【作者】 赵贺斌； 张双成； 刘奇； 马中民； 刘宁； 胡胜伟； 鲍琳； 周昕； 郭沁雨； 王力福； 万田荷；

【Author】 Hebin Zhao;Shuangcheng Zhang;Qi Liu;Zhongmin Ma;Ning Liu;Shengwei Hu;Lin Bao;Xin Zhou;Qinyu Guo;Lifu Wang;Tianhe Wan;College of Geology Engineering, Chang’an University;State Key Laboratory of Geo-Information Engineering;Altay National Reference Meteorological Station,China Meteorological Administration;

【机构】 长安大学地质工程学院； 地理信息工程国家重点实验室； 阿勒泰气象局；

【摘要】 随着GNSS-R技术的不断成熟,基于CYGNSS(Cyclone Global Navigation Satelite System)采集的信号数据对土壤湿度反演的研究进一步完善。本文利用多种辅助数据针对地表反射率进行改正以减弱地表粗糙度、植被等地表因素对反演过程的影响,并建立线性回归模型针对美国地区的土壤湿度进行反演外推。文章结合SMAP数据的地表粗糙度,植被含水量(VWC)等参数减弱地表参数对反射率计算过程中的误差。利用2020年整年CYGNSS数据计算反射率结合2020年整年SMAP数据作为土壤湿度真值建立回归模型计算模型回归参数,并反演外推2021年整年的土壤湿度数据。经过实验验证,利用SMAP辅助数据剔除地表粗糙度以及植被覆盖的影响过后,反演外推结果精度有明显的提升,反演的土壤湿度整体相关性由0.612提升到0.734,RMSE降低到0.0812。本次实验结果表明,地表参数即地表粗糙度和植被覆盖在反演过程中有重要的影响,为后续提升土壤湿度反演精度研究提供了一种新思路。更多还原

【Abstract】 With the continuous development of GNSS-R technology, the research on soil moisture retrieval based on signal data collected by CYGNSS(cyclone global navigation satellite system) is further improved.In this paper, we use a variety of auxiliary data to correct the surface reflectivity to weaken the influence of surface roughness, vegetation and other surface factors on the retrieval process, and establish a linear regression model to retrieve and extrapolate the soil moisture in the United States. In this paper, the surface roughness and vegetation water content(VWC) of SMAP data are used to reduce the error of surface parameters in the calculation of reflectivity. Using the CYGNSS data of the whole year in 2020 to calculate the reflectivity and the SMAP data of the whole year in 2020 as the true value of soil moisture, a regression model is established to calculate the regression parameters of the model, and the soil moisture data of the whole year in 2021 is retrieved and extrapolated. Through experimental verification, the accuracy of the extrapolation results has been significantly improved after the influence of surface roughness and vegetation coverage is eliminated by using SMAP auxiliary data. The overall correlation of retrieved soil moisture increased from 0.612 to 0.734, RMSE reduced to 0.0812.The results of this experiment show that the surface parameters, surface roughness and vegetation cover, have an important influence on the retrieval process,which provides a new idea for the subsequent research on improving the accuracy of soil moisture retrieval.更多还原