中分辨率遥感影像土地利用覆被信息自动提取研究——以太原市区Landsat8影像为例
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摘要
"土地利用/土地覆被"(简称LUCC)是全球环境变化研究的热点问题之一,遥感技术是LUCC研究的重要手段,遥感影像LUCC信息的高精度自动提取成为众多专家学者关注的重要研究领域.Landsat系列卫星影像是最早且最为广泛使用的中分辨率陆地遥感影像.文章以2013年2月发射的Landsat8卫星的OLI影像为研究对象,利用ENVI软件,对太原市区的土地利用/土地覆被信息分别用最大似然法和决策树分类法实现自动提取,并进行精度比较.结果表明:最大似然法提取的总体精度为69.33%,Kappa系数为0.605 5,主要是耕地与林地、草地、建设用地以及建设用地与裸地的混分、错分现象较为严重,造成分类精度较低;而决策树分类法的自动提取通过确定适当的判别规则,使地类间的混分、错分现象明显改善,分类总体精度提高到91.33%,Kappa系数达到0.892 3,各土地利用类型的分类精度均有一定提高.
" The land use and land cover(LUCC)" is one of the hotspot in global environmental change research,and RS technology is the important research means to LUCC study,so,the automatic extraction with high accuracy of LUCC information on RS image has become an important research field for many experts and scholars.Landsat Series Satellites image with medium resolution is the earliest RS data and has been used most widely.OLI image of Landsat8 satellite launched in February 2013 as the research object,based on ENVI,the paper studied the automatic extraction of land use/cover information using methods of decision tree and maximum likelihood in Taiyuan city center.The results showed that the accuracy of final classification was low,overall accuracy is 69.33%,Kappa coefficient is 0.605 5,because there were some error classification between cultivated land and forest land,grassland and construction land,so was it between construction land and bare land.However,the automatic extraction method of decision can obviously improve classification accuracy by appropriate discrimination rules,the overall accuracy could be 91.33%,Kappa coefficient reached 0.892 3,and higher precision can be seen in each land use type.
" The land use and land cover(LUCC)" is one of the hotspot in global environmental change research,and RS technology is the important research means to LUCC study,so,the automatic extraction with high accuracy of LUCC information on RS image has become an important research field for many experts and scholars.Landsat Series Satellites image with medium resolution is the earliest RS data and has been used most widely.OLI image of Landsat8 satellite launched in February 2013 as the research object,based on ENVI,the paper studied the automatic extraction of land use/cover information using methods of decision tree and maximum likelihood in Taiyuan city center.The results showed that the accuracy of final classification was low,overall accuracy is 69.33%,Kappa coefficient is 0.605 5,because there were some error classification between cultivated land and forest land,grassland and construction land,so was it between construction land and bare land.However,the automatic extraction method of decision can obviously improve classification accuracy by appropriate discrimination rules,the overall accuracy could be 91.33%,Kappa coefficient reached 0.892 3,and higher precision can be seen in each land use type.
引文
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[12]陈述,刘勇.基于多特征的遥感影像土地利用/土地覆盖分类-以腾格里沙漠东南边缘地区为例[J].遥感技术与应用,2006,21(2):154-158
[13]李德仁,王树良,李德毅,等.论空间数据挖掘和知识发现的理论与方法[J].武汉大学学报(信息科学版),2002,27(3):221-233
[14]杨存建,周成虎.基于知识的遥感图像分类方法探讨[J].地理学与国土研究,2001,17(1):72-77
[15]王志慧,李世明,刘良云,等.基于MODIS NDVI时间序列的土地覆盖分层分类方法研究[J].遥感技术与应用,2013,28(5):910-919
[16]王贺,陈劲松,余晓敏,等.HJ数据的LBV变换及其在面向对象分类中的应用[J].遥感技术与应用,2013,28(6):1 020-1 026
[17]许积层,唐斌,卢涛.基于多时相LandsatTM影像的汶川地震灾区河岸带植被覆盖动态监测——以岷江河谷映秀汶川段为例[J].生态学报,33(16):4 966-4 974
[18]金石柱,刘志峰.基于TM影像的延吉市土地利用动态变化研究[J].地理科学,2011,31(10):1 249-1 253
[2]冷疏影,宋长青,赵楚年,等.关于地理学科“十五”重点项目的思考[J].地理学报,2000,55(6):751-754
[3]刘纪元,刘明亮,庄大方,等.中国近期土地利用变化的空间格局分析[J].中国科学(D辑),2002,32(12):1 031-1 040
[4]杜云艳,王丽敬,季民,等.土地利用变化预测的案例推理方法[J].地理学报,2009,64(12)1 421-1 429
[5]戴声佩,张勃.基于CLUE-S模型的黑河中游土地利用情景模拟研究——以张掖市甘州区为例[J].自然资源学报,2013,28(2):336-348
[6]白元,徐海量,凌红波,等.塔里木河干流区土地利用与生态系统服务价值的变化[J].中国沙漠,2013,33(6):1 912-1 920
[7]刘慧平,朱启疆.应用高分辨率遥感数据进行土地利用与覆盖变化监测的方法及研究进展[J].资源科学,1999,21(3):23-27
[8]廖克.高分辨率卫星遥感影像在土地利用变化动态监测中的应用[J].测绘科学,2006,31(6):11-15
[9]许菡,燕琴,徐泮林,等.多源遥感影像融合最佳波段选择及质量评价研究[J].测绘科学,2007,32(3):72-76
[10]张韬,吕洪娟,孙美霞,等.遥感多光谱数据在内蒙古西部湿地监测中最佳波段选取的应用研究[J].干旱区资源与环境,2007,21(4):102-106
[11]杨桄,刘湘南,张柏,等.基于多特征空间的遥感信息自动提取方法[J].吉林大学学报(地球科学版),2005,35(2):257-260
[12]陈述,刘勇.基于多特征的遥感影像土地利用/土地覆盖分类-以腾格里沙漠东南边缘地区为例[J].遥感技术与应用,2006,21(2):154-158
[13]李德仁,王树良,李德毅,等.论空间数据挖掘和知识发现的理论与方法[J].武汉大学学报(信息科学版),2002,27(3):221-233
[14]杨存建,周成虎.基于知识的遥感图像分类方法探讨[J].地理学与国土研究,2001,17(1):72-77
[15]王志慧,李世明,刘良云,等.基于MODIS NDVI时间序列的土地覆盖分层分类方法研究[J].遥感技术与应用,2013,28(5):910-919
[16]王贺,陈劲松,余晓敏,等.HJ数据的LBV变换及其在面向对象分类中的应用[J].遥感技术与应用,2013,28(6):1 020-1 026
[17]许积层,唐斌,卢涛.基于多时相LandsatTM影像的汶川地震灾区河岸带植被覆盖动态监测——以岷江河谷映秀汶川段为例[J].生态学报,33(16):4 966-4 974
[18]金石柱,刘志峰.基于TM影像的延吉市土地利用动态变化研究[J].地理科学,2011,31(10):1 249-1 253
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