Mapping potential habitats of threatened plant species in a moist tall grassland using hyperspectral imagery

We examined the capability of hyperspectral imagery to map habitat types of under-storey plants in a moist tall grassland dominated by Phragmites australis and Miscanthus sacchariflorus, using hyperspectral remotely-sensed shoot densities of the two grasses. Our procedure (1) grouped the species using multivariate analysis and discriminated habitat types (species groups) based on P. australis and M. sacchariflorus shoot densities, (2) used estimated shoot densities from hyperspectral data to draw a habitat type map, and (3) analyzed the association of threatened species with habitat types. Our identification of four habitat types, using cluster analysis of the vegetation survey coverage data, was based on P. australis and M. sacchariflorus shoot density ratios and had an overall accuracy of 77.1% (kappa coefficient = 0.71). Linear regression models based on hyperspectral imagery band data had good accuracy in estimating P. australis and M. sacchariflorus shoot densities (adjusted R ² = 0.686 and 0.708, respectively). These results enabled us to map under-storey plant habitat types to an approximate prediction accuracy of 0.537. Among the eight threatened species we examined, four exhibited a significantly biased distribution among habitat types, indicating species-specific habitat use. These results suggest that this procedure can provide useful information on the status of potential habitats of threatened species.