基于Sentinel-2A影像估算黄土高原光合/非光合植被盖度

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Abstract 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 (f_NPV) estimation in the simulated and field mixed scenarios, respectively, and applied them to estimate f_NPV using Sentinel-2A data (10m) over the Loess Plateau. We applied a linear unmixing model to estimate Photosynthetic Vegetation (f_PV) and f_NPV 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 f_NPV was between 0.365 to 0.750, and 0.147 to 0.211 between each NPVI and f_NPV under the field mixed scenario. Using this approach, we estimated the Loess Plateau’s average f_PV and f_NPV 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 f_PV and f_NPV 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 f_PV from southeast to northwest over time, and the opposite trend for f_NPV. Our study suggests that the NDVI-SWIR32 model can be used with Sentinel-2A data to adequately monitor the spatiotemporal dynamics of f_PV and f_NPV in the Loess Plateau.

Key words： Sentinel-2A photosynthetic vegetation non-photosynthetic vegetation linear spectral mixture model the Loess Plateau

Received: 08 February 2022

PACS:	X171
	TP79

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	Lü Du
	LIU Bao-yuan
	HE Liang
	ZHANG Xiao-ping
	CHENG Zhuo
	HE Jie

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Lü Du,LIU Bao-yuan,HE Liang等. Sentinel - 2A data - derived estimation of photosynthetic and non - photosynthetic vegetation cover over the loess plateau[J]. CHINA ENVIRONMENTAL SCIENCECE, 2022, 42(9): 4323-4332.

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http://www.zghjkx.com.cn/EN/ OR http://www.zghjkx.com.cn/EN/Y2022/V42/I9/4323

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