Sentinel-2A data -derived estimation of photosynthetic and non-photosynthetic vegetation cover over the loess plateau [基于 Sentinel-2A 影像估算黄土高原光合/非光合植被盖度]

作者：Lü D.; Liu B.-Y.^*; He L.; Zhang X.-P.; Cheng Z.; He J.

来源：China Environmental Science, 2022, 42(9): 4323-4332.

• linear spectral mixture model
• non-photosynthetic vegetation
• photosynthetic vegetation
• Sentinel-2A
• the Loess Plateau

In this study, we evaluated four non-photosynthetic vegetation indices (NPVI), including Shortwave Infrared Ratio (SWIR32), Dead Fuel Index (DFI), Soil Tillage Index (STI) and Normalized Difference Tillage Index (NDTI) for Non-photosynthetic Vegetation (fNPV) estimation in the simulated and field mixed scenarios, respectively, and applied them to estimate fNPV using Sentinel-2A data (10m) over the Loess Plateau. We applied a linear unmixing model to estimate Photosynthetic Vegetation (fPV) and fNPV based on the triangular relationship between Normalized Vegetation Difference Index (NDVI) and NPVI (e.g., SWIR32). The NDVI-NPVI endmember values were determined. The results showed that the correlation coefficient (R2) between each NPVI and simulated fNPV was between 0.365 to 0.750, and 0.147 to 0.211 between each NPVI and fNPV under the field mixed scenario. Using this approach, we estimated the Loess Plateau’s average fPV and fNPV for April, August and December in 2019, being 20.3% and 59.2%, 48.6% and 33.1%, and 10.7% and 59.0%, respectively. The R2 of the model for fPV and fNPV estimation reached 0.817 and 0.463, respectively, while the NSE was 0.806 and 0.458, respectively. The results also revealed the seasonal variation fPV from southeast to northwest over time, and the opposite trend for fNPV. Our study suggests that the NDVI-SWIR32 model can be used with Sentinel-2A data to adequately monitor the spatiotemporal dynamics of fPV and fNPV in the Loess Plateau.

• 单位
  西北农林科技大学; 地表过程与资源生态国家重点实验室; 中国科学院大学