The use of normalized difference vegetation index (NDVI) data acquired with multiple satellite sensors has become a necessity in research fields such as agriculture, land-use and land-cover change and changes in the natural environment, where fast changes are taking place. A good understanding of these changes is a strong requirement of long-time-series monitoring programmes. In this paper, VEGETATION 10-day composite (VGT-S10) NDVI data with a 1 × 1 km resolution, covering the period from April 1998 to December 2006 and Advanced Very High Resolution Radiometer (AVHRR) Global Inventory Modeling and Mapping Studies (GIMMS) NDVI data with a 8 × 8 km resolution, covering the period form April 1998 to December 2003 are used. The differences between the datasets were analysed to enable an unbiased comparison between the two datasets and to enable the description of the characteristics of non-system related differences between the NDVI values acquired from the VGT and AVHRR sensors. A correlation analysis was applied to validate a linear relationship between the two types of NDVI products. This study led us to conclude that most of the Chinese land surfaces elicit good linearity between the VGT and GIMMS NDVI values. It also indicated that the correlations partly depend on vegetation density. A pixel-based one-dimensional linear regression was used to describe the relationship between the two datasets. Significance testing demonstrates that the model is valid for most land-cover types occurring in China. Finally, the VGT NDVI covering the period from 2003 to 2006 is converted to the GIMMS NDVI for the same period. A comparison of the trends calculated with the VGT NDVI and the GIMMS NDVI from the period 1998 to 2006 demonstrates the validity of the regression model when evaluated in detail.
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Document Type: Research Article
Cold and Arid Regions Environmental and Engineering Research Institute (CAREERI), Chinese Academy of Sciences, Lanzhou, China
Flemish Institute for Technological Research (VITO), Boeretang 200, Mol, Belgium
Publication date: 2010-03-01
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