湿地高分辨率遥感影像的变化检测

doi:10.3864/j.issn.0578-1752.2012.21.005

中国农业科学 ›› 2012, Vol. 45 ›› Issue (21): 4369-4376.doi: 10.3864/j.issn.0578-1752.2012.21.005

• 土壤肥料·节水灌溉·农业生态环境 • 上一篇下一篇

湿地高分辨率遥感影像的变化检测

祝锦霞, 郭庆华, 王珂

1.浙江财经学院经济与社会发展研究院，中国杭州310018
2. University of California，School of Engineering，Merced，CA 95343，US
3.浙江大学农业遥感与信息技术应用研究所，中国杭州 310029

收稿日期:2012-05-03 出版日期:2012-11-01 发布日期:2012-08-28
通讯作者: 祝锦霞，Tel：0571-87557369；E-mail：jxzhu1221@gmail.com
作者简介:祝锦霞，Tel：0571-87557369；E-mail：jxzhu1221@gmail.com
基金资助:
美国国家自然科学基金项目（EF0410408，CCF0120778）、国家自然科学基金（3080073，305711123）、国家“863”计划项目（2006AAI02204）

Change Detection on Wetlands Using High Spatial Resolution Imagery

ZHU Jin-Xia, GUO Qing-Hua, WANG Ke

1.浙江财经学院经济与社会发展研究院，中国杭州310018
2. University of California，School of Engineering，Merced，CA 95343，US
3.浙江大学农业遥感与信息技术应用研究所，中国杭州 310029

Received:2012-05-03 Online:2012-11-01 Published:2012-08-28

摘要/Abstract

摘要： 【目的】研究高分辨率遥感影像的湿地动态检测，为湿地资源的可持续发展提供信息支撑。【方法】充分利用面向像元和面向对象两种方法的优势和特点，结合多变量变化检测（MAD），提出对MAD变量的面向对象后分类方法（OB-M方法）。【结果】基于MAD变换的差异影像集中了两期影像的变化信息，基于像元差异影像的面向对象后分类方法能成功的检测多时相遥感影像的几何配准误差、单时相阴影、光照季节变化等“伪变化信息”，成功提取变化/未变化信息。【结论】比较传统的面向对象分类后比较和MAD方法，提出的OB-M方法能较好地提高湿地变化/未变化信息检测的精度。

关键词: 变化检测, 多变量变化检测, 湿地, 面向对象后分类

Abstract: 【Objective】With respect to the change detection on wetlands, very high spatial resolution images of drained managed wetland ponds were used, which could provide more information for further management. 【Method】 The proposed method is based on pixel-oriented difference image and object-based post-classification(OB-M). Multivariate alteration detection (MAD) transformation was used to get the extended difference image, and object-based decision tree classification was applied on MAD components to detect the true change information of difference image, which had a very significant shape feature.【Result】 The proposed OB-MAD can successfully detect the false change information, such as the inevitable mis-registration, shadow and vegetation phenology differences. Compared with the traditional MAD method with thresholds (Threshold-MAD) and the traditional object-based post-classification method (OB-T), the proposed OB-M method produced the highest accuracy, which took advantage of both pixel- and object-based technology.【Conclusion】Results indicated that the object-based post-classification on MAD components can well detect the change information of wetlands.

Key words: change detection, multivariate alteration detection(MAD), wetlands, object-oriented post-classification

祝锦霞, 郭庆华, 王珂. 湿地高分辨率遥感影像的变化检测[J]. 中国农业科学, 2012, 45(21): 4369-4376.

ZHU Jin-Xia, GUO Qing-Hua, WANG Ke. Change Detection on Wetlands Using High Spatial Resolution Imagery[J]. Scientia Agricultura Sinica, 2012, 45(21): 4369-4376.

0
/ / 推荐

导出引用管理器 EndNote|Reference Manager|ProCite|BibTeX|RefWorks

链接本文: https://www.chinaagrisci.com/CN/10.3864/j.issn.0578-1752.2012.21.005

https://www.chinaagrisci.com/CN/Y2012/V45/I21/4369

参考文献

[1]Toyra J, Pietroniro A. Towards operational monitoring of a northen wetland using geometics-based techiniques. Remote Sensing of Environment, 2005, 97: 174-191.

[2]Coppin I P, Jonckheere K, Muys N B. Digital change detection method in ecosystem monitoring: a review. International Journal of Remote Sensing, 2004,25(9): 1565-1596.

[3]王树功, 黎夏, 钟凯文, 周永章, 刘凯. 遥感与Gis技术在湿地定量研究中的应用趋势分析. 热带地理, 2005, 25(3): 201-205.

Wang S G, Li X, Zhong K W, Zhou Y Z, Liu K. Some trends of application of remote sensing and GIS to quantitative wetland research. Tropical Geography, 2005, 25(3): 201-205. (in Chinese)

[4]Toyra J, Pietroniro A, Martz L W. Summer flood mapping in a northern wetland using a combination of Radarsat and SPOT imagery. Remote Sensing and Hydrology, 2000, 267: 536-538.

[5]陈述彭. 遥感地学分析. 北京: 测绘出版社,1990: 17-19.

Chen S P. Remote Sensing Information for Geo-analysis. Beijing: Surveying and Mapping Press,1990: 17-19. (in Chinese)

[6]宋晓宇, 王纪华, 刘良云, 黄文江, 沈涛, 喻铮铮. 基于QuickBird 遥感影像的农田管理分区划分研究. 中国农业科学, 2007, 40(9): 1996-2006.

Song X Y, Wang J H, Liu L Y, Huang W J, Shen T, Yu Z Z. Rsearch of management zones generating based on QuickBird imagery. Scientia Agricultura Sinica, 2007, 40(9): 1996-2006. (in Chinese)

[7]钟家强, 王润生. 基于独立成分分析的多时相遥感图像变化检测. 电子与信息学报, 2006, 28(6): 994-998.

Zhong J Q. Wang R S. Multi-temporal remote sensing image change detection based on ICA. Journal of Electronics & Information Technology, 2006, 28(6): 994-998. (in Chinese)

[8]Canty M J, Nielsen A A. Visualization and unsupervised classification of changes in multispectral satellite imagery. International Journal of Remote Sensing, 2006, 27(18): 3961-3975.

[9]Nielsen A A, Conradsen K, Simpson J J. Multivariate alteration detection and MAF post-processing in multispectral, bi-temporal image data: new approaches to change detection studies. Remote Sensing of Environment, 1998, 64 (1): 1-19.

[10]Zhu J X, Guo Q H, Li D H, Harmon C. Reducing mis-registration and shadow effects on change detection in wetlands. Photogrammetric Engineering and Remote Sensing, 2011, 77(4): 325-334.

[11]Van de Voorde T W, De Genst F C. Improving pixel-based VHR land-cover classifications of urban areas with post-classification techniques. Photogrammetric Engineering & Remote Sensing, 2007, 73(9): 1017-1027.

[12]Mallinis G, Koutsias N, Tsakiri-Strati M, Karteris M. Object-based classification using Quickbird imagery for delineating forest vegetation polygons in a Mediterranean test site. Isprs Journal of Photogrammetry and Remote Sensing, 2008, 63(2): 237-250.

[13]王文杰, 赵忠明, 朱海青. 面向对象特征融合的高分辨率遥感图像变化检测方法. 计算机应用研究, 2009,26(8): 3149-3151.

Wang W J. Zhao Z M. Zhu H Q. Object-oriented change detection method based on features fusion for high-resolution remote sensing image. Application Research of Computers, 2009,26(8): 3149-3151. (in Chinese)

[14]张海霞, 卞正富. 遥感影像植被信息提取方法研究及思考. 地理空间信息, 2007, 5(6): 65-67.

Zhang H X, Bian Z F. Method for vegetation information extraction from remote sensing images. Geospatial Information, 2007, 5(6): 65-67. (in Chinese)

[15]Wulder M A, Kurz W A, Gillis M. National level forest monitoring and modeling in Canada. Progress in Planning, 2004, 61(4): 365-381.

[16]彭代亮, 黄敬峰, 金辉民. 基于MODIS-NDVI的浙江省耕地复种指数监测. 中国农业科学, 2006, 39(7): 1352-1357.

Peng D L, Huang J F, Jin H M. The monitoring for sequential cropping index of arable land in Zhejiang province using MODIS- NDVI. Scientia Agricultura Sinica, 2006, 39(7): 1352-1357. (in Chinese)

[17]Wang L, Sousa Wayne P, Gong P, Biging Gregory S. Comparison of IKONOS and QuickBird images for mapping mangrove species on the Caribbean coast of Panama. Remote Sensing of Environment, 2004, 91: 432-440.

[18]Desclée B, Bogaert P, Defourny P. Forest change detection by statistical object-based method. Remote Sensing of Environment, 2006, 102: 1-11.

[19]Im J, Jensen J R. A change detection model based on neighborhood correlation image analysis and decision tree classification. Remote Sensing of Environment, 2005, 99: 326-340.

[20]Im J, Rhee J, Jensen J R, Hodgson M E. Au automated binary change detection model using a calibration appraoch. Remote Sensing of Environment, 2007, 106: 89-105.

[21]Townshend J R G, Justice C O, Gurney C, McManus J. The impact of mis-registration on change detection. IEEE Transactions on Geoscience and Remote Sensing, 1992, 30(5): 1054-1060.

[22]汪求来. 面向对象遥感影像分类方法及其应用研究—以深圳市福田区植被提取为例[D]. 南京:南京林业大学,2008.

Wang Q L. Study on object-oriented remote sensing image classification and its application-taking urban vegetation extraction in Futian, Shenzhen city for example[D]. Nanjing: Nanjing Forestry University,2008. (in Chinese)

湿地高分辨率遥感影像的变化检测

Change Detection on Wetlands Using High Spatial Resolution Imagery

PDF

赞

可视化

被引次数

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 3

Metrics

本文评价

推荐阅读 0

[1]	袁武,靳振江,程跃扬,贾远航,梁锦桃,邱江梅,潘复静,刘德深. 岩溶湿地和稻田的土壤酶活性与CO₂和CH₄排放特征[J]. 中国农业科学, 2020, 53(14): 2897-2906.
[2]	靳振江, 邰继承, 潘根兴, 李恋卿, 宋祥云, 谢添, 刘晓雨, 王丹. 荆江地区湿地与稻田有机碳、微生物多样性及土壤酶活性的比较[J]. 中国农业科学, 2012, 45(18): 3773-3781.
[3]	曾希柏,黄雪夏,刘子刚,李莲芳,杨佳波. 种植年限对三江平原农田土壤剖面性质及碳、氮含量的影响[J]. 中国农业科学, 2006, 39(06): 1186-1195 .