In the eastern United States large amounts of smoke emitted from both wildfires and prescribed fires affect the regional air quality and long-term climate and may have an impact on public health. Satellite remote sensing is an effective approach for detecting and monitoring the smoke plume. The spectral characteristics of smoke plume are measurably different from those of other cover types, such as vegetation, cloud, snow, and so on. A multi-threshold method has been developed for detecting smoke plumes with eight MODIS spectral bands based on the analysis of spectral characteristics of different cover types. A series of tests are applied to all pixels in one granule (5-min measurements) to filter out non-smoke pixels step by step with water masking. At each step, specific thresholds are utilized. The results have been validated with true color images for a number of cases from different areas and time, showing that the algorithm works well except for a few missing or incorrect identified smoke pixels.