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Estimating Fraction of Absorbed Photosynthetically Active Radiation of Winter Wheat Based on Simulated Sentinel-2 Data under Different Varieties and Water Stress

文献类型： 外文期刊

作者： Sun, Zheng 1 ; Sun, Liang 1 ; Liu, Yu 1 ; Li, Yangwei 1 ; Crusiol, Luis Guilherme Teixeira 2 ; Chen, Ruiqing 1 ; Wuyun, Deji 1 ;

作者机构： 1.Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, State Key Lab Efficient Utilizat Arid & Semiarid A, Beijing 100081, Peoples R China

2.Natl Soybean Res Ctr Brazilian Agr Res Corp, Embrapa Soja, BR-86001970 Londrina, PR, Brazil

关键词： fraction of absorbed photosynthetically active radiation; MNDVI; winter wheat; vegetation index; Sentinel-2

期刊名称：REMOTE SENSING （ 影响因子：5.0； 五年影响因子：5.6 ）

ISSN：

年卷期： 2024 年 16 卷 2 期

页码：

收录情况： SCI

摘要： The fraction of absorbed photosynthetically active radiation (fPAR) is an important parameter reflecting the level of photosynthesis and growth status of vegetation, and is widely used in energy cycling, carbon cycling, and vegetation productivity estimation. In agricultural production, fPAR is often combined with the light use efficiency model to estimate crop yield. Therefore, accurate estimation of PAR is of great importance for improving the accuracy of crop yield estimation and ensuring national food security. Existing studies based on vegetation indices have not considered the effects of genetic variety, light, and water stress on fPAR estimation. This study uses ground-based reflectance data to simulate 21 common Sentinel-2 vegetation indices and compare their estimation ability for winter wheat fPAR. The stability of the vegetation index with the highest correlation in inverting fPAR under different cultivars, light, and water stress was tested, and then the model was validated at the satellite scale. Finally, a sensitivity analysis was performed. The results showed that the index model based on modified NDVI (MNDVI) had the highest correlation not only throughout the critical phenological period of winter wheat (R2 of 0.6649) but also under different varieties, observation dates, and water stress (R2 of 0.918, 0.881, and 0.830, respectively). It even performed the highest R2 of 0.8312 at the satellite scale. Moreover, through comparison, we found that considering water stress and variety differences can improve the estimation accuracy of fPAR. The study showed that using MNDVI for fPAR estimation is not only feasible but also has high accuracy and stability, providing a reference for rapid and accurate estimation of fPAR by Sentinel-2 and further exploring the potential of Sentinel-2 data for high-resolution fPAR mapping.

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