4.7 Article

Addressing validation challenges for TROPOMI solar-induced chlorophyll fluorescence products using tower-based measurements and an NIRv-scaled approach

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REMOTE SENSING OF ENVIRONMENT
卷 290, 期 -, 页码 -

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ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2023.113547

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Solar-induced chlorophyll fluorescence (SIF); TROPOMI; Validation; Near-infrared reflectance of vegetation (NIRv)

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In recent years, several satellite-based solar-induced chlorophyll fluorescence (SIF) products have emerged, but direct validation of these products has not been conducted. This study validated two groups of TROPOMI SIF products using tower-based SIF measurements at seven sites. Challenges such as spatial scale mismatch were addressed using a near-infrared reflectance of vegetation (NIRv)-scaled approach. The validation results showed differences in the performance of the SIF datasets and highlighted unresolved issues in SIF product quality.
Several satellite-based solar-induced chlorophyll fluorescence (SIF) products have progressively emerged and have been developed in recent years. However, till date, no direct validation has been conducted on existing satellite-based SIF products. In this study, validation of two groups of TROPOspheric Monitoring Instrument (TROPOMI) SIF products, namely TROPOSIFCaltech (containing far-red and red TROPOSIFCaltech datasets) and TROPOSIFESA (containing TROPOSIF735 and TROPOSIF743 datasets that are retrieved from two different retrieval windows), was conducted using tower-based SIF measurements over seven sites. Several issues and potential obstacles emerged while matching satellite-based and in situ SIF retrievals, including spatial scale mismatch. To overcome the spatial scale mismatch between the satellite data and ground observations, a near-infrared reflectance of vegetation (NIRv)-scaled approach was employed to mitigate the spatial difference between the locations of specific sites and the matched TROPOSIF samples using Sentinel-2 imagery. Other issues related to retrival methods and instrument differences were examined. Subsequently, the 3FLD retrieval method was chosed for the in situ data. The validation results showed that the three far-red TROPOSIF datasets exhibit slightly different performances in terms of the validation accuracy; the R2 for TROPOSIFCaltech, TROPOSIF735, and TROPOSIF743 was 0.43, 0.33 and 0.40, respectively, which is asociated with root-mean-square error(RMSE) values of 0.59, 0.42 and 0.57 mW m- 2 sr-1 nm- 1, respectively. However, red TROPOSIFCaltech exhibited no significant correlation with tower-based SIF with R2 of 0.02 and RMSE of 0.34 mW m- 2 sr-1 nm- 1. Furthermore, the validation results at different sites varied, with R2 ranging from 0.01 to 0.70. Uncertainties still exist in the validation of the four TROPOSIF datasets, which are attributed to some unresolved issues, such as the limited quality of in situ SIF retrievals and the spatial scaling difference. Thus, to fully utilize satellite-based SIF products for wide ranging applications, further improvements in SIF product quality are urgently required at both ground and satellite scales.

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