Shifting cultivation is an important driver of forest disturbance in the tropics. However, studies of shifting cultivation are limited and current area estimates of shifting cultivation are highly uncertain. Although Southeast Asia is a hotspot of shifting cultivation, there are no national maps of shifting cultivation in Southeast Asia at moderate or high resolution (less than or equal to 30 m). Monitoring shifting cultivation is challenging because the slash-and-burn events are highly dynamic and small in size. In this research, we present and test an approach to monitoring shifting cultivation using Landsat data on Google Earth Engine. CCDC-SMA (Continuous Change Detection and Classification - Spectral Mixture Analysis) is used to detect forest disturbances. Then, these disturbances are attributed by combining time series analysis, object-based image analysis (OBIA), and post-disturbance land-cover classification. Forest disturbances are assigned to shifting cultivation, new plantation, deforestation, severe drought, and subtle disturbance annually from 1991 to 2020 at a 30-meter resolution for the country of Laos. The major forest disturbances in 1991-2020 are mapped with an overall accuracy of 85%. Shifting cultivation is mapped with a producer’s accuracy of 88% and a user’s accuracy of 80%. The margin of error of the sampling-based area estimate of Shifting cultivation is 5.9%. The area estimates indicate that shifting cultivation is the main type of forest-disturbance in Laos, affecting 32.9% ± 1.9% of Laos over the past 30 years. To study the development of shifting cultivation over time, the area of slash-and-burn events is estimated at 5-year intervals of 1991-2020 with all margins of error less than 17%. Results show that the area of slash-and-burn activities in Laos increased in the most recent 5-year period. We believe that the methods developed and tested in Laos can be applied to other regions.