# Comparison of Methods for Reconstructing MODIS Land Surface Temperature under Cloudy Conditions
## 3 Results
### Validation of the Spatiotemporal Method  
Compared with the above method, for the STARFM algorithm using ERA5, the overall performance of LST fused with Terra data was relatively poor. Table 4 summarizes the validation statistics of LST reconstructed by STARFM using ERA5 data at eight sites. Among them, the R\({}^{2}\), RMSE, and NSE were 0.4, 21.28 K, and \(-1.10\), respectively. A negative NSE value indicates that the algorithm cannot be trusted. The main reason for this is that the performance of the STARFM algorithm at the Dashalong site was much worse than the other sites, lowering the overall level. In addition, for Aqua data, the overall performance of STARFM was at a relatively good level. The R\({}^{2}\), RMSE, and NSE were 0.79, 8.34 K, and 0.68, respectively. Compared with the other sites, the gap was not big for the Dashalong site, but it was also at the lowest level. This is mainly because the STARFM algorithm \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{3}{*}{**Satellite**} & \multirow{3}{*}{**Site**} & \multirow{3}{*}{**Statistics**} & \multicolumn{4}{c}{**Methods**} \\ \cline{3-6}  & & & **Fitting (NDVD)** &
\begin{tabular}{c} **Linear** \\ **Temporal** \\ **Interpolation** \\ \end{tabular} & **HANTS** & **SG** \\ \hline \multirow{6}{*}{Arou} & R\({}^{2}\) & 0.44 & 0.61 & 0.62 & 0.62 \\  & RMSE & 10.38 & 7.21 & 6.84 & 6.85 \\  & NSE & 0.12 & 0.58 & 0.62 & 0.62 \\  & Pbias & \(-0.79\%\) & \(0.39\%\) & \(0.30\%\) & \(0.27\%\) \\ \hline \multirow{6}{*}{Daman} & R\({}^{2}\) & 0.66 & 0.78 & 0.69 & 0.68 \\  & RMSE & 8.28 & 6.1 & 7.16 & 7.22 \\  & NSE & 0.56 & 0.76 & 0.66 & 0.65 \\  & Pbias & \(-0.67\%\) & \(-0.38\%\) & \(-0.64\%\) & \(-0.66\%\) \\ \hline \multirow{6}{*}{Dashalong} & R\({}^{2}\) & 0.46 & 0.71 & 0.52 & 0.52 \\  & RMSE & 9.66 & 6.45 & 7.92 & 7.95 \\  & NSE & 0.33 & 0.70 & 0.52 & 0.52 \\  & Pbias & \(-0.87\%\) & \(0.21\%\) & \(-0.34\%\) & \(-0.37\%\) \\ \hline \multirow{6}{*}{Aqua} & R\({}^{2}\) & 0.72 & 0.79 & 0.67 & 0.66 \\  & RMSE & 8.61 & 7.36 & 9.20 & 9.21 \\  & NSE & 0.71 & 0.79 & 0.66 & 0.66 \\  & Pbias & \(-0.21\%\) & \(-0.18\%\) & \(-0.54\%\) & \(-0.58\%\) \\ \hline \multirow{6}{*}{Aqua} & R\({}^{2}\) & 0.88 & 0.87 & 0.86 & 0.86 \\  & RMSE & 8.31 & 9.18 & 9.73 & 9.74 \\  & NSE & 0.74 & 0.69 & 0.66 & 0.66 \\  & Pbias & \(-1.81\%\) & \(-2.14\%\) & \(-2.38\%\) & \(-2.45\%\) \\ \hline \multirow{6}{*}{Sidaoqiao} & R\({}^{2}\) & 0.86 & 0.90 & 0.88 & 0.87 \\  & RMSE & 7.05 & 5.90 & 6.44 & 6.46 \\  & NSE & 0.78 & 0.85 & 0.82 & 0.82 \\  & Pbias & \(-1.29\%\) & \(-1.00\%\) & \(-1.13\%\) & \(-1.19\%\) \\ \hline \multirow{6}{*}{Yakou} & R\({}^{2}\) & 0.24 & 0.69 & 0.71 & 0.70 \\  & RMSE & 19.91 & 7.23 & 7.61 & 7.62 \\  & NSE & \(-2.79\) & 0.5 & 0.48 & 0.48 \\  & Pbias & \(-5.22\%\) & \(-1.52\%\) & \(-1.80\%\) & \(-1.81\%\) \\ \hline \multirow{6}{*}{Zhangye} & R\({}^{2}\) & 0.75 & 0.79 & 0.71 & 0.71 \\  & RMSE & 8.12 & 7.00 & 8.13 & 8.12 \\  & NSE & 0.52 & 0.64 & 0.50 & 0.50 \\  & Pbias & \(-1.61\%\) & \(-1.41\%\) & \(-1.73\%\) & \(-1.78\%\) \\ \hline \multirow{6}{*}{Overall} & R\({}^{2}\) & 0.64 & 0.82 & 0.76 & 0.76 \\  & RMSE & 10.63 & 7.13 & 7.97 & 7.98 \\ \cline{1-1}  & NSE & 0.51 & 0.78 & 0.71 & 0.71 \\ \cline{1-1}  & Pbias & \(-1.50\%\) & \(-0.76\%\) & \(-1.03\%\) & \(-1.07\%\) \\ \hline \hline \end{tabular}
\end{table} 
Table 3: The general performance results of reconstructed LST using temporal and spatial methods based on Aqua data from 2016 to 2019.  
cannot take into consideration the influence of elevation. The altitude of the Dashalong site is 3739 m. The altitudes of the Arou site and the Yakou site also reach 3033 m and 4148 m, respectively. However, the altitude of the other sites is only about 1500 m or even lower. Therefore, the performance at these three high-altitude sites was not as good as that at other sites. For other methods, the influence of elevation is also a factor. Figure 5 presents a comparison between the reconstructed LST obtained using Terra and Aqua data with the ground measurements.