不同空间分辨率遥感数据识别湖泊的误差分析
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摘要
湖泊面积及空间分布是表征水情变化的重要指示因子,对研究气候变化和人类活动对水资源的影响具有重要作用。如何利用遥感影像进行湖泊制图和面积估算是当前遥感应用研究中的难点问题。从实际应用需求出发,采用GF-1/WFV(Wide Field View)、Landsat-8 OLI(Operational Land Imager)、MODIS(Moderate-Resolution Image Spectroradiometer)遥感数据,选用安徽省受人类活动影响较大的54个湖泊为研究区域,采用NDWI二值分割法得到湖泊水体信息,使用30,500 m和1 000 m 3种空间分辨率的遥感影像进行湖泊制图,探讨制图精度与湖泊形态之间的关系。结果表明:湖泊分形维数值越大,湖泊形态越复杂, Kappa系数越高,面积误差越小;遥感影像分辨率越高,湖泊制图结果的Kappa系数和总体精度越高。
Lake area and corresponding spatial distributions are important indicators for monitoring environmental changes, which plays an important role in studying the impact of climate change and human activities on water resource. Accurate lake mapping and area estimation from existing remote sensing data still remain unsettled. To quantitatively investigate the association between the morphological complexity and lake mapping according to practical application, 18 m GF-1/WFV(Wide Field View), 30 m LandSat-8/OLI(Operational Land Imager), 500 m and 1000 m EOS/MODIS(Moderate-Resolution Imaging Spectroradiometer) data of 54 human-impacted lakes in Anhui Province were selected for map drawing. For lake mapping, water surface of lakes were extracted from remote sensing data by combining NDWI(Normalized Difference Water Index) and thresholding segmentation method. The main conclusions are as follows:(1) The larger the lake fractal dimension value is, the more complex the lake's shape is; the higher the Kappa coefficient is, the smaller the lake area error is;(2) The spatial resolution of remote sensing images can affect the Kappa coefficient and overall accuracy of the lake mapping results. The higher the spatial resolution is, the higher the lake's Kappa coefficient and overall accuracy in lake mapping are.
Lake area and corresponding spatial distributions are important indicators for monitoring environmental changes, which plays an important role in studying the impact of climate change and human activities on water resource. Accurate lake mapping and area estimation from existing remote sensing data still remain unsettled. To quantitatively investigate the association between the morphological complexity and lake mapping according to practical application, 18 m GF-1/WFV(Wide Field View), 30 m LandSat-8/OLI(Operational Land Imager), 500 m and 1000 m EOS/MODIS(Moderate-Resolution Imaging Spectroradiometer) data of 54 human-impacted lakes in Anhui Province were selected for map drawing. For lake mapping, water surface of lakes were extracted from remote sensing data by combining NDWI(Normalized Difference Water Index) and thresholding segmentation method. The main conclusions are as follows:(1) The larger the lake fractal dimension value is, the more complex the lake's shape is; the higher the Kappa coefficient is, the smaller the lake area error is;(2) The spatial resolution of remote sensing images can affect the Kappa coefficient and overall accuracy of the lake mapping results. The higher the spatial resolution is, the higher the lake's Kappa coefficient and overall accuracy in lake mapping are.
引文
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[11] 徐蓉,张增祥,温庆可,等.基于机理模型的不同空间分辨率影像提取湖面面积的误差研究[J].地球信息科学学报,2014,16(3):450-459.
[12] 熊金国,王世新,周艺,等.利用景观格局指数的空间分辨率对水域面积提取影响的分析[J].武汉大学学报(信息科学版),2011,36(1):98-103.
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[14] McFeeters SK.The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features[J].International journal of remote sensing,1996,17(7):1425-1432.
[15] 张晓冬,沈斯敏,朱首贤,等.海口湾海滩冲淤遥感分析[J].华东师范大学学报(自然科学版),2015(4):42-53.
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[17] 徐南,宫鹏.卡特里娜飓风对美国新奥尔良市西侧海岸线变化的影响[J].科学通报,2016,61(15):1687-1694.
[18] 彭瑞东,谢和平,鞠杨.二维数字图像分形维数的计算方法[J].中国矿业大学学报,2004,33(1):19-24.
[19] Xu Nan.Detecting coastline change with all available Landsat data over 1986–2015:a case study for the state of Texas,USA [J].Atmosphere 2018,9(3),107.
[2] Zhu LP,Xie M,Wu Y.Quantitative analysis of lake area variations and the influence factors from 1971 to 2004 in the Nam Co basin of the Tibetan Plateau[J].Chinese Science Bulletin,2010,55(13):1294-1303.
[3] 万玮,肖鹏峰,冯学智,等.卫星遥感监测近30年来青藏高原湖泊变化[J].科学通报,2014,8(8):701-714.
[4] 宋平,刘元波,刘燕春.陆地水体参数的卫星遥感反演研究进展[J].地球科学进展,2011,26(7):731-740.
[5] 廖安平,陈利军,陈军,等.全球陆表水体高分辨率遥感制图[J].中国科学(地球科学),2014(8):1634-1645.
[6] 郝振纯,池宸星.空间分辨率与取样方式对DEM流域特征提取的影响[J].冰川冻土,2004,26(5):610-616.
[7] 杨旭艳,赵婷.不同尺度遥感影像上水体提取效果分析[J].地下水,2012(2):212-215.
[8] 张毅,陈成忠,吴桂平,等.遥感影像空间分辨率变化对湖泊水体提取精度的影响[J].湖泊科学,2015,27(2):335-342.
[9] 于欢,张树清,李晓峰,等.基于TM影像的典型内陆淡水湿地水体提取研究[J].遥感技术与应用,2008,23(3):310-315.
[10] 曹广真,卢乃锰,侯鹏,等.遥感湖泊面积MTMF提取方法及空间尺度效应研究[J].遥感技术与应用,2016,31(5):864-871.
[11] 徐蓉,张增祥,温庆可,等.基于机理模型的不同空间分辨率影像提取湖面面积的误差研究[J].地球信息科学学报,2014,16(3):450-459.
[12] 熊金国,王世新,周艺,等.利用景观格局指数的空间分辨率对水域面积提取影响的分析[J].武汉大学学报(信息科学版),2011,36(1):98-103.
[13] Lyons EA,Sheng Y,Smith LC,et al.Quantifying sources of error in multitemporal multisensor lake mapping[J].International Journal of Remote Sensing,2013,34(22):7887-7905.
[14] McFeeters SK.The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features[J].International journal of remote sensing,1996,17(7):1425-1432.
[15] 张晓冬,沈斯敏,朱首贤,等.海口湾海滩冲淤遥感分析[J].华东师范大学学报(自然科学版),2015(4):42-53.
[16] Otsu N.A threshold selection method from gray-level histograms[J].Automatica,1975,11(285-296):23-27.
[17] 徐南,宫鹏.卡特里娜飓风对美国新奥尔良市西侧海岸线变化的影响[J].科学通报,2016,61(15):1687-1694.
[18] 彭瑞东,谢和平,鞠杨.二维数字图像分形维数的计算方法[J].中国矿业大学学报,2004,33(1):19-24.
[19] Xu Nan.Detecting coastline change with all available Landsat data over 1986–2015:a case study for the state of Texas,USA [J].Atmosphere 2018,9(3),107.