms cover large areas of …

Partial least squares regression (PLSR) modelling is a statistical technique for correlating
datasets, and involves the fitting of a linear regression between two matrices. One …

In the last few decades, researchers have developed a plethora of hyperspectral Earth
Observation (EO) remote sensing techniques, analysis and applications. While …

The recently launched and upcoming hyperspectral satellite missions, featuring contiguous
visible-to-shortwave infrared spectral information, are opening unprecedented opportunities …

Foliar functional traits are widely used to characterize leaf and canopy properties that drive
ecosystem processes and to infer physiological processes in Earth system models. Imaging …

Hyperspectral data (Table 1) is acquired as continuous narrowbands (eg, each band with 1
to 10 nanometer or nm bandwidths) over a range of electromagnetic spectrum (eg, 400 …

Spatial and temporal information on plant functional traits are lacking in ecology, which limits
our understanding of how plant communities and ecosystems are changing. This problem is …

They may influence us as individuals by their encouragement and guidance; they may affect
their community through their untiring commitment to service and the greater good; or they …