## 4 Combining ground data and VIs to scale biophysical processes over large areas
### Examples of Combining VIs and Flux Tower Data to Estimate Carbon Fluxes  
Measuring landscape-level carbon fluxes is essential in global change studies [e.g., 50]. Gross Primary Production (GPP) is defined as the amount of CO\({}_{2}\) fixed in photosynthesis, while Net Primary Production (NPP) is defined as GPP minus plant respiration [59]:  
\[\mathrm{NPP}=\mathrm{GPP}-(\mathrm{R}_{\mathrm{leaves}}+\mathrm{R}_{\mathrm{roots}}+\mathrm{R}_{\mathrm{ woody\ tissues}}) \tag{8}\]  
GPP can be estimated by satellite data based on the linear relationship between fPAR and VIs, for example NDVI:  
\[\mathrm{GPP}=\mathrm{LUE}\mathrm{\ x}\mathrm{\ fPAR}\mathrm{\ x}\mathrm{\ PAR}=\mathrm{ca.\ LU}\mathrm{\ x}\mathrm{\ NDVI}\mathrm{\ x}\mathrm{\ PAR} \tag{9}\]  
where LUE is Light Use Efficiency, the PAR conversion efficiency [59]. LUE values vary widely with vegetation type and environmental conditions. Currently, LUE and the respiration terms in (8) are estimated by modeling, using assumed values of parameters for broad biome types. For example, MODIS products include a combined, NDVI-based, LAI - fPAR term that is combined with meteorological variables and look-up tables of specific leaf area and respiration values for general biome types (evergreen needleleaf forest, deciduous broadleaf forest, shrubland, savanna, grassland, and cropland) to estimate GPP and NPP [59-61]. These models can be validated and improved by combining them with flux tower data [62-64]. Flux towers can estimate GPP and NPP separately by comparing daytime NPP with nighttime respiration and by other techniques, and LUE can also be calculated directly from canopy carbon fluxes divided by net radiation [50,51]. Time-series VIs and tower data have been successfully combined in a number of recent studies of ecosystem carbon exchange. [PERSON] et al. [65] showed that NDVI from AVHRR could be calibrated with BREB flux tower data to provide accurate 14-day estimates of daytime and nighttime carbon exchange from a sagebrush-steppe ecosystem in Idaho, and suggested that portable flux towers could be deployed to increase the spatial coverage of tower data. Using a hand-held radiometer in grazed and ungrazed prairie sites, [PERSON] and [PERSON] [25] found strong linear relationships between NDVI and carbon dioxide and moisture fluxes measured at towers, and strong but non-linear relationships between NDVI and LAI and standing biomass. They concluded that NDVI has the potential for predicting carbon and water fluxes in semiarid grasslands and shrublands. [PERSON] _et al._[66] found a consistent linear relationship between seasonal MODIS EVI and tower calibrated GPP in intact rainforests and rainforest land converted to pasture and agriculture in the Amazon. In relation to tower measured GPP, the MODIS EVI did not saturate in such high biomass tropical rainforests. [PERSON] _et al._[67] used this relationship to show that, contrary to ecosystem models of the Amazon, the forests are greener in the dry season than in the wet season, and a period of drought in 2005 actually stimulated carbon fixation rather than inhibiting it. Plants used water stored in the soil profile to support growth, and took advantage of higher radiation levels in the dry periods. [PERSON] _et al._[68] extended these studies to three distinct Monsoon Asia tropical forests and found similar MODIS EVI and tower GPP linear relationships across the multiple sites, potentially offering promising opportunities for regional scaling of carbon fluxes across the heterogeneous canopies of Southeast Asia. [PERSON] _et al._[69] and [PERSON] _et al._[70] also found a strong relationship between tower GPP and MODIS EVI across a wide range of biome types and concluded that EVI can be used to estimate GPP directly, without direct consideration of LUE required in many SVAT models. This simplifies the estimation of GPP, as LUE is difficult to determine by direct measurement.