Abstract: There is a large amount of carbon stored in scenic forest biomass, which plays an important role in regional carbon cycle. The spatial effect of forest disturbance and recovery on the release of carbon should be taken into account for accurately measuring scenic forest biomass. An estimation model using K nearest neighbor (KNN) algorithm for the biomass of scenic forest was built based on the survey data from 100 sample plots in 2002 at Zijin Mountain National Forest Park of Nanjing, and data of free Landsat time series stacks (LTSS) during 2001 to 2010 by using three approaches of original band, radiometric correction, and spectral index plus terrain factors. The time trajectory analysis of the biomass of scenic forest and drivers was conducted with three periods, i.e., before the renovation (2001-2004), during the renovation (2005-2007) and after the renovation (2008-2010) based on the precision validation. Study results showed that: 1) among the three approaches, comprehensive model of spectral index plus terrain factors outperformed others with the highest correlation coefficient and prediction accuracy, and the lowest standard error and the minimum mean relative error; 2 ) during 2001 to 2010, the biomass in scenic forest showed a complex trends of slow decline, down then up and slowly rising ; 3) during 2001 to 2010, forest disturbance in the study area had three different trends of slight fluctuation, slow increase, and rapid decline; 4) on the spatial distribution, the biomass in scenic forest experienced the trend of slow increase of aggregation, intensified fragmentation and stabilization in three periods respectively. Results of this study could provide a scientific basis for the establishment of long term high-precision carbon accounting models covering forest disturbance and recovery factors at regional scale.