Spatial downscaling of chlorophyll A in Himawari-8 based on Landsat 8 images [基于 Landsat 8 影像的 Himawari-8 叶绿素 a 空间降尺度研究]

作者：Xiong Y.-K.; Fan D.-L.^*; He H.-C.; Shi J.-K.; Zhang J.; Xiao B.; Fu B.-L.

来源：China Environmental Science, 2022, 42(11): 5341-5350.

• chlorophyll-a
• downscale
• himawari-8
• landsat 8
• random forests

The chlorophyll-a products of the new geostationary meteorological satellite Himawari-8 are difficult to meet the requirements of water quality monitoring in near-shore waters with high spatial heterogeneity due to their low spatial resolution. To overcome this limitation, a non-linear random forest algorithm was used to improve the spatial resolution of the chlorophyll a data from Himawari-8 by constructing a downscaling model using the band reflectance data from Landsat 8and the chlorophyll-a products from Himawari-8. The results showed that the coefficients of determination (R2) of the two autumn models and two winter models reached 0.6, 0.72, 0.71 and 0.85, respectively, and the root mean square errors (RMSE) were 1.47, 1.05, 1.89, 0.76mg/m3, respectively. The comparative analysis of the measured site data showed that the chlorophyll-a data generated by the downscaled model had a high consistency with the chlorophyll-a data of Himawari-8, and the R2 reached 0.81 The spatial variation of chlorophyll-a concentration in the near-shore sea area is well reflected by the spatial variation of chlorophyll a data.

• 单位
  桂林理工大学