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国土资源遥感  2017, Vol. 29 Issue (1): 29-35    DOI: 10.6046/gtzyyg.2017.01.05
  技术方法 本期目录 | 过刊浏览 | 高级检索 |
基于GF-1卫星影像的改进SWI水体提取方法
王瑾杰1,2, 丁建丽1, 张成2, 陈文倩1
1. 新疆大学资源与环境科学学院绿洲生态教育部重点实验室, 乌鲁木齐 830046;
2. 新疆交通职业技术学院, 乌鲁木齐 831401
Method of water information extraction by improved SWI based on GF-1 satellite image
WANG Jinjie1,2, DING Jianli1, ZHANG Cheng2, CHEN Wenqian1
1. Key Laboratory of Oasis Ecology, College of Resources and Environment Science, Xinjiang University, Urumqi 830046, China;
2. Vocational and Technical College of Xinjiang, Urumqi 831401, China
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摘要 

大尺度高精度山区河流信息提取是我国干旱区水资源开发利用的关键技术,而利用遥感影像提取水资源信息存在水体与山区阴影难以区分的瓶颈。以GF-1号卫星2 m分辨率全色波段影像和8 m分辨率多光谱影像为数据源,选取新疆特克斯河流域巴喀勒克水库为研究区,提出改进的阴影水体指数法(modified shade water index,MSWI)进行水体信息提取;同时运用单波段阈值法、NDWI法、单波段法与阴影水体指数法(shade water indes,SWI)相结合的决策树分类法(简称SWI)以及单波段法与MSWI相结合的决策树分类法(简称MSWI)分别对研究区水体信息进行提取,并进行了对比分析。研究结果表明,前2种方法与SWI和MSWI法相比,效果稍差;而SWI和MSWI法分类效果较好,其中MSWI比SWI法分类总精度高0.94%,提高了高分辨率遥感影像的解译精度,可为国产高分系列卫星影像在干旱区水资源信息提取中的应用提供技术支持。

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王旭东
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关键词 无人机影像Pix4D Mapper摄影测量点云nDSM面向对象支持向量机(SVM)建筑物提取    
Abstract

High-precision information extraction of mountainous rivers is a key technology for development and utilization of water resources in arid areas of China. Nevertheless, the utilization of remote sensing images cannot distinguish water form mountain shadows. In this paper, the authors used GF-1 satellite images with resolution of 2 m and 8 m as the data source, selected Baka Luck reservoirs as the study area, and put forward an improved method(modified shadow water index, MSWI) for water information extraction. At the same time, the authors used the single-band threshold method, the NDWI method, the single band method combined with the SWI decision tree classification(SWI) and the single band method combined with the MSWI decision tree classification (MSWI) respectively to extract water information in the study area. The results show that, compared with the SWI and the MSWI method, the first two methods have relatively poor performance. The SWI and MSWI classification effect is good and the total classification accuracy of MSWI is increased by 1.22% relative to the SWI method. It can provide technical support for the domestic high series satellite image information extraction in water resources in arid regions.

Key wordsUAV imagery data    Pix4D Mapper    photogrammetric point clouds    nDSM    objected-based    SVM    building extraction
收稿日期: 2015-10-08      出版日期: 2017-01-23
ZTFLH:  TP751.1  
基金资助:

国防科技工业局高分辨率对地观测重大专项(民用部分)项目“中亚地区跨境河流水资源利用开发遥感监测系统”(编号:95-Y40B02-9001-13/15-03-01)、教育部新世纪优秀人才支持计划项目“区域水盐遥感监测与模拟方法研究”(编号:NCET-12-1075)和2014年新疆研究生科研创新项目“基于国产高分卫星影像的水资源开发利用遥感监测系统”(编号:XJGRI2014022)共同资助。

通讯作者: 丁建丽(1974-),男,教授,博士生导师,主要从事干旱区资源遥感研究。Email:Ding_jl@163.com。     E-mail: Ding_jl@163.com
作者简介: 王瑾杰(1982-),女,博士研究生,主要研究方向为干旱区资源遥感。Email:skytian552@sohu.com。
引用本文:   
王瑾杰, 丁建丽, 张成, 陈文倩. 基于GF-1卫星影像的改进SWI水体提取方法[J]. 国土资源遥感, 2017, 29(1): 29-35.
WANG Jinjie, DING Jianli, ZHANG Cheng, CHEN Wenqian. Method of water information extraction by improved SWI based on GF-1 satellite image. REMOTE SENSING FOR LAND & RESOURCES, 2017, 29(1): 29-35.
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http://www.gtzyyg.com/CN/10.6046/gtzyyg.2017.01.05      或      http://www.gtzyyg.com/CN/Y2017/V29/I1/29

[1] 朱红雷,李颖,刘兆礼,等.基于半约束条件下不透水面的遥感提取方法[J].国土资源遥感,2014,26(2):48-53.doi:10.6046/gtzyyg.2014.02.09. Zhu H L,Li Y,Liu Z L,et al.Estimation of impervious surface based on semi-constrained spectral mixture analysis[J].Remote Sensing for Land and Resources,2014,26(2):48-53.doi:10.6046/gtzyyg.2014.02.09.
[2] 陈亚宁,杨青,罗毅,等.西北干旱区水资源问题研究思考[J].干旱区地理,2012,35(1):1-9. Chen Y N,Yang Q,Luo Y,et al.Ponder on the issues of water resources in the arid region of northwest China[J].Arid Land Geography,2012,35(1):1-9.
[3] 沈占锋,夏列钢,李均力,等.采用高斯归一化水体指数实现遥感影像河流的精确提取[J].中国图象图形学报,2013,18(4):421-428. Shen Z F,Xia L G,Li J L,et al.Automatic and high-precision extraction of rivers from remotely sensed images with Gaussian normalized water index[J].Journal of Image and Graphics,2013,18(4):421-428.
[4] 杨靛青,刘秉瀚.TM遥感图像中河流的自动提取[J].福州大学学报:自然科学版,2004,32(S1):99-102. Yang D Q,Liu B H.An automatic analysis method of rivers based on remote sensing image[J].Journal of Fuzhou University:Natural Science Edition,2004,32(S1):99-102.
[5] 钟春棋,郑彩红.基于TM影像的闽江口湿地信息提取及其动态变化研究[J].国土资源遥感,2008,20(1):38-42.doi:10.6046/gtzyyg.2008.01.08. Zhong C Q,Zheng C H.A study of wetland extraction and its dynamic changes in the estuary of the Minjiang river based on TM imaging[J].Remote Sensing for Land and Resources,2008,20(1):38-42.doi:10.6046/gtzyyg.2008.01.08.
[6] 邓劲松,王珂,邓艳华,等.SPOT-5卫星影像中水体信息自动提取的一种有效方法[J].上海交通大学学报:农业科学版,2005,23(2):198-201. Deng J S,Wang K,Deng Y H,et al.An effective way for automatically extracting water body information from SPOT-5 images[J].Journal of Shanghai Jiaotong University:Agricultural Science,2005,23(2):198-201.
[7] 都金康,黄永胜,冯学智,等.SPOT卫星影像的水体提取方法及分类研究[J].遥感学报,2001,5(3):214-219. Du J K,Huang Y S,Feng X Z,et al.Study on water bodies extraction and classification from SPOT image[J].Journal of Remote Sensing,2001,5(3):214-219.
[8] 骆剑承,盛永伟,沈占锋,等.分步迭代的多光谱遥感水体信息高精度自动提取[J].遥感学报,2009,13(4):604-615. Luo J C,Sheng Y W,Shen Z F,et al.Automatic and high-precise extraction for water information from multispectral images with the step-by-step iterative transformation mechanism[J].Journal of Remote Sensing,2009,13(4):604-615.
[9] 王秋燕,陈仁喜,徐佳,等.环境一号卫星影像中水体信息提取方法研究[J].科学技术与工程,2012,12(13):3051-3056. Wang Q Y,Chen R X,Xu J,et al.Research on methods for extracting water body information from HJ-1A/B data[J].Science Technology and Engineering,2012,12(13):3051-3056.
[10] 胡卫国,孟令奎,张东映,等.资源一号02C星图像水体信息提取方法[J].国土资源遥感,2014,26(2):43-47.doi:10.6046/gtzyyg.2014.02.08. Hu W G,Meng L K,Zhang D Y,et al.Methods of water extraction from ZY-102C satellite imagery[J].Remote Sensing for Land and Resources,2014,26(2):43-47.doi:10.6046/gtzyyg.2014.02.08.
[11] 马延辉,林辉,孙华,等.基于CIWI模型的水体信息提取研究[J].中国水土保持,2009(5):41-43. Ma Y H,Lin H,Sun H,et al.Research on water information extraction based on CIWI model[J].Soil and Water Conservation in China, 2009(5):41-43.
[12] 徐涵秋.利用改进的归一化差异水体指数(MNDWI)提取水体信息的研究[J].遥感学报,2005,9(5):589-595. Xu H Q.A study on information extraction of water body with the modified normalized difference water index(MNDWI)[J].Journal of Remote Sensing,2005,9(5):589-595.
[13] McFeeters S K.The use of the normalized difference water index(NDWI) in the delineation of open water features[J].International Journal of Remote Sensing,1996,17(7):1425-1432.
[14] 李艳华,丁建丽,闫人华.基于国产GF-1遥感影像的山区细小水体提取方法研究[J].资源科学,2015,37(2):408-416. Li Y H,Ding J L,Yan R H.Extraction of small river information based on China-made GF-1 remote sense images[J].Resources Science,2015,37(2):408-416.
[15] 白照广.高分一号卫星的技术特点[J].中国航天,2013(8):5-9. Bai Z G.Technical characteristics of GF-1 satellite[J].Aerospace China,2013(8):5-9.
[16] 陈文倩,丁建丽,李艳华,等.基于国产GF-1遥感影像的水体提取方法[J].资源科学,2015,37(6):1166-1172. Chen W Q,Ding J L,Li Y H,et al.Extraction of water information based on China-made GF-1 remote sense image[J].Resources Science,2015,37(6):1166-1172.
[17] 朱刚,高会军,曾光.近35a来新疆干旱区湖泊变化及原因分析[J].干旱区地理,2015,38(1):103-110. Zhu G,Gao H J,Zeng G.Lake change research and reasons analysis in Xinjiang arid regions during the past 35 years[J].Arid Land Geography,2015,38(1):103-110.
[18] 钟春棋,曾从盛,柳铮铮.基于谱间特征与比值型指数的水体影像识别分析[J].地球信息科学,2008,10(5):663-669. Zhong C Q,Zeng C S,Liu Z Z.Study on terrestrial water information identified based on the analysis of spectral signature and ratio index[J].Geo-information Science,2008,10(5):663-669.
[19] 王伟武,朱霞,孙跃池,等.基于ETM图像的山地水体提取方法研究[J].系统仿真学报,2013,25(9):2196-2200,2205. Wang W W,Zhu X,Sun Y C,et al.Water extraction method based on ETM image of mountain[J].Journal of System Simulation,2013,25(9):2196-2200,2205.
[20] 许章华,刘健,余坤勇,等.阴影植被指数SVI的构建及其在四种遥感影像中的应用效果[J].光谱学与光谱分析,2013,33(12):3359-3365. Xu Z H,Liu J,Yu K Y,et al.Construction of vegetation shadow index(SVI) and application effects in four remote sensing images[J].Spectroscopy and Spectral Analysis,2013,33(12):3359-3365.
[21] 郑晓燕,张艳红,刘万崧.扎龙湿地水体遥感提取过程中云阴影去除方法研究[J].湿地科学,2010,8(1):21-27. Zheng X Y,Zhang Y H,Liu W S.Method on cloud shadow removing from water bodies in the process of remote sensing extraction in Zhalong wetlands[J].Wetland Science,2010,8(1):21-27.
[22] 李正云,刘艳伟,王海星.基于决策树方法的杨凌示范区水体提取分析[J].水资源与水工程学报,2013,24(6):133-135. Li Z Y,Liu Y W,Wang H X.Analysis of water body extraction in Yangling demonstration zone based on decision tree method[J].Journal of Water Resources and Water Engineering,2013,24(6):133-135.
[23] 程晨,韦玉春,牛志春.基于ETM+图像和决策树的水体信息提取——以鄱阳湖周边区域为例[J].遥感信息,2012,27(6):49-56. Chen C,Wei Y C,Niu Z C.Water body extraction based on decision tree and ETM+ imagery:A case study of Poyang Lake Region[J].Remote Sensing Information,2012,27(6):49-56.

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