## 5 Conclusions  
An approach was implemented to identify vegetation variability and its dynamics by comprehensively using three vegetation indices (EVI, SAVI, and NDVI) estimated through MODIS time-series data in the Punjab Province of Pakistan. The varying associations of NDVI, EVI, and SAVI were estimated in different vegetation forms. A minor correlation exists between NDVI, EVI, and SAVI, with [PERSON]'s correlation coefficients ranging from 0.42 to 0.50. Due to the blue band reflectance disturbance, EVI typically showed high uncertainties in sparse vegetation areas of grassland and forest. The EVI time-series showed the highest inter-annual variability in Punjab from 2000 to 2019, with 14.28% of the total region showing higher variability than 40%. For most vegetation types, the phenological metrics of season-start and season-end generated by the NDVI, SAVI, and EVI were consistent. The greatest deviations from phenological metrics were obtained from the NDVI time-series (33.4 days at the start of the season and 40.7 days at the end of the season), suggesting soil context-sensitivity and atmospheric effects of the index. The annual mean VI images displayed parallel spatial arrangements of vegetation conditions with fluctuating levels. Major steps include using the temporal interpolation algorithm to remove contaminated pixels to reconstruct MODIS NDVI time-series data. The EVI time-series showed greater inter-annual variations from 2000 to 2019 compared to SAVI and NDVI. Given the high vegetation variability in northern Punjab, the high variability in EVI values could be due to variations in soil background properties. In the future, to assess the climatic effect on semi-arid, arid, and rainfed areas' vegetation dynamics, satellite data will be assessed along with climate data for the region and other larger areas.  
Conceptualization, P.H., A.T. and F.M.; Methodology, A.T. and P.H.; Software, P.H., A.S. and A.T.; Validation, P.H., A.T. and S.H.I.A.S.; Formal analysis, P.H., A.T. and M.N.T.; Investigation, P.H., A.T., M.N.T. and S.H.I.A.S.; Resources, P.H., A.T., A.S., M.N.T., L.Z., F.M. and S.H.I.A.S.; Data curation, P.H., A.T.; Writing--original draft preparation, P.H., A.T., A.S., S.H.I.A.S., F.M. and L.Z.; Writing--review and editing, P.H., A.T., A.S., S.H.I.A.S., F.M., M.N.T. and S.H.I.A.S.; Visualization, A.T.; Supervision, L.Z., A.S.; Project administration, L.Z.; Funding acquisition, L.Z. and P.H. All authors have read and agreed to the published version of the manuscript.  
This study was supported by the National Natural Science Foundation of China (grant 41907192), Civil Aerospace Pre-Research Project (D040102) and the Fundamental Research Funds for Beijing University of Civil Engineering and Architecture (No. X20045).  
Not applicable.  
The datasets generated and/or analyzed during the current study are not publicly available due to legal constraints because they are owned by different institutions, but are available from the authors on reasonable request.  
We are thankful to [PERSON] from the Pakistan Meteorological Department in Islamabad, who provided the meteorological data necessary for this research. Finally, we acknowledge the two anonymous reviewers and editors of the special issue of the journal who provided very helpful comments that helped improved the final version of the manuscript.  
The authors declare no conflict of interest.