测绘学报 ›› 2026, Vol. 55 ›› Issue (3): 451-464.doi: 10.11947/j.AGCS.2026.20250365

• 大地测量学与导航 • 上一篇    下一篇

顾及地表反射率不确定性的风云三号GNSS-R洪涝监测方法:以8·2广东极端暴雨灾害为例

马中民1(), 张双成1(), 周昕1, 刘奇2, 刘宁1, 王恒利1   

  1. 1.长安大学地质工程与测绘学院,陕西 西安 710054
    2.西安科技大学测绘科学与技术学院,陕西 西安 710054
  • 收稿日期:2025-09-05 修回日期:2026-03-25 出版日期:2026-04-16 发布日期:2026-04-16
  • 通讯作者: 张双成 E-mail:zhongminma@chd.edu.cn;shuangcheng369@chd.edu.cn
  • 作者简介:马中民(1997—),男,博士生,研究方向为GNSS反射测量理论与应用。E-mail:zhongminma@chd.edu.cn
  • 基金资助:
    国家自然科学基金(42474028; 42504042);中央高校基本科研业务费专项资金-长安大学优秀博士学位论文培育资助项目(300102263715);中国科协青年人才托举工程博士生专项计划(156-O-420-0000115-1)

A flood monitoring method using FY-3 GNSS-R accounting for surface reflectivity uncertainty: a case study of the August 2 Guangdong rainstorm disaster

Zhongmin MA1(), Shuangcheng ZHANG1(), Xin ZHOU1, Qi LIU2, Ning LIU1, Hengli WANG1   

  1. 1.College of Geological Engineering and Geomatics, Chang'an University, Xi'an 710054, China
    2.College of Geomatics, Xi'an University of Science and Technology, Xi'an 710054, China
  • Received:2025-09-05 Revised:2026-03-25 Online:2026-04-16 Published:2026-04-16
  • Contact: Shuangcheng ZHANG E-mail:zhongminma@chd.edu.cn;shuangcheng369@chd.edu.cn
  • About author:MA Zhongmin (1997—), male, PhD candidate, majors in GNSS reflectometry theory and applications. E-mail: zhongminma@chd.edu.cn
  • Supported by:
    The National Natural Science Foundation of China(42474028; 42504042);The Special Fund for Basic Scientific Research of Central Universities-The Cultivation Program for Outstanding Doctoral Dissertations of Chang'an University(300102263715);The Doctoral Student Special Program of The Young Elite Scientists Sponsorship Program of the China Association for Science and Technology(156-O-420-0000115-1)

摘要:

2025年8月2日至6日,广东经历了21世纪以来第5强、8月最强的极端暴雨,持续强降水引发严重洪涝灾害,造成重大人员伤亡和财产损失。星载全球导航卫星系统反射(GNSS-R)技术因其重访周期短、不受云雨影响,已在洪涝监测中展现出重要应用潜力。本文评估了我国自主研制的风云三号系列卫星GNSS-R数据在暴雨洪涝应急监测中的表现。首先,介绍了地表反射率(SR)的计算方法及多GNSS系统SR融合模型。针对传统“硬阈值”方法易受高土壤湿度干扰的问题,提出了一种改进的考虑SR模糊过渡的洪涝探测方法。该方法利用Sigmoid函数将连续的SR映射为地表淹没概率,并根据置信区间引入基于不确定性的动态阈值方法,将研究区划分为高置信水区、高置信非水区和不确定区。随后,通过与Cyclone GNSS(CYGNSS)地表水产品进行对比,利用混淆矩阵评估了本文方法的有效性。结果表明,与传统的硬阈值方法相比,本文方法在洪涝前后地表水探测的总体精度分别提高了10.38%和10.96%,有效减少了因土壤湿度偏高而产生的假阳性结果。进一步与SWOT和GFM产品对比发现,三者探测的洪涝范围基本一致。综上,本文结果验证了风云三号GNSS-R在洪涝应急监测中的能力,并为利用星载GNSS-R开展洪涝探测提供了一种方法。

关键词: 风云三号, 星载GNSS-R, GNOS-Ⅱ, 洪涝监测, 8·2广东极端暴雨

Abstract:

From August 2 to 6, 2025, Guangdong province experienced the fifth most intense and the strongest August rainstorm of 21st century. The prolonged extreme precipitation triggered severe flooding, causing significant casualties and economic losses. Spaceborne global navigation satellite system reflectometry (GNSS-R) has shown great potential for flood monitoring due to its short revisit cycle and insensitivity to clouds and rainfall. This study presents the first evaluation of GNSS-R data from China's Fengyun-3 (FY-3) satellite series for emergency flood monitoring during the August 2 Guangdong extreme rainstorm event. The calculation of surface reflectivity (SR) and the multi-GNSS SR fusion model are introduced. To address the limitations of traditional “hard threshold” methods, which are often affected by high soil moisture, an improved flood detection approach considering the fuzzy transition of SR is proposed. The method applies a Sigmoid function to map continuous SR values into surface inundation probabilities. Based on the confidence interval of these probabilities, an uncertainty-driven dynamic threshold is introduced to classify the study area into high-confidence water, high-confidence non-water, and uncertain regions. The effectiveness of the proposed method was evaluated by comparison with the cyclone GNSS (CYGNSS) surface water product using a confusion matrix. Results show that, compared with the traditional “hard threshold” method, the proposed approach improved the overall detection accuracy of surface water by 10.38% and 10.96% before and after the flood, respectively, effectively reducing false positives caused by high soil moisture. Further comparison with surface water and ocean topography (SWOT) and global flood monitoring (GFM) products indicates that the detected flood extents are largely consistent among the three datasets. In summary, the results demonstrate the capability of FY-3 GNSS-R for emergency flood monitoring and provide a new methodological framework for flood detection using spaceborne GNSS-R observations.

Key words: FY-3, spaceborne GNSS-R, GNOS-Ⅱ, flood monitoring, August 2 Guangdong extreme rainstorm

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