# Improving Spatial-Temporal Data Fusion by Choosing Optimal Input Image Pairs
## 4 Results and Analysis
### Effect of Data Sources  
Figure 5 shows the averaged MAD (<MAD>) for NDVI from the entire year for different image combinations. The patterns for the red and NIR results are similar so they are not shown here. It can be seen that <MAD> varies with data sources and pair dates. In this section, we only analyze the effect of data sources. The effect of pair dates will be analyzed in Section 4.3. For site 1, only three groups of results are compared since only Landsat 8 images are used as pair images (Figure 5a). From Figure 5, we can see that the data fusion accuracies vary based on the combination of pair images, even when the pair image dates are the same. In our two study areas, image pairs from Aqua NBAR + L8 generally produce better prediction than the Terra NBAR + L8 combination. In site 2 (Figure 5b), <MAD> based on the pairs from Terra NBAR + L7 are lower than the other combinations. Similar to Figure 4, the <MAD> of the combined NBAR + Landsat is generally between that of the combination of Terra/Aqua NBAR and Landsat. The differences of predictability from different pair image combinations can be partially explained by the inconsistency between Landsat and MODIS pair images (Section 4.1). Inconsistencies in reflectance between different sensors can be caused by many factors. One important factor is the variation in VZA for Terra and Aqua MODIS images over the study areas. Landsat sensors have a small field of view and are normally regarded as nadir viewing. MODIS data are collected over  
Figure 5: Temporally-averaged mean absolute difference (<MAD>) for different combinations of pair images from MODIS (Terra, Aqua, and combined NBAR) and Landsat ( Landsat 7 and 8) for site 1 (**a**) and site 2 (**b**). In site 1, <MAD> is calculated based on the predicted image from Landsat 8 (p28r31) in order to compare different pair combinations consistently. a large field of view and VZA varies from day to day. Although MODIS daily directional surface reflectance from Terra and Aqua has been corrected to daily NBAR and has the same spatial resolution, the pixel footprint area may be different due to the bowtie effect. In the areas studied here, the spatial detail in the image is degraded with increasing VZA. A larger VZA will cover a bigger footprint area and, thus, lead to lower effective spatial resolution and a blurred image [42]. The effect of neighboring pixels cannot be ignored, even though the image has been resampled into a grid with fixed resolution. Additionally, reflectances from larger VZAs are more difficult to adjust accurately to nadir view reflectance in a BRDF model. The mean VZA values for the Terra and Aqua MODIS images over our study areas on the Landsat overpass dates for different combinations of data sources throughout the year were calculated (Table 3). The mean VZAs of MODIS on the pair dates from the same Landsat-MODIS combination are similar. However, the different Landsat-MODIS combinations show large variability. Generally, the mean VZA of Terra + L7 is the smallest, while Terra + L8 shows the largest VZA among all these combinations. Since Terra and Landsat 7 are in the same sun-synchronous orbit, they have similar view and solar geometry and atmospheric and surface conditions [43]. This is the optimal situation for data fusion, with the two sensors flying in close formation. However, because Terra and Landsat 8 have an eight-day difference in nadir revisit, the Terra MODIS VZAs are always larger on the Landsat 8 overpass dates. For example, in site 2, the mean VZA of MODIS images varies from Terra + L7 (0.66 degree) to Terra + L8 (63.66 degree). The mean VZA of MODIS from the combinations of Aqua and Landsat are usually in the middle of these Terra values. This can explain why the prediction accuracy (<MAD>) based on the combination of Aqua + L7 is larger than that based on the combination of Terra + L7, as shown in Figure 5b.