Freeze-Thaw Effects on SAR-based Glacial Lake Mapping： Gongcuo and Langcuo Case Study

WU Renzhe; LIU Guoxiang; CAI Jiaxin

doi:10.11834/jrs.20265336

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Freeze-Thaw Effects on SAR-based Glacial Lake Mapping： Gongcuo and Langcuo Case Study
Pages: 1-13(2026)
Received：11 September 2025，

Online First：27 February 2026，
DOI： 10.11834/jrs.20265336
稿件说明：

移动端阅览

吴仁哲，刘国祥，蔡佳欣.XXXX.季节性冻融对SAR提取冰川湖精度的影响——基于贡措与郎措.遥感学报，XX（XX）： 1-13 DOI： 10.11834/jrs.20265336.

WU Renzhe，LIU Guoxiang，CAI Jiaxin. XXXX. Freeze-Thaw Effects on SAR-based Glacial Lake Mapping： Gongcuo and Langcuo Case Study. National Remote Sensing Bulletin， XX（XX）：1-13 DOI： 10.11834/jrs.20265336.

摘要

在全球变暖背景下，冰川湖扩张所诱发的溃决风险日益加剧，持续、精准的冰川湖监测已成为灾害防控的关键。现如今，合成孔径雷达（SAR）凭借全天时、全天候及对云雾穿透的独特优势，已在复杂山区冰川湖研究中广泛应用；其高时间分辨率更使捕捉冰川湖季节动态变化成为可能。然而，SAR后向散射特征受冰川湖季节性冻融导致的识别误差尚未有效探讨，限制了SAR提取冰川湖的准确性。本文以贡措、郎措为试验区，联合 Sentinel-1 SAR与多源光学影像，分析了2020年两湖面积变化，并探讨SAR特征对冻融过程的响应机制。结果显示：郎措较少出现季节性结冰，光学与SAR影像提取的湖泊面积基本一致；贡措则存在明显的季节性冻融差异，SAR影像提取的面积在1.85 km²~2.65 km²之间波动，而光学影像则稳定在2.6 km²~2.8 km²之间。进一步结合SAR强度与干涉相干性分析发现，贡措在每年11月至次年3月期间存在相对稳定的湖冰，是导致SAR与光学影像提取冰川湖提取差异的主要原因。基于这一发现，本研究通过分析不同状态下的SAR强度与相干性特征，采用经验性阈值有效划分了冰川湖水体与湖冰。综合贡措与郎措的监测结果可初步得知：SAR影像更适用于暖季无冰期冰川湖的监测，或适用于不发生显著季节性冻融的冰川湖研究；同时，SAR强度与干涉相干性结合能够为识别冰川湖是否存在稳定湖冰提供有效依据。

Abstract

Objective Under global warming

glacier retreat and meltwater accumulation drive the expansion of glacial lakes

significantly increasing the risk of glacial lake outburst floods (GLOFs) that threaten downstream infrastructure and communities. Continuous and accurate monitoring of glacial lakes is essential for disaster prevention. Synthetic Aperture Radar (SAR) has become widely applied in complex mountainous glacial lake studies due to its all-weather

day-night capability and cloud-penetrating advantage

with high temporal resolution enabling capture of seasonal dynamics. However

identification errors caused by seasonal freeze-thaw processes affecting SAR backscatter characteristics remain inadequately explored

limiting extraction accuracy. This study aims to systematically investigate the response mechanisms of SAR features to glacial lake freeze-thaw cycles and develop methods to improve monitoring reliability under seasonal ice conditions.Method This study selected two adjacent glacial lakes with distinct freeze-thaw characteristics—Gongcuo and Langcuo in Basu County

Tibet—as test sites. Combining Sentinel-1 SAR imagery with multi-source optical data (Sentinel-2

Landsat-8

and PlanetScope)

we analyzed lake area changes throughout 2020. SAR preprocessing included radiometric calibration

multi-looking

and geocoding using GAMMA software. Lake boundaries were extracted using Simple Non-Iterative Clustering (SNIC) algorithm applied to dual-polarization VV/VH intensity data. Interferometric coherence was computed from temporally adjacent SAR image pairs with 12-day intervals to assess surface stability. Dark channel prior algorithm was employed for cloud masking of optical imagery. ERA5-Land reanalysis climate data were integrated to correlate SAR feature variations with temperature

precipitation

and wind conditions through Pearson correlation analysis.Result Analysis revealed that Langcuo rarely experiences seasonal freezing

with lake areas extracted from optical and SAR imagery showing good agreement. In contrast

Gongcuo exhibited pronounced seasonal freeze-thaw differences

with SAR-derived areas fluctuating between 1.85 km² and 2.65 km²

while optical imagery showed stable areas of 2.6 km² to 2.8 km². Combined analysis of SAR intensity and interferometric coherence revealed that Gongcuo develops relatively stable lake ice from November through March annually

which constitutes the primary cause of discrepancies between SAR and optical lake extraction. Backscatter intensity exhibited strong negative correlation with temperature (r = -0.75)

confirming that warming promotes ice thinning and reduces effective scattering surfaces. Coherence analysis demonstrated that stable thick ice maintains higher coherence values (mean ~0.2

upper quartile 0.25-0.3)

while open water and thin ice show lower coherence (mean ~0.15). An empirical threshold classification was established: open water (VH ≤ -24 dB

coherence ≤ 0.15)

thin ice (-20 dB ≤ VH ≤ -24 dB

coherence ≤ 0.15)

and stable ice (VH ≥ -20 dB

coherence ≥ 0.15).Conclusion This study demonstrates that SAR imagery is more suitable for monitoring glacial lakes during warm ice-free seasons or for lakes without significant seasonal freeze-thaw cycles; meanwhile

combining SAR intensity with interferometric coherence provides effective evidence for identifying the presence of stable lake ice. The findings reveal that seasonal ice cover is the core source of SAR extraction errors in glacial lake monitoring. The proposed intensity-coherence joint threshold method offers a feasible technical approach for dynamic monitoring under seasonal freeze-thaw conditions

though further validation across the diverse glacial lakes of the Tibetan Plateau is needed to optimize broader applicability.

关键词

Keywords

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