Monitoring of spatial-temporal dynamic changes in water surface in marshes based on multi-temporal Sentinel-1A data
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摘要: 水是形成和维系湿地生态系统的重要因子,监测湿地水面积变化对湿地保护研究具有重要意义。以2018—2019年逐月的Sentinel-1A卫星数据为数据源,计算扎龙湿地年内和年际的合成孔径雷达(synthetic aperture Radar,SAR)后向散射系数(σ0)和相干系数(μ0)影像,根据彩色光学影像水体贴近程度赋予权重并构建提取湿地水面σ0与μ0的加权影像,通过阈值分割法、随机森林算法提取湿地水体,实现湿地水域面积的动态变化监测,探究湿地水域年内和年际变化规律。结果表明: 基于随机森林算法的水体提取精度最高,代表月份平均差值绝对值为6.69 km2,基于μ0影像使用阈值分割方法的分类精度最低,平均差值绝对值为13.07 km2; 整体趋势上,扎龙湿地水域面积年内有明显的季节性变化,春末夏初时水域面积在1 300~1 600 km2浮动,夏末秋始时水域面积在700~900 km2浮动; 年际水域面积会随着气候、温度等条件差异有不同变化,2019年10月、11月因降水量大湿地水域面积比2018年多出约1 050 km2,基于有效数据计算,总体上2019年比2018年水域面积多出约550 km2。
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关键词:
- 湿地水面年内年际变化 /
- Sentinel-1A /
- 后向散射系数 /
- 相干系数 /
- 阈值分割
Abstract: Water is an important factor in the formation and maintenance of wetland ecosystems. Monitoring the changes in the water area of wetlands is of great significance for wetland conservation. Taking Sentinel-1A data from 2018 to 2019 as the data source, this study calculated the intra- and inter-annual synthetic aperture radar (SAR) backscattering coefficient (σ0) and coherence coefficient (μ0) images of the Zhalong Wetland. Then, this study assigned weights according to the proximity to water bodies of color optical images and extracted the weighted images of σ0 and μ0. Finally, this study extracted the wetland water bodies using the threshold segmentation method and random forest algorithm. The purpose is to monitor the dynamic variations in the wetland water area and explore the intra- and inter-annual variation rules of the wetland water body. The results are as follows. The random forest algorithm yielded the highest extraction accuracy of water bodies, with an absolute value of the mean difference of representative months was 6.69 km2. The threshold segmentation method based on μ0 images yielded the lowest classification accuracy of water bodies, with an absolute value of the mean difference of 13.07 km2. Overall, the intra-annual water area of the Zhalong Wetland showed significant seasonal variations during 2018—2019. The water area fluctuated in the ranges of 1 300~1 600 km2 during late spring and early summer and 700~900 km2 during late summer and early autumn. The inter-annual water area varied with conditions such as climate and temperature. In particular, the wetland water area in October and November 2019 was approximately 1 050 km2 greater than that in 2018 due to large amounts of rainfall. As shown by the calculation based on effective data, the water area in 2019 was about 550 km2 greater than that in 2018 in the Zhalong Wetland. -
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