基于主波长水色参数的水库采砂遥感监测

Remotely Sensed Monitoring of Sand Mining in Reservoir by Using Dominant Wavelength of Water Color

利用遥感技术监测河道采砂行为,通常根据经验阈值划分水体悬浮物浓度高值区为采砂嫌疑区。针对分割阈值受大气纠正及悬浮物浓度反演模型精度限制难以自动客观确定的问题,提出了基于主波长水色参数自动识别异常浑浊水体的方法。采用Landsat8、Sentinel-2卫星图像数据,基于CIE-XYZ颜色系统,提取红、绿、蓝三波段遥感图像主波长水色参数,结合自然断点分类法将指示悬浮物浓度的主波长水色参数自动划分高、中、低3类,识别高值区为采砂嫌疑区。应用该方法研究浑浊水体时空分布,识别了2016—2017年广东鹤地水库九洲江、化州库湾水域的采砂现象,以及2019年11月—2020年4月广东枫树坝水库寻邬水水域的采砂现象。试验证明,方法具有抗大气干扰性强、自动性高、稳定可靠、适用于多源遥感图像的优势,可为传统人工巡查监管提供及时、有效的采砂嫌疑区时空分布信息,提升常态化采砂监管的能力。

In remotely sensed monitoring of sand mining in river channel,the area with high concentration of suspended solids in water body is usually classified as suspected area according to empirical threshold.The segmentation threshold is difficult to be automatically and objectively determined due to the accuracy limitation of atmospheric correction and suspended solids concentration inversion mode.A method of automatically recognizing abnormal turbid water body based on dominant wavelength of water color is proposed.The dominant wavelengths of water color information of remote sensing images of red,green and blue bands are extracted using Sentinel-2 and Landsat8 satellite image data based on CIE-XYZ color system.Furthermore,the dominant wavelengths of water color parameters indicating the concentration of suspended solids are automatically classified into high,medium,and low levels by using the natural breaks method,and the high value area is extracted as the suspected area of sand mining.The method was applied to reflect the temporal and spatial distribution of turbid water bodies,and had successfully identified the sand mining in the Jiuzhou River and Huazhou Bay waters of the Hedi Reservoir in Guangdong in 2016-2017 and in the Xunwushui River of the Fengshuba Reservoir in Guangdong from November 2019 to April 2020.Experiments have proved that the method is of strong resistance to atmospheric interference,high automation,stability and reliability,and is suitable for multi-source remote sensing images.The method also offers timely and effective tool for the temporal and spatial distribution of sand mining suspected areas for traditional manual inspections and supervision,and improves the capacity of normalized sand mining supervision.