A Reference Global Vegetation Index Annual Dynamic Profile
Kamel
Didan, The University of Arizona, didan@email.arizona.edu
(Presenting)
Armando
Barreto, The University of Arizona, abarreto@email.arizona.edu
Jing
Li, The University of Arizona, jinglich@email.arizona.edu
Vegetation indices are by far one of the most successful and widely used remote sensing measures of the land surface vegetation conditions. And although, vegetation indices are not explicit biophysical parameters, they are extensively used as proxies for many canopy state variables (leaf area index, fraction of absorbed photosynthetically-active radiation, chlorophyll content, canopy structure) and canopy biophysical processes (photosynthesis, transpiration, net primary production). To that end vegetation indices capture a composite property of the canopy and are unmatched with their abilities to efficiently capture the canopy dynamic behavior over space and time. Thus, a vegetation index is a perfect tool for effective characterization of ecosystem states and processes for long term climate change and near real time operation applications.
Vegetation indices are a key Earth Science Data Record (ESDR), also known as a Climate Data Record (CDR) or an Essential Climate Variable (ECV). The Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) are the most widely adopted indices. Combined NDVI and EVI span more than three decades of consistent measurements (from NOAA AVHRR and NASA MODIS) and continue to contribute significantly to understanding the Earth System functioning and change.
However, to accurately study change using Vegetation Index data a precise and consistent reference record is highly required. Change could then be measured against this reference record and accurately ascribed to disturbances and climate drivers. In this study we designed a methodology to generate such a reference record using the MODIS vegetation index 10-year data record. Both NDVI and EVI reference records were generated at an 8 day interval and different spatial resolutions (250m, 1km, and 5.6km). These records are projected to be particularly useful for annual and inter annual change studies, for long term trend analysis, and ready for integration into phenological, biogeochemical and global climate models.
Presentation Type: Poster
Poster Session: Data Records and Systems
NASA TE Funded Awards Represented:
NONE: Related Activity or Previously Funded TE Award