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Sensitivity of Sentinel-1 C-band SAR backscatter, polarimetry and interferometry to snow accumulation in the Alps
Remote Sensing of Environment ( IF 11.1 ) Pub Date : 2024-11-06 , DOI: 10.1016/j.rse.2024.114477 Jonas-Frederik Jans, Ezra Beernaert, Morgane De Breuck, Isis Brangers, Devon Dunmire, Gabrielle De Lannoy, Hans Lievens
Remote Sensing of Environment ( IF 11.1 ) Pub Date : 2024-11-06 , DOI: 10.1016/j.rse.2024.114477 Jonas-Frederik Jans, Ezra Beernaert, Morgane De Breuck, Isis Brangers, Devon Dunmire, Gabrielle De Lannoy, Hans Lievens
The physical drivers of Sentinel-1 C-band backscatter observations during snow accumulation are still uncertain. To investigate these, backscatter fluctuations (in co-polarization VV, cross-polarization VH, and cross-polarization ratio VH-VV) were temporally and spatially linked to modeled surface (0–10 cm) soil moisture (SM) and soil temperature (T) (here referred to as soil dynamics) and modeled snow depth (SD) and snow water equivalent (SWE) (snow dynamics) in the bare and herbaceous regions of the Alps at a spatial resolution of 1 km. Results demonstrate that, during snow accumulation and at a regional scale, VH and VH-VV variability is primarily influenced by SD and SWE, whereas VV fluctuations are driven by a combination of soil and snow dynamics. At low local incidence angles, VV is driven by snow dynamics rather than by soil dynamics, which results in a decreased sensitivity of VH-VV to snow accumulation, potentially degrading VH-VV based SD retrieval. Additionally, polarimetric and interferometric Sentinel-1 observations are generated to assess their sensitivity to snow dynamics. Results show that polarimetric α (from entropy-α dual-pol decomposition) and the first Stokes parameter are more sensitive to SD than VH-VV and VV, respectively, suggesting the potential for improved SD retrievals. Finally, results show that interferometric 6-day coherence observations respond to modeled SWE accumulation, with low coherence values after significant SWE accumulation and higher values in case of minor SWE changes.
中文翻译:
Sentinel-1 C 波段 SAR 反向散射、偏振和干涉测量对阿尔卑斯山积雪的敏感性
积雪期间 Sentinel-1 C 波段反向散射观测的物理驱动因素仍不确定。为了研究这些,反向散射波动(共极化 VV、交叉极化 VH 和交叉极化比 VH-VV)在时间和空间上与模拟的表面 (0-10 cm)、土壤水分 (SM) 和土壤温度 (T)(此处称为土壤动力学)以及模拟的雪深 (SD) 和雪水当量 (SWE)(雪动力学)相关联,空间分辨率为 1 公里。结果表明,在积雪期间和区域尺度上,VH 和 VH-VV 变化主要受 SD 和 SWE 的影响,而 VV 波动是由土壤和雪动力学共同驱动的。在低局部入射角下,VV 是由雪动力学而不是土壤动力学驱动的,这导致 VH-VV 对积雪的敏感性降低,可能会降低基于 VH-VV 的 SD 检索。此外,还生成了极化和干涉 Sentinel-1 观测值,以评估它们对雪动力学的敏感性。结果表明,极化α(来自熵α双极分解)和第一斯托克斯参数分别比 VH-VV 和 VV 对 SD 更敏感,这表明有可能改进 SD 检索。最后,结果表明,干涉测量 6 天相干性观测对建模的 SWE 累积做出响应,在显着的 SWE 积累后具有较低的相干值,而在 SWE 发生微小变化的情况下具有较高的值。
更新日期:2024-11-06
中文翻译:
Sentinel-1 C 波段 SAR 反向散射、偏振和干涉测量对阿尔卑斯山积雪的敏感性
积雪期间 Sentinel-1 C 波段反向散射观测的物理驱动因素仍不确定。为了研究这些,反向散射波动(共极化 VV、交叉极化 VH 和交叉极化比 VH-VV)在时间和空间上与模拟的表面 (0-10 cm)、土壤水分 (SM) 和土壤温度 (T)(此处称为土壤动力学)以及模拟的雪深 (SD) 和雪水当量 (SWE)(雪动力学)相关联,空间分辨率为 1 公里。结果表明,在积雪期间和区域尺度上,VH 和 VH-VV 变化主要受 SD 和 SWE 的影响,而 VV 波动是由土壤和雪动力学共同驱动的。在低局部入射角下,VV 是由雪动力学而不是土壤动力学驱动的,这导致 VH-VV 对积雪的敏感性降低,可能会降低基于 VH-VV 的 SD 检索。此外,还生成了极化和干涉 Sentinel-1 观测值,以评估它们对雪动力学的敏感性。结果表明,极化α(来自熵α双极分解)和第一斯托克斯参数分别比 VH-VV 和 VV 对 SD 更敏感,这表明有可能改进 SD 检索。最后,结果表明,干涉测量 6 天相干性观测对建模的 SWE 累积做出响应,在显着的 SWE 积累后具有较低的相干值,而在 SWE 发生微小变化的情况下具有较高的值。