# Validation Analysis of Drought Monitoring Based on FY-4 Satellite
## 3 Results
### Comparison with Other Satellites  
#### 3.3.1 Comparison with Earth Observation Satellites  
1. Comparison with MODIS  
Compared with the infrared (IR) and near-infrared (NIR) bands of FY-4A and MODIS (Figure 9), the band values of MODIS are slightly lower than those of FY-4A. The significantly positive correlation between the value of FY-4A and MODIS could be found in randomly 7 days of data (0.45 in NIR band pixels, 0.41 in IR band pixels, and 0.74 in NDVI pixels). Figure 8: Map of drought area difference: (**a**) Huanghuai region, (**b**) Yunnan Province, (**c**) Guangdong Province, (**d**) distribution of area difference among regions). Figure 9: The value of FY-4A and MODIS band: (**a**) NIR band; (**b**) IR band; (**c**) NDVI value. The high-value of NDVI pixels on FY-4A and MODIS are mainly distributed in the southwest of the Huanghuai region (Figure 10), which is consistent with the location of the woodland area (Figure 1a). The differences in NDVI between FY-4A and MODIS in the Huanghuai area (Figure 10c) are mainly concentrated in [\(-\)0.15, 0.15], accounting for 76.7%. The pixels with a difference less than \(-\)0.15 (7.7%) are more scattered, while those with a difference greater than 0.15 (15.6%) are mainly located in the high-value area of NDVI. The maps of different intensity drought identified by FY-4A TVDI, MODIS TVDI, and MCI on day 16 are shown in Figure 11. The severe drought of FY-4A TVDI is distributed in the north of the Huanghuai region, consistent with MCI, while those of MODIS TVDI are scattered in Shandong and Henan. In addition, the FY-4A TVDI has more valid pixels compared to the MODIS TVDI, with 14,149 pixels and 13,712 pixels, respectively. The proportion of severe drought is 60.32%, 19.62%, and 54.08% for FY-4A TVDI, MODIS TVDI, and MCI, respectively. The severe drought areas identified by FY-4A TVDI are similar to that of MCI (Figure 11). It can be attributed to the fact that FY-4A is a geostationary meteorological satellite with a higher observation frequency (every 30 min to 10 min over the full disk of the Asia-Oceania region), while MODIS is an earth observation satellite with 1-2 days observation frequency. As a result, FY-4A can provide more comprehensive and frequent monitoring of drought conditions. within a single day, a comparison was conducted using the available data for that region during a week to calculate TVDI. Except for 21 May, the spatial distribution of FY-4A and Landsat-8 was consistent in the remaining three days. The statistical results of bands, products, and TVDI among the three satellites are shown in Tables 2 and 3. The root mean square error (RMSE) for MODIS TVDI, Landsat-8 TVDI, and FY-4A TVDI are 0.26 and 0.13, respectively. The standard deviations of TVDI for MODIS, Landsat, and FY-4A are 0.15, 0.35, and 0.26, with value ranges of [0.13-0.97], [0.08, 0.93], and [0.02, 0.98], respectively. The computation time required for calculating TVDI over the entire Huanghuai region, FY-4A, MODIS, and Landsat-8 take 3.15 min, 5.56 min, and 17.31 min, respectively. FY-4A, MODIS, and Landsat-8 acquire images in the Huanghuai region at a frequency of 165 scenes per day, 2 scenes every 2 days, and 35 scenes every 16 days, respectively (Table 3). Moreover, FY-4A exhibits a wider NIR (0.15) and IR (0.2) band compared to the other two datasets (Table 2). \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Datasets** & **Band (Products)** & **Temporal Resolution** & **Spatial Resolution** & **Wavelength Band (\(\upmu\)m)** \\ \hline \multirow{3}{*}{MODIS} & Red & 1, 8, 16 days & 250 m & 0.620–0.670 \\  & NIR & 250 m & 0.841–0.876 \\  & LST & 8 days & 1000 m & - \\  & Red & & 30 m & 0.64–0.67 \\ Landsat-8 & NIR & 16 days & 30 m & 0.85–0.88 \\  & TIRS 1 & & 30 m & 10.6–11.19 \\  & Red & & 500 m & 0.55–0.75 \\ FY-4A & NIR & 15 min & 1000 m & 0.75–0.90 \\  & LST & & 4000 m & - \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Summary of the bands and products for FY-4A, MODIS, and Landsat-8.