The huge tsunami triggered by an earthquake of magnitude 9.0 on March 11, 2011 hit the east coast of Honshu, Japan, and caused serious social and economic losses. According to the characteristics of earthquake and tsunami disaster and the requirements of damage monitoring, a rapid disaster development detection process based on a decision level fusion of multiple features is designed. In this approach, each feature extracted from the original remote sensing images, including NDVI, NDWI, components of the principal component analysis and the independent component analysis, is used to derive a specific change map, and different change maps are then integrated by a decision level fusion algorithm to generate a synthetic change map with a higher reliability, which can be used for the damage assessment. Multi-temporal HJ-1A/B (environment and disaster monitoring and forecasting of small satellite constellation) images are processed by the proposed approach and used for detecting the devastated areas in east coast of Japan before and after tsunami. The experimental results confirm the feasibility and effectiveness of the proposed approach, and demonstrate the advantages of HJ-1A/B remote sensing data. This unsupervised change detection process can identify the tsunami-devastated regions quickly and efficiently, and provide the technical and decision support for the disaster emergency response and loss evaluation.