Fang Jianing, Lian Xu, Ryu Youngryel, Jeong Sungchan, Jiang Chongya, Gentine Pierre
Department of Earth and Environmental Engineering, Columbia University, New York, USA.
Interdisciplinary Program in Landscape Agriculture, Seoul National University, Seoul, Republic of Korea.
Sci Data. 2025 Mar 3;12(1):372. doi: 10.1038/s41597-025-04686-6.
Satellite-observed solar-induced chlorophyll fluorescence (SIF) is a powerful proxy for the photosynthetic characteristics of terrestrial ecosystems. Direct SIF observations are primarily limited to the recent decade, impeding their application in detecting long-term dynamics of ecosystem function. In this study, we leverage two surface reflectance bands available both from Advanced Very High-Resolution Radiometer (AVHRR, 1982-2023) and MODerate-resolution Imaging Spectroradiometer (MODIS, 2001-2023). Importantly, we calibrate and orbit-correct the AVHRR bands against their MODIS counterparts during their overlapping period. Using the long-term bias-corrected reflectance data from AVHRR and MODIS, a neural network is trained to produce a Long-term Continuous SIF-informed Photosynthesis Proxy (LCSPP) by emulating Orbiting Carbon Observatory-2 SIF, mapping it globally over the 1982-2023 period. Compared with previous SIF-informed photosynthesis proxies, LCSPP has similar skill but can be advantageously extended to the AVHRR period. Further comparison with three widely used vegetation indices (NDVI, kNDVI, NIRv) shows a higher or comparable correlation of LCSPP with satellite SIF and site-level GPP estimates across vegetation types, ensuring a greater capacity for representing long-term photosynthetic activity.
卫星观测的太阳诱导叶绿素荧光（SIF）是陆地生态系统光合特性的有力指标。直接的SIF观测主要限于近十年，这阻碍了它们在检测生态系统功能长期动态方面的应用。在本研究中，我们利用了先进甚高分辨率辐射计（AVHRR，1982 - 2023年）和中分辨率成像光谱仪（MODIS，2001 - 2023年）都有的两个地表反射率波段。重要的是，我们在重叠期将AVHRR波段相对于其MODIS对应波段进行校准和轨道校正。利用来自AVHRR和MODIS的长期偏差校正反射率数据，训练一个神经网络，通过模拟轨道碳观测站-2的SIF来生成长期连续的SIF驱动光合作用指标（LCSPP），并在1982 - 2023年期间进行全球映射。与之前的SIF驱动光合作用指标相比，LCSPP具有相似的技能，但可以有利地扩展到AVHRR时期。与三个广泛使用的植被指数（归一化植被指数（NDVI）、改进型归一化植被指数（kNDVI）、近红外植被指数（NIRv））的进一步比较表明，LCSPP与卫星SIF以及不同植被类型的站点级总初级生产力（GPP）估计值具有更高或相当的相关性，确保了其在表示长期光合活动方面具有更大的能力。
