Assessing the response of satellite sun-induced chlorophyll fluorescence and MODIS vegetation products to soil moisture from 2010 to 2017: a case in Yunnan Province of China

Abstract

ABSTRACTSun-induced chlorophyll fluorescence (SIF) is widely used to monitor vegetation physiological conditions. In this paper, SIF derived from the Global Ozone Monitoring Experiment–2 (GOME-2), and gross primary productivity (GPP), normalized difference vegetation index (NDVI), land surface temperature (LST), soil moisture and precipitation are used to investigate vegetation stress in six areas of Yunnan Province in China. The results illustrate that SIF, NDVI, and GPP all decrease in the condition of water stress and increase when recovering towards a healthy condition; LST increases under stress conditions and decreases gradually during recovery conditions. Then, analyses of long time-series for SIF, GPP, NDVI, and LST from 2010 to 2017 are conducted. These performances demonstrate SIF is much more sensitive than GPP, the NDVI, and LST during drought conditions. When vegetation is in the condition of water stress, SIF has earlier responses than other parameters. Last, the relationships between SIF and soil moisture in 2010–2016 yield significant results, with the correlation coefficient r = 0.56, 0.71, 0.75, 0.74, 0.62, 0.52 and 0.47, sequentially. The correlation coefficients are used to measure how strong a relationship is between two variables. This work demonstrates that SIF is a good way to monitor water condition change, and may play a great role in drought monitoring in the future.