부산대학교 도서관

The Amazon basin, one of the world's largest and most vital ecosystems, presents a formidable challenge for accurately mapping its extensive surface water extent and dynamic seasonal and long-term variations. This challenge arises from the region's dense vegetation and persistent cloud coverage, limiting the applicability of conventional remote sensing technologies. Spaceborne global navigation satellite system reflectometry (GNSS-R) offers a promising avenue to complement existing techniques, due to its distinctive sensitivity to surface water, coupled with its vegetation and cloud penetration and high spatio-temporal resolution. A trackwise method is developed for mapping surface water using data from cyclone GNSS (CYGNSS). Over a period of more than six years, from April 2017 to May 2023, monthly 3-km binary water/land maps covering the entire basin are produced. Comparative analyses are conducted using a comprehensive set of classification metrics with datasets derived from optical, passive microwave, and radar missions. The findings revealed that these products tend to underestimate the full extent of inundation across the basin. In contrast, CYGNSS, while exhibiting a slight tendency to overestimate surface water due to its heightened sensitivity to water and wet soils, provides valuable insights into inundation dynamics even in densely vegetated areas. Furthermore, monthly inundated area estimates are compared with water levels measured by four gauging stations across the basin. The results demonstrated a strong agreement between them and a maximum correlation coefficient of 0.74. Overall, the monthly water maps produced in this study hold significant promise for a wide range of hydrological investigations and practical applications.