地球信息科学学报 ›› 2011, Vol. 13 ›› Issue (2): 266-272.doi: 10.3724/SP.J.1047.2011.00266

• 遥感技术与应用 • 上一篇    下一篇

凝聚层次聚类的MODIS海冰外缘线提取算法与应用

王宁1,2,3, 张晰3, 纪永刚3, 鲁统臻3, 于波2   

  1. 1. 山东省海洋生态环境与防灾减灾重点实验室,青岛 266033;
    2. 国家海洋局北海预报中心,青岛 266033;
    3. 国家海洋局第一海洋研究所,青岛 266061
  • 收稿日期:2009-10-29 修回日期:2010-07-28 出版日期:2011-04-25 发布日期:2011-04-25
  • 通讯作者: 王宁(1978-),女,山东龙口人,硕士研究生。从事海洋遥感应用研究。E-mail:wn780324@126.com E-mail:wn780324@126.com
  • 基金资助:

    国家"863"计划资助项目"遥感海洋生态环境监测技术系统"(2007AA092102);国家自然科学基金项目"多时相SAR渤海薄冰厚度探测"(40906093)。

A Method of MODIS Sea Ice Edge Extraction Based on Agglomerative Hierarchical Clustering Method

WANG Ning1,2,3, ZHANG Xi3, JI Yonggang3, LU Tongzhen3, YU Bo2   

  1. 1. Shandong Provincial Key Laboratory of Marine Ecology and Environment & Disaster Prevention and Mitigation, Qingdao 266033,China;
    2. North China Sea Marine Forecasting Center of SOA,Qingdao 266033, China;
    3. The First Institute of Oceanography, SOA,Qingdao 266061, China
  • Received:2009-10-29 Revised:2010-07-28 Online:2011-04-25 Published:2011-04-25

摘要: 本文论述了海冰外缘线在我国海冰监测和预报中的重要作用,分析了常规的海冰外缘线提取方法存在的不足。同时,结合MODIS遥感影像和渤海悬浮泥沙分布的特点,讨论了凝聚层次聚类的MODIS影像分割算法[1]。该算法以影像光谱特性和形状特性作为判定规则,通过加入影像网格化、碎斑和噪声去除等分析,在优化冰水识别参数及分割结果提取海冰外缘线的基础上,将该算法提取的结果进行了分析。实验表明,该算法能够较好地去除碎斑和噪声。同时对MODIS遥感影像的分割,得到理想的结果。

关键词: 凝聚层次聚类算法, 海冰外缘线, MODIS, 冰水识别

Abstract: In this paper we suggested the importance of sea ice edge in our country's sea ice monitoring and forcasting. The sea ice edge is the boundary between water and ice. Monitoring of sea ice edge's position and the change is vital to sea water exchange, marine fishery, nearshore marine operation, offshore oil-gas exploration, meteorological observation and so on. The conventional method of sea ice edge extraction often has the shortcomings of massive mixed spots existing and the slow computation speed. Clustering is a way to group objects into more than one cluster, so that the same cluster objects have a higher similarity, and an object in a different cluster is larger. Agglomerative hierarchical clustering algorithm is a bottom-up policy. It first considers each object as a cluster, and then combines these clusters into larger cluster, until all the objects in a cluster, or one condition is met. Based on the agglomerative hierarchical clustering algorithm, combined with MODIS images and the characteristics of Bohai suspended sediment distribution, we discussed the MODIS image segmentation algorithm. The algorithm regards spectral characteristics and shape properties as the rule, joining image meshing, breaking grouper and noise removal and other functions, and optimizing the ice-water identification parameters. This algorithm can effectively improve the availability and accuracy of image segmentation results. We combined this algorithm and edge detection algorithms to extract sea ice edge of the image segmentation results. The algorithm has a better removal of broken spot and noise. Comparing the result of interpretation of MODIS data and the result from the algorithm, we can conclude that the algorithm can better complete the MODIS image segmentation and on this basis we can have a better result of the sea ice edge.

Key words: agglomerative hierarchical clustering method, sea ice edge, MODIS, ice-water identification