针对全国海域使用情况的监测需求,本文应用扩展的证据理论进行围填海区域检测,预设类别空间为{围填海,海水}。实验结果显示基于扩展的证据理论不仅能够较准确地检测出围填海区域,而且将浅海中的水下沙脊或小岛划分为不确定的未知类别。说明扩展的证据理论能够更好地完成围填海的检测,体现了扩展的证据理论解决实际问题的能力,同时,也为全海域的围填海监测提供了新的思路和扩展空间。
Abstract
Aiming at the monitoring requirement of sea area using situation, the extended evidence theory is used to detect reclamation area and the default category space is {reclamation, seawater}. Experimental results show that the extended evidence theory can not only detect the reclamation area with high accuracy, but also identify the underwater sand ridges or small islands in the shallow water as the uncertainty category. That shows the extended evidence theory has the ability to solve the problem of reclamation detection, which provides a new thinking of reclamation monitoring.
关键词
D-S证据理论 /
扩展 /
遥感影像 /
围填海检测
Key words
Dempster-Shafer evidence theory /
extended evidence theory /
remote sensing /
reclamation detection
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
参考文献
[1] State Oceanic Administration. National marine affairs development plan[EB/OL]. http://www.soa.gov.cn/zwgk/fwjgwywj/gwyfgwj/201211/t20121105_5261.html.
国家海洋局.国家海洋事业发展规划[EB/OL].http://www.soa.gov.cn/zwgk/fwjgwywj/gwyfgwj/201211/t20121105_5261.html.
[2] XIAO Kang, XU Hui-ping, YE Na. Preliminary research on the reclamation at the Fujian coast based on the remote sensing imagery[J]. Marine Science Bulletin,2013,32(6):685-694.
肖康,许惠平,叶娜.基于遥感影像的福建围填海初步研究[J].海洋通报,2013,32(6):685-694.
[3] LIU Rong-jie, ZHANG Jie, MA Yi, et al. Monitoring and analysis of sea reclamations in Sanshawan Bay based remote sensing in the past 30 years[J]. Ocean Development and Management, 2014(9): 17-21.
刘荣杰,张杰,马毅,等.三沙湾30余年来围填海遥感监测与分析[J].海洋开发与管理,2014(9):17-21.
[4] LIU Qin-qin. Survey and analysis of sea reclamations in Guangdong Province based on 3S[D]. Qingdao: Shandong University of Science and Technology, 2010.
刘琴琴.基于3S技术的广东省围填海调查与分析[D].青岛:山东科技大学,2010.
[5] WU Zheng-peng, XI Ge,WANG Jian-Jie. Reclamation monitoring based on the multi-source remote sensing image——As an example of Tianjin Nangang Industrial Zone[J]. Urban Geotechnical Investigation & Surveying,2012(6):77-80.
吴正鹏,奚歌,王健洁.基于多源遥感影像的围填海监测——以天津南港工业区为例[J].城市勘测,2012(6):77-80.
[6] JU Ming-ming, WANG Min, ZHANG Dong, et al. Study on the remote-sensing-based monitoring of reclamation project area by using the object-oriented image analysis technique[J]. Marine Science Bulletin,2013,32(6):678-684.
鞠明明,汪闽,张东,等.基于面向对象图像分析技术的围填海用海工程遥感监测[J].海洋通报,2013,32(6):678-684.
[7] ZHU Li-li, SHAO Feng-jing, WANG Chang-ying, et al. The Sea-filling land detect method research using remote sensing images based on data mining[J]. Journal of Qingdao University:Natural Science Edition,2012,25(2):53-57,66.
朱丽丽,邵峰晶,王常颖,等.基于数据挖掘的遥感影像围填海智能检测方法研究[J].青岛大学学报:自然科学版,2012,25(2):53-57,66.
[8] WANG Chang-ying. Coastal land covers classification of remote sensing images based on data mining technology[D]. Qingdao: Ocean University of China,2009.
王常颖.基于数据挖掘的遥感影像海岸带地物分类方法研究[D].青岛:中国海洋大学,2009.
[9] DEMPSTER A. Upper and lower probabilities induced by multivalued mapping[J]. Annals of Mathematical Statistics,1967,38(2):325-339.
[10] ZHU-GE Jian-wei, WANG Da-wei, CHEN Yi, et al. A network anomaly detector based on the D-S evidence theory[J]. Journal of Software,2006,17(3):463-471.
诸葛建伟,王大为,陈昱,等.基于D-S证据理论的网络异常检查方法[J].软件学报,2006,17(3):463-471.
[11] WANG Yong-qing. Principle and method of artificial intelligence[M]. Xi'an:Xi'an Jiaotong University Press,1998:185-190.
王永庆.人工智能原理与方法[M].西安:西安交通大学出版社,1998:185-190.
[12] WANG Chang-ying, ZHANG Jie, MA Yi. Coastal land covers classification of high-resolution images based on dempster-shafer evidence theory [C]//2008 International Conference on Computer Science and Software Engineering,2008:1 061-1 064.
[13] SHOYAIB M M, WADUD A A, CHAE O. A skin detection approach based on the Dempster-Shafer theory of evidence[J]. International Journal of Approximate Reasoning,2012,53(4):636-659.
[14] ZHANG Da-qiang, GUO Min-yi, ZHOU Jing-yu, et al. Context reasoning using extended evidence theory in pervasive computing environments[J].Future Generation Computer Systems,2010,26(2):207-216.
[15] JIROUŠEK R, VEJNAROVÁ J. Compositional models and conditional independence in evidence theory[J]. International Journal of Approximate Reasoning,2011,52(3):316-334.
[16] LIN T C. Decision-based fuzzy image restoration for noise reduction based on evidence theory[J]. Expert Systems with Applications,2011,38(7):8 303-8 310.
[17] COHEN Y, SHOSHANY M. Analysis of convergent evidence in an evidential reasoning knowledge-based classification[J]. Remote Sensing of Environment,2005,96(3-4):518-528.
[18] MAHDI T, REZA G, REZA E. Knitted fabric defect classification for uncertain labels based on Dempster-Shafer theory of evidence[J]. Expert Systems with Applications,2011,38(5):5 259-5 267.
基金
国家海洋局国家海域管理技术重点实验室开放基金项目资助(201205);国家自然科学基金项目资助(40906094,91130035);国家海洋公益性行业科研专项经费项目资助(201005011);山东省科技发展计划项目资助(2011YD15005);青岛市科技计划项目资助(13-1-4-156-jch)