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Proceedings Paper

A MODIS-based vegetation index climatology
Author(s): R. Bindlish; T. Jackson; T. Zhao
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Paper Abstract

Passive microwave soil moisture algorithms must account for vegetation attenuation of the signal in the retrieval process. One approach to accounting for vegetation is to use vegetation indices such as the Normalized Difference Vegetation Index (NDVI) to estimate the vegetation optical depth. The passive microwave sensor platforms typically do not include sensors for providing this information and the data must be acquired independently. This presents challenges to data processing and integration and concerns about data availability. As an alternative to routine updating of the NDVI, it is possible to use a global vegetation index climatology. This climatology is based on the long term set of observations from the MODIS instrument (10 years). A technique was developed to process the NASA NDVI and Enhanced Vegetation Index (EVI) data base to produce a 10-day annual cycle (climatology) for each 1 km pixel covering the Earth's land surface. Since our focus was on soil moisture, the classification rules and flags took this into consideration. Techniques developed for processing the indices, development of flags, and expected utilization in soil moisture retrieval algorithms are described.

Paper Details

Date Published: 16 September 2011
PDF: 8 pages
Proc. SPIE 8156, Remote Sensing and Modeling of Ecosystems for Sustainability VIII, 815603 (16 September 2011); doi: 10.1117/12.890311
Show Author Affiliations
R. Bindlish, USDA ARS Hydrology and Remote Sensing Lab. (United States)
T. Jackson, USDA ARS Hydrology and Remote Sensing Lab. (United States)
T. Zhao, USDA ARS Hydrology and Remote Sensing Lab. (United States)
Beijing Normal Univ. (China)


Published in SPIE Proceedings Vol. 8156:
Remote Sensing and Modeling of Ecosystems for Sustainability VIII
Wei Gao; Thomas J. Jackson; Jinnian Wang; Ni-Bin Chang, Editor(s)

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