Abstract
We developed a unique methodology that spectrally translates the enhanced vegetation index (EVI) across sensors for data continuity based on vegetation isoline equations and derived a moderate resolution imaging spectroradiometer (MODIS)-compatible EVI for the visible/infrared imager/radiometer suite (VIIRS) sensor. The derived equation had four coefficients that were a function of soil, canopy, and atmosphere, e.g., soil line slope, leaf area index (LAI), and aerosol optical thickness (AOT). The PROSAIL canopy reflectance and 6S atmospheric models were employed to numerically characterize the MODIS-compatible VIIRS EVI. MODIS-compatible VIIRS EVI values only differed from those of MODIS EVI by, at most, 0.002 EVI units, whereas VIIRS and MODIS EVI values differed by 0.018 EVI units. The derived coefficients were sensitive mainly to LAI and AOT for the full- and a partial-covered canopy, respectively. The MODIS-compatible EVI resulted in a reasonable level of accuracy when the coefficients were fixed at values found via optimization for model-simulated and actual sensor data (83 and 41% reduction in the root mean square error, respectively), demonstrating the potential practical utility of the derived equation. The developed methodology can be used to obtain a spectrally compatible EVI for any pair of sensors in the data continuity context.
Highlights
Spectral vegetation indices (VIs) have been used as proxies to such biophysical parameters as leaf area index (LAI), fraction of absorbed photosynthetically active radiation, and gross primary productivity (e.g., Ref. 1)
As a first practical application of the derived equations, we considered finding a single set of Ki values that minimizes differences between the moderate-resolution imaging spectroradiometer (MODIS)-compatible visible/infrared imager/radiometer suite (VIIRS) enhanced vegetation index (EVI) and the MODIS EVI via regression and determines whether that single set of Ki values could provide a reasonable level of compatibility
A cross-sensor spectral transformation equation for the three-band EVI was derived based on vegetation isoline equations, aimed at intersensor EVI continuity/compatibility between MODIS and VIIRS
Summary
Spectral vegetation indices (VIs) have been used as proxies to such biophysical parameters as leaf area index (LAI), fraction of absorbed photosynthetically active radiation, and gross primary productivity (e.g., Ref. 1). May degrade the enhanced capability of narrow bands by, for example, recontaminating the data with atmospheric water vapor.[36] Likewise, the methodology is only applicable to certain pairs of sensors Another set of studies derived cross-sensor spectral transformation equations analytically using vegetation isoline equations.[38,39] Vegetation isoline equations relate two spectral reflectances at two different wavelengths based on the radiative transfer through the atmosphere-canopy-soil system.[40] This isoline-based approach was used to translate MODIS red and NIR reflectances to the counterparts of Landsat-7 enhanced Thematic Mapper plus (ETM+) and NOAA-14 AVHRR, which resulted in >90% reductions in mean NDVI differences for those sensor pairs.[38] The approach was used to theoretically investigate intersensor relationships of two-band VIs,[39] including the NDVI, soil-adjusted vegetation index,[41] and two-band EVI (EVI2).[42] Yoshioka et al.[39] found that the two-band VI translation equation was a rational function of the source sensor VI where the coefficients of the equation were a function of soil, canopy, and atmosphere.
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