Novel vegetation indices for estimating photosynthetic and non-photosynthetic fractional vegetation cover from Sentinel data

红边 植被(病理学) 光合作用 增强植被指数 环境科学 遥感 大气科学 叶面积指数 地理 植被指数 物理 植物 归一化差异植被指数 生物 高光谱成像 病理 医学
作者
Jiali Liu,Jianrong Fan,Chao Yang,Fubao Xu,Xiyu Zhang
出处
期刊:International journal of applied earth observation and geoinformation 卷期号:109: 102793-102793 被引量:30
标识
DOI:10.1016/j.jag.2022.102793
摘要

The empirical retrieval method based on vegetation indices (VIs) has been extensively utilized to estimate the photosynthetic vegetation fractional cover (FPV) and non-photosynthetic vegetation fractional cover (FNPV). These indices, however, saturate in high biomass environments and are easily influenced by external factors. Three red edge (RE) bands (i.e., RE1, RE2, RE3) are available on the Sentinel-2 satellite, providing new options for estimating FPV and FNPV. Here, sensitivity analysis from PROSAIL-PRO simulations provided a theoretical foundation for developing new indices. Sentinel-2 images and field observations were collected at three growth stages to test the original and new-developed indices for FPV and FNPV estimations. Compared to the original photosynthetic vegetation indices (PVIs) containing the near-infrared (NIR) and red bands, the optimal combinations for FPV estimation in August were RE3 and red bands, while the combination of RE2 and RE1 bands performed best in April. By introducing RE3, RE2, RE1, and red bands in a certain proportion, 4-band red edge PVIs had the strongest correlation with FPV. Although the optimal 2-band non-photosynthetic vegetation indices (NPVIs) in November were two shortwave infrared (SWIR) bands, the combinations of NIR and RE3 bands performed best for FNPV estimation in April. Combining SWIR1, SWIR2, NIR, and RE3 bands, three 4-band red edge NPVIs were put forward, had the highest accuracy for estimating FNPV. The most prominent achievement of the red edge indices is to suppress undervaluation when vegetation cover is high while mitigating overestimation at low vegetation cover levels. However, the optimum weighting parameters of the improved VIs differed depending on different growth stages. We discovered novel 4-band red edge indices are useful for estimating FPV and FNPV.

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