A Non-Stationary 1981–2012 AVHRR NDVI3g Time Series

Remote Sensing

Jorge E. Pinzon¹ 

[1] Science Systems and Applications Inc., Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Code 618, Greenbelt, MD 20771, USA

关键词: Advanced Very High Resolution Radiometer (AVHRR);    Normalized Difference Vegetation Index (NDVI);    Bayesian analysis;    uncertainty;    bias;    climate variability;    non-stationary;   

DOI  :  10.3390/rs6086929

来源: mdpi

【 摘 要 】

The NDVI_3g time series is an improved 8-km normalized difference vegetation index (NDVI) data set produced from Advanced Very High Resolution Radiometer (AVHRR) instruments that extends from 1981 to the present. The AVHRR instruments have flown or are flying on fourteen polar-orbiting meteorological satellites operated by the National Oceanic and Atmospheric Administration (NOAA) and are currently flying on two European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) polar-orbiting meteorological satellites, MetOp-A and MetOp-B. This long AVHRR record is comprised of data from two different sensors: the AVHRR/2 instrument that spans July 1981 to November 2000 and the AVHRR/3 instrument that continues these measurements from November 2000 to the present. The main difficulty in processing AVHRR NDVI data is to properly deal with limitations of the AVHRR instruments. Complicating among-instrument AVHRR inter-calibration of channels one and two is the dual gain introduced in late 2000 on the AVHRR/3 instruments for both these channels. We have processed NDVI data derived from the Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) from 1997 to 2010 to overcome among-instrument AVHRR calibration difficulties. We use Bayesian methods with high quality well-calibrated SeaWiFS NDVI data for deriving AVHRR NDVI calibration parameters. Evaluation of the uncertainties of our resulting NDVI values gives an error of ± 0.005 NDVI units for our 1981 to present data set that is independent of time within our AVHRR NDVI continuum and has resulted in a non-stationary climate data set.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland