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。
Abstract
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.
关键词
采砂监管 /
遥感监测 /
主波长 /
水色参数 /
自然断点分类法
Key words
sand mining supervision /
remotely sensed monitoring /
dominant wavelength /
water color parameter /
natural breaks
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参考文献
[1] 徐 毅,王茂枚,朱 昊,等. 多个采砂工程对长江下游局部河段河势影响[J].水利水电技术(中英文) ,2021,52(6):117-129.doi:10.13928/j.cnki.wrahe.2021.06.013.
[2] 雷 鹏,罗 亮,侯 婷.采砂对天然河床断面演变及堤防稳定影响分析[J].人民珠江,2017,38(4):48-51.
[3] 黄本胜. 谈广东省主要河道采砂控制规划的必要性与紧迫性[J]. 广东水利水电,2006(2):5-6.
[4] 陈冬勤,熊文成. 基于多时相卫星数据的采砂场遥感调查研究:以青海省湟水流域为例[J]. 中国环境监测, 2013, 29(6):206-211.
[5] 付化胜.无人机测绘技术于河道采砂监管中的应用[J].现代信息科技,2020,4(20):42-46.
[6] 刘亦伦,李志威,陈益民,等.下荆江熊家洲河段平面形态与河床冲淤变化[J].长江科学院院报,2020,37(7):7-14.
[7] 肖 潇,徐 坚,赵登忠,等.基于高光谱数据的汉江中下游典型河段水体悬浮物遥感反演[J].长江科学院院报,2020,37(11):141-148.
[8] 陈亮雄,杨静学,李兴汉,等.基于无人机与3S技术的鹤地水库水政监管系统开发与应用[J].长江科学院院报,2020,37(12):176-182.
[9] 王守志,奚 歌,张福坤,等.基于集成学习算法的黄河中游采砂信息提取[J].水利水电技术,2020,51(12):161-168.
[10] 邬国锋,崔丽娟.基于遥感技术的鄱阳湖采砂对水体透明度的影响[J].生态学报,2008,28(12):6113-6120.
[11] 邬国锋,崔丽娟,纪伟涛. 基于遥感技术的鄱阳湖:长江水体清浊倒置现象的分析[J]. 长江流域资源与环境,2009,18(8):777-782.
[12] 张 伟,陈晓玲,田礼乔,等. 鄱阳湖HJ-1A/1B卫星CCD影像TSM浓度时空变化分析[J]. 华中师范大学学报(自然科学版),2013, 47(3):416-420.
[13] 杨静学,陈亮雄,李伟添,等. 多源卫星遥感数据和水色遥感技术在鹤地水库采砂监察中的应用[J]. 广东水利水电,2017,261(11):48-51,59.
[14] 温 爽,王 桥,李云梅,等. 基于高分影像的城市黑臭水体遥感识别:以南京为例[J]. 环境科学,2018,39(1):57-67.
[15] WANG S L,LI J S,ZHANG B,et al. Trophic State Assessment of Global Inland Waters Using a MODIS-derived Forel-Ule index [J]. Remote Sensing of Environment,2018,217: 444-460.
[16] 王胜蕾. 基于水色指数的大范围长时序湖库水质遥感监测研究 [D].北京:中国科学院大学(中国科学院遥感与数字地球研究所),2018.
[17] WANG S,LI J,ZHANG B,et al. Changes of Water Clarity in Large Lakes and Reservoirs across China Observed from long-term MODIS[J]. Remote Sensing of Environment,2020,247: 111949.
[18] ZHAO Y,SHEN Q,WANG Q,et al. Recognition of Water Colour Anomaly by Using Hue Angle and Sentinel 2 Image[J]. Remote Sensing,2020,12(4): 716. Doi: 10.3390/rs12040716.
[19] CIE. Commission Internationale de l′Eclairage Proceedings 1931[R]. Cambridgeshire: Cambridge University Press,1932: 19-29.
[20] XU H. Modification of Normalised Difference Water Index (NDWI) to Enhance Open Water FeaturesIn Remotely Sensed Imagery[J]. International Journal of Remote Sensing,2006,27(14): 3025-3033.
[21] 张晨朝.一种新的基于软件的LED主波长计算方法研究[J].电子测试,2020(7):53-55.
[22] JENKS G F. The Data Model Concept in Statistical Mapping[J]. International Yearbook Cartography,1967,7: 186-190.
基金
广东省重点领域研发计划项目(2020B0101130018);广东省自然科学基金项目(2017A030313238);广东省属科研机构稳定性支持专项资金院自设课题(2021L028)
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