Exploring the correlations between ten monthly climatic variables and the vegetation index of four different crop types at the global scale

ABSTRACT

The relationship between vegetation index (VI) and climatic variables such as temperature (TEP) and precipitation (PRE) at local, regional and global scales are conventionally analysed to understand the responses of vegetation to climate change. Those unique responses also afford opportunities for using climate variables to discriminate vegetation types. This paper presents a data-driven analysis to explore correlations between ten monthly climatic variables (temperature, precipitation, potential evapotranspiration (PET), vapour pressure (VAP), wet days (WET), and others) and monthly VIs of four different crop types (maize, rice, soybeans, and wheat) at global scale. The purpose is to show the VI–climate correlations in a spatially explicit way, laying the foundation for better crop type mapping by integrating climatic variables and remote sensing. The results show large variations in VI–climate correlation for different crop types and regions. Most cropland areas in the world show strong correlations between VI and VAP, and other variables such as WET, PET, and monthly average daily minimum temperature (TMN). This result encourages future studies using additional climate variables (in addition to TMP and PRE) for detailed vegetation/crop-type mapping.

Acknowledgments

This research was partially supported by the National Natural Science Foundation of China (grant number 41301445) and a research grant from Tsinghua University (grant number 20151080351). We thank two anonymous reviewers for their suggestions and comments.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [41301445];Tsinghua University [20151080351];