Tracking drought dynamics on China's Loess Plateau with the rapid change index of solar-induced chlorophyll fluorescence

Although solar-induced chlorophyll fluorescence (SIF) has been proven to be a useful indicator for dynamic drought monitoring, accurately quantifying the trajectory of vegetation SIF change during drought events remains a research challenge. In this case study, we applied a rapid change index (RCI) for the 8-day global ‘Orbiting Carbon Observatory (OCO-2)’ SIF product (GOSIF) to calculate the deviation between GOSIF trajectories and climate norms across China’s Loess Plateau (LP) from 2001 to 2020. We compared the performances of SIF-RCI with GOSIF values and GOSIF anomalies during drought events and evaluated the drought warning potential with the widely used 8-day Standardized Precipitation Evapotranspiration Index (SPEI). Our results showed that SIF-RCI captured the rapid change areas in GOSIF caused by drought and the trajectory of rapid vegetation changes compared to GOSIF values and GOSIF anomalies. The SIF-RCI negative signal accurately identified the onset of drought almost simultaneously with SPEI. The SIF-RCI positive signal also predicted drought recovery with at least 4 8-day periods of lead time. Meteorological factors, especially precipitation, had a great impact on vegetation photosynthesis and this was detected with GOSIF. These impacts varied in different climate zones and vegetation types. Our study contributes to regional drought monitoring and assessment.

Publication Details

Journal
Figshare
Published
2025-01-01
DOI
https://doi.org/10.6084/m9.figshare.28561500
Primary Topic
Remote Sensing in Agriculture
Type
article
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article

Tracking drought dynamics on China's Loess Plateau with the rapid change index of solar-induced chlorophyll fluorescence

Figshare
Remote Sensing in Agriculture
article

Tracking drought dynamics on China's Loess Plateau with the rapid change index of solar-induced chlorophyll fluorescence

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Abstract

Although solar-induced chlorophyll fluorescence (SIF) has been proven to be a useful indicator for dynamic drought monitoring, accurately quantifying the trajectory of vegetation SIF change during drought events remains a research challenge. In this case study, we applied a rapid change index (RCI) for the 8-day global ‘Orbiting Carbon Observatory (OCO-2)’ SIF product (GOSIF) to calculate the deviation between GOSIF trajectories and climate norms across China’s Loess Plateau (LP) from 2001 to 2020. We compared the performances of SIF-RCI with GOSIF values and GOSIF anomalies during drought events and evaluated the drought warning potential with the widely used 8-day Standardized Precipitation Evapotranspiration Index (SPEI). Our results showed that SIF-RCI captured the rapid change areas in GOSIF caused by drought and the trajectory of rapid vegetation changes compared to GOSIF values and GOSIF anomalies. The SIF-RCI negative signal accurately identified the onset of drought almost simultaneously with SPEI. The SIF-RCI positive signal also predicted drought recovery with at least 4 8-day periods of lead time. Meteorological factors, especially precipitation, had a great impact on vegetation photosynthesis and this was detected with GOSIF. These impacts varied in different climate zones and vegetation types. Our study contributes to regional drought monitoring and assessment.

Figshare
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Remote Sensing in Agriculture
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Tracking drought dynamics on China's Loess Plateau with the rapid change index of solar-induced chlorophyll fluorescence · Figshare (2025) | TGRS Research Map | TGRS