全球海岸带多源土地利用/覆盖遥感分类产品一致性分析
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摘要
多源土地利用/覆盖分类产品是陆地表层过程研究不可或缺的重要基础数据,而其一致性分析则是产品应用的前提和基础。本文基于类型面积偏差、类型面积相关、误差矩阵和类型空间混淆等方法,从面积一致性和空间一致性两方面分析了5种土地利用/覆盖分类产品(MCD12Q1-2010、GlobCover2009、CCI-LC2010、FROM-GLC2010和GlobeLand30-2010)在全球海岸带区域的一致性。结果表明:①各产品土地利用/覆盖类型的空间分布总体上表现出较强的一致性,但在细节上存在大面积不一致现象;②各产品对全球海岸带土地利用/覆盖构成的描述基本一致,即以水体为主,林地和未利用地次之,耕地、草地和灌木地较少,湿地和人造地表相对最少,但在细节上存在面积偏差;③在产品组合中,MCD12Q1-2010/GlobCover2009的相关系数、总体精度和Kappa系数均最低,分别为0.8814、67.46%和0.5748,而GlobCover2009/CCI-LC2010的相关系数、总体精度和Kappa系数均最高,分别为0.9869、81.50%和0.7505;④5种产品两两对比,草地、灌木地和湿地的混淆程度最高,耕地和人造地表次之,林地和未利用地较低,水体最低;⑤全球海岸带有28.81%的土地具有较低的一致性,这些区域地类混淆现象较为严重,尤其是耕地、林地、草地、灌木地、湿地和未利用地之间的相互混淆对5种产品的一致性程度有直接影响。本文有望为海岸带研究在已有土地利用/覆盖数据源选择和使用等方面提供参考和建议。
Land Use and Land Cover(LULC) classification products play an indispensable role in ecosystem assessment, climate change simulation, national geographical condition monitoring, and macro-control policy analysis at the global scale; consistency analysis is the precondition of applying various LULC classification products. This paper assessed the area consistency and spatial consistency of five LULC classification products-MCD12 Q1-2010, GlobCover2009, CCI-LC2010, FROM-GLC2010 and GlobeLand30-2010-in the global coastal zones. The five products were compared in terms of the deviation coefficient, correlation coefficient,error matrix, and spatial confusion of LULC types. The main findings are as follows:(1) The spatial patterns of LULC in five products demonstrate relatively strong overall consistency, but can have significant local inconsistency.(2) The five products are qualitatively consistent yet quantitatively inconsistent in classifying the LULC in the global coastal zones-in terms of structure, water ranks top one, followed by forest and unused land,next are farmland, grassland and shrubland, and lastly wetland and artificial surface, yet the exact area of each LULC type differs among different products.(3) For the correlation coefficient, overall accuracy and Kappa coefficient, MCD12 Q1-2010/Glob Cover2009 have the minimum values, 0.8814, 67.46% and 0.5748, respectively;while Glob Cover2009/CCI-LC2010 have the maximum values, 0.9869, 81.50% and 0.7505, respectively; it is because GlobCover2009 and CCI-LC2010 obtained from the same production organization have the same classification system, while MCD12 Q1-2010 is different from GlobCover2009 in terms of the production organization, data source, classification system, and classification method.(4) For the spatial confusion/misclassification between any two different products, grassland, shrubland, and wetland have the highest mix-up ratios, followed by farmland and artificial surface, and lastly forest, unused land, and water; this difference is because forest, unused land, and water have distinctive spectral characteristics and clear spatial textures, while grassland, shrubland, and wetland have similar spectral characteristics and fuzzy spatial distributions.(5) There are 28.81% land area in the global coastal zones with relatively low consistency, i.e., with severe spatial confusion; specifically, the misclassification of farmland, forest, grassland, shrubland, wetland, and unused land has direct influence on the spatial consistency of the five products. This paper is hoped to serve as a reference of selecting data from the five available LULC products for researching coastal zones.
Land Use and Land Cover(LULC) classification products play an indispensable role in ecosystem assessment, climate change simulation, national geographical condition monitoring, and macro-control policy analysis at the global scale; consistency analysis is the precondition of applying various LULC classification products. This paper assessed the area consistency and spatial consistency of five LULC classification products-MCD12 Q1-2010, GlobCover2009, CCI-LC2010, FROM-GLC2010 and GlobeLand30-2010-in the global coastal zones. The five products were compared in terms of the deviation coefficient, correlation coefficient,error matrix, and spatial confusion of LULC types. The main findings are as follows:(1) The spatial patterns of LULC in five products demonstrate relatively strong overall consistency, but can have significant local inconsistency.(2) The five products are qualitatively consistent yet quantitatively inconsistent in classifying the LULC in the global coastal zones-in terms of structure, water ranks top one, followed by forest and unused land,next are farmland, grassland and shrubland, and lastly wetland and artificial surface, yet the exact area of each LULC type differs among different products.(3) For the correlation coefficient, overall accuracy and Kappa coefficient, MCD12 Q1-2010/Glob Cover2009 have the minimum values, 0.8814, 67.46% and 0.5748, respectively;while Glob Cover2009/CCI-LC2010 have the maximum values, 0.9869, 81.50% and 0.7505, respectively; it is because GlobCover2009 and CCI-LC2010 obtained from the same production organization have the same classification system, while MCD12 Q1-2010 is different from GlobCover2009 in terms of the production organization, data source, classification system, and classification method.(4) For the spatial confusion/misclassification between any two different products, grassland, shrubland, and wetland have the highest mix-up ratios, followed by farmland and artificial surface, and lastly forest, unused land, and water; this difference is because forest, unused land, and water have distinctive spectral characteristics and clear spatial textures, while grassland, shrubland, and wetland have similar spectral characteristics and fuzzy spatial distributions.(5) There are 28.81% land area in the global coastal zones with relatively low consistency, i.e., with severe spatial confusion; specifically, the misclassification of farmland, forest, grassland, shrubland, wetland, and unused land has direct influence on the spatial consistency of the five products. This paper is hoped to serve as a reference of selecting data from the five available LULC products for researching coastal zones.
引文
[1]Giri C,Pengra B,Long J,et al.Next generation of global land cover characterization,mapping,and monitoring[J].International Journal of Applied Earth Observation and Geoinformation,2013,25:30-37.
[2]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 at 30-meter resolution:A case study of Henan province[J].Geographical Research,2016,35(8):1433-1446.]
[3]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.]
[4]Erb K H,Luyssaert S,Meyfroidt P,et al.Land management:Data availability and process understanding for global change studies[J].Global Change Biology,2017,23:512-533.
[5]陈军,陈晋,宫鹏,等.全球地表覆盖高分辨率遥感制图[J].地理信息世界,2011,9(2):12-14.[Chen J,Chen J,Gong P,et al.Higher resolution global land cover mapping[J].Geomatics World,2011,9(2):12-14.]
[6]Grekousis G,Mountrakis G,Kavouras M.An overview of21 global and 43 regional land-cover mapping products[J].International Journal of Remote Sensing,2015,36(21):5309-5335.
[7]Congalton R G,Gu J Y,Yadav K,et al.Global land cover mapping:A review and uncertainty analysis[J].Remote Sensing,2014,6:12070-12093.
[8]吴文斌,杨鹏,张莉,等.四类全球土地覆盖数据在中国区域的精度评价[J].农业工程学报,2009,25(12):167-173.[Wu W B,Yang P,Zhang L,et al.Accuracy assessment of four global land cover datasets in China[J].Transactions of the CSAE,2009,25(12):167-173.]
[9]刘琼欢,张镱锂,刘林山,等.七套土地覆被数据在羌塘高原的精度评价[J].地理研究,2017,36(11):2061-2074.[Liu Q H,Zhang Y L,Liu L S,et al.Accuracy evaluation of the seven land cover data in Qiangtang Plateau[J].Geographical Research,2017,36(11):2061-2074.]
[10]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.
[11]Giri C,Zhu Z L,Reed B.A comparative analysis of the Global Land Cover 2000 and MODIS land cover data sets[J].Remote Sensing of Environment,2005,94:123-132.
[12]KaptuéTchuentéA T,Roujean J L,De Jong S M.Comparison and relative quality assessment of the GLC2000,GLOBCOVER,MODIS and ECOLIMAP land cover data sets at the African continental scale[J].International Journal of Applied Earth Observation and Geoinformation,2011,13:207-219.
[13]胡云锋,张千力,戴昭鑫,等.多源遥感土地覆被产品在欧洲地区的一致性分析[J].地理研究,2015,34(10):1839-1852.[Hu Y F,Zhang Q L,Dai Z X,et al.Agreement analysis of multi-sensor satellite remote sensing derived land cover products in the Europe Continent[J].Geographical Research,2015,34(10):1839-1852.]
[14]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.]
[15]许光明,杨雅萍,杨飞,等.多分辨率遥感土地覆被数据质量综合评价--以湖南省桃源县为例[J].地球信息科学学报,2016,18(3):553-563.[Xu G M,Yang Y P,Yang F,et al.Quality assessment of multi-resolution remote sensing land cover data:A case study in Taoyuan county of Hunan province[J].Journal of Geo-information Science,2016,18(4):553-563.]
[16]张健,濮励杰,陕永杰,等.海岸带土地开发利用及生态环境效应研究简述[J].长江流域资源与环境,2012,21(1):36-43.[Zhang J,Pu L J,Shan Y J,et al.Progress of the research on land exploitation and its use and eco-environmental effects of coastal zone[J].Resources and Environment in the Yangtze Basin,2012,21(1):36-43.]
[17]Halkos G,Matsiori S.Environmental attitudes and preferences for coastal zone improvements[J].Economic Analysis and Policy,2018,58:153-166.
[18]Shi H,Singh A.全球海岸带环境问题现状和相互联系[J].AMBIO-人类环境杂志,2003,32(2):145-152.[Shi H,Singh A.Status and interconnections of selected environmental issues in the global coastal zones[J].AMBIO-A Journal of the Human Environment,2003,32(2):145-152.]
[19]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.
[20]An Y M,Zhao W W,Zhang Y H.Accuracy assessments of the GLOBCOVER dataset using global statistical inventories and FLUXNET site data[J].Acta Ecologica Sinica,2012,32:314-320.
[21]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.
[22]俞乐,王杰,李雪草,等.基于多源数据集成的多分辨率全球地表覆盖制图[J].中国科学:地球科学,2014,44(8):1646-1660.[Yu L,Wang J,Li X C,et al.A multi-resolution global land cover dataset through multisource data aggregation[J].Science China:Earth Sciences,2014,57(10):2317-2329.]
[23]Chen J,Chen J,Liao A P,et al.Global land cover mapping at 30 m resolution:A POK-based operational approach[J].ISPRS Journal of Photogrammetry and Remote Sensing,2015,103:7-27.
[24]Sulla-Menashe D,Friedl M A.User guide to collection 6MODIS land cover(MCD12Q1 and MCD12C1)product[C].May 14,2018.
[25]UCLouvain,ESA.GLOBCOVER 2009 products description and validation report[C].Feb 18,2011.
[26]UCL-Geomatics(Belgium),ESA.Land cover CCI product user guide version 2.0[C].April 10,2017.
[27]Gong P,Wang J,Yu L,et al.Finer resolution observation and monitoring of global land cover:first mapping results with Landsat TM and ETM+data[J].International Journal of Remote Sensing,2013,34(7):2607-2654.
[28]陈军,廖安平,陈晋,等.全球30 m地表覆盖遥感数据产品-Globe Land30[J].地理信息世界,2017,24(1):1-8.[Chen J,Liao A P,Chen J,et al.30-meter global land cover data product-GlobeLand30[J].Geomatics World,2017,24(1):1-8.]
[29]李晓迪,王淑民,张黎明,等.土壤数据源和制图比例尺对旱地土壤有机碳储量估算的影响[J].土壤学报,2016,53(1):58-71.[Li X D,Wang S M,Zhang L M,et al.Impacts of source of soil data and scale of mapping on assessment of organic carbon storage in upland soil[J].Acta Pedologica Sinica,2016,53(1):58-71.]
[30]宋宏利,张晓楠.中国区域多源土地覆被遥感产品精度分析与验证[J].农业工程学报,2012,28(22):207-214.[Song H L,Zhang X N.Precision analysis and validation of multi-sources landcover products derived from remote sensing in China[J].Transactions of the Chinese Society of Agricultural Engineering,2012,28(22):207-214.]
[31]Foody G M.Valuing map validation:The need for rigorous land cover map accuracy assessment in economic valuations of ecosystem services[J].Ecological Economics,2015,111:23-28.
[32]侯西勇,邸向红,侯婉,等.中国海岸带土地利用遥感制图及精度评价[J].地球信息科学学报,2018,20(10):1478-1488.[Hou X Y,Di X H,Hou W,et al.Accuracy evaluation of land use mapping using remote sensing techniques in coastal zone of China[J].Journal of Geo-information Science,2018,20(10):1478-1488.]
[33]刘向培,王汉杰,何明元,等.三种土地覆盖遥感数据在中国区域的精度分析[J].农业工程学报,2012,28(24):252-259.[Liu X P,Wang H J,He M Y,et al.Precision analysis of three land-cover types in China region[J].Transactions of the Chinese Society of Agricultural Engineering,2012,28(24):252-259.]
[2]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 at 30-meter resolution:A case study of Henan province[J].Geographical Research,2016,35(8):1433-1446.]
[3]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.]
[4]Erb K H,Luyssaert S,Meyfroidt P,et al.Land management:Data availability and process understanding for global change studies[J].Global Change Biology,2017,23:512-533.
[5]陈军,陈晋,宫鹏,等.全球地表覆盖高分辨率遥感制图[J].地理信息世界,2011,9(2):12-14.[Chen J,Chen J,Gong P,et al.Higher resolution global land cover mapping[J].Geomatics World,2011,9(2):12-14.]
[6]Grekousis G,Mountrakis G,Kavouras M.An overview of21 global and 43 regional land-cover mapping products[J].International Journal of Remote Sensing,2015,36(21):5309-5335.
[7]Congalton R G,Gu J Y,Yadav K,et al.Global land cover mapping:A review and uncertainty analysis[J].Remote Sensing,2014,6:12070-12093.
[8]吴文斌,杨鹏,张莉,等.四类全球土地覆盖数据在中国区域的精度评价[J].农业工程学报,2009,25(12):167-173.[Wu W B,Yang P,Zhang L,et al.Accuracy assessment of four global land cover datasets in China[J].Transactions of the CSAE,2009,25(12):167-173.]
[9]刘琼欢,张镱锂,刘林山,等.七套土地覆被数据在羌塘高原的精度评价[J].地理研究,2017,36(11):2061-2074.[Liu Q H,Zhang Y L,Liu L S,et al.Accuracy evaluation of the seven land cover data in Qiangtang Plateau[J].Geographical Research,2017,36(11):2061-2074.]
[10]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.
[11]Giri C,Zhu Z L,Reed B.A comparative analysis of the Global Land Cover 2000 and MODIS land cover data sets[J].Remote Sensing of Environment,2005,94:123-132.
[12]KaptuéTchuentéA T,Roujean J L,De Jong S M.Comparison and relative quality assessment of the GLC2000,GLOBCOVER,MODIS and ECOLIMAP land cover data sets at the African continental scale[J].International Journal of Applied Earth Observation and Geoinformation,2011,13:207-219.
[13]胡云锋,张千力,戴昭鑫,等.多源遥感土地覆被产品在欧洲地区的一致性分析[J].地理研究,2015,34(10):1839-1852.[Hu Y F,Zhang Q L,Dai Z X,et al.Agreement analysis of multi-sensor satellite remote sensing derived land cover products in the Europe Continent[J].Geographical Research,2015,34(10):1839-1852.]
[14]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.]
[15]许光明,杨雅萍,杨飞,等.多分辨率遥感土地覆被数据质量综合评价--以湖南省桃源县为例[J].地球信息科学学报,2016,18(3):553-563.[Xu G M,Yang Y P,Yang F,et al.Quality assessment of multi-resolution remote sensing land cover data:A case study in Taoyuan county of Hunan province[J].Journal of Geo-information Science,2016,18(4):553-563.]
[16]张健,濮励杰,陕永杰,等.海岸带土地开发利用及生态环境效应研究简述[J].长江流域资源与环境,2012,21(1):36-43.[Zhang J,Pu L J,Shan Y J,et al.Progress of the research on land exploitation and its use and eco-environmental effects of coastal zone[J].Resources and Environment in the Yangtze Basin,2012,21(1):36-43.]
[17]Halkos G,Matsiori S.Environmental attitudes and preferences for coastal zone improvements[J].Economic Analysis and Policy,2018,58:153-166.
[18]Shi H,Singh A.全球海岸带环境问题现状和相互联系[J].AMBIO-人类环境杂志,2003,32(2):145-152.[Shi H,Singh A.Status and interconnections of selected environmental issues in the global coastal zones[J].AMBIO-A Journal of the Human Environment,2003,32(2):145-152.]
[19]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.
[20]An Y M,Zhao W W,Zhang Y H.Accuracy assessments of the GLOBCOVER dataset using global statistical inventories and FLUXNET site data[J].Acta Ecologica Sinica,2012,32:314-320.
[21]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.
[22]俞乐,王杰,李雪草,等.基于多源数据集成的多分辨率全球地表覆盖制图[J].中国科学:地球科学,2014,44(8):1646-1660.[Yu L,Wang J,Li X C,et al.A multi-resolution global land cover dataset through multisource data aggregation[J].Science China:Earth Sciences,2014,57(10):2317-2329.]
[23]Chen J,Chen J,Liao A P,et al.Global land cover mapping at 30 m resolution:A POK-based operational approach[J].ISPRS Journal of Photogrammetry and Remote Sensing,2015,103:7-27.
[24]Sulla-Menashe D,Friedl M A.User guide to collection 6MODIS land cover(MCD12Q1 and MCD12C1)product[C].May 14,2018.
[25]UCLouvain,ESA.GLOBCOVER 2009 products description and validation report[C].Feb 18,2011.
[26]UCL-Geomatics(Belgium),ESA.Land cover CCI product user guide version 2.0[C].April 10,2017.
[27]Gong P,Wang J,Yu L,et al.Finer resolution observation and monitoring of global land cover:first mapping results with Landsat TM and ETM+data[J].International Journal of Remote Sensing,2013,34(7):2607-2654.
[28]陈军,廖安平,陈晋,等.全球30 m地表覆盖遥感数据产品-Globe Land30[J].地理信息世界,2017,24(1):1-8.[Chen J,Liao A P,Chen J,et al.30-meter global land cover data product-GlobeLand30[J].Geomatics World,2017,24(1):1-8.]
[29]李晓迪,王淑民,张黎明,等.土壤数据源和制图比例尺对旱地土壤有机碳储量估算的影响[J].土壤学报,2016,53(1):58-71.[Li X D,Wang S M,Zhang L M,et al.Impacts of source of soil data and scale of mapping on assessment of organic carbon storage in upland soil[J].Acta Pedologica Sinica,2016,53(1):58-71.]
[30]宋宏利,张晓楠.中国区域多源土地覆被遥感产品精度分析与验证[J].农业工程学报,2012,28(22):207-214.[Song H L,Zhang X N.Precision analysis and validation of multi-sources landcover products derived from remote sensing in China[J].Transactions of the Chinese Society of Agricultural Engineering,2012,28(22):207-214.]
[31]Foody G M.Valuing map validation:The need for rigorous land cover map accuracy assessment in economic valuations of ecosystem services[J].Ecological Economics,2015,111:23-28.
[32]侯西勇,邸向红,侯婉,等.中国海岸带土地利用遥感制图及精度评价[J].地球信息科学学报,2018,20(10):1478-1488.[Hou X Y,Di X H,Hou W,et al.Accuracy evaluation of land use mapping using remote sensing techniques in coastal zone of China[J].Journal of Geo-information Science,2018,20(10):1478-1488.]
[33]刘向培,王汉杰,何明元,等.三种土地覆盖遥感数据在中国区域的精度分析[J].农业工程学报,2012,28(24):252-259.[Liu X P,Wang H J,He M Y,et al.Precision analysis of three land-cover types in China region[J].Transactions of the Chinese Society of Agricultural Engineering,2012,28(24):252-259.]