异质背景下黄河三角洲潮沟的遥感提取方法

doi:10.13287/j.1001-9332.201909.019

应用生态学报 ›› 2019, Vol. 30 ›› Issue (9): 3097-3107.doi: 10.13287/j.1001-9332.201909.019

异质背景下黄河三角洲潮沟的遥感提取方法

王启为^1,2,3,4, 宫兆宁^1,2,3,4*, 关鸿亮^1,2,3,4, 张磊^1,2,3,4, 井然^1,2,3,4, 汪星^1,2,3,4

¹北京市成像技术高精尖创新中心, 首都师范大学, 北京 100048;
²首都师范大学资源环境与旅游学院, 北京 100048;
³三维信息获取与应用教育部重点实验室, 北京 100048;
⁴资源环境与地理信息系统北京市重点实验室, 北京 100048)

收稿日期:2018-11-06 出版日期:2019-09-15 发布日期:2019-09-15
通讯作者: * E-mail: gongzhn@163.com
作者简介:王启为,男,1995年生,硕士研究生.主要从事遥感地学应用研究.E-mail:wqwczly@163.com
基金资助:
国家重点研发计划项目(2017YFC0505903)资助

Extracting method of tidal creek features under heterogeneous background at Yellow River Delta using remotely sensed imagery.

WANG Qi-wei^1,2,3,4, GONG Zhao-ning^1,2,3,4*, GUAN Hong-liang^1,2,3,4, ZHANG Lei^1,2,3,4, JING Ran^1,2,3,4, WANG Xing^1,2,3,4

¹Beijing Advanced Innovation Center for Imaging Technology, Capital Normal University, Beijing 100048, China;
²College of Resources Environment & Tourism, Capital Normal University, Beijing 100048, China;
³ Ministry of Education Key Laboratory of 3D Information Acquisition and Application, Beijing 100048, China;
⁴Beijing Municipal Key Laboratory of Resources Environment and GIS, Beijing 100048, China

Received:2018-11-06 Online:2019-09-15 Published:2019-09-15
Contact: * E-mail: gongzhn@163.com
Supported by:
This work was supported by National Key R&D Program of China (2017YFC0505903).

摘要/Abstract

摘要： 以黄河三角洲为研究区域,针对该区域潮滩背景异质性强、潮沟宽度不一和潮沟各向异性强等特点,选取高分二号多光谱影像作为数据源,首先利用归一化水体指数(NDWI)和最大类间方差法(OTSU)提取宽阔潮沟,其次,使用改进的模糊C均值算法(MFCM)和多尺度高斯匹配滤波(MGMF),在削弱潮滩背景异质性的基础上增强细小潮沟,接着利用自适应阈值分割提取细小潮沟,最后合并细小潮沟和宽阔潮沟,形成完整的潮沟网络.不仅充分利用了高分二号影像的空间分辨率和光谱信息,也顾及了线状要素的几何特征,保证了潮沟提取结果的空间连续性.在4个局部测试区域,提取结果的Kappa系数大于0.8,总体精度高于97%,优于最大似然法和支持向量机.结果表明: 本研究提出的方法能够较完整地提取不同类型的潮沟,表现出较好的提取精度和稳定性,能够为潮沟的实时动态监测及其发育演化规律研究提供科学参考.

Abstract: The Yellow River Delta exhibits irregular tidal flat, with tidal creeks that vary in width and experience tidal creek current anisotropy. Given such characteristics, the GF-2 multi-spectral image was selected as the data source to characterize the details of tidal creeks. First, the normali-zed difference water index (NDWI) and OTSU classification were used to delineate the wide tidal creeks. Second, the modified fuzzy C-means clustering algorithm (MFCM) and multi-scale Gaussian matching filter (MGMF) were used to enhance the narrow tidal creeks on the basis of weakening the heterogeneity of tidal flat background. Then, the adaptive threshold segmentation was conducted to delineate the narrow tidal creeks. Finally, the complete tidal creek networks were delineated by combining the wide and narrow tidal creeks. We fully used the spatial resolution and spectral information of the GF-2 image and took into account the geometric features of the linear features, ensuring the spatial continuity of the tidal creek extraction results. In the four tested areas, the Kappa coefficient was greater than 0.8 and the overall accuracy was greater than 97%, which performed better than the maximum likelihood method and support vector machine. The results showed that the proposed method could completely differentiate different types of tidal creeks, with good extraction accuracy and stability. The method could provide scientific reference for real-time dynamic monitoring of tidal creek and its development and evolution.

王启为, 宫兆宁, 关鸿亮, 张磊, 井然, 汪星. 异质背景下黄河三角洲潮沟的遥感提取方法[J]. 应用生态学报, 2019, 30(9): 3097-3107.

WANG Qi-wei, GONG Zhao-ning, GUAN Hong-liang, ZHANG Lei, JING Ran, WANG Xing. Extracting method of tidal creek features under heterogeneous background at Yellow River Delta using remotely sensed imagery.[J]. Chinese Journal of Applied Ecology, 2019, 30(9): 3097-3107.

参考文献

[1] Lyu T-Y (吕亭豫), Gong Z (龚政), Zhang C-K (张长宽), et al. Reviews of morphological characteristics and evolution processes of silty mud tidal creeks. Journal of Hohai University (Natural Sciences) (河海大学学报:自然科学版), 2016, 44(2): 178-188 (in Chinese)
[2] Shen Y-M (沈永明), Zhang R-S (张忍顺), Wang Y-H (王艳红). The tidal creek character in salt marsh of Spartina alterniflora Loisel on strong tide coast. Geographical Research (地理研究), 2003, 22(4): 520-527 (in Chinese)
[3] Hou M-X (侯明行), Liu H-Y (刘红玉), Zhang H-B (张华兵). Effection of tidal creek system on the expansion of the invasive Spartina in the coastal wetland of Yancheng. Acta Ecologica Sinica (生态学报), 2014, 34(2): 400-409 (in Chinese)
[4] Luo M (骆梦), Wang Q (王青), Qiu D-D (邱冬冬), et al. Hydrological connectivity characteristics and ecological effects of a typical tidal channel system in the Yellow River Delta. Journal of Beijing Normal University (Natural Science) (北京师范大学学报:自然科学版), 2018, 54(1): 17-24 (in Chinese)
[5] Yang X-M (杨晓梅). Coastal Zone Remote Sensing Integrated Technology and Case Study. Beijing: Ocean Press, 2005 (in Chinese)
[6] Liu Z-J (刘志杰). Study on the Regional Differentiation and Evolution of Coastal Wetland in Yellow River Delta. Master Thesis. Qingdao: Ocean University of China, 2013 (in Chinese)
[7] Liu Y, Zhou M, Zhao S, et al. Automated extraction of tidal creeks from airborne laser altimetry data. Journal of Hydrology, 2015, 527: 1006-1020
[8] Mason DC, Scott TR, Wang HJ. Extraction of tidal channel networks from airborne scanning laser altimetry. Isprs Journal of Photogrammetry and Remote Sensing, 2007, 61: 67-83
[9] Zhou M-X (周旻曦). Monitoring Technique Research for Tidal Networks Developed in Jiangsu Middle Coast based on Multi-Source Remote Sensing Databases. Master Thesis. Nanjing: Nanjing University, 2016 (in Chinese)
[10] Yang K (杨康), Li M-C (李满春), Liu Y-X (刘永学), et al. Road extraction method using multi-points fast marching and minimum paths. Remote Sensing Technology and Application (遥感技术与应用), 2011, 26(3): 294-302 (in Chinese)
[11] He C, Liao ZX, Yang F, et al. Road extraction from sar imagery based on multiscale geometric analysis of detector responses. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2012, 5: 1373-1382
[12] Shao Y, Guo B, Hu X, et al. Application of a fast linear feature detector to road extraction from remotely sensed imagery. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2011, 4: 626-631
[13] Li Q, You J, Zhang D. Vessel segmentation and width estimation in retinal images using multiscale production of matched filter responses. Expert Systems with Applications, 2012, 39: 7600-7610
[14] Fraz MM, Remagnino P, Hoppe A, et al. Blood vessel segmentation methodologies in retinal images: A survey. Computer Methods and Programs in Biomedicine, 2012, 108: 407-433
[15] Zhang B, Zhang L, Zhang L, et al. Retinal vessel extraction by matched filter with first-order derivative of Gaussian. Computers in Biology and Medicine, 2010, 40: 438-445
[16] Wang X-H (王晓红), Zhao Y-Q (赵于前), Liao M (廖苗), et al. Automatic segmentation for retinal vessel based on multi-scale 2d gabor wavelet. Acta Automatica Sinica (自动化学报), 2015, 41(5): 970-980 (in Chinese)
[17] Dillabaugh CR, Niemann KO, Richardson DE. Semi-automated extraction of rivers from digital imagery. Geoinformatica, 2002, 6: 263-284
[18] Shen Z-F (沈占锋), Xia L-G (夏列钢), Li J-L (李均力), et al. Automatic and high-precision extraction of rivers from remotely sensed images with Gaussian normalized water index. Journal of Image and Graphics (中国图象图形学报), 2013, 18(4): 421-428 (in Chinese)
[19] Yang K, Li M, Liu Y, et al. River delineation from remotely sensed imagery using a multi-scale classification approach. IEEE Journal of Selected Topics in Applied Earth Observations & Remote Sensing, 2015, 7: 4726-4737
[20] Liu X-L (刘旭拢), Zhong K-W (钟凯文), Chen Z-L (陈志良), et al. Fast etraction technique of river channels based on landsat TM. Remote Sensing Technology and Application (遥感技术与应用), 2008, 23(1): 57-61 (in Chinese)
[21] Zhang Q (张强), Wu B (吴波). A novel method to extract narrow water with white top-hat transform. Journal of Fuzhou University (Natural Science) (福州大学学报:自然科学版), 2018, 46(1): 75-81 (in Chinese)
[22] O’callaghan JF, Mark DM. The extraction of drainage networks from digital elevation data. Computer Vision Graphics and Image Processing, 1984, 28: 323-344
[23] Freeman TG. Calculating catchment area with divergent flow based on a regular grid. Computers and Geosciences, 1991, 17: 413-422
[24] Sarmiento GN, Cipolletti MP, Perillo MM, et al. Metho-dology for classification of geographical features with remote sensing images: Application to tidal flat. Geomorphology, 2016, 257: 10-22
[25] Fu Y-Y (付勇勇), Wang X-H (王旭航), Deng J-S (邓劲松), et al. Extraction of water information in complex water-net plain with Chinese GF-2. Journal of Zhejiang University (Engineering Science) (浙江大学学报:工学版), 2017, 51(12): 2474-2480 (in Chinese)
[26] Li Y-H (李艳华), Ding J-L (丁建丽), Yan R-H (闫人华). Extraction of small river information based on China-made GF-1 remote sense images. Resources Science (资源科学), 2015, 37(2): 408-416 (in Chinese)
[27] Lohani B, Mason DC. Application of airborne scanning laser altimetry to the study of tidal channel geomorphology. Isprs Journal of Photogrammetry and Remote Sensing, 2001, 56: 100-120
[28] Jiang H (姜浩), Feng M (冯敏), Xiao T (肖桐), et al. A narrow river extraction method based on linear feature enhancement in tm image. Acta Geodaetica et Cartographica Sinica (测绘学报), 2014, 43(7): 705-710 (in Chinese)
[29] Isikdogan F, Bovik A, Passalacqua P. Automatic channel network extraction from remotely sensed images by singularity analysis. IEEE Geoscience and Remote Sensing Letters, 2015, 12: 2218-2221
[30] Luo W, Pingel T, Heo J, et al. A progressive black top hat transformation algorithm for estimating valley volu-mes on Mars. Computers and Geosciences, 2015, 75: 17-23
[31] Zhang Y-S (张永生), Liu J (刘军), Gong D-C (巩丹超). High-Resolution Remote Sensing Satellite Applications: Imaging Models, Processing Algorithms and Application Techniques. Beijing: China Science Publishing and Media LTD, 2014 (in Chinese)
[32] Liu Y-X (刘艳霞), Huang H-J (黄海军), Qiu Z-F (丘仲锋), et al. Monitoring change and position of coastlines from satellite images using slope correction in a tidal flat: A case study in the Yellow River Delta. Acta Geographica Sinica (地理学报), 2012, 67(3): 377-387 (in Chinese)
[33] Li Y-F (李元芳), Huang Y-L (黄云麟), Li S-K (李拴科). Preliminary analysis of tidal flat landforms and their sediments in the modern Yellow River Delta. Acta Oceanologica Sinica (海洋学报), 1991, 13(5): 662-671 (in Chinese)
[34] Healey RG, Pye K, Stoddart DR, et al. Velocity variations in salt marsh creeks, Norfolk, England. Estuarine, Coastal and Shelf Science, 1981, 13: 535-545
[35] Wang C-Y (王长耀), Liu Z-J (刘正军),Yan C-Y (颜春燕). A experimental study on imaging spectrometer data feature selection and wheat type identification. Journal of Remote Sensing (遥感学报), 2006, 10(2): 249-255 (in Chinese)
[36] Ohtsu N. A Threshold selection method from gray-level histograms. IEEE Transactions on Systems, Man, and Cybernetics, 1979, 9: 62-66
[37] Rocchini D, Foody GM, Nagendra H, et al. Uncertainty in ecosystem mapping by remote sensing. Computers and Geosciences, 2013, 50: 128-135
[38] Yang Y, Liu Y, Zhou M, et al. Landsat 8 OLI image based terrestrial water extraction from heterogeneous backgrounds using a reflectance homogenization approach. Remote Sensing of Environment, 2015, 171: 14-32
[39] Wang XY, Bu J. A fast and robust image segmentation using FCM with spatial information. Digital Signal Processing, 2010, 20: 1173-1182
[40] Ahmed MN, Yamany SM, Mohamed N, et al. A modified fuzzy c-means algorithm for bias field estimation and segmentation of MRI data. IEEE Transactions on Medical Imaging, 2002, 21: 193-199
[41] Ghaffarian S, Ghaffarian S. Automatic histogram-based fuzzy C-means clustering for remote sensing imagery. Isprs Journal of Photogrammetry and Remote Sensing, 2014, 97: 46-57
[42] Chaudhuri S, Chatterjee S, Katz N, et al. Detection of blood vessels in retinal images using two-dimensional matched filters. IEEE Transactions on Medical Imaging, 1989, 8: 263-269
[43] Li Q, You J, Zhang D. Vessel segmentation and width estimation in retinal images using multiscale production of matched filter responses. Expert Systems with Applications, 2012, 39: 7600-7610
[44] Yang K, Li M, Liu Y, et al. River detection in remotely sensed imagery using gabor filtering and path opening. Remote Sensing, 2015, 7: 8779-8802
[45] Li W-P (李文苹), Wang X-H (王旭红), Li T-W (李天文), et al. Extraction method of spectral information of inland surface water body in yellow river basin. Bulletin of Soil and Water Conservation (水土保持通报), 2017, 37(2): 158-164 (in Chinese)

异质背景下黄河三角洲潮沟的遥感提取方法

Extracting method of tidal creek features under heterogeneous background at Yellow River Delta using remotely sensed imagery.

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 0

编辑推荐

Metrics

本文评价