Research on GNSS-IR soil moisture retrieval based on random forest algorithm

Author:

Zheng NaiquanORCID,Chai Hongzhou,Wang Zhihao,Pu Dongdong,Zhang Qiankun

Abstract

Abstract Soil moisture (SM) retrieval is of great significance in climate, agriculture, ecology, hydrology, and natural disaster monitoring, and it is one of the essential hydrometeorological parameters studied in the world at present. With the continuous development of the global navigation satellite system (GNSS), a technique called GNSS interferometric reflectometry (GNSS-IR) became widely used in ground SM inversion. Therefore, based on the frequency, amplitude and phase of signal-to-noise ratio residuals (δSNR), this study takes P037 and P043 stations set by UNAVCO in the United States as examples and develops the research of SM inversion from random forest regression (RFR) prediction. The experimental results show that the retrieval accuracy of SM under different practical schemes can be in descending order: L1 + L2 dual frequency combination > L2 single frequency > L1 single frequency. It is confirmed that the experimental scheme based on the L1 + L2 dual-frequency combination is beneficial to the inversion of SM. In the L1 + L2 dual-frequency combination, the prediction set accuracy of the P037 station is as follows: R is 0.796, root mean square error (RMSE) is 0.032 cm3 cm−3, ME is 0.002 cm3 cm−3. The prediction accuracy of the P043 station is as follows: R is 0.858, RMSE is 0.039 cm3 cm−3, ME is −0.009 cm3 cm−3. Among them, the RMSE of the L1 + L2 dual-frequency combination of the two stations has an improvement effect of 13%–37% compared with their single-frequency, which has a noticeable improvement effect. The difference between the SM retrieved by GNSS-IR and the reference value of PBO-H2O is concentrated around 0, further showing the accuracy of SM retrieved by GNSS-IR technology. To sum up, this study considers that SM retrieval based on the RFR model has good reliability and accuracy, which makes GNSS-IR technology an efficient means for SM retrieval. With the continuous improvement of the GNSS system and technology, the application of GNSS-IR technology in SM will become broader.

Funder

National Natural Science Foundation of China

Publisher

IOP Publishing

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3