## 2 Materials and Methods
### Data Acquisition  
Table 1 summarizes the datasets used in this study including MODIS time-series data. The three vegetation indices (VIs) used in this study included NDVI, EVI, and SAVI, and all images were extracted from MOD13Q1. All data were acquired from the years 2000 to 2019, which laid the basis for analyzing MODIS time-series data. In particular, a combined time-series of TERRA 16-day composite vegetation indexes (MODIS products MOD13Q1 time-series) at 250 m spatial resolution satellite data was downloaded from the Earth-data ([[https://lpdaacsvc.cr.usgs.gov/appeears/](https://lpdaacsvc.cr.usgs.gov/appeears/)]([https://lpdaacsvc.cr.usgs.gov/appeears/](https://lpdaacsvc.cr.usgs.gov/appeears/))) (accessed on 20 May 2020) using the Application for Extracting and Exploring Analysis Ready Samples (A\(\rho\)pEEARS) tool to extract data [41; 42]. The study area's annual rainfall and mean temperature data from 2000 to 2019 were acquired from the Pakistan Meteorological Department (PMD) to determine the mean annual rainfall and mean monthly temperature ([[http://www.pmd.gov.pk/](http://www.pmd.gov.pk/)]([http://www.pmd.gov.pk/](http://www.pmd.gov.pk/))) (accessed on 12 August 2020).  
The ArcMap v.10.6 software was used to map and analyze vegetation variability, and ERDAS Imagine 2015 was used for image classification in this study. The shapefile of the respective areas was created, and the area-of-interest (AOI) was extracted by masking using ArcMap v.10.6. image processing tasks and NDVI analysis were accomplished by using ENVI 5.4 [43; 44]. The MODIS product (MCD12Q1) of 500 m resolution was used to illustrate  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**S. No**} & \multirow{2}{*}{**Data**} & \multicolumn{2}{c}{**Spatial**} & \multirow{2}{*}{**Time Period**} & \multirow{2}{*}{**Source**} \\  & & & **Resolution** & & \\ \hline \multirow{2}{*}{01} & \multirow{2}{*}{MOD13Q1} & \multirow{2}{*}{250} & \multirow{2}{*}{2000–2019} & [[https://lpdaacsvc.cr.usgs.gov/](https://lpdaacsvc.cr.usgs.gov/)]([https://lpdaacsvc.cr.usgs.gov/](https://lpdaacsvc.cr.usgs.gov/)) & & \\  & & & & & 2020 \\ \multirow{2}{*}{02} & \multirow{2}{*}{MCD12Q1} & \multirow{2}{*}{500} & \multirow{2}{*}{2019} & [[https://lpdaacsvc.cr.usgs.gov/](https://lpdaacsvc.cr.usgs.gov/)]([https://lpdaacsvc.cr.usgs.gov/](https://lpdaacsvc.cr.usgs.gov/)) & & \\  & & & & 2020 \\ \multirow{2}{*}{03} & \multirow{2}{*}{Rainfall data} & \multirow{2}{*}{2000–2019} & [[http://www.pmd.gov.pk/](http://www.pmd.gov.pk/)]([http://www.pmd.gov.pk/](http://www.pmd.gov.pk/)) & \\  & & & & (accessed on 12 August 2020) \\ \multirow{2}{*}{04} & \multirow{2}{*}{Temperature data} & \multirow{2}{*}{2000–2019} & [[http://www.pmd.gov.pk/](http://www.pmd.gov.pk/)]([http://www.pmd.gov.pk/](http://www.pmd.gov.pk/)) & \\  & & & & (accessed on 12 August 2020) \\ \hline \hline \end{tabular}
\end{table}
Table 1: Datasets used in the present research study.  
Figure 2: Spatiotemporal distribution of mean annual (**a**) rainfall and (**b**) temperature in the study area from 2000 to 2019.  
the land use and land cover areas. The legend of the International Geosphere-Biosphere Program (IGBP) was also used in the present study. We downloaded the MCD12Q1-2019 from NASA-lpdaac [45].