基于多源特征融合的高分辨率遥感图像近海养殖区提取方法研究
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摘要
近海养殖区是重要的海洋灾害承灾体,开展基于遥感技术的近海养殖区提取研究,对快速掌握沿海地区基础信息、减轻与防御海洋灾害有重要意义。利用国产高分系列遥感卫星图像,以福建省东山岛海域为实验区,在分析近海养殖区光谱特征的基础上,构建特征指数提取光谱特征,利用灰度共生矩阵的方法提取养殖区纹理特征,经过特征选择后融合养殖区的光谱与纹理特征,实现特征降维生成新特征,最后利用Otsu阈值法分别提取筏式养殖区与渔排网箱养殖区两种近海养殖区,实现对近海养殖区的高精度提取与分类。最终筏式养殖区的提取精度在80%以上,鱼排网箱养殖区的提取精度在90%以上,养殖区整体提取精度可达87%。
Coastal aquaculture areas are the important marine disaster bearing body,it is of great significance to carry out the research about automatically extraction aquaculture areas based on remote sensing for master basic information of coastal areas,mitigation and prevention of marine disasters.Used Gaofen-2 images for experimental data,and chose Dongshan Island sea in Fujian province as the experimental area,on the basis of analyzed the spectral characteristics of the aquaculture areas,construct feature index to extract spectral feature,used gray-level co-occurrence matrix method to extract the texture feature of the aquaculture areas,fused spectral features and texture features after feature selection,then used Otsu method to determine the threshold for raft culture area and fishing cage culture area,to achieve high precision intelligent extraction and classification for coastal aquaculture areas.The extraction accuracy of the raft culture area is more than 80%,and the extraction precision of the fish cage culture area is above 90%,and the overall extraction precision of the culture area is up to 87%.
Coastal aquaculture areas are the important marine disaster bearing body,it is of great significance to carry out the research about automatically extraction aquaculture areas based on remote sensing for master basic information of coastal areas,mitigation and prevention of marine disasters.Used Gaofen-2 images for experimental data,and chose Dongshan Island sea in Fujian province as the experimental area,on the basis of analyzed the spectral characteristics of the aquaculture areas,construct feature index to extract spectral feature,used gray-level co-occurrence matrix method to extract the texture feature of the aquaculture areas,fused spectral features and texture features after feature selection,then used Otsu method to determine the threshold for raft culture area and fishing cage culture area,to achieve high precision intelligent extraction and classification for coastal aquaculture areas.The extraction accuracy of the raft culture area is more than 80%,and the extraction precision of the fish cage culture area is above 90%,and the overall extraction precision of the culture area is up to 87%.
引文
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[3]Cheng Tianfei,Zhou Weifeng,Fan Wei.Progress in the Methods for Extracting Aquaculture Areas from Remote Sensing Data[J].Remote Sensing for Land&Resources,2012,94(3):1-5.[程田飞,周为峰,樊伟.水产养殖区域的遥感识别方法进展[J].国土资源遥感,2012,94(3):1-5.]
[4]Li Xinguo,Jiang Nan,Yang Yingbao,et al.Remote Sensing Investigation and Survey of Lake Reclamation and Enclosure Aquaculture in Lake Taihu[J].Transaction of Oceanology and Limnology,2006,(1):93-99.[李新国,江南,杨英宝,等.太湖围网利用与围网养殖的遥感调查与研究[J]海洋湖沼通报,2006,(1):93-99.]
[5]Fan Jianyong,Huang Haijun,Fan Hui,et al.Extracting Aquaculture Area with RADSAT-1[J].Marine Sciences,2005,29(10):44-47.[樊建勇,黄海军,樊辉,等.利用RADASAT-1数据提取海水养殖区面积[J].海洋科学,2005,29(10):44-47.]
[6]Lu Yewei,Li Qiangzi,Du Xin,et al.A Method of Coastal Aquaculture Area Automatic Extraction with High Spatial Resolution Images[J].Remote Sensing Technology and Application,2015,30(3):486-494.[卢业伟,李强子,杜鑫,等.基于高分辨率影像的近海养殖区的一种自动提取方法[J].遥感技术与应用,2015,30(3):486-494.]
[7]Wang Jing,Gao Junfeng.Extraction of Enclosure Culture in Gehu Lake based on Correspondence Analysis[J].Journal of Remote Sensing,2008,12(5):716-723.[王静,高俊峰.基于对应分析的湖泊围网养殖范围提取[J].遥感学报,2008,12(5):716-723.]
[8]Zhou Xiaocheng,Wang Xiaoqin,Xiang Tianliang,et al.Method of Automatic Extraction Seaside Aquaculture Land based on ASTER Remote Sensing Image[J].Wetland Science,2006,4(1):64-68.[周小成,汪小钦,向天梁,等.基于ASTER影像的近海水产养殖信息自动提取方法[J].湿地科学,2006,4(1):64-68.]
[9]Xie Yulin,Wang Min,Zhang Xinyue.An Object-oriented Approach for Extracting Farm Waters within Coastal Belts[J].Remote Sensing Technology and Application,2009,24(1):68-72.[谢玉林,汪闽,张新月.面向对象的海岸带养殖水域提取[J].遥感技术与应用,2009,24(1):68-72.]
[10]Chu Jialan,Zhao Dongzhi,Zhang Fengshou.Wakame Raft Interpretation Method of Remote Sensing based on Association Rules[J].Remote Sensing Technology and Application,2012,27(6):941-946.[初佳兰,赵东至,张丰收.基于关联规则的裙带菜筏式养殖遥感识别方法[J].遥感技术与应用,2012,27(6):941-946.]
[11]Ma Yanjuan,Zhao Dongling,Wang Ruimei,et al.Offshore Aquatic Farming Areas Extraction Method based on ASTER Data[J].Transaction of the CASE,2010,26(Z2):120-124.[马艳娟,赵冬玲,王瑞梅,等.基于ASTER数据的近海水产养殖区提取方法[J].农业工程学报,2010,26(Z2):120-124.]
[12]Haralick R M,Shanmugam K,Dinstein I.Textural Features for Image Classification[J].IEEE Transactions on Systems,Man,and Cybernetics,1973.
[13]Xu Jia,Chen Yuanyuan,Huang Qihuan,et al.Built-up Areas Extraction in High Resolution Space-borne SAR Image based on the Integration of Grey and Texture Features[J].Remote Sensing Technology and Application,2012,27(5):692-698.[徐佳,陈媛媛,黄其欢,等.综合灰度与纹理特征的高分辨率星载SAR图像建筑区提取方法研究[J].遥感技术与应用,2012,27(5):692-698.]
[14]Wu Bing,Qin Zhiyuan.New Approaches for the Automatic Selection of the Optimal Threshold in Images Binarization[J].Journal of Institute of Surveying and Mapping,2001,18(4):283-286.[吴冰,秦志远.自动确定图像二值化最佳阈值的新方法[J].测绘学院学报,2001,18(4):283-286.]