Paper
27 September 2006 Investigation on functional form in cross-calibration of spectral vegetation index
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Abstract
Cross calibration of data products across generations of satellite program is indispensable to facilitate continuous data products by satellite observations. To investigate long term environmental change through vegetation monitoring, it is required to use data from different platforms, e.g., normalized difference vegetation index (NDVI) from NOAA-AVHRR series with the ones from TERRA- and AQUA-MODIS. In this context, cross calibration of spectral vegetation index (VI) is an important factor which determine the accuracy of such changes. In our previous work, we introduced a way of deriving analytical relationships between two vegetation indices based on an equation of vegetation isoline. The functional form of the relationships was found to be a ratio of polynomials. On the other hand, most of the studies that investigate relationships of NDVI products between two sensors simply assumed first- or second-order polynomial to describe the relationships of the two data products. In this paper, we discuss the relevancy of using higher-order polynomials by relating those coefficients implicitly to biophysical parameters, atmospheric properties, and soil optical properties. The order of polynomials sufficient to approximate the relationships is clarified from both analytical and numerical point of view by conducting numerical experiments in addition to analytical derivations.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hiroki Yoshioka, Tomoaki Miura, and Hirokazu Yamamoto "Investigation on functional form in cross-calibration of spectral vegetation index", Proc. SPIE 6298, Remote Sensing and Modeling of Ecosystems for Sustainability III, 629813 (27 September 2006); https://doi.org/10.1117/12.681564
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Cited by 4 scholarly publications.
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KEYWORDS
Vegetation

Sensors

Calibration

Atmospheric modeling

Satellites

Atmospheric physics

Earth observing sensors

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