Indication of the Two Linear Correlation Methods Between Vegetation Index and Climatic Factors: An Example in the Three River-Headwater Region of China During 2000–2016

Abstract

The within-growing-season correlations (WGSC) and the inter-growing-season correlations (IGSC) are widely used linear correlation analysis methods between vegetation index and climatic factors (such as temperature, precipitation, and so on). The WGSC method usually calculates the linear correlation coefficient between vegetation index and climatic factors of each month in all the growing seasons, for instance, whether vegetation index or temperature had data of 204 months (12 months × 17 years) during 2000–2016 to get the WGSC. The IGSC calculates the linear correlation coefficient between the vegetation index and climatic factors in the same month of each growing season among all the years, for example, only 17 couples’ data of vegetation index and temperature during 2000–2016 were used to get the linear correlation of IGSC. What is the difference between the results of the two methods and why do the results show that difference? Which is the more suitable method for the analysis of the relationship between the vegetation index and climatic conditions? To clarify the difference of the two methods and to explore more about the relationship between the vegetation index and climatic factors, we collected the data of 2000–2016 moderate resolution imaging spectroradiometer (MODIS) 13A1 normalized difference vegetation index (NDVI) and the meteorological data-temperature and precipitation, then calculated WGSC and IGSC between NDVI and the climatic factor in three river-headwater regions of China. The results showed that: (1) As for WGSC, the more of the years included, the higher the correlation coefficient between NDVI and the temperature/precipitation. The correlation coefficient of WGSC is dependent on how many years’ the data were included, and it was increased with the more year’s data included, while the correlation coefficients of IGSC are relatively independent on the amount of the data; (2) the WGSC showed a pseudo linear correlation between NDVI and climatic conditions caused by the accumulation of data amount, while the IGSC can more accurately indicate the impact of climatic factors on vegetation since it did not rely on the data amount.