## 3 Materials
### Satellite Image Pre-Processing
#### 3.3.1 HR Reflectance Data

Table 1: Summary of different types of satellite images used in Huailai. transfer model. Landsat 5 Thematic Mapper (TM) operational imaging ended in November 2011. On 31 May 2003, the Scan Line Corrector (SLC), which compensates for the forward motion of the satellite, failed. For the scan line errors of the Landsat 7, we masked the missing data and fill in empty pixels using data from HJ-1 and GF-1 acquired in the same period. Landsat 8 launched on 11 February 2013. The OLI is intended to be broadly compatible with the previous ETM+ bands. At the same time, the OLI bands are refined in order to avoid atmospheric absorption features. All HJ-1 CCD and GF-1 WFV scenes for the study area were acquired through the China Center for Resources Satellite Data and Application (CRESDA) ([[http://www.cresda.com](http://www.cresda.com)]([http://www.cresda.com](http://www.cresda.com))). Before constructing the HR datasets, the following steps were applied in the HJ-1 CCD and GF-1 WFV data processing: absolute radiometric calibration, cloud detection, atmospheric correction, and geometric correction. Absolute calibration parameters provided by CRESDA were also used to carry out radiometric calibration for HJ-1 and GF-1 so that the digital number (DN) value could be translated into apparent reflectance. In this processing, the first step is to convert the DN to spectral radiance \(L\). The formula for GF-1 data is  
\[L=Gain*DN \tag{4}\]  
The calibration formula for HJ-1 data is  
\[L=Gain*DN+Offset \tag{5}\]  
The apparent reflectance is calculated as  
\[p_{toa}=\frac{\pi Ld^{2}}{cos(\theta_{s})E_{s}} \tag{6}\]  
\(E_{s}\) is the band-specific exoatmospheric solar constant, \(\theta_{s}\) is solar zenith angle, and \(d\) is the Earth-Sun distance in astronomical units. \(E_{s}\), \(Gain\) and \(Offset\) can be found on the website of CRESDA. Due to the impact of clouds and haze, the surface reflectance changes over the course of a time series; in addition, all data require cloud detection before they can be used to ensure that ground survey sites exhibit clear-sky conditions. This approach ensures that the acquired data represent actual surface physical parameters. Due to the need for cloud detection in HR data, simple indices and thresholding methods must be applied initially to detect thick clouds:  
\[\left\{ \begin{array}{c}\text{R}_{\text{Red}}>0.3\\ 0.8<\text{R}_{\text{R}_{\text{Red}}}<1\end{array} \right. \tag{7}\]  
where R\({}_{\text{Red}}\) is the reflectance of the red band and R\({}_{\text{NIR}}\) is the reflectance of the NIR band. For the detection results, visual acquisition is used again to determine the presence of clouds and haze. Images that are still contaminated by clouds and haze are discarded. Atmospheric corrections for HJ-1 and GF-1 satellite data are performed based on the new proposed aerosol retrieval algorithm [46; 47] with prior surface reflectance data support. The distributions and surface reflectance of dense pixels are determined using the MOD09 8-day synthetic surface reflectance products to estimate the aerosol contents. Then, these estimates are used as inputs in the 6S radiative transfer model to perform atmospheric correction on every pixel along with precalculated Look-Up Tables (LUTs). As a level-2 product, the HJ-1 satellite data experience systemic geometric corrections. By comparison, GF-1 is a level-1 product with built-in rational polynomial coefficient (RPC) parameters that must be used to perform coarse geometrical corrections so that geographical coordinate projection can be realized for related images. Level 1 products have experienced only rough geometric correction, and some geometrical errors remain with respect to other remote sensing images. The GF-1 WFV images were resampled to 30 m resolution using the average resampling method to match the HJ-1 CCD data. Because geometric correction at the system level has low positioning precision, high-precisiongeometric corrections are still required.