Assessing the Impact of Spectral Resolution on Classification of Lowland Native Grassland Communities Based on Field Spectroscopy in Tasmania, Australia

Bethany Melville,Jagannath Aryal,Arko Lucieer

doi:10.3390/rs10020308

Abstract

This paper presents a case study for the analysis of endangered lowland native grassland communities in the Tasmanian Midlands region using field spectroscopy and spectral convolution techniques. The aim of the study was to determine whether there was significant improvement in classification accuracy for lowland native grasslands and other vegetation communities based on hyperspectral resolution datasets over multispectral equivalents. A spectral dataset was collected using an ASD Handheld-2 spectroradiometer at Tunbridge Township Lagoon. The study then employed a k-fold cross-validation approach for repeated classification of a full hyperspectral dataset, a reduced hyperspectral dataset, and two convoluted multispectral datasets. Classification was performed on each of the four datasets a total of 30 times, based on two different class configurations. The classes analysed were Themeda triandra grassland, Danthonia/Poa grassland, Wilsonia rotundifolia/Selliera radicans, saltpan, and a simplified C3 vegetation class. The results of the classifications were then tested for statistically significant differences using ANOVA and Tukey’s post-hoc comparisons. The results of the study indicated that hyperspectral resolution provides small but statistically significant increases in classification accuracy for Themeda and Danthonia grasslands. For other classes, differences in classification accuracy for all datasets were not statistically significant. The results obtained here indicate that there is some potential for enhanced detection of major lowland native grassland community types using hyperspectral resolution datasets, and that future analysis should prioritise good performance in these classes over others. This study presents a method for identification of optimal spectral resolution across multiple datasets, and constitutes an important case study for lowland native grassland mapping in Tasmania.

Highlights

The results of this study indicated that accurate discrimination was possible using multispectral data; there was some indication of improved discrimination between lowland native grassland communities in the higher spectral resolution WorldView-2 datasets
The analysis of variance (ANOVA) test undertaken to determine whether class-specific classification accuracies vary based on the dataset indicated that for the three-class results, there was no significant difference in classification accuracy for any class
For the Danthonia class, and the overall classification accuracy, it was found that the Landsat OLI and WorldView-2 accuracies were significantly lower than the accuracies obtained in the full HSR results by an average of 2% to 3%

Summary

Introduction

Under Federal Australian law, 25 of the approximately 750 species found in these communities are protected under the Environmental Protection and Biodiversity Conservation Act (EPBC) [3], and an additional 60 species are listed under the Tasmanian Threatened Species Act [4]. Despite such protections, loss of native grassland communities across the State is a major concern. Beeton [1] estimated that the extent of lowland native grasslands has decreased by up to 90%, while Gilfedder [6] estimated the decrease to be approximately 60% from an original estimated extent of 450 km

Methods

Results

Discussion

Conclusion