## 2 Materials and Methods
### Materials  
The data used in this paper include NDVI, SRTM, clay content, earthquake intensity and vegetation types.  
The NDVI images used in this paper were taken by the MODIS sensor on the Terra satellite, which also provides NDVI images every 16 days at 250-m spatial resolution (MOD13Q1). These data can be used to monitor global vegetation conditions, display land cover and track changes [26].  
There are 12 bands for MOD13Q1, and two bands, NDVI and Pixel Reliability, were used in this study. The two NDVI and Pixel Reliability bands were extracted using MRT software, resampled from 231.7 m to 250 m and projected from SIN to an Albers Equivalent Conical Projection. NDVI was used to calculate the fractional vegetation coverage and the band called Pixel Reliability is used to evaluate data availability. The average of the images from 145 to 225 Julian days, collected between 12 May and the end of August each year from 2005 to 2013 was chosen to represent optimal vegetation growth for each year. The reasons for selecting this period of time are: (1) it concludes with the period immediately following the data of the Wenchuan earthquake (12 May) and was therefore suitable for comparing the vegetation for the years before and the years after the earthquake on 12 May 2008; (2) it was the period of the most luxurian vegetation growth each year, thereby providing the best opportunity to observe the recovery of the vegetation. The Pixel Reliability band shows whether the pixel is useful or not (e.g., potential interference from cloud cover or snow cover). As determined by Pixel Reliability, images from 2009, 2010 and 2012 were influenced by various levels of cloud cover and required preprocessing. The images from 2011 and 2013 had very little cloud cover and did not require preprocessing. The cloud algorithm used in this study was the maximum value composites [27], and the procedure for its use was as follows: images from every two periods were compounded into one representative period, and the resulting image was obtained from the composite of the representative periods. The average cloud cover of the representative image between May and August in 2009 decreased from 19.83% to 6.75%, from 40.13% to 21.54% in 2010 and from 23.01% to 9.57% in 2012. The 2010 image was excluded due to the high level of cloud cover.  
The altitude data (Figure 2a) were derived from the Shuttle Radar Topography Mission (SRTM) [28] at 90-meter spatial resolution and used to research the relationship between the vegetation recovery and altitude.  
The soil data (Figure 2b) were obtained from the Harmonized World Soil Database (HWSD) of FAO, at 1 km spatial resolution. The clay content of the soil was derived by HWSD and used to evaluate the relationship between the vegetation recovery and soil texture.  
The earthquake intensity data (Figure 2b) were downloaded from the website of the China Earthquake Administration [29] and used to research the relationship between the vegetation recovery and earthquake intensity.  
The vegetation types (Figure 2c) were obtained from the title Vegetation of China and Its Geographic Pattern [30] and used to research the relationship between the vegetation recovery and vegetation types.  
The field survey points from all counties in the study area (4751 points in total) were used to validate the precision of the extraction. These points, shown in Figure 2a, were geological hazard points marked by researchers immediately following the earthquake and included landslides, debris flows, collapses and unstable slopes.  
Figure 2: Map shows different data sources used in this paper. (**a**) Altitude (SRTM) and field points. Field points are marked by researchers just after the earthquake; (**b**) Clay content (FAO) and earthquake intensity (China Earthquake Administration) (**c**) Vegetation types.