Vegetation indices (VIs) are widely used in long-term measurement studies of vegetation changes, including seasonal vegetation activity and interannual vegetation-climate interactions. There is much interest in developing cross-sensor/multi-mission vegetation products that can be extended to future sensors while maintaining continuity with present and past sensors. In this study we investigated multi-sensor spectral bandpass dependencies of the enhanced vegetation index (EVI), a 2-band EVI (EVI2), and the normalized difference vegetation index (NDVI) using spectrally convolved Earth Observing-1 (EO-1) Hyperion satellite images acquired over a range of vegetation conditions. Two types of analysis were carried out, including (1) empirical relationships among sensor reflectances and VIs and (2) decomposition of bandpass contributions to observed cross-sensor VI differences. VI differences were a function of cross-sensor bandpass disparities and the integrative manner in which bandpass differences in red, near-infrared (NIR), and blue reflectances combined to influence a VI. Disparities in blue bandpasses were the primary cause of EVI differences between the Moderate Resolution Imaging Spectroradiometer (MODIS) and other course resolution sensors, including the upcoming Visible Infrared Imager / Radiometer Suite (VIIRS). The highest compatibility was between VIIRS and MODIS EVI2 while AVHRR NDVI and EVI2 were the least compatible to MODIS.
The enhanced vegetation index (EVI) has been found useful in improving linearity with biophysical vegetation
properties and in reducing saturation effects found in densely vegetated surfaces, commonly encountered in the
normalized difference vegetation index (NDVI). However, EVI requires a blue band and is sensitive to variations in blue
band reflectance, which limits consistency of EVI across different sensors. The objectives of this study are to develop a
2-band EVI (EVI2) without a blue band that has the best similarity with the 3-band EVI, and to investigate the crosssensor
continuity of the EVI2 from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Very
High Resolution Radiometer (AVHRR). A linearity-adjustment factor (β) was introduced and coupled with the soil
adjustment factor (L) used in the soil-adjusted vegetation index (SAVI) in the development of the EVI2 equation. The
similarity between EVI and EVI2 was validated at the global scale. After a linear adjustment, the AVHRR EVI2 was
found to be comparable with the MODIS EVI2. The good agreement between the AVHRR and MODIS EVI2 suggests
the possibility of extending the current MODIS EVI time series to the historical AVHRR data, providing another longterm
vegetation record different from the NDVI counterpart.
Current earth observing satellite sensors have different temporal, spectral and spatial characteristics that present
problems in the establishment of long term, time series data records. Vegetation indices (VI's) are commonly used in
deriving long term measures of vegetation biophysical properties, which have been shown useful in interannual climate
studies and phenology studies. While significant improvements have been made with new sensors, and algorithms, and
processing methods, backward compatibility of VI's is desired so that the long term record can extend back and utilize
the AVHRR record to 1981. Conversely, any reprocessing of the AVHRR record should consider steps to allow forward
compatibility with newer sensors and products. In this study we evaluated the use of sensor-specific enhanced vegetation
index (EVI) and normalized difference vegetation index (NDVI) data sets, using a time sequence of Hyperion images
over Tapajos National Forest in Brazil over the 2001 and 2002 dry seasons. We computed NDVI, EVI, and a 2-band
version of EVI (EVI2) for different sensor systems (AVHRR, MODIS, VIIRS, SPOT-VGT, and SeaWiFS) and
evaluated their differences and continuity in the characterization of tropical forest phenology. We also analyzed the
influence of different atmosphere correction scenarios to assess noise in the phenology signal. Our analyses show that
EVI2 maintains the desirable properties of increased sensitivity in high biomass forests across all sensor systems
evaluated in this study. We further conclude that EVI2 can be extended to the AVHRR time series record and
compliment that current NDVI time series record.
In red-NIR reflectance space, the Modified Soil Adjusted Vegetation Index (MSAVI) isolines, representing similar vegetation biophysical quantities, are neither convergent to a point nor parallel to each other. Consequently, the treatment of the MSAVI isolines is distinctly different from those of other vegetation index isolines, such as the normalized difference vegetation index (NDVI), the perpendicular vegetation index (PVI), and the soil-adjusted vegetation index (SAVI). In this study, the MSAVI isolines are shown to be the tangent lines of the parabola, (NIR-0.5)2+2Red=0, and the values of the MSAVI isolines are equal to the ordinates of their tangent points plus 0.5. These findings provide a graphic interpretation of the MSAVI and are useful in understanding the biophysical characteristics of the MSAVI. The MSAVI isolines are shown to better approximate field data and simulated vegetation biophysical isolines than the other 2-band vegetation index isolines. As the treatment of the MSAVI isolines can be depicted by the parabola curve, the MSAVI can be referred to as a parabola-based vegetation index.