Vegetation indices are among the most widely used satellite data products providing key measurements of vegetation canopy variables and biophysical processes. There are currently two vegetation index (VI) products generated with data from both Terra and Aqua MODIS instruments, the NDVI and the EVI. Recent cross-sensor studies have shown the potential to fuse NDVI measurements from MODIS and other sensors with the existing 25 year AVHRR data record at coarse resolutions, while the recent availability of continuous flux tower measures of photosynthesis now provides opportunities for testing and evaluating the performance of VIs at short- and seasonal time scales. Comparisons of flux tower data with satellite measures of greenness have shown the EVI to accurately depict vegetation growth and seasonality across a wide range of tropical and temperate ecosystems An accurate depiction of seasonal vegetation dynamics is a desired prerequisite for ecosystem models and provides confidence in model capabilities to predict longer term, inter-annual vegetation responses to climate variability. We propose to extend the advanced capabilities of the Terra and Aqua MODIS VI data record into the NPOESS Preparatory Project (NPP) at moderate resolution and evaluate VI measurement suitability as Earth System and Climate Data Records (ESDR/ CDR) through in-situ coupling with flux tower data under a wide array of climate and vegetation conditions.
We aim to adapt MODIS algorithms in support of the production of a consistent and long-term VI- data record as a unified and coherent set of observations of photosynthetic potential (greenness). Specifically, we aim to (1) assess key determinants in the translation and extension of MODIS VI products across current sensor systems and to the NPOESS (VIIRS) era; (2) evaluate data fusion of satellite VI time series with in-situ flux tower time series measurements of photosynthesis and in-situ tower-based measures of broadband/albedo VIs; (3) investigate continuity of the EVI with 2- and 3-band sensors, including the AVHRR; (4) assess seasonal and inter-annual sensitivities and uncertainties in VI measurements for climate variability signal detection; and (5) test and evaluate the consistency of the cross-sensor VI data records with output comparisons from ecosystem models. The assessment of vegetation condition, cover, processes, and changes are major components of national and international global change research programs and are topics of considerable societal relevance. Our proposal contributes directly to several Earth Science Strategic Research questions, including how are global ecosystems changing?
