A method for estimating total primary productivity of vegetation by remote sensing considering soil moisture stress

Abstract

The application discloses a vegetation total primary productivity remote sensing estimation method considering soil moisture stress, and belongs to the technical field of remote sensing estimation of land ecosystem carbon cycle. The method comprises the following steps: obtaining vegetation leaf area index, meteorological, soil and remote sensing and other multi-source data and uniformly preprocessing; based on two leaf light energy utilization rate models, the photosynthetically active radiation absorbed by sun leaves and shade leaves is calculated, and temperature, saturated vapor pressure difference and carbon dioxide concentration stress factors are constructed; the relative abundance and deficiency degree index of plant available soil moisture is calculated by using soil moisture content and soil properties, a soil moisture sensitive coefficient is constructed by combining the actual evapotranspiration and potential evapotranspiration ratio, and a three-section soil moisture stress function is established to represent the photosynthetic inhibition effect under the conditions of water deficit, suitable and oversaturation. The application improves the precision and adaptability of remote sensing estimation of vegetation productivity under different water environments by simultaneously depicting the double restriction effects of soil water deficit and oversaturation.

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