Abstract
Wetland monitoring and especially wetland vegetation classification are crucial for preserving valuable wetland ecosystems. The development of remote sensing technique for wetland monitoring is of urgent necessity. In order to improve the accuracy of vegetation classification, we have investigated the wetland vegetation classification using multi-temporal Landsat TM images. Because the growth pattern of a wetland vegetation changes according to the vegetation type, we can used this difference of temporal growth pattern which appear in the multitemporal images for classifying the vegetation types. In order to clarify this temporal growth pattern of wetland vegetation types, we have conducted sampling experiments to measure the biomass growth during the growing season. And also spectral reflectance measurements were conducted to see the spectral difference between the vegetation types as well. As the result of supervised classifications using the multitemporal Landsat TM image, an accurate wetland vegetation classification map has been produced.
