Can the MODIS Data Achieve the Downscaling of GOME-2 SIF? Validation of Data from China

Abstract

Solar-induced chlorophyll fluorescence (SIF) can accurately reflect the photosynthetic capacity of vegetation and information on the physiological status of vegetation, which is of great research significance and application value. However, the low resolution of the solar-induced chlorophyll fluorescence product of the inverse performance makes it difficult to perform fine-scale studies. Therefore, concerning the above problem, this study proposes a random-forest-based downscaling method based on random forest. We used MODIS reflectance data to analyze GOME-2 SIF data at 0.5° resolution over the Chinese mainland in 2011 and created a monthly SIF product at 0.05° resolution for the Chinese mainland through downscaling. Then we performed a veracity check on the downscaled SIF data, analyzed factors (land cover type, climate zone type, and DEM) that could affect its accuracy, and explored the feasibility of using MODIS data in future GOME-2 SIF downscaling studies. The results show that the downscaled SIF is in remarkable agreement with the GOME-2 SIF, with an improved spatial resolution from 0.5° to 0.05°, and that the structural and physiological information of the SIF is well represented in the downscaled SIF, which is essential for assessing global photosynthesis. In addition, in the region with grassland land cover type, temperate grassland climate region, alpine vegetation climate region of Qinghai–Tibet Plateau, as well as the region with high altitude and complex terrain, the accuracy of using MODIS to downscale the GOME-2 SIF data is low.