18 Jun 2021

18 Jun 2021

Review status: this preprint is currently under review for the journal ESSD.

Fusing MODIS and AVHRR products to generate a global 1-km continuous NDVI time series covering four decades

Xiaobin Guan1,2, Huanfeng Shen1,3, Yuchen Wang1, Dong Chu1, Xinghua Li4, Linwei Yue5, Xinxin Liu6, and Liangpei Zhang3,7 Xiaobin Guan et al.
  • 1School of Resource and Environmental Sciences, Wuhan University, Wuhan, 430079, PR China
  • 2Department of Geography and Planning, University of Toronto, Toronto M5S3G3, Canada
  • 3Collaborative Innovation Centre of Geospatial Technology, Wuhan 430079, PR China
  • 4School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, PR China
  • 5School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, PR China
  • 6College of Electrical and Information Engineering, Hunan University, Changsha 410205, PR China
  • 7The State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, PR China

Abstract. Satellite normalized difference vegetation index (NDVI) time-series data are an essential data source for numerous ecological and environmental applications. Although various long-term global NDVI products have been produced with different characteristics over the past decades, there is still an apparent trade-off between the spatiotemporal resolution and time coverage. The Advanced Very High-Resolution Radiometer (AVHRR) instrument can provide the only continuous time series with the longest time coverage since the early 1980s, but with the drawback of a coarse spatial resolution and poor data quality compared to the observations of later instruments. To address this issue, a spatio-temporal fusion-based long-term NDVI product (STFLNDVI) since 1982 was generated in this study, with a 1-km spatial resolution and a monthly temporal resolution. A multi-step processing fusion framework was employed to combine the superior characteristics of Moderate Resolution Imaging Spectroradiometer (MODIS) and AVHRR products, respectively. Simulated and real-data assessments both confirm the ideal accuracy of the fusion result with regard to the spatial distribution and temporal variation. Only a few relatively unsatisfactory results are found due to the poor relationship between the original AVHRR and MODIS data. The evaluations also show that the proposed fusion framework can obtain stable results similar to MODIS data in different years and seasons, even when the temporal distance between the fusion data and the reference data is large. We believe that the STFLNDVI product will be of great significance to characterize the spatial patterns and long-term variations of global vegetation. The NDVI product is available at DOI: (Guan et al., 2021).

Xiaobin Guan et al.

Status: open (until 13 Aug 2021)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2021-156', Anonymous Referee #1, 01 Jul 2021 reply
  • RC2: 'Comment on essd-2021-156', Anonymous Referee #2, 21 Jul 2021 reply

Xiaobin Guan et al.

Data sets

STFLNDVI: A long-term 1km NDVI time series since 1982 by fusing MODIS and AVHRR products Xiaobin Guan, Huanfeng Shen, Yuchen Wang, Dong Chu, Xinghua Li, Linwei Yue, Xinxin Liu, Liangpei Zhang

Xiaobin Guan et al.


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Short summary
This study generated the first global 1-km continuous NDVI product (STFLNDVI) for 4-decades by fusing multi-source satellite products. Simulated and real-data assessments confirmed the satisfactory and stable accuracy of STFLNDVI regarding spatial details and temporal variations. STFLNDVI is an ideal solution to the trade-off between spatial resolution and time coverage in current NDVI products, which of great significance for long-term regional and global vegetation and climate change studies.