ABSTRACT
The global navigation satellite system-interferometric reflectometry (GNSS-IR) technique has emerged as an effective coastal sea-level monitoring solution. However, the accuracy and stability of GNSS-IR sea-level estimation based on quadratic fitting are limited by the retrieval range of reflector height (RH range) and satellite-elevation range, reducing the flexibility of this technology. This study introduces a new GNSS-IR sea-level estimation model that combines local mean decomposition (LMD) and Lomb-Scargle periodogram (LSP). LMD can decompose the signal-to-noise ratio (SNR) arc into a series of signal components with different frequencies. The signal components containing information from the sea surface are selected to construct the oscillation term, and its frequency is extracted by LSP. To this end, observational data from SC02 sites in the United States are used to evaluate the accuracy level of the model. Then, the performance of LMD and the influence of noise on retrieval results are analyzed from two aspects: RH ranges and satellite-elevation ranges. Finally, the sea-level variation for one consecutive year is estimated to verify the stability of the model in long-term monitoring. The results show that the oscillation term obtained by LMD has a lower noise level than other signal separation methods, effectively improving the accuracy of retrieval results and avoiding abnormal values. Moreover, it still performs well under loose constraints (a wide RH range and a high-elevation range). In one consecutive year of retrieval results, the new model based on LMD has a significant improvement effect over quadratic fitting, and the root mean square error and mean absolute error of retrieval results obtained in each month on average are improved by 8.34% and 8.87%, respectively.
ABSTRACT
Urban development in developing regions increases ecological and environmental pressures. Few annual ecological studies have been conducted on tourist-oriented cities. Guilin is famous as an international tourist destination in Chine. Analyzing its coupling coordination between urbanization and ecology is vital for subsequent sustainable development. This paper constructed a night-time light index (NTLI) based on DMSP/OLS, NPP/VIIRS night-time light data in response to these problems. The remote sensing ecological index (RSEI) model was established in this study by using four indexes: greenness, wetness, dryness and heat. The coupling coordination degree model (CCDM) was built. From the dynamic time-series changes of CCDM, the urban development and ecological environment of the urban area of Guilin, from 2000 to 2020, were analyzed. The results showed that the urban area of Guilin's urbanization had developed rapidly over the past 20 years. NTLI in 2020 was 7.72 times higher than in 2000. The overall ecological quality of the main urban area of Guilin has improved significantly, while local ecological pressure in Lingui District has increased. CCDM has shifted from low to high coupling coordination, and the relationship between urban development and the ecological environment has improved. The method of annual spatial-temporal analysis of urban ecology in this paper can be applied in similar studies on other cities, and the results obtained for Guilin have reference value for future urban planning and environmental protection work.
