Abstract

Sentinel-1 provides improved temporal and spatial resolutions in comparison with previous satellite missions. Unlike the change detection method that assumes the time-invariance of surface roughness at a coarse resolution, this study spatially inverted roughness and soil moisture from Sentinel-1 backscatter. Although it is important at high-resolution, local measurements of surface roughness are not available in an operational setting. Thus, question was how often time-varying soil roughness information should be updated in operations for reasonable soil moisture retrievals but at effective computational cost. Local validations show that a monthly update for surface roughness is sufficient for soil moisture retrievals. In more details, Root Mean Square Errors (RMSE) of 0.01 m³/m³ is found at Yanco A3 site, and 0.03 m³/m³ at Yanco A5 site, with differences in backscattering between Integral Equation Model (IEM) simulation and Sentinel-1 measurement of 0.78 dB at Yanco A3 site and 0.012 dB at Yanco A5 site, respectively.

摘要

与以前的卫星任务相比，Sentinel-1 提供了改进的时间和空间分辨率。与假设表面粗糙度在粗分辨率下的时间不变性的变化检测方法不同，本研究从 Sentinel-1 后向散射中空间反演粗糙度和土壤水分。尽管在高分辨率下它很重要，但表面粗糙度的局部测量在操作环境中是不可用的。因此，问题是在操作中应该多久更新一次随时间变化的土壤粗糙度信息，以进行合理的土壤水分检索，但需要有效的计算成本。当地验证表明，表面粗糙度的每月更新足以用于土壤水分检索。更详细地说，均方根误差 (RMSE) 为 0.01 m ³ /m ³在 Yanco A3 站点发现，在 Yanco A5 站点发现为 0.03 m ³ /m ³，积分方程模型 (IEM) 模拟和 Sentinel-1 测量之间的反向散射差异在 Yanco A3 站点为 0.78 dB，在 Yanco A5 站点为 0.012 dB ， 分别。