## 3 Results
### NDVI Intercomparison
NDVIg has a similar spatial pattern except for lower slopes (less than 0.5) in parts of the Mexican Plateau, southern Texas and the southeastern US There is a  
Figure 1: Scatterplot matrix for the NDVI of all 10-day periods from 2001 to 2008 for nine selected point locations spanning multiple climate and vegetation regimes (see Section 3.2 for locations), comparing each combination of six datasets (NDVIg, NDVIg, VIP, STAR, Terra, SPOT). Linear least square regression equation and correlation coefficient (r) are in the top-left corner of each panel. smaller area of slopes greater than 2 or less than 0.5 from SPOT and VIP than from NDVIg or NDVIg indicating that the relationship of SPOT and VIP with Terra is more uniform in space than Terra's relationship with NDVIg and NDVIg. Additionally, over most of the area, the slope of the relationship between STAR and Terra is less than 1. There are also significant temporal changes in the relationship between products. Figure 3 shows that the spatial correlations for NDVI (blue) remain above 0.85 over all times among all products and above 0.95 among VIP, SPOT, and Terra. The correlations between STAR and all other products are the lowest, and they also show a negative trend with time. The reasons for these trends are unknown at present and need to be explored in the future. Also, there are seasonal variations in correlations (not-shown) that generally show a late spring-summer maximum and a late fall-winter minimum. Figure 4 shows how the spatial regression slopes in NDVI changed from 1982 to 2008 between the four long-term datasets. NDVIg and NDVIg have a fairly stable relationship through time, because they are different versions of the product from the same group. VIP shows strong interannual changes in the regression slopes with both NDVIg and NDVI3g. The strongest changes coincide with a change from using AVHRR data to using MODIS data in the year 2000. Between 2001 and 2008 the  
Figure 2: Spatial plot of (**Left**) pixel-to-pixel temporal correlation coefficients and (**Right**) regression slopes of the NDVI of five datasets in each row (ordinate) compared to Terra (abscissa) for all 10-day periods from 2001 to 2008.  
relationship between VIP and NDVIg and NDVI3g is virtually the same as the relationship between Terra and NDVIg and NDVI3g (shown by green line) which is evidence of the strong relationship between VIP and MODIS. Also, consistent with Figures 1 and 2, STAR has very low regression slopes with the other 3 datasets. The interannual mean and range of \(N_{p,max}\) is explored in Table 2. Also, the mean and range of the maximum annual green vegetation fraction (MGVF) is shown and will be discussed in Section 3.3. The highest means of \(N_{p,max}\) are seen in the deciduous broadleaf forest, evergreen broadleaf forest, mixed forest, woody savannah and mixed cropland vegetation areas. The lowest \(N_{p,max}\) are seen in the barren and open shrubland classes. There are significant \(N_{p,max}\) differences between datasets in magnitude with the highest (or lowest) \(N_{p,max}\) values from NDVI3g (or STAR) on average. The interannual ranges of \(N_{p,max}\) for most classes vary between 0.02 and 0.04 with noticeably higher ranges for SPOT \(N_{p,max}\) in most classes. The largest interannual variations are seen in open and closed shrublands, barren areas and savannah. Also, grasslands and wetlands have moderate to high ranges. NDVI3g has both the lowest interannual range for all land pixels as well as lower ranges for most land cover classes. Furthermore, NDVI3g has better calibration and inter-sensor alignment than NDVIg and this is likely one of the reasons for the lower interannual variability [59]. Figure 3: Matrix of plots showing the time-series of the spatial correlation coefficients (R) of NDVI (blue) and green vegetation fraction (GVF) (red) for each 10 day period annually averaged from 2003 to 2008 comparing each combination of six datasets to each other.