Please wait a minute...
img

官方微信

遥感技术与应用  2015, Vol. 30 Issue (6): 1146-1152    DOI: 10.11873/j.issn.1004-0323.2015.6.1146
遥感应用     
基于决策树的干旱区湿地信息自动提取—以疏勒河流域为例
韩忻忆1,2,颉耀文1
(1.兰州大学资源环境学院,甘肃兰州730000,
2.北京师范大学减灾与应急管理研究院,北京100875)
The Automatic Extraction of Wetland Information in Arid Zone based on Decision Tree Algorithm—— A Case Study in the Shule River Basin
Han Xinyi1,2,Xie Yaowen1
(1.College of Earth and Environmental Sciences,Lanzhou University,Lanzhou 730000,China;
2.Academy of Disaster Reduction and Emergency Management Ministry,
Beijing Normal University,Beijing 100875,China)
 全文: PDF(6463 KB)  
摘要:

以疏勒河流域为研究区,探讨了干旱区湿地的遥感影像自动提取方法。以Landsat 8卫星影像数据为主要数据源并辅以数字高程模型(DEM),利用改进的干旱区湿地指数(MAZWI)、归一化植被指数(NDVI)、地表反照率(Albedo)、灰度共生矩阵(GLCM)的非相似性分量等识别指数构建决策树模型,对研究区湿地进行提取,并将结果与最大似然分类结果进行对比。结果表明:该方法在一定程度上提高了湿地提取的精度,与最大似然分类结果相比总体精度和Kappa系数分别提高了6.52%和0.124。证明决策树法是干旱区水域湿地自动提取的一种有效手段。

关键词: 干旱区湿地决策树信息提取遥感分类    
Abstract:

Selecting the Shule River Basin which locates in the west of Gansu Province as the study area,the automated extraction method for wetlands in arid regions was discussed.Using the Landsat 8 satellite images as the data sources,supported by the digital elevation model (DEM),the modified arid zone wetlands index (MAZWI),the normalized difference vegetation indices (NDVI) and the surface albedo,and the identification of dissimilarity index of the gray level co-occurrence matrix (GLCM),were used as the indicators to establish the decision tree model and the wetlands were extracted.Comparing with the results obtaining by the maximum likelihood supervised classification,it showed that the decision tree method based on the indices can improve the overall accuracy by 6.52% and the overall kappa coefficient by 0.1243.The results of this study suggested that the decision tree method based on indices is an effective tool for wetlands classification in arid zone.

Key words: Arid zone    Decision tree    Information extraction    Remote sensing classification
收稿日期: 2014-04-14 出版日期: 2016-01-25
:  TP 79  
基金资助:

国家基础科学人才培养基金科研训练及科研能力提高项目(J1210065),国家自然科学基金项目(41471163)。

通讯作者: 颉耀文(1969-),男,甘肃天水人,教授,博士生导师,主要从事基于地理信息技术的干旱区环境变化研究。Email: xieyw@lzu.edu.cn。   
作者简介: 韩忻忆(1993-),女,青海西宁人,硕士研究生,主要从事灾害遥感方面的研究。Email:yixin_sunny@126.com。
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章  
韩忻忆
颉耀文

引用本文:

韩忻忆,颉耀文. 基于决策树的干旱区湿地信息自动提取—以疏勒河流域为例[J]. 遥感技术与应用, 2015, 30(6): 1146-1152.

Han Xinyi,Xie Yaowen. The Automatic Extraction of Wetland Information in Arid Zone based on Decision Tree Algorithm—— A Case Study in the Shule River Basin. Remote Sensing Technology and Application, 2015, 30(6): 1146-1152.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2015.6.1146        http://www.rsta.ac.cn/CN/Y2015/V30/I6/1146

[1]Wang Xiao,Zhang Kebin,Yang Xiaohui,et al.Research on Boundary Definition and Changes of Wetland-dry Grassland[J].Acta Ecologica Sinica,2012,32(16):5121-5127.[王晓,张克斌,杨晓晖,等.半干旱区湿地-干草原交错带边界判定及其变化[J].生态学报,2012,32(16):5121-5127.]

[2]Qi Dengchen,Chen Wenye,Zhang Jiqiang,et al.Status,Degraded Causes and Comprehensive Treatment of Dunhuang Xihu Wetland Ecosystem[J].Acta Prataculturae Sinica,2010,19(4):194-203.[戚登臣,陈文业,张继强,等.敦煌西湖湿地生态系统现状、退化原因及综合修复对策[J].草业学报,2010,19(4):194-203.]

[3]Wang Aihua,Zhang Shuqing,Zhang Bai.Application of Remote Sensing and Geographical Information System Technology to Wetland Research[J].Remote Sensing Technology and Application,2001,16(3):200-204.[汪爱华,张树清,张柏.遥感和地理信息系统技术在湿地研究中的应用[J].遥感技术与应用,2001,16(3):200-204.]

[4]Chopra R,Verma V K,Sharma P K.Mapping Monitoring and Conservation of Harike Wetland Ecosystem,Punjab,India,through Remote Sensing[J].International Journal of Remote Sensing,2001,(1):89-98.

[5]Shen Songping,Wang Jun,You Lijun,et al.Remote Sensing Dynamic Monitoring of the Zoigê Marsh Wetland[J].Acta Geologica Sichuan,2005,25(2):119-121.[沈松平,王军,游丽君,等.若尔盖沼泽湿地遥感动态监测[J].四川地质学报,2005,25(2):119-121.]

[6]Kindscher K,Fraser A,Jakubauskas M E.Identifying Wetland Meadows in Grand Teton National Park Using Remote Sensing and Average Wetland Values[J].Wetlands Ecology and Management,1997,5(4):265-273.

[7]Wu Yunjun,Zhang Shuwen,Bao Chunhong.Study on Quantificational Model of Marsh Information based on TM Spectral Characteristics[J].Wetland Science,2005,3(3):205-209.[吴运军,张树文,包春红.基于TM光谱特征的沼泽地定量提取模式研究[J].湿地科学,2005,3(3):205-209.]

[8]Qiao Ting,Zhang Huaiqing,Chen Yongfu,et al.Extraction of Vegetation Information based on NDVI Segmentation and Object-oriented Method[J].Journal of Northwest Forestry University,2013,28(4):170-175.[乔婷,张怀清,陈永富,等.基于NDVI分割与面向对象的东洞庭湖湿地植被信息提取技术[J].西北林学院学报,2013,28(4):170-175.][9]Tian Bo,Zhou Yunxuan,Zheng Zongsheng.Object-oriented Image Analysis Method for Estuarine Tidal Flat Accretion and Erosion Study[J].Resources and Environment in the Yangtze Basin,2008,(3):419-423.[田波,周云轩,郑宗生.面向对象的河口滩涂冲淤变化遥感分析[J].长江流域资源与环境,2008,(3):419-423.]

[10]Xie Jing,Wang Zongming,Mao Dehua,et al.Remote Sensing Classification of Wetlands Using Object-oriented Method and Multi-season HJ-1 Images——A Case Study in the Sanjiang Plain North of the Wandashan Mountain[J].Wetland Science,2012,10(4):429-438.[谢静,王宗明,毛德华,等.基于面向对象方法和多时相 HJ-1影像的湿地遥感分类——以完达山以北三江平原为例[J].湿地科学,2012,10(4):429-438.]

[11]Wu Jian,Peng Daoli.Wetland Information Extraction based on Improved Linear Spectral Mixture Model[J].Journal of China Agricultural University,2011,16(3):140-144.[吴见,彭道黎.改进线性光谱混合分解模型湿地信息提取[J].中国农业大学学报,2011,16(3):140-144.]

[12]Zhang Yuhong,Zhang Ce,Zang Shuying.Applying Shape Morphology Image Processing Method to Analyze Landscape Pattern at Zhalong Wetland[J].Geography and Geo-Information Science,2011,27(4):103-106.[张玉红,张策,臧淑英.形态学图像处理方法在扎龙湿地景观格局分析中的应用[J].地理与地理信息科学,2011,27(4):103-106.]

[13]Li Xiaodong,Guo Zhongyang,Zhu Yanling,et al.Artificial Neural Network Classification of Wetland Integrating GIS Data:A Case Study of Dongtan Wetland in Chongming,Shanghai[J].Journal of East China Normal University (Natural Science),2010,(4):26-34.[栗小东,过仲阳,朱燕玲,等.结合GIS数据的神经网络湿地遥感分类方法:以上海崇明岛东滩湿地为例[J].华东师范大学学报(自然科学版),2010,(4):26-34.]

[14]Wang Qingguang,Pan Yanfang.Study on Wetland Remote Sensing based on BP Neural Network[J].Journal of Shaoguan University·Natural Science,2007,28(3):72-75.[王庆光,潘燕芳.基于BP神经网络的湿地遥感分类[J].韶关学院学报(自然科学),2007,28(3):72-75.]

[15]Yao Yunjun,Zhang Zexun,Qin Qiming,et al.Study on Wet-land Information Extraction of Remote Sensing Images based on Support Vector Machine[J].Application Research of Computers,2005,25(4):989-990,995.[姚云军,张泽勋,秦其明,等.基于支持向量机的遥感影像湿地信息提取研究[J].计算机应用研究,2005,25(4):989-990,995.]

[16]Zhang Ce,Zang Shuying,Jin Zhu,et al.Remote Sensing Classification for Zhalong Wetlands based on Support Vector Machine[J].Wetland Science,2011,9(3):263-269.[张策,臧淑英,金竺,等.基于支持向量机的扎龙湿地遥感分类研究.湿地科学,2011,9(3):263-269.]

[17]Liu Bing,Lin Yi.Wetland Information Extraction from ETM+〖JP〗 Image based on Decision Tree Method[J].Engineering of Surveying and Mapping,2013 (1):63-66.[刘冰,林怡.基于决策树方法的ETM+影像湿地信息提取[J].测绘工程,2013 (1):63-66.]

[18]Qiao Yanwen,Zang Shuying,Na Xiaodong.The Information Extraction of Freshwater Marsh Wetland based on the Decision Tree Method:Taking Zhalong Wetland as an Example[J].Chinese Agricultural Science Bulletin,2013,29(8):169-174.[乔艳雯,臧淑英,那晓东.基于决策树方法的淡水沼泽湿地信息提取[J].中国农学通报,2013,29(8):169-174.]

[19]Li Jing,Sun Hu,Xing Dongxing,et al.Characteristics of Wetland and Its Conservation in Arid and Semi-arid Areas in North West of China[J].Journal of Desert Research,2003,23(6):670-674.[李静,孙虎,邢东兴,等.西北干旱半干旱区湿地特征与保护[J].中国沙漠,2003,23(6):670-674.]

[20]Zou Wentao,Zhang Huaiqing,Ju Hongbo,et al.Study on Highland Wetlands Remote Sensing Classification based on Decision Tree Algorithm[J].Forest Research,2011,24(4):464-469.[邹文涛,张怀清,鞠洪波,等.基于决策树的高寒湿地类型遥感分类方法研究[J].林业科学研究,2011,24(4):464-469.]

[21]Breiman L,Friedman J H,Olshen R A,et al.Classification and Regression Trees[M].Monterey,California,USA:Wadsworth International Group,1984.

[22]Yohannes Y,Hoddinott J.Classification and Regression Tree:An Introduction[M].Washington,D.C.,U.S.A:International Food Policy Research Institute,1999.

[23]Zhang Fang.Study on Extraction Method of Arid Zone Wetlands Information based on Remote Sensing Technic:A Case Study in the Hetian Oasis[D].Urumqi:Xinjiang University,2008.[张芳.基于遥感技术的干旱区湿地信息提取方法研究[D].乌鲁木齐:新疆大学,2008.]

[24]Chen Xiaoling,Zhao Hongmei,Tian Liqiao.Remote Sensing of Environment:Models and Applications[M].Wuhan:Wuhan University Press,2008.[陈晓玲,赵红梅,田礼乔.环境遥感模型与应用[M].武汉:武汉大学出版社,2008.]

[25]Wang K,Liang S,Schaaf C L,et al.Evaluation of Moderate Resolution Imaging Spectroradiometer Land Surface Visible and Shortwave Albedo Products at FLUXNET Sites[J].Journal of Geophysical Research:Atmospheres (1984~2012),2010,115(D17).

[26]Liang S.Narrowband to Broadband Conversion of Land Surface Albedo.I.Algorithms[J].Remote Sensing of Environment,2001,76:213-238.

[27]Feng Yan,Feng Haixia.TM Data Retrieval and Analysis of Beijing Area Surface Albedo[J].Science of Surveying and Mapping,2012,37(5):164-166.[冯焱,冯海霞.北京地区地表反照率 TM 数据反演与分析[J].测绘科学,2012,37(5):164-166.]

[28]Feng Jianhui,Yang Yujing.Study of Texture Images Extraction based on Gray Level Co-Occurrence Matrix[J].Beijing Surveying and Mapping,2007,(3):19-22.[冯建辉,杨玉静.基于灰度共生矩阵提取纹理特征图像的研究[J].北京测绘,2007,(3):19-22.]

[1] 王常颖,田德政,韩园峰,隋毅,初佳兰. 基于属性差决策树的全极化SAR影像海冰分类[J]. 遥感技术与应用, 2018, 33(5): 975-982.
[2] 李想,刘凯,朱远辉,蒙琳,于晨曦,曹晶晶. 基于资源三号影像的红树林物种分类研究[J]. 遥感技术与应用, 2018, 33(2): 360-369.
[3] 王凯,赵军,朱国锋. 基于GF-1遥感数据决策树与混合像元分解模型的冬小麦种植面积早期估算[J]. 遥感技术与应用, 2018, 33(1): 158-167.
[4] 周晓宇,陈富龙. 四川大熊猫栖息地PALSAR时序数据森林覆盖动态监测研究[J]. 遥感技术与应用, 2017, 32(6): 1100-1106.
[5] 周在明,杨燕明,陈本清. 基于无人机影像的滩涂入侵种互花米草植被信息提取与覆盖度研究[J]. 遥感技术与应用, 2017, 32(4): 714-720.
[6] 姬忠林,张月平,李乔玄,刘绍贵,李淑娟,任红艳. 基于GF-1影像的冬小麦和油菜种植信息提取[J]. 遥感技术与应用, 2017, 32(4): 760-765.
[7] 吕利利,颉耀文,黄晓君,张秀霞,李汝嫣. 基于CART决策树分类的沙漠化信息提取方法研究[J]. 遥感技术与应用, 2017, 32(3): 499-506.
[8] 郝泷,陈永富,刘华,朱雪林,达哇扎西,李伟娜. 基于纹理信息CART决策树的林芝县森林植被面向对象分类[J]. 遥感技术与应用, 2017, 32(2): 386-394.
[9] 马斅良,王钦军,陈玉. 基于图像模拟的蚀变矿物信息提取技术评价[J]. 遥感技术与应用, 2016, 31(4): 756-763.
[10] 雷光斌,李爱农,谭剑波,张正健,边金虎,靳华安,赵伟,曹小敏. 基于多源多时相遥感影像的山地森林分类决策树模型研究[J]. 遥感技术与应用, 2016, 31(1): 31-41.
[11] 董保根,马洪超,车森,解龙根,何乔. LiDAR点云支持下地物精细分类的实现方法[J]. 遥感技术与应用, 2016, 31(1): 165-169.
[12] 林志垒,晏路明. 高光谱影像的BDT-SVM地物分类算法与应用[J]. 遥感技术与应用, 2016, 31(1): 177-185.
[13] 王颖洁,刘良云,王志慧. 基于时序Landsat数据的三江平原植被地表类型变化遥感探测研究[J]. 遥感技术与应用, 2015, 30(5): 959-968.
[14] 刘吉凯,钟仕全,梁文海. 基于多时相Landsat8 OLI影像的作物种植结构提取[J]. 遥感技术与应用, 2015, 30(4): 775-783.
[15] 田力,徐雯佳. 卫星遥感海冰监测技术在河北省近海海域的应用[J]. 遥感技术与应用, 2015, 30(4): 793-797.