###### Abstract  
In order to assess the impact of the M\({}_{5}\)7.0 Jiaxiaigou earthquake that occurred on 8 August 2017 on vegetation, the Carnegie-Ames-Stanford Approach (CASA) model was adopted to estimate the vegetation net primary productivity (NPP) of Jiaxiaigou Valley, one of the World Heritage Sites, in July, August and September from 2015 to 2019. Then the characteristics of the impact of different earthquake-induced gebazards on vegetation were discussed, and a vulnerability-resilience assessment system concerning the seismic intensity was proposed. The results show that the NPP\({}_{\text{max}}\) and NPP\({}_{\text{mean}}\) values in Jiaxiaigou Valley first decreased and then increased and were 151.5-261.9 gC/m\({}^{2}\) and 54.6-116.3 gC/m\({}^{2}\), respectively. The NPP value of more than 70% area was 90-150 gC/m\({}^{2}\) in July. In August, the NPP\({}_{\text{mean}}\) values decreased, and the areas with lower values became larger; the NPP\({}_{\text{mean}}\) values of most areas affected by gebazards were 60-150 gC/m\({}^{2}\). During the earthquake, the NPP\({}_{\text{mean}}\) values of areas hit by gebhazards sharply declined by 27.2% (landslide), 22.4% (de debris flow) and 15.7% (collapse) compared with those in the same month in 2016. Vegetation in debris flow zones showed a stronger recovery, with a maximum NPP value increase of about 23.0% in September 2017. The vegetation gradually recovered after the earthquake, as indicated by the uptrend of the NPP values in the corresponding period in 2018 and 2019. In general, the reduction magnitude of NPP values decreased year by year in comparison to that in 2015 and 2016, and the decrease slowed down after the earthquake. The vulnerability and resilience index corresponding to the three seismic intensity ranges were 0.470-0.669 and 0.642-0.693, respectively, and those of Jiaxiaigou Valley were 0.473 and 0.671, respectively. The impact coefficient defined to represent the impact of the earthquake on NPP was 0.146-0.213. This paper provides a theoretical reference and guidance for the impact assessment of earthquakes on the ecosystem. net primary productivity; Jiaxiaigou earthquake; CASA model; geological hazard; seismic intensity 2 geohazards induced by it, such as landslides, debris flows, and avalanches, seriously damaged the ecosystem and affected over 30% of vegetation there [6]. The trend of vegetation change, which can be represented by the vegetation NPP, provides important information for landscape protection and restoration at WHSs after earthquakes [7; 8]. Accurate estimation of terrestrial vegetation NPP is difficult due to the complex effects of various factors. With the development of the terrestrial ecosystem model (TEM) [9], the equilibrium terrestrial biosphere model (BIOME3) [10], the BioGeochemical Cycles (BIOME-BGC) model [11], the carbon exchange between vegetation, soil and atmosphere (CEVSA) model [12], and the ecosystem modeling framework LPJ-GUESS [13], the estimation accuracy was greatly improved, which is more suitable in small areas than in large-scale regions [14]. Although these models were well known for simplicity and fewer parameter requirements, they are limited by the uncertainty in iterations, image inaccuracy, heterogeneous vegetation, standard errors of measurements, and phenological characteristics. In the context of global advances in 3S technologies, simulation models for large-scale NPP estimation were developed [15; 16]. The Carnegie-Ames-Stanford Approach (CASA) model is a global NPP simulation model combining multi-year satellite, climate, and other land surface remote-sensing databases. Many researchers have applied this model in studies related to ecosystems at high altitudes [17; 18; 19]. The advantages mentioned above have promoted its application in the assessment of the relationship between the dynamic changes in NPP and the driving forces. For instance, the NPP changing trend was related to urbanization [20], climate change [2], ecological transibility [21], and human activities. [PERSON] et al.