CORS stations for integrated monitoring of surface environmental parameters
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摘要: 卫星导航定位连续运行参考站(continuously operating reference stations，CORS)系统作为GNSS与网络通信技术结合发展出的新兴导航定位CORS系统，具有快速高效、高精度、网络化等优点，不仅可以测量地表位置及运动，还可以借助GNSS信号的折射与反射特征监测地表环境参数变化情况. 本文提出一种将CORS站用于“积雪深度、土壤湿度、大气水汽、地表形变”的地表环境多参数综合监测体系，用以拓展CORS站在生态环境中的广泛应用. 以齐齐哈尔市CORS站BFQE为实验案例，首先获取实验时段中CORS站接收的GNSS观测数据(含信噪比(signal to noise ratio，SNR)数据)、星历数据及气象数据对其进行预处理；其次对重采样的SNR数据采用非线性最小二乘及Lomb-Scargle谱分析方法解译特定时间段的浅层土壤湿度及地表积雪深度；然后通过联测远距离国际地球动力学服务机构站(International GPS Service for Geodynamics，IGS)采用相对定位技术获取测站的地表形变序列与大气水汽序列；最后，结合上述多种地表环境参数结果进行相关性分析，获得参数间的响应关系. 实验结果表明：CORS站用于地表环境综合监测能够有效地监测多参数时间变化，反演得到的环境参数之间具有一定的响应关系. 大气水汽含量会影响降雨的时空分布和强度，大气水汽反演值与降雨在趋势上呈现高度相关；在积雪时段，大气水汽的增加伴随着积雪深度的增加；大气水汽增加形成的降雨是土壤湿度的主要来源，解译土壤湿度总是在强降雨后呈现上升趋势，基于单星的土壤湿度与实测数据平均相关性为0.75，多星融合解译结果的相关性达到0.89，土壤含水率的均方根误差(root mean squared error，RMSE)为0.87%；地表形变时间序列在北(north，N)、东(east，E)方向形变较为稳定，天顶(up，U)方向的形变与大气水汽、积雪深度和土壤湿度存在一定的响应性波动.Abstract: Continuously operating reference stations (CORS), as an emerging navigation and positioning continuously operating reference station system developed by combining Global Navigation Satellite System (GNSS) and network communication technology, has the advantages of fast, efficient, high-precision, networked and so on. It can not only measure the position and movement of the ground surface, but also monitor the changes of environmental parameters on the ground surface with the help of refractive and reflective features of GNSS signals. In this paper, we propose a multi-parameter integrated monitoring system of surface environment by using CORS station for “snow depth, soil moisture, atmospheric water vapor, and surface deformation”, which is used to expand the wide application of CORS station in ecological environment. Taking Qiqihar CORS station BFQE as an experimental case, firstly, the GNSS observation data (including SNR data), ephemeris data and meteorological data received by the CORS station during the experimental period are obtained and pre-processed; secondly, the non-linear least squares and Lomb-Scargle spectral analysis methods are applied to the re-sampled SNR data to decipher the shallow soil humidity and surface snow depth in the specific period. Then, the surface deformation sequence and atmospheric water vapor sequence of the station were obtained by the International GPS service for Geodynamics (IGS) using the relative positioning technique; finally, the correlation analysis was carried out by combining the results of the above surface environmental parameters to obtain the response relationship between the parameters. The experimental results show that the CORS station used for integrated monitoring of the surface environment can effectively monitor the temporal changes of multiple parameters, and the environmental parameters obtained from the inversion have a certain response relationship with each other. The atmospheric water vapor content affects the spatial and temporal distribution and intensity of rainfall, and the atmospheric water vapor inversion values are highly correlated with rainfall in trend. During the snowy period, the increase in atmospheric water vapor is accompanied by an increase in snow depth during snow accumulation periods. Rainfall formed by the increase of atmospheric water vapor is the main source of soil moisture, and the interpreted soil moisture always shows an increasing trend after heavy rainfall. The average correlation between soil moisture and measured data based on single stars is 0.75, and the correlation of the results of multi-satellite fusion interpretation reaches 0.89, and the root-mean-square error of soil moisture content is 0.87%. The surface deformation time series is stable in the north (N) and east (E) directions, and the deformation in the up (U) direction has some responsive fluctuations with atmospheric water vapor, snow depth and soil moisture.
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