湿地植被遥感分类研究进展
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摘要
植被是湿地生态系统的重要组成部分,湿地植被遥感分类研究能为湿地保护、管理和恢复提供实践指导。文中主要从湿地植被遥感分类的数据源和分类方法2方面综述湿地植被遥感分类研究的现状,分析目前湿地植被遥感分类研究的不足,展望未来我国湿地植被遥感分类的发展趋势。
Vegetation is an important part of wetland ecosystem, and the study of remote sensing based wetland vegetation classification can provide practical guidance for wetland protection, management and restoration. This paper reviewed the current research on remote sensing classification from the aspects of the data sources of remote sensing classification of wetland vegetation and the classification methods, analyzed the shortcomings in this research at present, and prospected the future development trend of remote sensing classification of wetland vegetation in China.
Vegetation is an important part of wetland ecosystem, and the study of remote sensing based wetland vegetation classification can provide practical guidance for wetland protection, management and restoration. This paper reviewed the current research on remote sensing classification from the aspects of the data sources of remote sensing classification of wetland vegetation and the classification methods, analyzed the shortcomings in this research at present, and prospected the future development trend of remote sensing classification of wetland vegetation in China.
引文
[1]BARDLEY J C,HAUER F R.Effects of hydrologic connectivity on water chemistry,soils,and vegetation structure and function in an intermontane deprssional wetland landscape [J].Wetlands,2007,27(3):719-738.
[2]KOKALY R F,DESPAIN D G,CLARK R N,et al.Mapping vegetation in ellowstone national park using spectral feature analysis of AVIRIS data [J].Remote Sensing of Environment,2003,84(3):437-456.
[3]闫利,江维薇.多光谱遥感影像植被覆盖分类研究进展 [J].国土资源遥感,2016,28(2):8-13.
[4]杜培军,夏俊士,薛朝辉,等.高光谱遥感影像分类研究进展 [J].遥感学报,2016,20(2):236-256.
[5]李方方,刘正军,徐强强,等.面向对象随机森林方法在湿地植被分类的应用 [J].遥感信息,2018,33(1):111-116.
[6]HARVEY K R,Hill G J E.Vegetation mapping of a tropical freshwater swamp in the Northern Territory,Australia:a comparison of aerial photography,Landsat TM and SPOT satellite imagery [J].International Journal of Remote Sensing,2001,22(15):2911-2925.
[7]LABA M,DOWNS R,SMITH S,et al.Mapping invasive wetland plants in the Hudson River National Estuarine Research Reserve using Quickbird satellite imagery [J].Remote Sensing of Environment,2008,112(1):286-300.
[8]杜红艳,张洪岩,张正祥.GIS支持下的湿地遥感信息高精度分类方法研究 [J].遥感技术与应用,2004,19(4):244-248.
[9]衣伟宏,杨柳,张正祥.基于ETM+影像的扎龙湿地遥感分类研究 [J].湿地科学,2004,2(3):208-212.
[10]PAOLETTI M E,HAUT J M,PLAZA J.A new deep convolutional neural network for fast hyperspectral image classification [J].ISPRS Journal of Photogrammetry and Remote Sensing,2017,11(21):1-28.
[11]刘丹,杨风暴,卫红,等.基于多分类器的C5.0决策树植被分类方法 [J].图学学报,2017,38(5):722-728.
[12]BARDUCCI A,GUZZI D,MARCOONNI P,et al.Aerospace wetland monitoring by hyperspectral imaging sensors:a case study in the coastal zone of San Rossore Natural Park [J].Journal of Environmental Management,2009,90(7):2278-2286.
[13]ZOMER R J,TRABUCCO A,USTIN S L.Building spectral libraries for wetlands land cover classification and hyperspectral remote sensing [J].Journal of Environmental Management,2009,90(7):2170-2177.
[14]庞勇,李增元,陈尔学,等.激光雷达技术及其在林业上的应用 [J].林业科学,2005,41(3):129-136.
[15]GUO X,COOPSA N C,TOMPALSKI P,et al.Regional mapping of vegetation structure for biodiversity monitoring using airborne lidar data [J].Ecological Informatics,2017,38:50-61.
[16]RAPINEL S,MOY L H,CLEMENT B.Combined use of LiDAR data and multispectral earth observation imagery for wetland habitat mapping [J].International Journal of Applied Earth Observation and Geoinformation,2015,37:56-64.
[17]谢瑞,程效军,管海燕.机载激光扫描与航空影像的融合分类与精度分析 [J].同济大学学报(自然科学版),2013,41(4):607-603.
[18]ASHRAF S,BRABYN L,HICKS B J.Image data fusion for the remote sensing of freshwater environments [J].Applied Geography,2012,3232(2):619-628.
[19]CHEN B,CHEN L F,LU M,et al.Wetland mapping by fusing fine spatial and hyperspectral resolution images [J].Ecological Modelling,2017,353:1-12.
[20]SHI Y F,ANDREW K S,WANG T J,et al.Tree species classification using plant functional traits from LiDAR and hyperspectral data [J].International Journal of Applied Earth Observation and Geoinformation,2018,73:207-219.
[21]AMANI M,SALEHI B,MAHDAVI S,et al.Spectral analysis of wetlands suing multi-source optical satellite imagery [J].ISPRS Journal of Photogrammetry and Remote Sensing,2018,144:119-136.
[22]JAHCCKE R,LEBLON B,BUSH P,et al.Mapping wetlands in Nova Scotia with multi-beam RADARSAT-2 Polarimetric SAR,optical satellite imagery,and Lidar data [J].International Journal of Applied Earth Observation and Geoinformation,2018,68:139-156.
[23]MUNYATI C,RATSHIBVUMO T,OGOLA J.Landsat TM image segmentation for delineating geological zone correlated vegetation stratification in the Kruger National Park,South Africa [J].Physics and Chemistry of the Earth(Parts A/B/C)2013,55/56/57:1-10.
[24]CHURCHES C E,WAMPLER P J,SUN W X,et al.Evaluation of forest cover estimates for Haiti using supervised classification of Landsat data [J].International Journal of Applied Earth Observation and Geoinformation,2014,30:203-216.
[25]王建强,吴连喜,张岩岩.基于3S技术湿地遥感信息分类方法的研究 [J].水利科技与经济,2006,12(10):718-720.
[26]GERKE M,XIAO J.Fusion of airborne laser scanning point clouds and images for supervised and unsupervised scene classification [J].ISPRS Journal of Photogrammetry and Remote Sensing,2014,87:78-92.
[27]张树文,颜凤芹,于灵雪,等.湿地遥感研究进展 [J].地理科学,2013,33(11):1406-1412.
[28]CRASTO N,HOPKINSON C,FORBES D,et al.A LiDAR based decision-tree classification of open water surfaces in an Arctic delta [J].Remote Sensing of Environment,2015,164:90-102.
[29]王鹏,万荣荣,杨桂山.基于多源遥感数据的湿地植物分类和生物量反演研究进展 [J].湿地科学,2017,15(1):114-124.
[30]BAO Y H,REN J B.Wetland landscape classification based on the BP neural network in DaLinor Lake Area [J].Procedia Environmental Sciences,2011,10:2360-2366.
[31]ZHANG C,XIE Z.Combining object-based texture measures with a neural network for vegetation mapping in the Everglades from hyperspectral imagery [J].Remote Sensing of Environment,2012,124:310-320.
[32]臧淑英,张策,张丽娟,等.遗传算法优化的支持向量机湿地遥感分类:以洪河国家级自然保护区为例 [J].地理科学,2012,32(4):434-441.
[33]LI L,CHEN Y,XU T,et al.Super-resolution mapping of wetland inundation from remote sensing imagery based on integration of back-propagation neural network and genetic algorithm [J].Remote Sensing of Environment,2015,164:142-154.
[34]MOUNTRAKIS G,IM J,OGOLE C.Support vector machines in remote sensing:a review [J].ISPRS Journal of Photogrammetry and Remote Sensing,2011,66 (3):247-259.
[35]HEUMANN B W.An object-based classification of mangroves using a hybrid decision tree-support vector machine approach [J].Remote Sensing,2011,33(11):2440-2460.
[36]莫利江,曹宇,胡远满,等.面向对象的湿地景观遥感分类:以杭州湾南岸地区为例 [J].湿地科学,2012,10(2):206-213.
[37]MELGANI F,BRUZZONE L.Classification of hyperspectral remote sensing images with support vector machines [J].IEEE Transactions on Geoscience and Remote Sensing,2004,42(8):1778-1790.
[38]MAULIK U,CHAKRABORTY D.Learning with transductive SVM for semi-supervised pixel classification of remote sensing imagery [J].ISPRS Journal of Photogrammetry and Remote Sensing,2013,77:66-78.
[39]ONEILA G L,GOODALLA J L,WATSON L T.Evaluating the potential for site-specific modification of LiDAR DEM derivatives to improve environmental planning-scale wetland identification using Random Forest classification [J].Journal of Hydrology,2018,559:192-208.
[40]MASUND M,BAHRAM S,FARIBA M.Random forest wetland classification using ALOS-2 L-band,RADARSAT-2 C-band,and Terra SAR-X imagery [J].ISPRS Journal of Photogrammetry and Remote Sensing,2017,130:13-31.
[41]KRISTIN B,BYRDA,LAUREL B,et al.A remote sensing based model of tidal marsh aboveground carbon stocks for the conterminous United States [J].ISPRS Journal of Photogrammetry and Remote Sensing,2018,139:255-271.
[42]IRYNA D,GONG P,NICHOLAS E,et al.Landscape analysis of wetland plant functional types:the effects of image segmentation scale,vegetation classes and classification methods [J].Remote Sensing of Environment,2012,127:357-369.
[43]GU H,ADITYA S,PHILIP A.Detection of gradients of forest composition in an urban area using imaging spectroscopy [J].Remote Sensing of Environment,2015,167:168-180.
[44]CHRIS W,GALLANT A.Improved wetland remote sensing in Yellowstone National Park using classification trees to combine TM imagery and ancillary environmental data [J].Remote Sensing of Environment,2007,107:582-605.
[45]宋仁飞,林辉,严恩萍等.洞庭湖湿地植被分类研究 [J].中南林业科技大学学报,2015,35(11):27-31.
[46]BONTEMPS S,BOGAERT P,TITEUX N,et al.An object-based change detection method accounting for temporal dependences in time series with medium to coarse spatial resolution [J].Remote Sensing of Environment,2008,112:3181-3191.
[47]KIM K G,PARK M Y,CHOI H S.Developing a wetland-type classification system in the Republic of Korea [J].Landscape and Ecological Engineering,2006,2(2):93-110.
[2]KOKALY R F,DESPAIN D G,CLARK R N,et al.Mapping vegetation in ellowstone national park using spectral feature analysis of AVIRIS data [J].Remote Sensing of Environment,2003,84(3):437-456.
[3]闫利,江维薇.多光谱遥感影像植被覆盖分类研究进展 [J].国土资源遥感,2016,28(2):8-13.
[4]杜培军,夏俊士,薛朝辉,等.高光谱遥感影像分类研究进展 [J].遥感学报,2016,20(2):236-256.
[5]李方方,刘正军,徐强强,等.面向对象随机森林方法在湿地植被分类的应用 [J].遥感信息,2018,33(1):111-116.
[6]HARVEY K R,Hill G J E.Vegetation mapping of a tropical freshwater swamp in the Northern Territory,Australia:a comparison of aerial photography,Landsat TM and SPOT satellite imagery [J].International Journal of Remote Sensing,2001,22(15):2911-2925.
[7]LABA M,DOWNS R,SMITH S,et al.Mapping invasive wetland plants in the Hudson River National Estuarine Research Reserve using Quickbird satellite imagery [J].Remote Sensing of Environment,2008,112(1):286-300.
[8]杜红艳,张洪岩,张正祥.GIS支持下的湿地遥感信息高精度分类方法研究 [J].遥感技术与应用,2004,19(4):244-248.
[9]衣伟宏,杨柳,张正祥.基于ETM+影像的扎龙湿地遥感分类研究 [J].湿地科学,2004,2(3):208-212.
[10]PAOLETTI M E,HAUT J M,PLAZA J.A new deep convolutional neural network for fast hyperspectral image classification [J].ISPRS Journal of Photogrammetry and Remote Sensing,2017,11(21):1-28.
[11]刘丹,杨风暴,卫红,等.基于多分类器的C5.0决策树植被分类方法 [J].图学学报,2017,38(5):722-728.
[12]BARDUCCI A,GUZZI D,MARCOONNI P,et al.Aerospace wetland monitoring by hyperspectral imaging sensors:a case study in the coastal zone of San Rossore Natural Park [J].Journal of Environmental Management,2009,90(7):2278-2286.
[13]ZOMER R J,TRABUCCO A,USTIN S L.Building spectral libraries for wetlands land cover classification and hyperspectral remote sensing [J].Journal of Environmental Management,2009,90(7):2170-2177.
[14]庞勇,李增元,陈尔学,等.激光雷达技术及其在林业上的应用 [J].林业科学,2005,41(3):129-136.
[15]GUO X,COOPSA N C,TOMPALSKI P,et al.Regional mapping of vegetation structure for biodiversity monitoring using airborne lidar data [J].Ecological Informatics,2017,38:50-61.
[16]RAPINEL S,MOY L H,CLEMENT B.Combined use of LiDAR data and multispectral earth observation imagery for wetland habitat mapping [J].International Journal of Applied Earth Observation and Geoinformation,2015,37:56-64.
[17]谢瑞,程效军,管海燕.机载激光扫描与航空影像的融合分类与精度分析 [J].同济大学学报(自然科学版),2013,41(4):607-603.
[18]ASHRAF S,BRABYN L,HICKS B J.Image data fusion for the remote sensing of freshwater environments [J].Applied Geography,2012,3232(2):619-628.
[19]CHEN B,CHEN L F,LU M,et al.Wetland mapping by fusing fine spatial and hyperspectral resolution images [J].Ecological Modelling,2017,353:1-12.
[20]SHI Y F,ANDREW K S,WANG T J,et al.Tree species classification using plant functional traits from LiDAR and hyperspectral data [J].International Journal of Applied Earth Observation and Geoinformation,2018,73:207-219.
[21]AMANI M,SALEHI B,MAHDAVI S,et al.Spectral analysis of wetlands suing multi-source optical satellite imagery [J].ISPRS Journal of Photogrammetry and Remote Sensing,2018,144:119-136.
[22]JAHCCKE R,LEBLON B,BUSH P,et al.Mapping wetlands in Nova Scotia with multi-beam RADARSAT-2 Polarimetric SAR,optical satellite imagery,and Lidar data [J].International Journal of Applied Earth Observation and Geoinformation,2018,68:139-156.
[23]MUNYATI C,RATSHIBVUMO T,OGOLA J.Landsat TM image segmentation for delineating geological zone correlated vegetation stratification in the Kruger National Park,South Africa [J].Physics and Chemistry of the Earth(Parts A/B/C)2013,55/56/57:1-10.
[24]CHURCHES C E,WAMPLER P J,SUN W X,et al.Evaluation of forest cover estimates for Haiti using supervised classification of Landsat data [J].International Journal of Applied Earth Observation and Geoinformation,2014,30:203-216.
[25]王建强,吴连喜,张岩岩.基于3S技术湿地遥感信息分类方法的研究 [J].水利科技与经济,2006,12(10):718-720.
[26]GERKE M,XIAO J.Fusion of airborne laser scanning point clouds and images for supervised and unsupervised scene classification [J].ISPRS Journal of Photogrammetry and Remote Sensing,2014,87:78-92.
[27]张树文,颜凤芹,于灵雪,等.湿地遥感研究进展 [J].地理科学,2013,33(11):1406-1412.
[28]CRASTO N,HOPKINSON C,FORBES D,et al.A LiDAR based decision-tree classification of open water surfaces in an Arctic delta [J].Remote Sensing of Environment,2015,164:90-102.
[29]王鹏,万荣荣,杨桂山.基于多源遥感数据的湿地植物分类和生物量反演研究进展 [J].湿地科学,2017,15(1):114-124.
[30]BAO Y H,REN J B.Wetland landscape classification based on the BP neural network in DaLinor Lake Area [J].Procedia Environmental Sciences,2011,10:2360-2366.
[31]ZHANG C,XIE Z.Combining object-based texture measures with a neural network for vegetation mapping in the Everglades from hyperspectral imagery [J].Remote Sensing of Environment,2012,124:310-320.
[32]臧淑英,张策,张丽娟,等.遗传算法优化的支持向量机湿地遥感分类:以洪河国家级自然保护区为例 [J].地理科学,2012,32(4):434-441.
[33]LI L,CHEN Y,XU T,et al.Super-resolution mapping of wetland inundation from remote sensing imagery based on integration of back-propagation neural network and genetic algorithm [J].Remote Sensing of Environment,2015,164:142-154.
[34]MOUNTRAKIS G,IM J,OGOLE C.Support vector machines in remote sensing:a review [J].ISPRS Journal of Photogrammetry and Remote Sensing,2011,66 (3):247-259.
[35]HEUMANN B W.An object-based classification of mangroves using a hybrid decision tree-support vector machine approach [J].Remote Sensing,2011,33(11):2440-2460.
[36]莫利江,曹宇,胡远满,等.面向对象的湿地景观遥感分类:以杭州湾南岸地区为例 [J].湿地科学,2012,10(2):206-213.
[37]MELGANI F,BRUZZONE L.Classification of hyperspectral remote sensing images with support vector machines [J].IEEE Transactions on Geoscience and Remote Sensing,2004,42(8):1778-1790.
[38]MAULIK U,CHAKRABORTY D.Learning with transductive SVM for semi-supervised pixel classification of remote sensing imagery [J].ISPRS Journal of Photogrammetry and Remote Sensing,2013,77:66-78.
[39]ONEILA G L,GOODALLA J L,WATSON L T.Evaluating the potential for site-specific modification of LiDAR DEM derivatives to improve environmental planning-scale wetland identification using Random Forest classification [J].Journal of Hydrology,2018,559:192-208.
[40]MASUND M,BAHRAM S,FARIBA M.Random forest wetland classification using ALOS-2 L-band,RADARSAT-2 C-band,and Terra SAR-X imagery [J].ISPRS Journal of Photogrammetry and Remote Sensing,2017,130:13-31.
[41]KRISTIN B,BYRDA,LAUREL B,et al.A remote sensing based model of tidal marsh aboveground carbon stocks for the conterminous United States [J].ISPRS Journal of Photogrammetry and Remote Sensing,2018,139:255-271.
[42]IRYNA D,GONG P,NICHOLAS E,et al.Landscape analysis of wetland plant functional types:the effects of image segmentation scale,vegetation classes and classification methods [J].Remote Sensing of Environment,2012,127:357-369.
[43]GU H,ADITYA S,PHILIP A.Detection of gradients of forest composition in an urban area using imaging spectroscopy [J].Remote Sensing of Environment,2015,167:168-180.
[44]CHRIS W,GALLANT A.Improved wetland remote sensing in Yellowstone National Park using classification trees to combine TM imagery and ancillary environmental data [J].Remote Sensing of Environment,2007,107:582-605.
[45]宋仁飞,林辉,严恩萍等.洞庭湖湿地植被分类研究 [J].中南林业科技大学学报,2015,35(11):27-31.
[46]BONTEMPS S,BOGAERT P,TITEUX N,et al.An object-based change detection method accounting for temporal dependences in time series with medium to coarse spatial resolution [J].Remote Sensing of Environment,2008,112:3181-3191.
[47]KIM K G,PARK M Y,CHOI H S.Developing a wetland-type classification system in the Republic of Korea [J].Landscape and Ecological Engineering,2006,2(2):93-110.