京津冀地区GNSS对流层延迟空间插值研究
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摘要
对流层延迟差异影响合成孔径雷达干涉测量技术(InSAR)形变测量精度;水汽的变化影响天气变化.对流层延迟与水汽具有较好的对应,因此有必要开展全球导航卫星系统(GNSS)对流层延迟的插值研究.以京津冀地区为例,针对GNSS对流层延迟,开展对流层延迟的空间插值研究.首先开展了GNSS对流层延迟与水汽的比较分析,两者存在显著正相关特性,相关性超过91.7%,论证了对流层延迟取代水汽的可行性.然后利用反距离权重法对京津冀地区2016年9月至2017年8月的12组GNSS测站对流层延迟进行空间插值,通过提取插值点对流层延迟与GNSS站点对流层延迟比较验证空间插值精度.全年数据平均偏差最大为1.12cm,均方根误差最大为0.89cm;未发生降水过程平均偏差最大为1.25cm,均方根误差最大为0.82cm;发生降水过程平均偏差最大为1.08cm,均方根误差最大为1.38cm.京津冀平原区域的GNSS对流层延迟空间插值结果精度满足气象等应用要求,可为气象预报和InSAR大气校正提供参考.
The difference of zenith tropospheric delay(ZTD)during different periods affects the accuracy of InSAR deformation;changes in precipitable water vapor(PWV)affect weather changes.The ZTD has a good correlation with PWV,so it is necessary to carry out an interpolation study of GNSS ZTD.Taking Beijing-Tianjin-Hebei region as an example,the spatial interpolation of ZTD is studied for GNSS ZTD.Firstly,the comparative analysis of ZTD and PWV in GNSS is carried out.The two have significant positive correlation characteristics,and the correlation is larger than 91.7%.The feasibility of ZTD to replace PWV is demonstrated.Then,using the inverse distance weighting method,that of 12 groups of GNSS stations in Beijing-Tianjin-Hebei region from September 2016 to August 2017 are spatially interpolated.The spatial interpolation accuracy is verified by extracting the ZTD of the interpolation points and that of the GNSS station.The average deviation of the annual data is1.12 cm,the root mean square error is 0.89 cm;the average deviation of non-precipitation is1.25 cm,the root mean square error is 0.82 cm,and the average deviation of precipitation is 1.08 cm,the root mean square error is 1.38 cm.The GNSS ZTD spatial interpolation results in as a Beijing-Tianjin-Hebei plain area meet the meteorological requirements,which can provide as a reference for meteorological forecasting and InSAR atmospheric correction.
The difference of zenith tropospheric delay(ZTD)during different periods affects the accuracy of InSAR deformation;changes in precipitable water vapor(PWV)affect weather changes.The ZTD has a good correlation with PWV,so it is necessary to carry out an interpolation study of GNSS ZTD.Taking Beijing-Tianjin-Hebei region as an example,the spatial interpolation of ZTD is studied for GNSS ZTD.Firstly,the comparative analysis of ZTD and PWV in GNSS is carried out.The two have significant positive correlation characteristics,and the correlation is larger than 91.7%.The feasibility of ZTD to replace PWV is demonstrated.Then,using the inverse distance weighting method,that of 12 groups of GNSS stations in Beijing-Tianjin-Hebei region from September 2016 to August 2017 are spatially interpolated.The spatial interpolation accuracy is verified by extracting the ZTD of the interpolation points and that of the GNSS station.The average deviation of the annual data is1.12 cm,the root mean square error is 0.89 cm;the average deviation of non-precipitation is1.25 cm,the root mean square error is 0.82 cm,and the average deviation of precipitation is 1.08 cm,the root mean square error is 1.38 cm.The GNSS ZTD spatial interpolation results in as a Beijing-Tianjin-Hebei plain area meet the meteorological requirements,which can provide as a reference for meteorological forecasting and InSAR atmospheric correction.
引文
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[2]崔喜爱,曾琪明,童庆禧,等.重轨星载InSAR测量中的大气校正方法综述[J].遥感技术与应用,2014,29(1):9-17.
[3]张杏清,周元华.GPS与MODIS数据融合的D-InSAR大气延迟改正方法研究[J].测绘通报,2015(8):13-18.
[4]刘严萍,王勇,张立辉.基于多要素大气延迟改正的InSAR地面沉降监测研究[J].灾害学,2013,28(3):38-41.
[5]陈元洪,郭际明,陈品祥,等.基于CORS的DInSAR大气延迟校正方法研究[J].大地测量与地球动力学,2015,35(6):1026-1030.
[6]黄长军,陈元洪,周吕.不同空间插值对InSAR大气延迟改正影响研究[J].北京测绘,2018,32(6):629-632.
[7]WILLIAMS S D P,BOCK Y,FANG P.Integrated satellite interferometry:tropospheric noise,GPS estimates and implications for interferometric synthetic aperture radar products[J].Journal of Geophysical Research,1998,1032(B11):27051-27068.
[8]王勇,刘严萍,李江波,等.GPS和无线电探空的水汽变化与PM2.5/PM10变化的相关性研究[J].武汉大学学报(信息科学版),2016,41(12):1626-1631.
[9]金鑫,施昆,陈云波,等.GPS可降水汽含量在强降雨过程中的特征分析[J].全球定位系统,2018,43(2):65-71.
[10]申建华,赵兴旺,许九靖,等.基于超快速星历进行实时反演大气水汽总量的可行性研究[J].全球定位系统,2018,43(1):54-59.
[11]刘严萍,王勇,李江波.北京APEC会议期间GPS水汽与PM2.5/PM10的相关性比较[J].灾害学,2015(3):26-28,42.
[12]王勇,刘严萍,李江波,等.河北省GPS水汽与PM2.5质量浓度的比较研究[J].大地测量与地球动力学,2016,36(1):40-42.
[13]张双成,张鹏飞,范朋飞.GPS对流层改正模型的最新进展及对比分析[J].大地测量与地球动力学,2012,32(2):91-95.
[14]张双成,赵立都,吕旭阳,等.GPS水汽在雾霾天气监测中的应用研究[J].武汉大学学报(信息科学版),2018,43(3):451-456.
[15]王勇,郝振航,任栋,等.中国大陆地区GNSS对流层延迟与PM2.5浓度的相关性研究[J].灾害学,2017,32(4):6-10.
[16]刘严萍,王勇.基于GNSS技术的城市灾害监测研究[M].北京:中国建筑工业出版社,2016.
[17]姚顽强,陈卫南,李涛,等.卫星轨道和大气延迟误差联合校正的山地DEM提取[J].测绘科学,2016,41(8):54-58,66.