Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: QP model with dual-channel algorithm could accurately represent the effect of surface roughness on emission at different polarization under big view angle. The purpose of this paper is to estimate long temporal series soil moisture product based on the QP algorithm, and compared it with JAXA, LPRM in Genhe basin. The results indicate that QP retrieval values are closest to the ground data but it have many missing values and high RMSE (around 0.15m 3 m −3 ); JAXA product has good correlation coefficients (around 0.4) but underestimates the ground data. LPRM product overestimates the ground data and it is found to be very noisy and unstable. Finally, In order to improve the model, this paper analysed the tendency of QP retrievals with satellite brightness temperature, and examined the influence of auxiliary data for retrievals.
['Huizhen Cui', 'Lingmei Jiang', 'Jinyang Du', 'Gongxue Wang', 'Zheng Lu']
I am writing a research paper on a idea Assessment of QP model based two channel algorithm with JAXA, LPRM soil moisture products over Genhe area in China
[{"from": "human", "value": "I am writing a research paper on a idea Assessment of QP model based two channel algorithm with JAXA, LPRM soil moisture products over Genhe area in China"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: QP model with dual-channel algorithm could accurately represent the effect of surface roughness on emission at different polarization under big view angle. The purpose of this paper is to estimate long temporal series soil moisture product based on the QP algorithm, and compared it with JAXA, LPRM in Genhe basin. The results indicate that QP retrieval values are closest to the ground data but it have many missing values and high RMSE (around 0.15m 3 m \u22123 ); JAXA product has good correlation coefficients (around 0.4) but underestimates the ground data. LPRM product overestimates the ground data and it is found to be very noisy and unstable. Finally, In order to improve the model, this paper analysed the tendency of QP retrievals with satellite brightness temperature, and examined the influence of auxiliary data for retrievals."}]