This paper aims to develop a new methodology for monitoring forest disturbances and regrowth using ALOS PALSAR data in tropical regions. In the study, forest disturbances and regrowth were assessed between 2007 and 2010 in Vietnam, Cambodia and Lao People’s Democratic Republic. The deforestation rate in Vietnam has been among the highest in the tropics in the last few decades, and those in Cambodia and Lao are increasing rapidly. L-band ALOS PALSAR mosaic data were used for the detection of forest disturbances and regrowth, because L-band SAR intensities are sensitive to forest aboveground biomass loss. The methodology used here combines SAR data processing, which is particularly suited for change detection, forest detection and forest disturbances and regrowth detection using expectation maximization, which is closely related to fuzzy logic. A reliable training and testing database has been derived using AVNIR-2 and Google Earth images for calibration and validation. Efforts were made to apply masking areas that are likely to show different SAR backscatter temporal behaviors from the forests considered in the study, including mangroves, inundated forests, post-flooding or irrigated croplands and water bodies, as well as sloping areas and urban areas. The resulting forest disturbances and regrowth map (25-m resolution) indicates disturbance rates of −1.07% in Vietnam, −1.22% in Cambodia and −0.94% in Lao between 2007 and 2010, with corresponding aboveground biomass losses of 60.7 Tg
, 59.2 Tg
and 83.8 Tg
, respectively. It is expected that the method, relying on free of charge data (ALOS and ALOS2 mosaics), can be applied widely in the tropics.
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