Key Laboratory of Advanced Process Control for Light Industry, Ministry of Education, Jiangnan University, Wuxi, China.
Department of Plant Biology, Department of Biochemistry, and Center of Biophysics & Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.
Big Data. 2022 Jun;10(3):230-245. doi: 10.1089/big.2020.0350. Epub 2021 May 13.
Drought is the primary and dominant natural cause of stress on vegetation, and thus, it needs our full attention. Current understanding of drought across extensive spatial measures, around the world, is considerably limited. As case studies to evaluate the feasibility of utilizing space-based solar-induced chlorophyll fluorescence (SIF) across extensive spatial measures, here, we have used data from 2007 to 2017 in Heilongjiang and Jiangsu provinces of China. The onset of the 2015 drought was accompanied by a substantial response of SIF from vegetation in both the provinces; these data were associated with changes in soil moisture, standardized precipitation evapotranspiration index, and emissivity. Our findings suggest that SIF can effectively provide the spatial and temporal progress of drought, as inferred through substantial associations with SIF normalized by absorbed photosynthetically active radiation (related to Φ) and by photosynthetically active radiation . For the depiction of onset to drought, SIF, Φ, and provide a significant association and a quicker response than the leaf area index and the normalized difference vegetation index. Furthermore, we found that the correlation between gross primary productivity and SIF is highly substantial in both Heilongjiang ( = 0.85, < 0.001) and Jiangsu ( = 0.75, < 0.001) during the drought period. Our results indicate that continuing evaluation from space-based SIF can indeed provide an understanding of the seasonal differences in vegetation for evaluating the impact of drought across extensive spatial measures.
干旱是植被胁迫的主要和主要自然原因，因此需要我们充分关注。目前，对全球广泛空间尺度的干旱的理解相当有限。作为评估利用基于空间的太阳诱导叶绿素荧光 (SIF) 在广泛空间尺度上的可行性的案例研究，在这里，我们使用了 2007 年至 2017 年中国黑龙江省和江苏省的数据。2015 年干旱的开始伴随着两省植被 SIF 的大幅响应；这些数据与土壤湿度、标准化降水蒸散指数和发射率的变化有关。我们的研究结果表明，SIF 可以有效地提供干旱的时空进展，通过与通过吸收光合有效辐射归一化的 SIF（与 Φ 相关）和与光合有效辐射相关的 SIF 进行实质性关联来推断。对于干旱开始的描述，SIF、Φ 和 与叶面积指数和归一化差异植被指数相比提供了显著的关联和更快的响应。此外，我们发现，在干旱期间，黑龙江省（ = 0.85， < 0.001）和江苏省（ = 0.75， < 0.001）的总初级生产力与 SIF 之间存在高度实质性的相关性。我们的结果表明，继续从基于空间的 SIF 进行评估确实可以提供对植被季节性差异的理解，从而评估干旱对广泛空间尺度的影响。
