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Global Navigation Satellite System interferometric reflectometry (GNSS-IR), a new and inexpensive technique, has become available to the broader scientific community for detecting surface environmental information, such as soil moisture, snow depth and vegetation growth. However, there have been limited experiments focusing on the potential of crop height retrieval, especially the performance evaluation of BeiDou Navigation Satellite System (BDS) with other GNSS. Accuracy and reliability are challenging to achieve with traditional methods utilizing a single GNSS, and few measured verification data. In this study, an improved method that includes segmentation processing and multi-GNSS fusion is proposed based on GPS/GLONASS/Galileo/BDS multi-frequency data. Furthermore, experiments were carried out on a farmland in Fengqiu County, Henan Province, China. The results show that the height retrievals from four GNSS were in good agreement with the in situ observations during the whole growth cycle of the wheat after overwintering. Meanwhile, the retrievals based on the proposed method exhibited greater correspondence than the single frequency results, the correlation coefficient was increased and the root-mean-square error (RMSE) was reduced, respectively. Therefore, this study illustrates the feasibility of the proposed method to precisely estimate wheat height and its potential for use in the early warning of wheat lodging based on GNSS-IR. [ABSTRACT FROM AUTHOR]

• A method of retrieving plant height and phonological information by GNSS is proposed. • The retrieval heights are in relatively high agreement with in-situ values, with RMSE of less than 9 cm. • The difference between estimated phenology metric dates and reference value from NDVI is within 8 days. • High correlations observed between GNSS-IR observations and NDVI and low to LAI. Monitoring vegetation growth utilizing the Global Navigation Satellite System-interferometric reflectometry (GNSS-IR) technology has obtained widespread attention in recent years. GNSS-IR based approaches demonstrate the advantageous characteristics of high temporal resolution while maintaining cost-effectiveness. Most existing studies generally utilize reflected signals to retrieve the plant height and vegetation water content, while few studies focus on vegetation phenology and yield. In this study, both phenology metric dates and plant height of wheat were extracted using reflected signals data from GPS and BeiDou Navigation Satellite System (BDS) in a wheat farmland, located at northeast of Henan, China. The results showed that there was reasonable consistency between the retrieval heights and in-situ measurements, with the correlation coefficient of 0.836 for GPS and 0.868 for BDS. The damping coefficient calculated by signal-to-noise ratio (SNR) presented obvious characteristics during different wheat growth stages and the trends of the damping coefficient were basically consistent with that of the normalized difference vegetation index (NDVI). When taking a lag between the leaf area index (LAI) and the damping coefficient into consideration, the correlation was greatly increased. Moreover, the phenology metrics dates extracted by the damping coefficient were close to those estimated by NDVI with errors less than 8 days. Hence, this research preliminarily proves the feasibility of obtaining the wheat phenological period by using GNSS-IR technology. [ABSTRACT FROM AUTHOR]

Soil moisture monitoring using Global Navigation Satellite System (GNSS) multipath signals has gained continuous interests in recent years. However, traditional GNSS-interferometric reflectometry (GNSS-IR) soil moisture retrieval methods generally utilize a single frequency or single satellite, which fail to take full advantage of different and complementary of satellite signals with different frequencies. An improved algorithm for soil moisture retrieval based on principal component analysis (PCA) and entropy method using multi-frequency amplitude and phase offset fusion data was proposed in this research. The performance of the proposed soil moisture retrieval method was evaluated using data recorded by Plate Boundary Observatory (PBO) H2O networks and a self-built site in Henan, China. The results from GPS and BeiDou both showed that the retrieved soil moisture has a stronger correlation with in situ soil moisture, which can better reflect the fluctuation of ground truth measurements. Compared with the traditional method, the retrieval accuracy of the proposed method in terms of root-mean-square error (RMSE) was improved by 50.93%, and the average correlation coefficient were increased by 11.71%. This research proved that the proposed method could effectively improve retrieval accuracy due to the increasing number of frequencies and tracks clustering. Moreover, this study has illustrated the feasibility of BeiDou signals to precisely estimate surface soil moisture. [ABSTRACT FROM AUTHOR]