Abstract
This Soil moisture is an important part of the surface water cycle. Effective monitoring of soil moisture is of great significance for weather forecasting, flood forecasting and crop growth. Existing soil moisture monitoring methods (such as drying weighing, remote sensing observation, hygrometer measurement, etc.) have high cost, low spatial and temporal resolution, damage to observation objects, time-consuming and laborious, and long repeated observation periods. With the rapid development of GNSS remote sensing, the GPS signal based on microwave L-band is used for soil moisture monitoring with the advantages of low cost, high time resolution, strong real-time and high automation, which has attracted the attention of many scholars. This paper intends to study the soil moisture inversion algorithm based on GPS signal-to-noise ratio. Firstly, based on the basic principle, the inversion process is given. The fitting phase is zero-processed and the fusion is performed according to the correlation coefficient. Finally, a linear model of humidity is established. The inversion of the PBO plan station data was carried out, and the soil moisture data provided by PBO was compared. The results confirmed that the accuracy and stability of soil moisture inversion using GPS signal-to-noise ratio were improved by zero processing and weighted fusion.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Jackson T, Schmugge J, Engman E (1996) Remote sensing applications to hydrology: oilmoisture. Hydrol Sci 41(4):517–530
Larson KM, Small EE et al (2008) Using GPS multipath to measure soil moisture fluctuations: initial results. GPS Solutions 12(3):173–177
Chew CC, Small EE, Larson KM (2014) Effects of near-surface soil moisture on GPS SNR data: development of a retrieval algorithm for soil moisture. IEEE Trans Geosci Remote Sens 51(1):537–543
Vey S, Wickert J, Guntner A et al (2013) Derivation of near-surface soil moisture from the GNSS site Sutherland, South Africa. In: Workshop of GNSS-Reflectometry, Brest, France
Liu J, Shao L, Zhang X et al (2007) Advance in GNSS-R studies and key technologies. Geomatics Inf Sci Wuhan Univ 32(11):955–960
Zhang Q, Jin S (2018) Application of GNSS SNR data in detection of volcanicplume. J Navig Positioning 6(1):15–20
Jin S, Zhang Q, Qian X (2017) New progress and application prospects of global navigation satellite system reflectometry (GNSS + R). Acta Geodaetica et Cartographica Sinica 46(10):1389–1398
Yan S, Gong J, Zhang X et al (2011) Ground based GNSS-R observations for soil moisture. Chin J Geophys 54(11):2735–2744
Zou W, Zhang B, Yang D et al (2016) Soil moisture retrieval using reflected signals of BeiDou GEO satellites. Acta Geodaetica et Cartographica Sinica 45(2):199–204
Ao M, Hu Y, Liu Y et al (2012) Inversion of soil moisture fluctuation based on signal-to-noise ratio of global positioning system. J Geomatics Sci Technol 29(2):66–69
Larson KM, Braun J, Small EE et al (2010) Use of GPS receivers as a soil moisture network for water cycle studies. IEEE J Sel Top Appl Earth Obs Remote Sens 3(1):91–99
Axelrad P, Larson K, Jones B (2005) Use of the correct satellite repeat period to characterize and reduce site-specific multipath errors. In: Proceedings of the ION GNSS, pp 2638–2648
Dai K, Zhang S, Zhang Q et al (2015) Preliminary results of snow depth monitoring based on GPS SNR. Sci Surv Mapp 40(12):112–115
Nan Y, Zhang S, Zhang Q et al (2015) Preliminary results of sea level change monitoring with GNSS-MR. Sci Surv Mapp 40(12):125–129
Ao M, Zhu J, Hu Y et al (2015) Comparative experiments on soil moisture monitoring with GPS SNR observations. Geomatics Inf Sci Wuhan Univ 40(1):117–120
Acknowledgments
We gratefully acknowledge the provision of data, equipment, and engineering services by the Plate Boundary Observatory operated by UNAVCO for Earth Scope. This work was supported by China Desert Meteorological Science Research Foundation (Sqj2017002), National Science Foundation of China (41731066, 41674001, 41104019) and the Special Fund for Basic Scientific Research of Central Colleges (310826172202).
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Zhao, G., Zhang, S., Zhang, Q., Zhang, J., Wang, L., Wang, T. (2019). Ground-Based GPS for Soil Moisture Monitoring. In: Sun, J., Yang, C., Yang, Y. (eds) China Satellite Navigation Conference (CSNC) 2019 Proceedings. CSNC 2019. Lecture Notes in Electrical Engineering, vol 562. Springer, Singapore. https://doi.org/10.1007/978-981-13-7751-8_2
Download citation
DOI: https://doi.org/10.1007/978-981-13-7751-8_2
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-7750-1
Online ISBN: 978-981-13-7751-8
eBook Packages: EngineeringEngineering (R0)