# Improving Spatial-Temporal Data Fusion by Choosing Optimal Input Image Pairs
## 5 Discussion  
### Selection of Data Sources  
MODIS observations are subject to variations in view zenith angle. According to our results, the combinations of data sources with smaller VZA have the smaller RMSE and larger R between MODIS and Landsat (Figure 4) and produce the better predictions (Figure 5). Using six combinations of MODIS (Terra, Aqua, and combined) and Landsat (Landsat 7 and 8) images as data fusion sources, we find that daily MODIS observations with a smaller view zenith angle can produce better data fusion results. This can be taken as a rule to select appropriate MODIS image pairs. In fact, the VZAs of MODIS data on Landsat acquisition dates are basically similar for the same study area due to the same nadir revisit cycle (every 16 days). Therefore, pairs of Terra + L7 images usually work better as input to a fusion system than the other combinations, because both sensors are flying in formation and are viewing near-nadir on Landsat overpass dates. However, Landsat 7 has been suffering the failure of the SLC since May 2003. The combination of Terra + L7 is not very effective for data fusion especially at the edge of the Landsat scene. A remedy is to gap-fill the Landsat 7 ETM+ images before data fusion. Several gap filling methods have been developed in the past, such as the histogram matching approach, the Neighborhood Similar Pixel Interpolator (NSPI) and the Geostatistical Neighborhood Similar Pixel Interpolator (GNSPI) approach [35; 44; 45]. More efforts are needed to evaluate the usability of the gap-filled Landsat data. Other medium-resolution data, such as the Sentinel-2 Multispectral Instrument (MSI), with similar spectral bands to Landsat and MODIS, may be used as a data source to improve spatial-temporal data fusion. For the Aqua + L8 combination, Aqua images are acquired around 1:30 P.M. local time and Landsat 8 are often acquired at ca. 11 A.M. Even though VZAs of Aqua MODIS are normally smaller at Landsat 8 overpass time than Terra MODIS, the different atmospheric conditions in the morning and afternoon may also introduce inconsistency. The Collection 6 MODIS daily NBAR product is now available. It is generated using all clear sky directional reflectances over a 16-day period from both Aqua and Terra. Therefore, the combined NBAR product usually has more valid data than the contemporaneous daily Terra and Aqua MODIS image. The data quality of the Collection 6 NBAR product has been improved because more data are now used in inversion than in Collection 5, especially in the higher latitudes with high revisit frequency [27]. The mean RMSE and R for the combined NBAR used in data fusion are slightly lower than for our best combination of Terra/Aqua and Landsat. One reason is that the spatial resolution of the NBAR product (500 m) is lower than our in-house Terra and Aqua daily NBAR (250 m) in the red and NIR bands. It is reasonable to try Terra or Aqua MODIS with small VZA in data fusion first. If Aqua or Terra MODIS at 250 m resolution with small VZA is not available, or daily Terra/Aqua MODIS NBAR cannot be produced in-house, the Collection 6 MODIS daily NBAR product would be a good choice for data fusion. In this study, we pay more attention to the solar-viewing characteristics of MODIS, while directional reflectance effects in Landsat data are ignored due to the narrow field of view (15\({}^{\circ}\)) and the small view zenith angle (\(\leq\)7.5\({}^{\circ}\)). [PERSON] et al. found that the variations of solar-viewing geometry over the year can cause apparent changes in reflectance even if the surface properties remain constant [25]. Therefore, they developed a general approach to producing Landsat NBAR for a nadir view and fixed solar zenith geometry. In the future, the Landsat NBAR data can be used instead of Landsat directional reflectance in data fusion experiments, which may improve the consistency of Landsat and MODIS NBAR images.