利用 D-InSAR 增强测高法水位的时间分辨率:10 个瑞典湖泊的案例研究

IF 5.7 Q1 ENVIRONMENTAL SCIENCES Science of Remote Sensing Pub Date : 2024-09-10 DOI:10.1016/j.srs.2024.100162
Saeid Aminjafari , Frédéric Frappart , Fabrice Papa , Ian Brown , Fernando Jaramillo
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引用次数: 0

摘要

湖泊为社会和自然生态系统提供了宝贵的服务,如淡水供应和洪水控制。湖泊水位的变化反映了湖泊对气候和人为压力因素的自然反应;然而,由于安装和维护要求,对湖泊的监测成本高昂。凭借先进的硬件和计算能力,测高法已成为传统现场测量法的热门替代方法,但受制于测高观测数据的时间可用性。为了进一步提高测高数据的时间分辨率,我们在此将雷达测高数据与差分干涉合成孔径雷达(D-InSAR)相结合,以瑞典的十个湖泊为测试平台。首先,我们使用 Sentinel-1A 和 Sentinel-1B SAR 图像生成跨越 2019 年的连续六天基线干涉图。然后,我们累积相干像素的相位变化,构建 InSAR 衍生水位异常的时间序列。最后,我们检索 Sentinel-3 的测高观测数据,估计其平均值和标准偏差,并将其应用于 D-InSAR 标准化异常。这样,我们就建立了一个具有更多时间观测数据的水位时间序列。总体而言,我们发现 D-InSAR 与卫星测高相结合(DInSAlt)得出的水位估计值与 8 个湖泊的现场观测值高度一致(一致相关系数 - CCC >0.8),与 2 个湖泊的水位估计值中度一致(CCC >0.57)。DInSAlt 的适用性仅限于具有适合双弹散射条件的湖泊,例如有树木或沼泽的湖泊。水位估计的准确性取决于测高观测的质量和湖泊的宽度。考虑到最近发射的地表水和海洋地形(SWOT)卫星,这些发现具有重要意义,因为该卫星的功能可以扩大我们方法的地理适用性,并减少对地面测量的依赖。
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Enhancing the temporal resolution of water levels from altimetry using D-InSAR: A case study of 10 Swedish Lakes

Lakes provide societies and natural ecosystems with valuable services such as freshwater supply and flood control. Water level changes in lakes reflect their natural responses to climatic and anthropogenic stressors; however, their monitoring is costly due to installation and maintenance requirements. With its advanced hardware and computational capabilities, altimetry has become a popular alternative to conventional in-situ gauging, although subject to the temporal availability of altimetric observations. To further improve the temporal resolution of altimetric measurements, we here combine radar altimetry data with Differential Interferometric Synthetic Aperture Radar (D-InSAR), using ten lakes in Sweden as a testing platform. First, we use Sentinel-1A and Sentinel-1B SAR images to generate consecutive six-day baseline interferograms across 2019. Then, we accumulate the phase change of coherent pixels to construct the time series of InSAR-derived water level anomalies. Finally, we retrieve altimetric observations from Sentinel-3, estimate their mean and standard deviation, and apply them to the D-InSAR standardized anomalies. In this way, we build a water-level time series with more temporal observations. In general, we find a strong agreement between water level estimates from the combination of D-InSAR and Satellite Altimetry (DInSAlt) and in-situ observations in eight lakes (Concordance Correlation Coefficient - CCC >0.8) and moderate agreement in two lakes (CCC >0.57). The applicability of DInSAlt is limited to lakes with suitable conditions for double-bounce scattering, such as the presence of trees or marshes. The accuracy of the water level estimates depends on the quality of the altimetry observations and the lake's width. These findings are important considering the recently launched Surface Water and Ocean Topography (SWOT) satellite, whose capabilities could expand our methodology's geographical applicability and reduce its reliance on ground measurements.

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