Publications

Li, HW; Cao, Y; Xiao, JF; Yuan, ZQ; Hao, ZQ; Bai, XY; Wu, YP; Liu, Y (2024). A daily gap-free normalized difference vegetation index dataset from 1981 to 2023 in China. SCIENTIFIC DATA, 11(1), 527.

Abstract
Long-term, daily, and gap-free Normalized Difference Vegetation Index (NDVI) is of great significance for a better Earth system observation. However, gaps and contamination are quite severe in current daily NDVI datasets. This study developed a daily 0.05 degrees gap-free NDVI dataset from 1981-2023 in China by combining valid data identification and spatiotemporal sequence gap-filling techniques based on the National Oceanic and Atmospheric Administration daily NDVI dataset. The generated NDVI in more than 99.91% of the study area showed an absolute percent bias (|PB|) smaller than 1% compared with the original valid data, with an overall R 2 and root mean square error (RMSE) of 0.79 and 0.05, respectively. PB and RMSE between our dataset and the MODIS daily gap-filled NDVI dataset (MCD19A3CMG) during 2000 to 2023 are 7.54% and 0.1, respectively. PB between our dataset and three monthly NDVI datasets (i.e., GIMMS3g, MODIS MOD13C2, and SPOT/PROBA) are only -5.79%, 4.82%, and 2.66%, respectively. To the best of our knowledge, this is the first long-term daily gap-free NDVI in China by far.

DOI:
10.1038/s41597-024-03364-3

ISSN:
2052-4463