面向对象的沿海地区土地利用/覆被信息提取研究
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摘要
土地利用/覆被(LUC)可为土地资源领域相关研究提供基础数据。本文构建了面向对象的LUC分类方法,并以沿海特殊土地类型区连云港市为例,应用Landsat 8影像开展了实证研究。结果表明:①总体分类精度达到85.06%,总体Kappa系数为0.83,超过了0.7的最低允许判别精度;②该方法可以有效地减少研究区因南北部区域耕地植被覆盖度不同导致的错分现象,并可以用于盐田与滩涂信息的提取工作;③该方法既可为研究区土地利用相关研究提供符合精度要求的数据,也可为其他沿海地区进行土地利用/覆被信息提取工作提供参考和借鉴。
Land use/cover( LUC) information is a very essential dataset in supporting the related research and application. To extract the LUC information in the coastal area,an object-oriented based classification method is proposed and applied to Lianyungang city using Landsat 8 imagery. The results indicate that the accuracy of the classification exceeded the minimum allowed discriminant accuracy 0. 7 with the overall accuracy 85. 06% and the overall Kappa coefficient is 0. 83. The methodology can reduce the misclassification of arable land due to the vegetation coverage between the southern plains and northern hills,and can be used to extract the tideland and salt-field in the area. The methodology can provide the LUC data with agreed accuracy for the land related research for Lianyungang city,and support the extraction of LUC information in other similar coastal areas.
Land use/cover( LUC) information is a very essential dataset in supporting the related research and application. To extract the LUC information in the coastal area,an object-oriented based classification method is proposed and applied to Lianyungang city using Landsat 8 imagery. The results indicate that the accuracy of the classification exceeded the minimum allowed discriminant accuracy 0. 7 with the overall accuracy 85. 06% and the overall Kappa coefficient is 0. 83. The methodology can reduce the misclassification of arable land due to the vegetation coverage between the southern plains and northern hills,and can be used to extract the tideland and salt-field in the area. The methodology can provide the LUC data with agreed accuracy for the land related research for Lianyungang city,and support the extraction of LUC information in other similar coastal areas.
引文
[1]伍星,沈珍瑶,刘瑞民.长江上游土地利用/覆被变化及区域分异研究[J].应用基础与工程科学学报,2008,16(6):819-829.
[2]CHEN L,LI L,YANG X,et al.A worst-case scenario based methodology to assess the environmental impact of land use planning[J].Habitat International,2017,67:148-163.
[3]CHEN L,YANG X,CHEN L,et al.A state-impactstate methodology for assessing environmental impact in land use planning[J].Environmental Impact Assessment Review,2014,46(4):1-12.
[4]马腾,刘全明,孙红.多源遥感技术在土地利用分类中的应用[J].测绘通报,2018(8):56-61.
[5]兰泽英,刘洋.领域知识辅助下基于多尺度与主方向纹理的遥感影像土地利用分类[J].测绘学报,2016,45(8):973-982.
[6]陈龙高,李英奎,陈龙乾,等.土地生态利用视角下的连云港空间管制分区研究[J].应用基础与工程科学学报,2014,22(4):685-697.
[7]陈绍杰,李光丽,张伟,等.基于多分类器集成的煤矿区土地利用遥感分类[J].中国矿业大学学报,2011,40(2):273-278.
[8]孔博,邓伟,李爱农,等.多源数据的面向对象国际河流土地覆被分类研究[J].武汉大学学报(信息科学版),2015,40(7):943-949.
[9]苑全治,吴炳方,张磊,等.辅助数据在面向对象分类方法中的应用---以密云水库上游为例[J].生态学报,2014,34(24):7202-7209.
[10]孙丹峰,杨冀红,刘顺喜.高分辨率遥感卫星影像在土地利用分类及其变化监测的应用研究[J].农业工程学报,2002,18(2):160-164.
[11]殷瑞娟,施润和,李镜尧.一种高分辨率遥感影像的最优分割尺度自动选取方法[J].地球信息科学学报,2013,15(6):902-910.
[12]王贺,陈劲松,余晓敏.面向对象分类特征优化选取方法及其应用[J].遥感学报,2013,17(4):816-829.
[13]张明媚,姚国红.面向对象的高分辨率遥感影像信息提取技术[J].地理空间信息,2013,11(1):89-91.
[14]JANSSEN L L F,WEL F J M.Accuracy assessment of satellite derived land cover data:a review[J].Photogrammetric Engineering and Remote Sensing,1994,60(4):419-426.
[15]LANDIS J R,KOCH G G.The measurement of observer agreement for categorical data[J].Biometrics,1977,33(1):159-174.
[16]陈龙高,李英奎,杨小艳,等.土地利用/覆被遥感分类评价与季节变化分析---以连云港为例[J].中国矿业大学学报,2013,42(5):873-879.
[17]YANG X,CHEN L,LI Y,et al.Rule-based land use/land cover classification in coastal areas using seasonal remote sensing imagery:a case study from Lianyungang city,China[J].Environmental Monitoring and Assessment,2015,187(7):1-15.
[2]CHEN L,LI L,YANG X,et al.A worst-case scenario based methodology to assess the environmental impact of land use planning[J].Habitat International,2017,67:148-163.
[3]CHEN L,YANG X,CHEN L,et al.A state-impactstate methodology for assessing environmental impact in land use planning[J].Environmental Impact Assessment Review,2014,46(4):1-12.
[4]马腾,刘全明,孙红.多源遥感技术在土地利用分类中的应用[J].测绘通报,2018(8):56-61.
[5]兰泽英,刘洋.领域知识辅助下基于多尺度与主方向纹理的遥感影像土地利用分类[J].测绘学报,2016,45(8):973-982.
[6]陈龙高,李英奎,陈龙乾,等.土地生态利用视角下的连云港空间管制分区研究[J].应用基础与工程科学学报,2014,22(4):685-697.
[7]陈绍杰,李光丽,张伟,等.基于多分类器集成的煤矿区土地利用遥感分类[J].中国矿业大学学报,2011,40(2):273-278.
[8]孔博,邓伟,李爱农,等.多源数据的面向对象国际河流土地覆被分类研究[J].武汉大学学报(信息科学版),2015,40(7):943-949.
[9]苑全治,吴炳方,张磊,等.辅助数据在面向对象分类方法中的应用---以密云水库上游为例[J].生态学报,2014,34(24):7202-7209.
[10]孙丹峰,杨冀红,刘顺喜.高分辨率遥感卫星影像在土地利用分类及其变化监测的应用研究[J].农业工程学报,2002,18(2):160-164.
[11]殷瑞娟,施润和,李镜尧.一种高分辨率遥感影像的最优分割尺度自动选取方法[J].地球信息科学学报,2013,15(6):902-910.
[12]王贺,陈劲松,余晓敏.面向对象分类特征优化选取方法及其应用[J].遥感学报,2013,17(4):816-829.
[13]张明媚,姚国红.面向对象的高分辨率遥感影像信息提取技术[J].地理空间信息,2013,11(1):89-91.
[14]JANSSEN L L F,WEL F J M.Accuracy assessment of satellite derived land cover data:a review[J].Photogrammetric Engineering and Remote Sensing,1994,60(4):419-426.
[15]LANDIS J R,KOCH G G.The measurement of observer agreement for categorical data[J].Biometrics,1977,33(1):159-174.
[16]陈龙高,李英奎,杨小艳,等.土地利用/覆被遥感分类评价与季节变化分析---以连云港为例[J].中国矿业大学学报,2013,42(5):873-879.
[17]YANG X,CHEN L,LI Y,et al.Rule-based land use/land cover classification in coastal areas using seasonal remote sensing imagery:a case study from Lianyungang city,China[J].Environmental Monitoring and Assessment,2015,187(7):1-15.