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GNSS/MODIS信号紧耦合水汽层析算法
引用本文:张文渊,张书毕,郑南山,丁楠,刘鑫,马朋序.GNSS/MODIS信号紧耦合水汽层析算法[J].测绘学报,2021,50(4):496-508.
作者姓名:张文渊  张书毕  郑南山  丁楠  刘鑫  马朋序
作者单位:中国矿业大学自然资源部国土环境与灾害监测重点实验室,江苏 徐州 221116;中国矿业大学环境与测绘学院,江苏 徐州 221116;江苏师范大学地理测绘与城乡规划学院,江苏 徐州 221116
摘    要:GNSS水汽层析技术凭借高精度、高时空分辨率及全天候监测等优点,已成为探测大气水汽最具潜力的技术之一。目前,融合多源大气遥感数据逐步成为弥补传统层析模型GNSS信号几何缺陷的研究热点。本文利用Terra卫星上的中分辨率成像光谱仪(moderate resolution imaging spectroradiometer,MODIS)提供的观测数据,首先分析了传统体素模型融合MODIS信号的不足;然后提出了基于体素节点模型的GNSS/MODIS信号紧耦合水汽层析算法,该算法将高分辨率MODIS PWV以三维信号的形式引入层析模型中;最后利用2016年7月徐州地区的15幅MODIS影像及同步GNSS数据对3种模型的层析结果质量进行了评估。试验结果表明:利用本文所提出的紧耦合算法,层析模型的平均有效观测信号数量提高了34.15%,层析结果平均RMSE(root mean square error)值降低了25.10%。此外,以邻近时刻探空站数据作为参考值,发现0~2 km的近地层,紧耦合算法的层析结果明显优于传统算法,这表明融合MODIS观测信号可改善近地层三维水汽场的重构质量。

关 键 词:GNSS水汽层析  MODIS  PWV  KRIGING插值  体素节点模型  探空站

Tightly coupled water vapor tomography algorithm for combining GNSS and MODIS signals
ZHANG Wenyuan,ZHANG Shubi,ZHENG Nanshan,DING Nan,LIU Xin,MA Pengxu.Tightly coupled water vapor tomography algorithm for combining GNSS and MODIS signals[J].Acta Geodaetica et Cartographica Sinica,2021,50(4):496-508.
Authors:ZHANG Wenyuan  ZHANG Shubi  ZHENG Nanshan  DING Nan  LIU Xin  MA Pengxu
Institution:(MNR Key Laboratory of Land Environment and Disaster Monitoring, China University of Mining and Technology, Xuzhou 221116, China;School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China;School of Geography, Geomatics and Planning, Jiangsu Normal University, Xuzhou 221116, China)
Abstract:Due to several significant advantages,including high-precision observation data,high spatio temporal resolution,and all-weather availability,GNSS tomography technology has become one of the most potential technologies for sensing the atmospheric water vapor.Currently,fusion of multi-source atmospheric remote sensing data has gradually become a research hotspot to make up for the geometric defects of GNSS signal in the tomography model.In this paper,the disadvantage of traditional model including the MODIS signals is analyzed at first.An improved tomography method,combining the GNSS and MODIS signals,based on the voxel node model is proposed,which introduces high-resolution MODIS PWV into the tomographic model in the form of three-dimensional signals.To assess the validity of the proposed algorithm,three experimental schemes are carried out using the 15 MODIS images and the simultaneous GNSS data derived from five GNSS stations over Xuzhou region.The experimental results show that the average number of effective signals is increased by 34.15%and the mean root mean square error(RMSE)of tomography results is decreased by 25.10%with the proposed tomography approach.Furthermore,the water vapor profiles retrieved from the three schemes are assessed using the reference profiles from the radiosonde data close to the acquisition time.It is found that in the lower layers from 0 to 2 km,the improved method retrieves better 3D distribution of water vapor than the traditional approach,which highlights that the reconstruction quality of 3D water vapor field near the surface can be optimized by including the MODIS signals.
Keywords:GNSS water vapor tomography  MODIS PWV  Kriging interpolation  voxel node model  radiosonde
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