## 4 Combining ground data and VIs to scale biophysical processes over large areas
### Examples of VIs and Flux Tower Data to Estimate ET  
Remote sensing approaches to estimating ET have historically used measurements of land surface temperature (LST) from Thermal Infrared (TIR) sensors as the key satellite measurement [6, 38, 39, 40, 43, 44]. These methods were developed starting in the 1970s and continue to dominate ET studies today. They typically use the difference between air temperature (measured on the ground) and LST (measured by satellites) to estimate sensible heat flux from the land surface. Then they obtain estimates of R\({}_{\rm n}\) and G from ground or remote sensing data (typically from VIs) and compute ET, expressed as the latent heat of evaporation, as a residual in the surface energy balance (Equation 4). These methods present a number of difficulties due in part to the lack of 1:1 correspondence between the LST measured by satellite and the so-called \"aerodynamic surface temperature\" required to calculate H [6, 38], and a number of methods have been devised to surmount this problem using context within the imagery, e.g. [38, 39, 44, 75]. Recent studies have combined flux tower measurements of ET with time-series VIs to accurately scale ET over larger landscape units without the use of LST. They take advantage of the strong correlation between ET and VIs observed in numerous studies. Table 1 gives correlation coefficients between ET and MODIS EVI or NDVI at 11 tower sites in the southwestern U.S. The sites included nine riparian sites with different types of vegetation [34], plus one upland shrub site and one upland grass site [76]. Towers included both BREB and EC types. ET values from towers were compiled in 16-day intervals over multiple years and correlated with 16-day composite MODIS VI values. The correlation analysis used the single MODIS pixel encompassing the tower location at each site. EVI was strongly correlated with ET at all tower sites, and correlation coefficients were higher for EVI than NDVI at all sites. At the riparian sites, EVI combined with maximum daily air temperature (T\({}_{\rm a}\)) across all sites produced a simple model that predicted ET with r\({}^{2}\) = 0.79, leaving only 21% of the variance in ET unexplained. At the two semiarid upland sites, EVI plus precipitation produced a model with an r\({}^{2}\) = 0.76, even though the sites were only 20-25% vegetated. ET is dominated by T from vegetation even in dry ecosystems, and VIs (especially the EVI) clearly have great potential for scaling point measurements of ET over large areas. [PERSON] _et al_. [34] used the EVI-T\({}_{\rm a}\) relationship to produce tower-validated estimates of ET for the major vegetation types on western U.S. rivers and reported that the exotic species saltcedar, thought to be a heavy water user, actually had low to moderate rates of ET compared to native species. [PERSON] _et al_. [77] combined MODIS NDVI and surface meteorology data to estimate ET in two different Australian ecosystems, and reported r\({}^{2}\) = 0.74 between remote sensing and tower measurements, demonstrating the validity of the method over regional scales of measurement. [PERSON] _et al_. [78] used MODIS EVI and meteorological data to predict ET at the continental scale, and produced r\({}^{2}\) = 0.76 when estimates were compared to ET measured at 19 Ameriflux towers. They extended their model to the global scale, and concluded that MODIS EVI and ground meteorological data can be used to provide critical information on the regional and global water cycle resulting from environmental changes. [PERSON] _et al_. [79] combined MODIS EVI meteorological data in a Machine Learning Program to predict ET at 19 towers sites with r\({}^{2}\) = 0.75 for the under continuous U.S., and [PERSON] _et al_. [80] combined MODIS EVI, T\({}_{\rm a}\) and surface net radiation to predict ET in the Southern Great Plains of the U.S. with r\({}^{2}\) = 0.83 compared to flux tower values. The accuracy of the ET predictions in each case iswithin the error and uncertainty range inherent in the flux tower measurements of ET.