Abstract: sing the landscape pattern and landscape function to construct a landscape ecological vulnerability model for Shaanxi Province,this work analyzes two dimensions (provincial and internal natural units) of the spatiotemporal evolution of landscape ecological vulnerability.It also explores the multiscale driving mechanism of landscape ecological vulnerability by applying a geographical probe model.The results showed the following:(1) The landscape pattern vulnerability index of Shaanxi Province in 2000 and 2015 was 0.477 3 and 0.409 7,respectively,suggesting a decrease of 6.76%.The spatial difference in landscape pattern vulnerability shows that high values are distributed in the north,whereas low values are distributed on both sides of the central area.The landscape function vulnerability index in 2000 and 2015 was 0.492 6 and 0.417 4,respectively,suggesting a decrease of 7.52%.The spatial difference in landscape functional vulnerability is concentrated in the scattered spatial layout of lowvalue areas in the north and the central region.(2) In 2000 and 2015,the landscape ecological vulnerability index of Shaanxi Province was 0.427 5 and 0.369 7,respectively,suggesting a decrease of 5.78%.The spatial difference in vulnerability is significant,and the overall distribution pattern from south to north shows a high-low zonal staggered distribution pattern,with an obvious transition between internal partitions.The vulnerabilities of the Loess Plateau,Guanzhong Basin,and the Qinba Mountains were reduced by 8.55%,3.81%,and 1.20%,respectively.(3) The influencing factors of the whole province and internal divisions vary with the geographical scale.Natural environmental factors play a vital role in the change in vulnerability,while the role of socioeconomic factors are continuously increasing.The landscape ecological vulnerability assessment method proposed in this paper can provide a reference for the ecological vulnerability assessment.The research conclusion can provide a decisionmaking basis for regional sustainable development.

Key words: landscape ecological, vulnerability, spatiotemporal change, driving force, geographical detector, Shaanxi Province