Multi-evidence-based assessment and selection of nine reconstructed solar-induced fluorescence products over China
- 1College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830000, China; Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830000, China; Xinjiang Field Scientific Observation and Research Station for the Oasisization Process in the Hinterland of the Taklamakan Desert, Yutian, Xinjiang 848400, China
Abstract
The availability of multiple long-term reconstructed solar-induced chlorophyll fluorescence (SIF) datasets at varying spatiotemporal resolutions provides new opportunities for investigating vegetation dynamics, particularly for estimating gross primary productivity (GPP) and assessing ecosystem responses to environmental stress. Evaluating the consistency and performance of reconstructed SIF (SIFr) products across different land cover types is therefore essential for their effective application in carbon–water cycle studies. In this study, we conducted a comprehensive assessment of nine widely used SIFr products (GOSIF, CSIF, RTSIF, LTSIF, HSIF, JJSIF, PKSIF, DSIF, and HCSIF) across China at a spatial resolution of 0.05° and a monthly temporal scale over the period 2007–2016. A multi-source validation framework was employed, integrating tower-based SIF, site-level and gridded GPP, and the Standardized Precipitation Evapotranspiration Index. We found that although all SIFr products exhibited strong agreement in long-term spatial patterns, substantial discrepancies existed in interannual trends. Agreement in long-term mean spatial patterns was generally higher than that in the spatial patterns of temporal trends and varied across land cover types, with stronger agreement observed in grasslands and croplands and lower agreement in forests. Across multiple validation datasets, RTSIF shows comparatively favorable performance, followed by CSIF and GOSIF, which exhibit similar performance. CSIF performs relatively well for GPP but shows lower performance in representing meteorological moisture conditions. Furthermore, product performance exhibits clear land cover dependence, with more reliable results in structurally simple ecosystems and reduced performance in complex canopy environments. We also identified differences in the relative performance of SIFr products across application scenarios and land cover types. These findings highlight the importance of product selection tailored to research objectives and environmental conditions and provide useful information for SIF-based monitoring of vegetation dynamics.
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BibTeX
@article{xu2026multievidencebased,
title = {{Multi-evidence-based assessment and selection of nine reconstructed solar-induced fluorescence products over China}},
author = {Fujin Xu and Changchun Xu},
journal = {International Journal of Applied Earth Observations and Geoinformation},
year = {2026},
month = oct,
doi = {10.1016/j.jag.2026.105650},
url = {https://doi.org/10.1016/j.jag.2026.105650},
note = {CC BY},
}
RIS
TY - JOUR
TI - Multi-evidence-based assessment and selection of nine reconstructed solar-induced fluorescence products over China
AU - Fujin Xu
AU - Changchun Xu
PY - 2026
DA - 2026/10/30
JO - International Journal of Applied Earth Observations and Geoinformation
DO - 10.1016/j.jag.2026.105650
UR - https://doi.org/10.1016/j.jag.2026.105650
AB - The availability of multiple long-term reconstructed solar-induced chlorophyll fluorescence (SIF) datasets at varying spatiotemporal resolutions provides new opportunities for investigating vegetation dynamics, particularly for estimating gross primary productivity (GPP) and assessing ecosystem responses to environmental stress. Evaluating the consistency and performance of reconstructed SIF (SIFr) products across different land cover types is therefore essential for their effective application in carbon–water cycle studies. In this study, we conducted a comprehensive assessment of nine widely used SIFr products (GOSIF, CSIF, RTSIF, LTSIF, HSIF, JJSIF, PKSIF, DSIF, and HCSIF) across China at a spatial resolution of 0.05° and a monthly temporal scale over the period 2007–2016. A multi-source validation framework was employed, integrating tower-based SIF, site-level and gridded GPP, and the Standardized Precipitation Evapotranspiration Index. We found that although all SIFr products exhibited strong agreement in long-term spatial patterns, substantial discrepancies existed in interannual trends. Agreement in long-term mean spatial patterns was generally higher than that in the spatial patterns of temporal trends and varied across land cover types, with stronger agreement observed in grasslands and croplands and lower agreement in forests. Across multiple validation datasets, RTSIF shows comparatively favorable performance, followed by CSIF and GOSIF, which exhibit similar performance. CSIF performs relatively well for GPP but shows lower performance in representing meteorological moisture conditions. Furthermore, product performance exhibits clear land cover dependence, with more reliable results in structurally simple ecosystems and reduced performance in complex canopy environments. We also identified differences in the relative performance of SIFr products across application scenarios and land cover types. These findings highlight the importance of product selection tailored to research objectives and environmental conditions and provide useful information for SIF-based monitoring of vegetation dynamics.
SN - 1569-8432
SN - 1872-826X
ER -