中国海岸带土地利用遥感制图及精度评价
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摘要
土地利用遥感制图结果是支撑全球气候变化和区域可持续发展等领域科学研究不可或缺的重要基础数据,而制图精度方面的评价信息则决定土地利用遥感制图结果的完整性、可靠性、可用性、可控性和可传播性。本文概述2000、2005、2010和2015年多时相中国海岸带土地利用遥感制图的数据源和技术方法,针对2010年和2015年制图结果,基于Google Earth高分影像通过目视判读获得精度评价所需的参考数据,进而建立混淆矩阵并评估制图的精度。结果表明:(1) 2010和2015年中国海岸带土地利用遥感制图结果的总体精度分别为95.15%和93.98%,Kappa系数分别为0.9357和0.9229,表明2个时相遥感制图结果的精度总体较好;(2)中国海岸带土地利用遥感制图结果的精度水平存在较为显著的区域差异,2010年时相江苏沿海区域的精度最高,2015年时相津冀沿海区域、上海市、海南省和台湾省的精度均比较高,2个时相均以福建省沿海区域的精度最低;(3)中国海岸带土地利用遥感制图结果的精度水平存在显著的类型差异,总体上,耕地、林地、草地和滨海湿地的分类精度较高,而建设用地、内陆水体和人工咸水湿地的分类精度则相对较低,未利用土地则是错分最严重的类型;(4)耕地与林地之间、建设用地与草地之间相互误分比较显著,内陆水体容易被错分为耕地、林地和建设用地,人工咸水湿地容易被误分为耕地和建设用地,未利用土地容易被误分为耕地,这些都是未来时期数据持续更新过程中应该重视的问题。本文有望为海岸带土地利用变化遥感监测和科学研究提供必要的支持。
Land use mapping using remote sensing techniques supplies essential datasets for scientific researches including global climate change, regional sustainable development and so on. The evaluation information on the accuracy of the land use mapping determines the integrity, reliability, usability, controllability and shareability of the land use maps obtained by the applications of remote sensing techniques. In this paper, the methods,processes and results of multiple temporal land use mapping for China's coastal zone using remote sensing techniques were overviewed, and the land use maps in 2010 and 2015 were selected for accuracy evaluation. The validation samples were collected based on Google Earth and the confusion matrices were established for the whole coastal zone and its sub-regions, respectively. Then, the overall accuracy and Kappa coefficient were calculated. Main findings are as follows:(1) Results of land use mapping in 2010 and 2015 using remote sensing techniques achieved high accuracy. For the entire coastal zone in China, the overall accuracy came to 95.15%and 93.98%, with the Kappa coefficients of 0.9357 and 0.9229 in 2010 and 2015, respectively.(2) The accuracy of land use mapping in China's coastal zone exhibited obvious regional differences. The best accuracy was found in the coastal area of Jiangsu province in 2010, and very high accuracy were found in the coastal area of HebeiTianjin, Shanghai city, Hainan province and Taiwan province in 2015, while the worst accuracy was found in the coastal area of Fujian province in both 2010 and 2015.(3) The accuracy of land use mapping in China's coastal zone exhibited obvious typological differences. The very high accuracy(both producer precision and user precision) were achieved for farmland, forest, grassland and saltwater wetlands, and the high accuracy for builtup, freshwater wetlands and human made saltwater wetland, while the worst accuracy for unused land.(4) The misclassification between cultivated land and forest land, construction land and grassland is quite significant.Inland water bodies were easily misclassified into cultivated land, forest land and construction land. Artificial salt water wetlands were easily misclassified into cultivated land and construction land, and unused land. It was easy to mistakenly classify the unused land as cultivated land. These are the issues that should be paid more attention during the continuous update of the land use maps in the future. This study provides supports for the dynamic monitoring and scientific researches on coastal land use changes.
Land use mapping using remote sensing techniques supplies essential datasets for scientific researches including global climate change, regional sustainable development and so on. The evaluation information on the accuracy of the land use mapping determines the integrity, reliability, usability, controllability and shareability of the land use maps obtained by the applications of remote sensing techniques. In this paper, the methods,processes and results of multiple temporal land use mapping for China's coastal zone using remote sensing techniques were overviewed, and the land use maps in 2010 and 2015 were selected for accuracy evaluation. The validation samples were collected based on Google Earth and the confusion matrices were established for the whole coastal zone and its sub-regions, respectively. Then, the overall accuracy and Kappa coefficient were calculated. Main findings are as follows:(1) Results of land use mapping in 2010 and 2015 using remote sensing techniques achieved high accuracy. For the entire coastal zone in China, the overall accuracy came to 95.15%and 93.98%, with the Kappa coefficients of 0.9357 and 0.9229 in 2010 and 2015, respectively.(2) The accuracy of land use mapping in China's coastal zone exhibited obvious regional differences. The best accuracy was found in the coastal area of Jiangsu province in 2010, and very high accuracy were found in the coastal area of HebeiTianjin, Shanghai city, Hainan province and Taiwan province in 2015, while the worst accuracy was found in the coastal area of Fujian province in both 2010 and 2015.(3) The accuracy of land use mapping in China's coastal zone exhibited obvious typological differences. The very high accuracy(both producer precision and user precision) were achieved for farmland, forest, grassland and saltwater wetlands, and the high accuracy for builtup, freshwater wetlands and human made saltwater wetland, while the worst accuracy for unused land.(4) The misclassification between cultivated land and forest land, construction land and grassland is quite significant.Inland water bodies were easily misclassified into cultivated land, forest land and construction land. Artificial salt water wetlands were easily misclassified into cultivated land and construction land, and unused land. It was easy to mistakenly classify the unused land as cultivated land. These are the issues that should be paid more attention during the continuous update of the land use maps in the future. This study provides supports for the dynamic monitoring and scientific researches on coastal land use changes.
引文
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[17] McCallum I, Obersteiner M, Nilsson S, et al. A spatial comparison of four satellite derived 1 km global land cover datasets[J]. International Journal of Applied Earth Observation and Geoinformation, 2006,8:246-255.
[18]杨永可,肖鹏峰,冯学智,等.大尺度土地覆盖数据集在中国及周边区域的精度评价[J].遥感学报,2014,18(2):453-475.[Yang Y K, Xiao P F, Feng X Z, et al. Comparison and assessment of large-scale land cover datasets in China and adjacent regions[J]. Journal of Remote Sensing,2014,18(2):453-475.]
[19]黄亚博,廖顺宝.首套全球30 m分辨率土地覆被产品区域尺度精度评价——以河南省为例[J].地理研究,2016,35(8):1433-1446.[Huang Y B, Liao S B. Regional accuracy assessments of the first global land cover dataset at30-meter resolution:A case study of Henan province[J].Geographical Research, 2016,35(8):1433-1446.]
[20] Liu J Y, Liu M L, Zhuang D F, et al. Study on spatial pattern of land-use change in China during 1995-2000[J]. Science in China(Series D-Earth Sciences), 2003,46(4):373-384.
[21]刘纪远,张增祥,庄大方,等. 20世纪90年代中国土地利用变化时空特征及其成因分析[J].地理研究,2003,22(1):1-12.[Liu J Y, Zhang Z X, Zhuang D F, et al. A study on the spatial-temporal dynamic changes of land-use and driving forces analyses of China in the 1990s[J]. Geographical Research, 2003,22(1):1-12.]
[22]邸向红.21世纪初期中国海岸带区域土地利用变化特征研究[D].北京:中国科学院大学,2013.[Di X H. Characteristics of land use change in China's coastal zone in the early 21st century[D]. Beijing:The University of Chinese Academy of Sciences, 2013.]
[23]邸向红,侯西勇,吴莉.中国海岸带土地利用遥感分类系统研究[J].资源科学,2014,36(3):463-472.[Di X H, Hou X Y, Wu L. Land use classification system for China's coastal zone based on remote sensing[J]. Resources Science, 2014,36(3):463-472.]
[24] Di X H, Hou X Y, Wang Y D, et al. Spatial-temporal characteristics of land use intensity of coastal zone in China during 2000-2010[J]. Chinese Geographical Science, 2015,25(1):51-61.
[25]刘佳,王利民,滕飞,等. Google Earth影像辅助的农作物面积地面样方调查[J].农业工程学报,2015,31(24):149-154.[Liu J, Wang L M, Teng F, et al. Crop area ground sample survey using Google Earth image-aided[J]. Transactions of the Chinese Society of Agricultural Engineering, 2015,31(24):149-154.]
[26] Grekousis G, Mountrakis G, Kavouras M. An overview of 21 global and 43 regional land-cover mapping products[J]. International Journal of Remote Sensing, 2015,36(21):5309-5335.
[27] Yang Y K, Xiao P F, Feng X Z, et al. Accuracy assessment of seven global land cover datasets over China[J].ISPRS Journal of Photogrammetry and Remote Sensing,2017,125:156-173.
[28]王蕾,王鹏新,田苗,等.效率系数和一致性指数及其在干旱预测精度评价中的应用[J].干旱地区农业研究,2016,34(1):229-251.[Wang L, Wang P X, Tian M, et al. Application of the coefficient of efficiency and index of agreement on accuracy assessment of drought forecasting models[J]. Agricultural Research in the Arid Areas, 2016,34(1):229-251.]
[29]牛振国,单玉秀,张海英.全球土地覆盖GlobCover2009数据中的中国区域湿地数据精度评价[J].湿地科学,2012,10(4):389-395.[Niu Z G, Shan Y X, Zhang H Y. Accuracy Assessment of Wetland Categories from the GlobCover2009 Data Over China[J]. Wetland Science, 2012,10(4):389-395.]
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(1)制图范围:早期的研究工作是以“大陆海岸带(沿海)”为重点,因而未包含海南省和台湾省,后续进行了补充;二级类型中的“浅海水域”仅通过光学遥感技术难以确定其具体范围,因而早期数据产品缺少这一类型,导致海部边界不固定,后期以-10 m等深线和离岸10 km缓冲区为依据,取二者的并集建立了固定的海域边界,因此数据产品中实际上是“浅海/近海水域”。
[2]杜国明,匡文慧,孟凡浩,等.巴西土地利用/覆盖变化时空格局及驱动因素[J].地理科学进展,2015,34(1):73-82.[Du G M, Kuang W H, Meng F H, et al. Spatiotemporal pattern and driving forces of land use/cover change in Brazil[J]. Progress in Geography, 2015,34(1):73-82.]
[3]廖顺宝,刘睿,尹芳.全国1:25万土地覆被遥感制图精度在内蒙古东部的实地验证[J].地理研究,2011,30(3):555-563.[Liao S B, Liu R, Yin F. Validation for accuracy of land cover remote sensing mapping of China at scale of 1:250 000 in East Inner Mongolia[J]. Geographical Research, 2011,30(3):555-563.]
[4]华文剑,陈海山,李兴.中国土地利用/覆盖变化及其气候效应的研究综述[J].地球科学进展,2014,29(9):1025-1036.[Hua W J, Chen H S, Li X. Review of land use and land cover change in China and associated climatic effects[J]. Advances in Earth Science, 2014,29(9):1025-1036.]
[5] Loveland T R, Reed B C, Brown J F, et al. Development of a global land cover characteristics database and IGBP DIS Cover from 1 km AVHRR data[J]. International Journal of Remote Sensing, 2000,21(6-7):1303-1330.
[6] Hansen M C, Reed B. A comparison of the IGBP DISCover and University of Maryland 1 km global land cover products[J]. International Journal of Remote Sensing,2000,21(6-7):1365-1373.
[7] BartholoméE, Belward A S. GLC2000:A new approach to global land cover mapping from Earth observation data[J]. International Journal of Remote Sensing, 2005,26(9):1959-1977.
[8] Friedl M A, McIver D K, Hodges J C F, et al. Global land cover mapping from MODIS:Algorithms and early results[J]. Remote Sensing of Environment, 2002,83:287-302.
[9]宁佳,张树文,蔡红艳,等. MODIS和GLOBCOVER全球土地覆盖数据集对比分析——以黑龙江流域为例[J].地球信息科学学报,2012,14(2):240-249.[Ning J, Zhang S W, Cai H Y, et al. A comparative analysis of the MODIS land cover data sets and Globcover land cover data sets in Heilongjiang Basin[J]. Journal of Geo-information Science, 2012,14(2):240-249.]
[10] Li W, Ciais P, MacBean N, et al. Major forest changes and land cover transitions based on plant functional types derived from the ESA CCI Land Cover product[J]. International Journal of Applied Earth Observation and Geoinformation, 2016,47:30-39.
[11]宫鹏,张伟,俞乐,等.全球地表覆盖制图研究新范式[J].遥感学报,2016,20(5):1002-1016.[Gong P, Zhang W, Yu L,et al. New research paradigm for global land cover mapping[J]. Journal of Remote Sensing, 2016,20(5):1002-1016.]
[12] Chen X H, Cao X, Liao A P, et al. Global mapping of artificial surface at 30-m resolution[J]. Science China:Earth Sciences, 2016,59:2295-2306.
[13]刘纪远,匡文慧,张增祥,等. 20世纪80年代末以来中国土地利用变化的基本特征与空间格局[J].地理学报,2014,69(1):3-14.[Liu J Y, Kuang W H, Zhang Z X, et al.Spatiotemporal characteristics, patterns and causes of land use changes in China since the late 1980s[J]. Acta Geographica Sinica, 2014,69(1):3-14.]
[14] Ning J, Liu J Y, Kuang W H, et al. Spatiotemporal patterns and characteristics of land-use change in China during2010-2015[J]. Journal of Geographical Sciences, 2018,28(5):547-562.
[15]马京振,孙群,肖强,等.河南省GlobeLand30数据精度评价及对比分析[J].地球信息科学学报,2016,18(11):1563-1572.[Ma J Z, Sun Q, Xiao Q, et al. Accuracy assessment and comparative analysis of GlobeLand30 dataset in Henan province[J]. Journal of Geo-information Science, 2016,18(11):1563-1572.]
[16]卢玲,李新,董庆罕,等. SPOT4-VEGETATION中国西北地区土地覆盖制图与验证[J].遥感学报,2003,7(3):214-220.[Lu L, Li X, Dong Q H, et al. The mapping and validation of land cover in Northwest China from SPOT4-VEGETATION[J]. Journal of Remote Sensing, 2003,7(3):214-220.]
[17] McCallum I, Obersteiner M, Nilsson S, et al. A spatial comparison of four satellite derived 1 km global land cover datasets[J]. International Journal of Applied Earth Observation and Geoinformation, 2006,8:246-255.
[18]杨永可,肖鹏峰,冯学智,等.大尺度土地覆盖数据集在中国及周边区域的精度评价[J].遥感学报,2014,18(2):453-475.[Yang Y K, Xiao P F, Feng X Z, et al. Comparison and assessment of large-scale land cover datasets in China and adjacent regions[J]. Journal of Remote Sensing,2014,18(2):453-475.]
[19]黄亚博,廖顺宝.首套全球30 m分辨率土地覆被产品区域尺度精度评价——以河南省为例[J].地理研究,2016,35(8):1433-1446.[Huang Y B, Liao S B. Regional accuracy assessments of the first global land cover dataset at30-meter resolution:A case study of Henan province[J].Geographical Research, 2016,35(8):1433-1446.]
[20] Liu J Y, Liu M L, Zhuang D F, et al. Study on spatial pattern of land-use change in China during 1995-2000[J]. Science in China(Series D-Earth Sciences), 2003,46(4):373-384.
[21]刘纪远,张增祥,庄大方,等. 20世纪90年代中国土地利用变化时空特征及其成因分析[J].地理研究,2003,22(1):1-12.[Liu J Y, Zhang Z X, Zhuang D F, et al. A study on the spatial-temporal dynamic changes of land-use and driving forces analyses of China in the 1990s[J]. Geographical Research, 2003,22(1):1-12.]
[22]邸向红.21世纪初期中国海岸带区域土地利用变化特征研究[D].北京:中国科学院大学,2013.[Di X H. Characteristics of land use change in China's coastal zone in the early 21st century[D]. Beijing:The University of Chinese Academy of Sciences, 2013.]
[23]邸向红,侯西勇,吴莉.中国海岸带土地利用遥感分类系统研究[J].资源科学,2014,36(3):463-472.[Di X H, Hou X Y, Wu L. Land use classification system for China's coastal zone based on remote sensing[J]. Resources Science, 2014,36(3):463-472.]
[24] Di X H, Hou X Y, Wang Y D, et al. Spatial-temporal characteristics of land use intensity of coastal zone in China during 2000-2010[J]. Chinese Geographical Science, 2015,25(1):51-61.
[25]刘佳,王利民,滕飞,等. Google Earth影像辅助的农作物面积地面样方调查[J].农业工程学报,2015,31(24):149-154.[Liu J, Wang L M, Teng F, et al. Crop area ground sample survey using Google Earth image-aided[J]. Transactions of the Chinese Society of Agricultural Engineering, 2015,31(24):149-154.]
[26] Grekousis G, Mountrakis G, Kavouras M. An overview of 21 global and 43 regional land-cover mapping products[J]. International Journal of Remote Sensing, 2015,36(21):5309-5335.
[27] Yang Y K, Xiao P F, Feng X Z, et al. Accuracy assessment of seven global land cover datasets over China[J].ISPRS Journal of Photogrammetry and Remote Sensing,2017,125:156-173.
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(1)制图范围:早期的研究工作是以“大陆海岸带(沿海)”为重点,因而未包含海南省和台湾省,后续进行了补充;二级类型中的“浅海水域”仅通过光学遥感技术难以确定其具体范围,因而早期数据产品缺少这一类型,导致海部边界不固定,后期以-10 m等深线和离岸10 km缓冲区为依据,取二者的并集建立了固定的海域边界,因此数据产品中实际上是“浅海/近海水域”。