2022 年 42 巻 2 号 p. 129-134
Satellite remote sensing is the most cost-effective method for observing forests in areas where it is difficult to conduct field surveys, and it is expected to be used for tree species classification. Although seasonal characteristics are useful clues for tree species classification by remote sensing technology, there are few studies on tree species discrimination by satellite using these characteristics. In this study, using Tsukuba City and Boso Peninsula as test sites, we show that two evergreen broad-leaved tree species, namely, C. sieboldii and L. edulis, can be extracted from Sentinel-2/MSI images by their flowering signals. Although these two species have similar flowering signals, they can be separated from each other due to their different flowering times. The results also suggest the possibility of using the flowering signal to estimate the damage from harmful insects and diseases, and the possibility of misclassification of the land cover map by the flowering signal.