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Effect of Orbital Drift and Sensor Changes on the Time Series of AVHRR Vegetation Index Data

Kaufmann R.K., Zhou L., Knyazikhin Y., Shabanov N.V., Myneni R.B., Tucker C.J.

// Transactions on Geoscience Remote Sensing, 2000. Vol. 38. No. 6. P. 2,584-2,597.

This  paper  assesses  the  effect  of  changes  in  solar zenith angle (SZA) and sensor changes on reflectances in channel 1, channel 2, and normalized difference vegetation index (NDVI) from  the  advanced  very  high  resolution  radiometer  (AVHRR) Pathfinder   land   data   set   for   the   period   July   1981   through September  1994. First,  the  effect  of  changes  in  SZA  on  channel reflectances  and  NDVI  is  derived  from  equations  of  radiative transfer  in  vegetation  media.  Starting  from  first  principles,  it is  rigorously  shown  that  the  NDVI  of  a  vegetated  surface  is  a function  of  the  maximum  positive  eigenvalue  of  the  radiative transfer  equation  within  the  framework  of  the  theory  used  and its  assumptions.  A  sensitivity  analysis  of  this  relation  indicates that  NDVI  is  minimally  sensitive  to  SZA   changes,  and  this sensitivity  decreases  as  leaf  area  increases.  Second,  statistical methods  are  used  to  analyze  the  relationship  between  SZA  and channel reflectances or NDVI. It is shown that the use of ordinary least  squares  can  generate  spurious  regressions  because  of  the nonstationary property of time series. To avoid such a confusion, we use the notion of cointegration to analyze the relation between SZA and AVHRR data. Results are consistent with the conclusion of theoretical analysis from equations of radiative transfer. NDVI is not related to SZA in a statistically significant manner except for biomes with relatively low leaf area. From the theoretical and empirical  analysis,  we  conclude  that  the  NDVI  data  generated from the AVHRR Pathfinder land data set are not contaminated by  trends  introduced  from  changes  in  solar  zenith  angle  due  to orbital decay and changes in satellites (NOAA-7, 9, 11). As such, the NDVI data can be used to analyze interannual variability of global vegetation activity.

Ссылка на текст: files/publications/schabanov/sza.pdf
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