The absorption characteristics of the water column have a significant impact on the reflectance of the coupled submerged vegetation-water column system. In the case of a deeper water or a higher concentration of water color constitutes, the vegetation features of the reflectance of submerged vegetation will gradually weaken or even disappear and eventually show similar features to those of the water, which affects the effectiveness of the application of remote sensing monitoring of wetlands. To address this problem, this paper proposes a water column correction method based on the semi-analytical model and evaluates the accuracy through the model simulation data from the aquatic vegetation radiative transfer model. The results show that the semi-analytical model can better restore the curve shape of vegetation in the range of 500–750 nm, where the average relative errors at 550 nm, 670 nm, and 720 nm are about 6.75%, 10.76%, and 33.11%, respectively, which is better than the other models according to the comparison. The method proposed in this paper can help to solve the difficulties in the application of wetland remote sensing.

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Research on Water Column Correction for Submerged Vegetation Reflectance Based on a Semi-analytical Model

  • Zhongqi Ma,
  • Yongshi Jie,
  • Cheng Jiang

摘要

The absorption characteristics of the water column have a significant impact on the reflectance of the coupled submerged vegetation-water column system. In the case of a deeper water or a higher concentration of water color constitutes, the vegetation features of the reflectance of submerged vegetation will gradually weaken or even disappear and eventually show similar features to those of the water, which affects the effectiveness of the application of remote sensing monitoring of wetlands. To address this problem, this paper proposes a water column correction method based on the semi-analytical model and evaluates the accuracy through the model simulation data from the aquatic vegetation radiative transfer model. The results show that the semi-analytical model can better restore the curve shape of vegetation in the range of 500–750 nm, where the average relative errors at 550 nm, 670 nm, and 720 nm are about 6.75%, 10.76%, and 33.11%, respectively, which is better than the other models according to the comparison. The method proposed in this paper can help to solve the difficulties in the application of wetland remote sensing.