Beschreibung: Accurately monitoring forest dynamics in the tropical regions is essential for ecological studies and forest management. In this study, images from phase-array L-band synthetic aperture radar (PALSAR), PALSAR-2, and Landsat in 2006–2010 and 2015 were combined to identify tropical forest dynamics on Hainan Island, China. Annual forest maps were first mapped from PALSAR and PALSAR-2 images using structural metrics. Those pixels with a high biomass of sugarcane or banana, which are widely distributed in the tropics and subtropics and have similar structural metrics as forests, were excluded from the SAR-based forest maps by using phenological metrics from time series Landsat imagery. The optical–SAR-based forest maps in 2010 and 2015 had high overall accuracies (OA) of 92–97% when validated with ground reference data. The resultant forest map in 2010 shows good spatial agreement with public optical-based forest maps (OA = 88–90%), and the annual forest maps (2007–2010) were spatiotemporally consistent and more accurate than the PALSAR-based forest map from the Japan Aerospace Exploration Agency (OA = 82% in 2010). The areas of forest gain, loss, and net change on Hainan Island from 2007 to 2015 were 415 000 ha (+2.17% yr –1 ), 179 000 ha (–0.94% yr –1 ), and 236 000 ha (+1.23% yr –1 ), respectively. About 95% of forest gain and loss occurred in those areas with an elevation less than 400 m, where deciduous rubber, eucalyptus plantations, and urbanization expanded rapidly. This study demonstrates the potential of- PALSAR/PALSAR-2/Landsat image fusion for monitoring annual forest dynamics in the tropical regions.