Bird vocalizations are one of the important subjects in ecoacoustics because birds communicate diversely using various vocalizations such as songs and calls. We have developed a portable system, HARKBird to provide a basic function, i.e., birdsong localization, which automatically extracts sound sources and their direction of arrivals (DOA) using robot audition techniques based on HARK. In this paper, we introduce HARKBird 2.0 which is empowered for higher understanding of birdsongs. A new soundscape annotation tool for localization results is enhanced by an interactive interface for song classification based on an unsupervised feature mapping t-SNE. We show that HARKBird 2.0 provides bird researchers with an integrated framework to analyze spatio-spectro-temporal dynamics of birdsongs using the song analysis of Japanese bush warbler (Horornis diphone).