Abstract: Taking the Qianjiangyuan National Park Pilot Area and the surrounding 10 km wide buffer zone as our research case, based on the Google Earth Engine(GEE) cloud platform, Landsat satellite imagery, and remote sensing based forest fire monitoring data, visual interpretation combined with spectral index method was implemented to extract the burned scars quickly. Then the extracted forest fires were statistically analyzed in terms of fire occurrence time, frequency, and burned area. In addition, several landscape indices were calculated to describe the spatial pattern of the burned scars. The results showed that during the period 1999 to 2019, 19 forest fires occurred in the study area, of which forest fires occurred in spring and winter seasons accounting for 47.37% and 42.11% of the fires, respectively. The biggest forest fire, with a size of 83.54 hm², was observed in 2013, while the highest occurrence frequency of forest fires(6 times) was discovered in 2011, and their burned areas differed largely. In contrast, there was only one fire each in 2014 and 2019. The total burned area was approximately 766.55 hm² during the study period, and there was a trend of increasing first and then decreasing in the study period. Besides, the burned area within Qianjiangyuan National Park was 9.05 hm²(9.04 hm² and 0.01 hm² in 2011 and 2014 respectively). The proposed method in the current work is suitable for quickly obtaining 30 m resolution scale post-fire information by means of free historical Landsat data, establishing a spatially explicit historical archive of disastrous events, and evaluating the effectiveness of disaster management for the national park timely and objectively.