Title
Misestimation of Growing Season Length Due to Inaccurate Construction of Satellite Vegetation Index Time Series
Abstract
Satellite-based vegetation index (VI) is widely used in monitoring land surface phenology (LSP). Currently, well-developed VI products utilize the maximum value composite (MVC) algorithm to produce a composite VI time series (TS). Many of these products, however, lack the actual acquisition date (AD) of the VI value. As an alternative, the median or mean date of a composite period is used to reconstruct the VI TS, which might lead to bias on LSP detection. This letter quantifies the LSP bias in the Northern Hemisphere by generating a 15-day composited normalized difference vegetation index (NDVI) TS from the land long-term data record daily NDVI products using the MVC method. The results show that the AD of the NDVI value is usually later than the mean date of a composite period in spring and earlier in fall, effectively leading to a total overestimation of the growing season length of 5.91 days on average across the Northern Hemisphere (north of 30° N). This bias has a significant spatial pattern with high values observed in Northeastern China, Central North America, and high-latitude areas. However, the temporal trend is not largely influenced overall. Accordingly, we suggest the research community using accurate temporal information, whenever possible, in extracting LSP from VI TS.
Year
DOI
Venue
2019
10.1109/lgrs.2019.2895805
IEEE Geoscience and Remote Sensing Letters
Keywords
Field
DocType
Vegetation mapping,Springs,MODIS,Indexes,Earth Observing System,Land surface,Market research
Common spatial pattern,Physical geography,Northern Hemisphere,Growing season,Satellite,Vegetation Index,Remote sensing,Normalized Difference Vegetation Index,Mathematics,Phenology
Journal
Volume
Issue
ISSN
16
8
1545-598X
Citations 
PageRank 
References 
0
0.34
0
Authors
2
Name
Order
Citations
PageRank
Cong Wang121.16
Kai Zhu200.68