Please wait a minute...
img

官方微信

遥感技术与应用  2015, Vol. 30 Issue (5): 959-968    DOI: 10.11873/j.issn.1004-0323.2015.5.0959
遥感应用     
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
王颖洁1,2,刘良云1,王志慧1
(1.中国科学院遥感与数字地球研究所,北京100094;
2.中国科学院大学,北京100049)
Land Covermapping based on Landsat Time-series Stacks in Sanjiang Plain
Wang Yingjie1,2,Liu Liangyun1,Wang Zhihui1
(1.Institute of Remote Sensing and Digital Earth,Chinese Academy of Sciences,Beijing 100094,China;
2.University of Chinese Academy of Sciences,Beijing 100049,China)
 全文: PDF 
摘要:

Landsat 卫星遥感数据具有分辨率较高,数据积累时间长的特点,在探测地表覆盖变化和地物分类中得到广泛应用。首先,对获取的Landsat TM/ETM+时间序列数据进行了定量化处理,获取了三江平原七台河市1989~2012年时间序列Landsat地表反射率图像。其次,设计了林地指数和湿地指数,提取了三江平原七台河区域地物光谱和时序特征,同时设计构建了地表覆盖分类和植被地表类型变化探测的决策树算法,实现了1989~2012年七台河区域的植被地表覆盖变化的动态监测,提取了森林覆盖变化的空间分布与变化时间。最后,对七台河区域地表覆盖与植被地表类型变化进行了精度检验,分类总体精度达到90.04%,Kappa系数达0.88。研究结果表明:基于定量化的Landsat时间序列数据的分类算法能克服单时相影像分类的缺陷,实现区域地物自动分类和地表覆盖变化的动态监测。

关键词: 时间序列数据地表覆盖变化动态监测决策树分类    
Abstract:

Landsat satellite data is widely used in monitoring land cover change and land cover classification by its medium resolution and long time\|series records.In this paper,twenty Landsat TM/ETM+ images in Qitaihe district in Sanjiang Plain were collected,and quantitatively processed for time\|series ground surface reflectance stacks from 1989 to 2012.Then,the forest index and wetland index were designed,and the spectral characteristics and their time\|series variation features of different land covers were extracted from these time\|series reflectance stacks.Thirdly,a decision tree\|algorithm was designed to classify different land covers and detect the temporal change of vegetation land\|types from 1989 to 2012.Finally,the classification result was validated by the ground survey data,with an overall precision of 90.04%,and a Kappa coefficient of 0.88.The result proved the potential of time\|series Landsat images for land\|cover and land\|use change.

Key words: Time-series data    Land cover change    Dynamic detect    Decision tree
收稿日期: 2014-07-18 出版日期: 2015-12-08
:  TP 79  
基金资助:

中国科学院对外合作重点项目(GJH21123),国家自然科学基金项目(4122208)。
刘良云(1975-),男,湖南邵阳人,研究员,主要从事植被遥感研究。Email:liuly@radi.ac.cn。

作者简介: 王颖洁(1990-),女,重庆人,硕士研究生,主要从事植被遥感应用研究。Email:wangyingjie213@mails.ucas.ac.cn。
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  
王颖洁
刘良云
王志慧

引用本文:

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.

Wang Yingjie,Liu Liangyun,Wang Zhihui. Land Covermapping based on Landsat Time-series Stacks in Sanjiang Plain. Remote Sensing Technology and Application, 2015, 30(5): 959-968.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2015.5.0959        http://www.rsta.ac.cn/CN/Y2015/V30/I5/959

[1]Conese C,Maselli F.Use of Multi-temporal Information to Improve Classification Performance of TM Scenes in Complex Terrain[J].ISPRS Journal of Photogrammetry and Remote Sensing,1991,46(4):187-197.

[2]Ma Li,Xu Xingang,Liu Liangyun,et al.Study on Crops Classification based on Multi-temporal NDVI and Characteristic Bands[J].Remote Sensing Technology and Application,2008,23(5):520-524.[马丽,徐新刚,刘良云,等.基于多时相 NDVI 及特征波段的作物分类研究[J].遥感技术与应用,2008,23(5):520-524.]

[3]Hansen M C,Egorov A,Roy D P,et al.Continuous Fields of Land Cover for the Conterminous United States Using Landsat Data:First Results from The Web—Enabled Landsat Data (WELD) Project[J].Remote Sensing Letters,2010,2(4):279     

[4]Tang Huan,Liu Liangyun,Jia Jianhua,et al.Land Cover Mapping based on Multi-temporal Spectral and Phenological Information in Shenmu County,Shanxi Province[J].Remote Sensing Information,2013,28(2):76-81.[唐欢,刘良云,贾建华,等.基于多时相光谱和物候特征的陕西神木县地物遥感分类研究[J].遥感信息,2013,28(2):76-81.]

[5]Liu Jiyuan,Zhang Zengxiang,Xu Xinliang,et al.Spatial Patterns and Driving Forces of Land Use Change in China in the Early 21st Century[J].Acta Geographica Sinica,2009,64(12):1411-1420.[刘纪远,张增祥,徐新良,等.21世纪初中国土地利用变化的空间格局与驱动力分析[J].地理学报,2009,64(12):1411-1420.]

[6]Brandt J S,Kuemmerle T,Li Haomin,et al.Using Landsat Imagery to Map Forest Change in Southwest China in Response to the National Logging Ban Ecotourism Development[J].Remote Sensing of Environment,2012,121:358-369.

[7]Kennedy R E,Cohen W B,Schroeder T A.Trajectory-based Change Detection for Automated Characterization of Forest Disturbance Dynamics[J].Remote Sensing of Environment,2007,110(3):370-386.

[8]Huang C Q,Goward S N,Schleeweis K,et al.Dynamics of National Forests Assessed Using the Landsat Record:Case Studies in Eastern United States[J].Remote Sensing of Environment,2009,113(7):1430-1442.

[9]Liu L Y,Tang H,Caccetta P,et al.Mapping Afforestation and Deforestation from 1974-2012 Using Landsat Time-series Stacks in Yulin District,a Key Region of the Three-north Shelter Region,China[J].Environmental Monitoring and Assessment,2013,185:9949-9965.

[10]Hansen M C,Potapov P V,Moore R,et al.High-resolution Global Maps of 21st-Century Forest Cover Change[J].Science,2013,342(6160):850-853.

[11]Jiang Gengming,Niu Zheng,Ruan Weili,et al.A Study on Removing the Noises in MODIS 1B Images[J].Remote Sensing Technology and Application,2003,18(6):393-398.[蒋耿明,牛铮,阮伟利,等.MODIS 影像条带噪声去除方法研究[J].遥感技术与应用,2003,18(6):393-398.]

[12]Song Xiaoyu,Liu Liangyun,Li Cunjun et al.Cloud Removing based on Single Remote Sensing Image[J].Optical Technique,2006,32(2):299-303.[宋晓宇,刘良云,李存军,等.基于单景遥感影像的去云处理研究[J],光学技术,2006,32(2):299-303.]

[13]Caccetta P,Furby S L,O’Connell J,et al.Continental Monitoring:34 Years of Land Cover Change Using Landsat Imagery[J].32nd International Symposium on Remote Sensing of Environment,2007:25-29.

[14]Hu Y,Liu L Y,Liu L L,et al.A Landsat-5 Atmospheric Correction based on MODIS Atmosphere Products and 6S Model[J].IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2014,7(5):1609-1615.

[15] Cohen W B,Maiersperger T K,Gower S T,et al.An Improved Strategy for Regression of Biophysical Variables and Landsat ETM+ Data[J].Remote Sensing of Environment,2003,84(4):561-571.

[16]Canty M J,Nielsen A A.Automatic Radiometric Normalization of Multi-temporal Satellite Imagery with the Iteratively Re-weighted MAD Transformation[J].Remote Sensing of Environment,2008,112(3):1025-1036.

[17]Huang C Q,Goward S N,Masek J G,et al.An Automated Approach for Reconstructing Recent Forest Disturbance History Using Dense Landsat Time Series Stacks[J].Remote Sensing of Environment,2010,114(1):183-198.

[18]Savitzky A,Golay M J E.Smoothing and Differ-entiation of Data by Simplified Least Squares Procedures[J].Analytical Chemistry,1964,36:1627-1639.

[19]Deng Shubin.ENVI for Remote Sensing Image Processing[M].Beijing:Science Press,2010.[邓书斌.ENVI遥感图像处理方法[M].北京:科学出版社,2010.]

[1] 汪航,师茁. 基于MODIS时间序列数据的春尺蠖虫害遥感监测方法研究—以新疆巴楚胡杨为例[J]. 遥感技术与应用, 2018, 33(4): 686-695.
[2] 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.
[3] 赵永光,李传荣,马灵玲,唐伶俐,王宁. 一种遥感图像太阳—观测几何归一化方法[J]. 遥感技术与应用, 2016, 31(2): 260-266.
[4] 范一大,和海霞,李博,刘明. 基于HJ-1 CCD数据的洪涝灾害范围动态监测研究—以黑龙江省抚远县为例[J]. 遥感技术与应用, 2016, 31(1): 102-108.
[5] 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.
[6] 耿丽英,马明国. 长时间序列NDVI数据重建方法比较研究进展[J]. 遥感技术与应用, 2014, 29(2): 362-368.
[7] 黄威,汪小钦,陈芸芝,周小成,肖能文. 基于面向对象的平潭岛大比例尺森林资源监测方法[J]. 遥感技术与应用, 2014, 29(1): 138-143.
[8] 丁 一,张 杰,马 毅,江 涛,王 强,单春之. 一种考虑与主要水体距离关系的海岸带湿地遥感分类方法[J]. 遥感技术与应用, 2013, 28(5): 785-790.
[9] 王嘉楠,叶勤,林怡. 不同大气校正方法对中小湖泊蓝藻遥感动态监测的影响[J]. 遥感技术与应用, 2013, 28(1): 157-164.
[10] 郭芬芬,范建容,边金虎,刘飞,张怀珍. 基于MODIS NDVI时间序列数据的藏北草地类型识别[J]. 遥感技术与应用, 2011, 26(6): 821-826.
[11] 周淑玲,徐涵秋. 基于决策树的泉州湾沿海防护林动态变化研究[J]. 遥感技术与应用, 2011, 26(5): 619-626.
[12] 宋春桥,柯灵红,游松财,刘高焕,钟新科. 基于TIMESAT的3种时序NDVI拟合方法比较研究—以藏北草地为例[J]. 遥感技术与应用, 2011, 26(2): 147-155.
[13] 李杭燕, 马明国, 谭俊磊. 时序NDVI数据集重建综合方法研究[J]. 遥感技术与应用, 2010, 25(6): 891-896.
[14] 邵晓敏, 刘勇. 基于纹理的乌兰布和沙漠地区植被信息提取[J]. 遥感技术与应用, 2010, 25(5): 687-694.
[15] 别 强, 赵传燕, 彭守璋, 冯兆东. 基于多元数据和不同分类算法的遥感影像信息提取及精度评价
——以祁连山东段为例
[J]. 遥感技术与应用, 2009, 24(5): 576-581.