Using BDS MEO and IGSO Satellite SNR Observations to Measure Soil Moisture Fluctuations Based on the Satellite Repeat Period
Soil moisture is an important geophysical parameter for studying terrestrial water and energy cycles. It has been proven that Global Navigation Satellite System Interferometry Reflectometry (GNSS-IR) can be applied to monitor soil moisture. Unlike the Global Positioning System (GPS) that has only me...
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| Format: | Article |
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MDPI AG
2021-10-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/19/3967 |
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| author | Fei Shen Mingming Sui Yifan Zhu Xinyun Cao Yulong Ge Haohan Wei |
| author_facet | Fei Shen Mingming Sui Yifan Zhu Xinyun Cao Yulong Ge Haohan Wei |
| author_sort | Fei Shen |
| collection | DOAJ |
| description | Soil moisture is an important geophysical parameter for studying terrestrial water and energy cycles. It has been proven that Global Navigation Satellite System Interferometry Reflectometry (GNSS-IR) can be applied to monitor soil moisture. Unlike the Global Positioning System (GPS) that has only medium earth orbit (MEO) satellites, the Beidou Navigation Satellite System (BDS) also has geosynchronous earth orbit (GEO) satellites and inclined geosynchronous satellite orbit (IGSO) satellites. Benefiting from the distribution of three different orbits, the BDS has better coverage in Asia than other satellite systems. Previous retrieval methods that have been confirmed on GPS cannot be directly applied to BDS MEO satellites due to different satellite orbits. The contribution of this study is a proposed multi-satellite soil moisture retrieval method for BDS MEO and IGSO satellites based on signal-to-noise ratio (SNR) observations. The method weakened the influence of environmental differences in different directions by considering satellite repeat period. A 30-day observation experiment was conducted in Fengqiu County, China and was used for verification. The satellite data collected were divided according to the satellite repeat period, and ensured the response data moved in the same direction. The experimental results showed that the BDS IGSO and MEO soil moisture estimation results had good correlations with the in situ soil moisture fluctuations. The BDS MEO B1I estimation results had the best performance; the estimation accuracy in terms of correlation coefficient was 0.9824, root mean square error (RMSE) was 0.0056 cm<sup>3</sup>cm<sup>−3</sup>, and mean absolute error (MAE) was 0.0040 cm<sup>3</sup>cm<sup>−3</sup>. The estimations of the BDS MEO B1I, MEO B2I, and IGSO B2I performed better than the GPS L1 and L2 estimations. For the BDS IGSO satellites, the B1I signal was more suitable for soil moisture retrieval than the B2I signal; the correlation coefficient was increased by 19.84%, RMSE was decreased by 42.64%, and MAE was decreased by 43.93%. In addition, the BDS MEO satellites could effectively capture sudden rainfall events. |
| first_indexed | 2024-03-10T06:52:01Z |
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| id | doaj.art-535c7d92ac9e4ef98e7158151247140a |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T06:52:01Z |
| publishDate | 2021-10-01 |
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| spelling | doaj.art-535c7d92ac9e4ef98e7158151247140a2023-11-22T16:43:30ZengMDPI AGRemote Sensing2072-42922021-10-011319396710.3390/rs13193967Using BDS MEO and IGSO Satellite SNR Observations to Measure Soil Moisture Fluctuations Based on the Satellite Repeat PeriodFei Shen0Mingming Sui1Yifan Zhu2Xinyun Cao3Yulong Ge4Haohan Wei5School of Geography, Nanjing Normal University, Nanjing 210023, ChinaCollege of Civil Engineering, Nanjing Forestry University, Nanjing 210037, ChinaSchool of Geography, Nanjing Normal University, Nanjing 210023, ChinaSchool of Geography, Nanjing Normal University, Nanjing 210023, ChinaSchool of Marine Science and Engineering, Nanjing Normal University, Nanjing 210023, ChinaCollege of Civil Engineering, Nanjing Forestry University, Nanjing 210037, ChinaSoil moisture is an important geophysical parameter for studying terrestrial water and energy cycles. It has been proven that Global Navigation Satellite System Interferometry Reflectometry (GNSS-IR) can be applied to monitor soil moisture. Unlike the Global Positioning System (GPS) that has only medium earth orbit (MEO) satellites, the Beidou Navigation Satellite System (BDS) also has geosynchronous earth orbit (GEO) satellites and inclined geosynchronous satellite orbit (IGSO) satellites. Benefiting from the distribution of three different orbits, the BDS has better coverage in Asia than other satellite systems. Previous retrieval methods that have been confirmed on GPS cannot be directly applied to BDS MEO satellites due to different satellite orbits. The contribution of this study is a proposed multi-satellite soil moisture retrieval method for BDS MEO and IGSO satellites based on signal-to-noise ratio (SNR) observations. The method weakened the influence of environmental differences in different directions by considering satellite repeat period. A 30-day observation experiment was conducted in Fengqiu County, China and was used for verification. The satellite data collected were divided according to the satellite repeat period, and ensured the response data moved in the same direction. The experimental results showed that the BDS IGSO and MEO soil moisture estimation results had good correlations with the in situ soil moisture fluctuations. The BDS MEO B1I estimation results had the best performance; the estimation accuracy in terms of correlation coefficient was 0.9824, root mean square error (RMSE) was 0.0056 cm<sup>3</sup>cm<sup>−3</sup>, and mean absolute error (MAE) was 0.0040 cm<sup>3</sup>cm<sup>−3</sup>. The estimations of the BDS MEO B1I, MEO B2I, and IGSO B2I performed better than the GPS L1 and L2 estimations. For the BDS IGSO satellites, the B1I signal was more suitable for soil moisture retrieval than the B2I signal; the correlation coefficient was increased by 19.84%, RMSE was decreased by 42.64%, and MAE was decreased by 43.93%. In addition, the BDS MEO satellites could effectively capture sudden rainfall events.https://www.mdpi.com/2072-4292/13/19/3967SNRBDSMEOIGSOsoil moisture retrieval |
| spellingShingle | Fei Shen Mingming Sui Yifan Zhu Xinyun Cao Yulong Ge Haohan Wei Using BDS MEO and IGSO Satellite SNR Observations to Measure Soil Moisture Fluctuations Based on the Satellite Repeat Period Remote Sensing SNR BDS MEO IGSO soil moisture retrieval |
| title | Using BDS MEO and IGSO Satellite SNR Observations to Measure Soil Moisture Fluctuations Based on the Satellite Repeat Period |
| title_full | Using BDS MEO and IGSO Satellite SNR Observations to Measure Soil Moisture Fluctuations Based on the Satellite Repeat Period |
| title_fullStr | Using BDS MEO and IGSO Satellite SNR Observations to Measure Soil Moisture Fluctuations Based on the Satellite Repeat Period |
| title_full_unstemmed | Using BDS MEO and IGSO Satellite SNR Observations to Measure Soil Moisture Fluctuations Based on the Satellite Repeat Period |
| title_short | Using BDS MEO and IGSO Satellite SNR Observations to Measure Soil Moisture Fluctuations Based on the Satellite Repeat Period |
| title_sort | using bds meo and igso satellite snr observations to measure soil moisture fluctuations based on the satellite repeat period |
| topic | SNR BDS MEO IGSO soil moisture retrieval |
| url | https://www.mdpi.com/2072-4292/13/19/3967 |
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