SENTINEL-1 TIME SERIES ANALYSIS ON CENTRAL AMAZON FLOODS
收藏DataCite Commons2022-12-17 更新2024-07-29 收录
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Abstract This study aimed to analyze the dynamics of the flooded areas of the Sentinel 1-SAR time series in a section of the Central Amazon between September 26, 2016, and February 8, 2020. The total of images was 59 for each polarization. In addition, the study calculated the average ordinary flood line (ALOF) from the heights of the fluviometric rulers between the years 1967 to 2020 and compared it with the values present in the radar time series. The pre-processing of the Sentinel-1 time series in the VV and VH polarizations used the following methodological sequence: Apply Orbit File, Radiometric Calibration (σ0), Range-Doppler Terrain Correction, Speckle Filter, and conversion to decibels (dB). The previous analysis of the adaptive filters showed different results for the two polarizations, obtaining the best result for the VV polarization using the Frost filter with 3x3 and the VH polarization with the Lee filter 3x3. The extraction of water bodies and wetlands used a threshold value, making masks for the entire period. The most considerable extent of the floodable area occurred on June 17, 2019, with 6,611.86 km2, representing 16.42% of the SAR scene in the VH polarization and 6,443.19 km2, representing 16.10% of the SAR scene in the VV polarization. The relationship between the VH and VV wetlands to the ruler's height was satisfactory, with coefficients of determination (R2) of 0.79 in the VH polarization and of 0.64 in the VV polarization and a p-value less than 0.05.
摘要 本研究旨在分析2016年9月26日至2020年2月8日期间,亚马逊中部某区域的Sentinel-1合成孔径雷达(Sentinel-1 SAR)时间序列的洪水区域动态变化。每种极化方式下的影像总数均为59景。此外,本研究基于1967年至2020年的水文标尺水位数据计算得到平均常规洪水线(Average Ordinary Flood Line, ALOF),并将其与雷达时间序列中的对应值进行对比。针对VV与VH极化的Sentinel-1时间序列数据,预处理流程遵循以下方法步骤:加载轨道文件、辐射定标(后向散射系数σ⁰)、距离多普勒地形校正、斑点滤波,以及转换为分贝(dB)单位。此前针对自适应滤波器的对比分析显示,两种极化方式的滤波效果存在差异:VV极化采用3×3弗罗斯特滤波可获得最优结果,VH极化则采用3×3李滤波效果最佳。研究通过阈值法提取水体与湿地信息,生成全时段的掩膜产品。研究区域内最大的可洪水面积出现在2019年6月17日,VH极化下面积达6611.86 km²,占对应SAR场景的16.42%;VV极化下面积达6443.19 km²,占对应SAR场景的16.10%。VH与VV极化下提取的湿地面积与水文标尺水位之间的相关性良好:VH极化的决定系数(R²)为0.79,VV极化为0.64,且二者p值均小于0.05。
提供机构:
SciELO journals
创建时间:
2022-12-17



