## 5 Conclusions  
In this study, the time-series characteristics of three GLASS products (LAI, FVC, and GPP) were assessed based on the tendency, correlation, and phenological retrieval methods during 2000 to 2018 in the TRSR. Moreover, the performances of these products over different surfaces and terrain were analyzed. We found that three products reasonably displayed the vegetation phenological characteristics and their interannual variations across TRSR. Nevertheless, the phenological differences between FVC and two other products were larger than 10 days in more than 35% of pixels in the study area, and the proportion of large differences of LSP between GPP and LAI was only 10%. Moreover, we proved that the long temporal variations of FVC were significantly different from LAI and GPP in the TRSR from 2000 to 2018. The significant positive trends of LAI and GPP (~5%) were much weaker than those in the FVC (~17%). Note that the poor performances of LSP metrics and long-term changes were observed at the regions with heterogeneous land cover (i.e., low RVP level) and rugged surfaces (i.e., high TNI level). This demonstrates that the complex effects of both the algorithm and the environmental factors at high elevation can cause a high degree of difference in the time-series performances of different products. In brief, this research highlights the potentiality of joint application of GLASS products for observing vegetation characteristics and regional carbon dynamics in mountainous areas. The intercomparison of different time-series products is crucial for not only the recognition of the relationship between vegetation greening and the carbon cycle in mountainous areas, but also the refinement of the retrieval algorithm of global products over mountain areas. In the future, we will evaluate the performance of various biophysical products with high spatial resolution and utilize the process-based models to assess vegetation dynamics at global or regional scales. Conceptualization, H.J., H.S. and W.Z. ; methodology, H.J., H.S. and W.Z. ; software, G.L., X.N. and X.X. ; writing--original draft preparation, W.Z. and W.F. ; writing--review and editing, H.J., A.L. and H.S. ; visualization, W.Z. and G.H. ; supervision, H.J., A.L. and H.S. ; project administration, H.J. and A.L. ; funding acquisition, H.J. and A.L. All authors have read and agreed to the published version of the manuscript. **Funding:** This research was funded by National Key Research and Development Program of China (Grant No. 2016 YFA0600103), National Natural Science Foundation of China (Grant No. 42071352, 41631180, 41801370), and the Chinese Academy of Sciences (CAS) \"Light of West China\" Program. **Informed Consent Statement:** Not applicable. **Data Availability Statement:** (1) The GLASS products introduced in this paper are available in [[[http://www.geodata.cn/index.html](http://www.geodata.cn/index.html)]([http://www.geodata.cn/index.html](http://www.geodata.cn/index.html)), accessed on 20 November 2021] or [[[http://glass.umd.edu/Download.html](http://glass.umd.edu/Download.html)]([http://glass.umd.edu/Download.html](http://glass.umd.edu/Download.html)), accessed on 20 November 2021], reference number [2; 3; 4; 5; 6; 7]. (2) DEM and land cover data can be found in: [[[http://www.gscloud.cn/](http://www.gscloud.cn/)]([http://www.gscloud.cn/](http://www.gscloud.cn/)), accessed on 20 November 2021] or [[[http://data.ess.tsinghua.edu.cn/](http://data.ess.tsinghua.edu.cn/)]([http://data.ess.tsinghua.edu.cn/](http://data.ess.tsinghua.edu.cn/)), accessed on 20 November 2021], reference number [35]. **Acknowledgments:** The authors would like to thank teachers and work fellows of the Research Center for Digital Mountain and Remote Sensing Application, Institute of Mountain Hazards and Environment for their support during this research. Meanwhile, we thank all members of Shunlin Liang's team providing the GLASS products for us. In addition, we are also most thankful to the anonymous reviewers and all the editors for their helpful comments and suggestions.