TROPOMI SIF reveals large uncertainty in estimating the end of plant growing season from vegetation indices data in the Tibetan Plateau
TROPOMI SIF reveals large uncertainty in estimating the end of plant growing season from vegetation indices data in the Tibetan Plateau
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DOI：
10.1016/j.rse.2022.113209
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发表时间：
2022-10
影响因子：
13.5
通讯作者：
Jilin Yang;Xiangming Xiao;R. Doughty;Miaomiao Zhao;Yao Zhang;P. Köhler;Xiaocui Wu;C. Frankenberg-C.-Frankenb
中科院分区：
文献类型：
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作者：
Jilin Yang;Xiangming Xiao;R. Doughty;Miaomiao Zhao;Yao Zhang;P. Köhler;Xiaocui Wu;C. Frankenberg-C.-Frankenb
大尺度陆面物候（LSP）信息已经从基于遥感的植被指数（维斯）数据。然而，有相当大的差异和不确定性的LSP数据产品的开始和结束的生长季节（SOS; EOS）作为不同的植被指数和算法使用。本文利用对流层监测仪（TROPOMI）的太阳诱导叶绿素荧光（SIF）数据估算了青藏高原的SOS和EOS。我们将基于SIF的物候指标与来自维斯的指标（例如，归一化植被指数（NDVI）、增强植被指数（EVI）和植被近红外反射率（NIRv）），以及由植被光合作用模型（VPM）模拟的总初级生产力（GPP）。我们发现SIF和维斯之间SOS的差异相对较小，但EOS差异较大。因此，从维斯指数得出的生长季节长度比SIF估计的长两个月。这些结果在三个产品中是一致的，双向反射分布函数（BRDF）调整（MCD 43），标准MODIS（MOD 09）和TROPOMI产品。在排除卫星传感器之间的两个不匹配（太阳光照和视角）后，EOS差异仍然存在。我们还发现，基于VIS的EOS发生在冰点以下，而基于SIF的EOS发生在冰点以上，这表明基于SIF的EOS更有生理意义。我们的研究表明，后期基于VIS的EOS部分是由于土壤背景变化对维斯和基于VIS的EOS的影响。我们的研究结果强调，需要重新评估目前的LSP数据产品来自反射率为基础的维斯和开发新的植被物候数据产品，如SIF排放的能量。
Large-scale land surface phenology (LSP) information has been developed from remote sensing-based vegetation indices (VIs) data. However, there are considerable discrepancies and uncertainties in the LSP data products for the start and end of growing seasons (SOS; EOS) as different vegetation indices and algorithms are used. Here, we used the TROPOspheric Monitoring Instrument (TROPOMI) solar-induced chlorophyll fluorescence (SIF) data to estimate SOS and EOS in the Tibetan Plateau, a global hotspot of vegetation response to climate change. We compared SIF-based phenological metrics to those derived from VIs (e.g., normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and near-infrared reflectance of vegetation (NIRv)), and gross primary production (GPP) simulated by the vegetation photosynthesis model (VPM). We found relatively small discrepancies in SOS between SIF and VIs, but large differences in EOS. Thus, the length of the growing season derived from VIs was as much as two months longer than that estimated by SIF. These results were consistent across three products, bidirectional reflectance distribution function (BRDF) adjusted (MCD43), standard MODIS (MOD09), and TROPOMI products. The EOS discrepancy remained after excluding two mismatches (solar illumination and viewing angle) between satellite sensors. We also found that VIs-based EOS occurred below the freezing point, while SIF-based EOS occurred above the freezing point, suggesting that SIF-based EOS is more physiologically meaningful. Our study proposed that the late VIs-based EOS was caused in part by the effect of changes in soil background on VIs and VIs-based EOS. Our results highlight the need to re-evaluate current LSP data products derived from reflectance-based VIs and to develop new vegetation phenology data products using emitted energy such as SIF.