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Proceedings Paper

Temporal influences on normalized difference vegetation index
Author(s): Yuanbo Liu; Yousuke Noumi
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Paper Abstract

Normalized difference vegetation index (NDVI) is defined as a ratio of the difference of the infrared and red bands to the sum of the two bands. It can be estimated directly from satellite data, and has been widely used in numerous environmental studies. Yet the satellite-based NDVI was criticized for its variations with temporal factors (e.g. sun-surface-satellite geometry, atmospheric variations). Such variations may result in false change of vegetation over surface. However, the uncertainties relevant to the false change are generally unquantified in the studies. It is therefore unclear to what extent the satellite-based NDVI would be reliable. In this study, we used a derived relationship between the digital number (DN) with and without temporal influences for the same area. Using the derived relationship, NDVI can be expressed as a function of atmospheric optical thickness (AOT), view angle, and DN without temporal influences. As a result, the uncertainties relevant to the temporal factors were quantified with a mathematical expression. We found that satellite-based NDVI was a function of AOT, day of year, latitude, and NDVI without temporal influences. We made simulations in the case of Landsat TM data. Simulations showed that atmospheric effect was most influential to a satellite-based NDVI, and the NDVI would suffer more serious influences at higher latitude than at lower latitude. In general, the temporal influences on NDVI cannot be ignored for a reliable monitoring of surface phenological processes.

Paper Details

Date Published: 30 October 2009
PDF: 8 pages
Proc. SPIE 7494, MIPPR 2009: Multispectral Image Acquisition and Processing, 74940Y (30 October 2009); doi: 10.1117/12.833221
Show Author Affiliations
Yuanbo Liu, Nanjing Institute of Geography and Limnology, CAS (China)
Okayama Univ. of Science (Japan)
Yousuke Noumi, Okayama Univ. of Science (Japan)


Published in SPIE Proceedings Vol. 7494:
MIPPR 2009: Multispectral Image Acquisition and Processing

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