## 1 Introduction  
Biophysical parameters retrieved from Earth observation data are crucial for improving our understanding of biosphere-atmosphere interactions (e.g., [1]). Spectral vegetation indices (VIs) derived from remotely sensed data have been used successfully to estimate biophysical parameters, for example, the fraction of photosynthetically active radiation (FAPAR), leaf area index (LAI) [2], and green vegetation fraction [3]. The normalized difference vegetation index (NDVI) has been the most widely used index. The NDVI has been found to be highly correlated with the biophysical properties of vegetation canopies and able to reduce the effects of topographic shading and shadowing for seasonal trend analyses of terrestrial vegetation [4] and global carbon cycle modeling [5]. However, the NDVI is affected by other factors such as soil background brightness and aerosol contamination [6]. The enhanced vegetation index (EVI), developed for Moderate Resolution Imaging Spectroradiometer (MODIS) of the National Aeronautics and Space Administration's (NASA) Earth Observing System (EOS), was designed to optimize the vegetation signal with improved sensitivity in high biomass regions and improved vegetation monitoring through a decoupling of the canopy background signal and a reduction in atmospheric aerosol influences that affect the NDVI [7]:  
\[\text{EVI}=G\frac{\rho_{n}-\rho_{r}}{\rho_{n}+C_{1}\rho_{r}-C_{2}\rho_{b}+L} \tag{1}\]  
where \(\rho\) are the total- or partial (uncorrected for aerosols)-atmosphere corrected reflectances, subscripts \"\(n\)\", \"\(r\)\", and \"\(b\)\" represent the near-infrared (NIR), red, and blue bands, respectively, \(L\) is the canopy background brightness adjustment factor, and \(C_{1}\) and \(C_{2}\) are the coefficients of the aerosol resistance term. The coefficients adopted in the MODIS EVI algorithm are: \(L=1.0\), \(C_{1}=6.0\), \(C_{2}=7.5\), and \(G\) (gain factor) = 2.5 [8]. MODIS was designed to be highly calibrated and to have explicit atmospheric corrections and, thereby, EVI has been used in a wide range of applications including ecosystem resilience studies [9], an estimation of gross primary production (GPP) [10], and evapotranspiration estimates [11]. The Visible Infrared Imaging Radiometer Suite (VIIRS) sensor onboard Suomi-National Polar-orbiting Partnership (S-NPP) has begun to collect data, which is slated to replace the Advanced Very-High Resolution Radiometer (AVHRR) onboard the National Oceanic and Atmospheric Administration (NOAA) polar-orbiting satellite series with afternoon overpass, and to continue the MODIS highly calibrated data stream. The VIIRS geophysical product, termed environmental data records (EDRs), includes the top-of-atmosphere (TOA) NDVI and top-of-canopy (TOC) EVI [12]. VI continuity/compatibility across AVHRR, MODIS, and VIIRS is of great importance for understanding spatial and temporal dynamics of global vegetation over several decades. Differences in sensor and platform characteristics, and product generation algorithms, however, cause systematic errors in VI time series across sensors. Spectral bandpasses are one major issue in using multi-sensor data [13] and, thus, this study was focused on inter-sensor spectral compatibility and calibration of the EVI between MODIS and VIIRS. Numerical experiments using Earth Observing-1 (EO-1) Hyperion data showed that VIIRS EVI was higher than MODIS EVI with the maximum differences reaching 0.040 EVI units over a tropical forest-savanna eco-gradient in Brazil [14] and the same trend was observed in a Hyperion-based bandpass simulation analysis conducted over AERONET sites in the conterminous United States [15]. An initial assessment of actual VIIRS EVI data was reported in [16]; an average (bias) of VIIRS EVI minus MODIS EVI (a gain factor G = 2.5) was zero when EVI was zero, but always positive for the rest of EVI dynamic range, indicating that VIIRS EVI was always higher than the MODIS counterpart.