Linear spectral mixture analysis of Landsat TM data for monitoring invasive exotic plants in estuarine wetlands

Abstract

This study assessed the feasibility of spectral mixture analysis (SMA) of Landsat thematic mapper (TM) data for monitoring estuarine vegetation at species level. SMA modelling was evaluated, using χ² test, by comparing SMA fraction images with a precisely classified QuickBird image that has a higher spatial resolution. To clearly understand the strengths and weaknesses of SMA, eight SMA models with different endmember combinations were assessed. When the TM data dimension for SMA and the endmember number required were balanced, a model with three endmembers representing water and two vegetation types was most accurate, whereas a model with five endmembers approximated the actual surface situation and generated a relatively accurate result. Our results indicate that an SMA model with appropriate endmembers had relatively satisfactory accuracy in monitoring vegetation. However, errors might occur in SMA fraction images, especially in models with an inappropriate endmember combination, and the errors were mainly distributed in areas filled with water or near water. Therefore, short vegetation usually submerged during high tide tended to be poorly predicted by SMA models. These results strongly suggest that tide water has a great influence on SMA modelling, especially for short vegetation.

Acknowledgements

This work was supported by the National Basic Research Program of China (No. 2006CB403305), the Science and Technology Commission of Shanghai (No. 07DZ12038-2), the National Natural Science Foundation of China (No. 30870409 and 40471087) and the Program for New Century Excellent Talents in University (NCET-06–0364) funded by the Ministry of Education of China. We thank Chongming Dongtan National Natural Reserve and the students in our laboratories for their assistance in field sampling.