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山貫 緋称*; 市井 和仁*; 山本 雄平*; 小槻 峻司*; Sun, L.*; Liang, N.*; 寺本 宗正*; 永野 博彦*; 平野 高司*; 高木 健太郎*; et al.
no journal, ,
Soil respiration (SR) is one of the most essential components of soil carbon cycles. Many observation stations directly measure SR using chambers. In this study, we updated our data-driven estimation of SR across Japan with observation data (eight sites across Japan), remote sensing data (MODIS land products), and random forest regression. As soil meteorological variables, we used soil temperature and moisture by a process-based model, the Simple Biosphere model including Urban Canopy (SiBUC). Our estimation shows a reasonable performance with R = 0.72 for the in-situ model and R = 0.73 for remote sensing and in-situ combined model on average. Based on the established model, we also produced upscaled estimations of SR across Japan with a spatial resolution of 1 km from 2000 to 2020.