Plant species richness prediction from DESIS hyperspectral data: A comparison study on feature extraction procedures and regression models

no code implementations • 5 Jan 2023 • Yiqing Guo, Karel Mokany, Cindy Ong, Peyman Moghadam, Simon Ferrier, Shaun R. Levick

The advanced spectral and spatial specification of the recently launched DESIS (the DLR Earth Sensing Imaging Spectrometer) instrument provides a unique opportunity to test the potential for monitoring plant species diversity with spaceborne hyperspectral data.

GPR regression

Quantitative Assessment of DESIS Hyperspectral Data for Plant Biodiversity Estimation in Australia

no code implementations • 6 Jul 2022 • Yiqing Guo, Karel Mokany, Cindy Ong, Peyman Moghadam, Simon Ferrier, Shaun R. Levick

Though remote sensing has been seen as a promising and cost-effective proxy for estimating plant diversity, there is a lack of quantitative studies on how confidently plant diversity can be inferred from spaceborne hyperspectral data.

regression