Abstract
Vegetation is a significant link between soil, moisture, organisms and the atmosphere. Recording vegetation changes has important significance in climate change. Traditional remote sensing has the drawback with low temporal resolution in monitoring vegetation, while GNSS multipath can provide a more complete vegetation growth process. Firstly, the multipath characteristics of GNSS are analyzed, and then basic principles and processes of multipath interpret vegetation growth are introduced in detail. Finally, GNSS continuous tracking stations P476 and P542 deployed in California are used for analysis. The preliminary results show that, at P476, the correlation coefficient between multipath and Normalized Difference Vegetation Index (NDVI) is 0.64 (When the lag time is considered, the correlation can reach 0.88), and similar results are obtained at P542. The results show that GNSS multipath interpret vegetation growth process is effective. In phenology, GNSS multipath estimated phenology variables have later growth season start time and peak time, and shorter season length, mainly affected by lag time.
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Acknowledgements
We gratefully acknowledge the provision of data, equipment, and engineering services by the Plate Boundary Observatory operated by UNAVCO for Earth Scope. The authors thank Carolyn Roesler and Kristine M. Larson for providing Software Tools for GNSS Interferometric Reflectometry (GNSS-IR) by (https://www.ngs.noaa.gov/gps-toolbox/GNSS-IR.htm). This work was supported by Institute of Desert Meteorology in China Meteorological Administration (Ground-based GNSS monitoring snow depth in Altay, Sqj2017002) and. Thanks to anonymous reviewers for providing valuable comments and suggestions in this paper!
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Peng, J., Zhang, S., Zhang, J., Liu, Q., Wang, T. (2020). Preliminary Research on GNSS Multipath Interpret the Process of Vegetation Growth. In: Sun, J., Yang, C., Xie, J. (eds) China Satellite Navigation Conference (CSNC) 2020 Proceedings: Volume I. CSNC 2020. Lecture Notes in Electrical Engineering, vol 650. Springer, Singapore. https://doi.org/10.1007/978-981-15-3707-3_18
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DOI: https://doi.org/10.1007/978-981-15-3707-3_18
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