Validation of the MODIS NDVI Products in Different Land-Use Types Using In Situ Measurements in the Heihe River Basin

• Published in: IEEE geoscience and remote sensing letters Vol. 11; no. 9; pp. 1649 - 1653
• Main Authors: Geng, Liying, Ma, Mingguo, Yu, Wenping, Wang, Xufeng, Jia, Shuzhen
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.09.2014; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Agriculture; Correlation; Ground-based normalized difference vegetation index (NDVI); Meteorology; Moderate Resolution Imaging Spectroradiometer (MODIS); MODIS; Remote sensing; Satellites; Spatial resolution; validation; vegetation; Vegetation mapping; Ground-based normalized difference vegetation index (NDVI); remote sensing; vegetation; Moderate Resolution Imaging Spectroradiometer (MODIS); validation
• ISSN: 1545-598X; 1558-0571
• DOI: 10.1109/LGRS.2014.2314134

An evaluation of the Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) products is essential for their use in scientific studies. We evaluated the accuracy of MODIS NDVI data that were derived from the MOD09GQ and MYD09GQ products using ground-based measurements from nearly one complete growing season (from May 2 to September 28, 2013) for six land-use types in the upper and middle reaches of the Heihe River Basin. The spatial heterogeneity and scale effects of the NDVI were analyzed using TM8 images of the observation sites. A comparison of the field measurements showed that the MODIS NDVI data were correlated with the in situ data and had an R 2 of 0.60-0.98. The semivariance analysis results showed that scale effects were common for MODIS data at a pixel resolution of 250 m for corn, potato, rape, and barley crops. Upscaling the in situ NDVI data using high spatial resolution satellite images can improve the validation accuracy of pixel-level NDVI. The results from this letter provide ground-based NDVI data that are required for the calibration and validation of satellite observations and products.