Estimation of abundance and distribution of two moist tall grasses in the Watarase wetland, Japan, using hyperspectral imagery

The dominant grasses in a wetland are of critical concern for the wetland’s ecological integrity, because these species provide the habitats for many small plants and animals. In this study, we used hyperspectral imagery to map the distributions of two dominant tall grasses (Miscanthus sacchariflorus (Maxim.) Benth and Phragmites australis (Cav.) Trin. ex Stend) in the Watarase wetland, in central Japan. Stepwise multiple linear regression analysis was applied to the hyperspectral data to predict the shoot density and biomass of the two grasses. The independent data sets included original reflectance, band ratios, significant components identified by principal components analysis (PCA), and significant components identified by decision boundary feature extraction (DBFE). The coefficient of determination ( R 2 ) and the root-mean-square error (RMSE) of model calibration and validation were used to evaluate the models. The significant DBFE components showed better ability at predicting shoot density of the two grasses than the other variables in the validating areas. The RMSE values were 7.40/m2 for M. sacchariflorus and 13.09/m2 for P. australis, which amounted to errors of around 10.0% and 12.6%, respectively, of the maximum shoot density measured during our surveys. All variables showed similar performance at predicting biomass, but the results were less accurate than those for shoot density. Considering the performance of the DBFE components for both shoot density and biomass prediction, we suggest that these are the best indicators for estimating the abundance of the two grasses.