基于HICO波段的滨海土壤盐分遥感反演研究
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摘要
本研究以黄河三角洲滨海盐渍土为例,尝试使用HICO(Hyperspectral Imager for the Coastal Ocean)高光谱影像结合现场实测高光谱数据进行表层土壤全盐含量的反演。采用波段组合的方法建立光谱参量,通过相关分析筛选出敏感光谱参量,以决定系数R2选出最佳模型;利用HICO影像反射率与实测高光谱反射率之间的关系,对模型进行修正,并应用于影像。研究发现,比值(RI)、差值(DI)波段组合方法建立的光谱参量与表层土壤全盐含量的相关性明显提高。DI_((845,473))、DI_((839,490))、DI_((845,496))及DI_((839,501))的幂函数模型效果最好,且验证决定系数R~2均大于0.86,相对分析误差RPD>3,RMSE较小。此外,HICO遥感影像的模型反演结果较为一致,能够反映表层土壤全盐含量的分布。研究显示,利用高光谱数据进行表层土壤全盐含量的反演建模具有可行性,可为区域表层土壤全盐含量的定量反演提供参考。
This study aims to use hyperspectral reflectance to estimate soil salinity.Taking the coastal saline soil of the Yellow River Delta as an example,we collected insituground surface reflectance and soil samples for salinity analysis,and integrated with the HICO(Hyperspectral Imager for the Coastal Ocean)imagery data to map the distribution of salinity.The spectral features were established by band combination method.The sensitive features were selected by correlation analysis.The optimal models were selected by the determination coefficients R~2.The relationship between the in situ reflectance and the HICO hyperspectral reflectance is used to modify the model.And these models were applied to HICO images.The study showed that the models of band ratio(RI)and band difference(DI)with significantly high correlations with the soil salinity were established.The power function models established by DI_((845,473)),DI_((839,490)),DI_((845,496)),DI_((839,501)) were the best ones(the determination coefficients R~2>0.86,and the relative prediction deviation RPD>3).The inversion results in the HICO from these models were consistent with each other,and can reflect the distribution of soil salinity for the Yellow River Delta.This study suggests that it is feasible to estimate the soil salinity by using the hyperspectral data,which can provide a reference for quantitative inversion of soil salinity in the coastal region.
This study aims to use hyperspectral reflectance to estimate soil salinity.Taking the coastal saline soil of the Yellow River Delta as an example,we collected insituground surface reflectance and soil samples for salinity analysis,and integrated with the HICO(Hyperspectral Imager for the Coastal Ocean)imagery data to map the distribution of salinity.The spectral features were established by band combination method.The sensitive features were selected by correlation analysis.The optimal models were selected by the determination coefficients R~2.The relationship between the in situ reflectance and the HICO hyperspectral reflectance is used to modify the model.And these models were applied to HICO images.The study showed that the models of band ratio(RI)and band difference(DI)with significantly high correlations with the soil salinity were established.The power function models established by DI_((845,473)),DI_((839,490)),DI_((845,496)),DI_((839,501)) were the best ones(the determination coefficients R~2>0.86,and the relative prediction deviation RPD>3).The inversion results in the HICO from these models were consistent with each other,and can reflect the distribution of soil salinity for the Yellow River Delta.This study suggests that it is feasible to estimate the soil salinity by using the hyperspectral data,which can provide a reference for quantitative inversion of soil salinity in the coastal region.
引文
[1]Metternicht G I,Zinck J A.Remote sensing of soil salinity:potentials and constraints[J].Remote Sensing of Environment,2003,85(1):1-20.
[2]Dwivedi R S,Rao B R M.The selection of the best possible landsat TM band combination for delineating salt affected soils[J].International Journal of Remote Sensing,1992,13(11):2051-2058.
[3]李百红,赵庚星,秦元伟,等.黄河三角洲滨海盐碱退化土地变化遥感监测研究[J].江西农业大学学报,2009,31(6):1166-1171.Li Baihong,Zhao Gengxing,Qing Yuanwei,et al.A study of remote sensing detection of salt-affected coastal Land degradation in the Yellow River Delta[J].Acta Agriculturae Universitatis Jiangxiensis,2009,31(6):1166-1171.
[4]李晋,赵庚星,常春燕,等.基于HSI高光谱和TM图像的土地盐渍化信息提取方法[J].光谱学与光谱分析,2014,34(2):520-525.Li Jin,Zhao Gengxing,Chang Chunyan,et al.Land salinization information extraction method based on HSI hyper-spectral and TM imagery[J].Spectroscopy and Spectral Analysis,2014,34(2):520-525.
[5]Liu Ya,Pan Xianzhang,Wang Changkun,et al.Can subsurface soil salinity be predicted from surface spectral information?-From the perspective of structural equation modelling[J].Biosystems Engineering,2016,152:138-147.
[6]Bouaziz M,Matschullat J,Gloaguen R.Improved remote sensing detection of soil salinity from a semi-arid climate in northeast brazil[J].Comptes Rendus Geoscience,2011,343(11/12):795-803.
[7]陈红艳,赵庚星,陈敬春,等.基于改进植被指数的黄河口区盐渍土盐分遥感反演[J].农业工程学报,2015,31(5):107-112,114.Chen Hongyan,Zhao Gengxing,Chen Jingchun,et al.Remote sensing inversion of saline soil salinity based on modified vegetation index in estuary area of Yellow River[J].Transactions of the Chinese Society of Agricultural Engineering,2015,31(5):107-112,114.
[8]蒲瑞良,宫鹏.高光谱遥感及其应用[M].北京:高等教育出版社,2000.Pu Ruiliang,Gong Peng.Hyperspectral Remote Sensing and Its Application[M].Beijing:Higher Education Press,2000.
[9]Ben-Dor E,Patkin K,Banin A,et al.Mapping of several soil properties using DAIS-7915hyperspectral scanner data.A case study over soils in Israel[J].International Journal of Remote Sensing,2002,23(6):1043-1062.
[10]张飞,塔西甫拉提·特依拜,丁建丽,等.塔里木河流域中游渭干河-库车河绿洲盐渍土水盐信息光谱特征研究[J].地理与地理信息科学,2012,28(1):65-70.Zhang Fei,Tashpolat獉Tiyip,Ding Jianli,et al.Study on water-salt information and Spectral characteristics of saline soil in the Weigan and Kuqa River delta oasis of the middle[J].Geography and Geo-Information Science,2012,28(1):65-70.
[11]丁建丽,伍漫春,刘海霞,等.基于综合高光谱指数的区域土壤盐渍化监测研究[J].光谱学与光谱分析,2012,32(7):1918-1922.Ding Jianli,Wu Manchun,Liu Haixia,et al.Study on the soil salinization monitoring based on synthetical hyper-spectral index[J].Spectroscopy and Spectral Analysis,2012,32(7):1918-1922.
[12]王静,刘湘南,黄方,等.基于ANN技术和高光谱遥感的盐渍土盐分预测[J].农业工程学报,2009,25(12):161-166.Wang Jing,Liu Xiangnan,Huang Fang,et al.Salinity forecasting of saline soil based on ANN and hyperspectral remote sensing[J].Transactions of the CSAE,2009,25(12):161-166.
[13]杨佳佳,姜琦刚,赵静,等.基于环境减灾卫星高光谱数据的盐碱地等级划分[J].农业工程学报,2011,27(10):118-124.Yang Jiajia,Jiang Qigang,Zhao Jing,et al.Quantitative retrieval and classification of saline soil using HJ-1Ahyperspectral data[J].Transactions of the CSAE,2011,27(10):118-124.
[14]Farifteh J,Van der Meer F,Atzberger C,et al.Quantitative analysis of salt-affected soil reflectance spectra:a comparison of two adaptive methods(PLSR and ANN)[J].Remote Sensing of Environment,2007,110(1):59-78.
[15]任广波,张杰,马毅.基于HJ-1A高光谱的黄河口碱蓬和柽柳盖度反演模型研究[J].海洋学报,2015,37(9):51-58.Ren Guangbo,Zhang Jie,Ma Yi.Suaeda-salsa and tamarisk fractional cover inversion models by HJ-1Ahyperspectral remote sensing image in Yellow River Estuary[J].Haiyang Xuebao,2015,37(9):51-58.
[16]Xing Qianguo,Lou Mingjing,Chen Chuqun,et al.Using in situ and Satellite hyperspectral data to estimate the surface suspended sediments concentrations in the Pearl River Estuary[J].IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2013,6(2):731-738.
[17]An Deyu,Zhao Gengxing,Chang Chunyan,et al.Hyperspectral field estimation and remote-sensing inversion of salt content in coastal saline soils of the Yellow river delta[J].International Journal of Remote Sensing,2016,37(2):455-470.
[18]翁永玲,戚浩平,方洪宾,等.基于PLSR方法的青海茶卡-共和盆地土壤盐分高光谱遥感反演[J].土壤学报,2010,47(6):1255-1263.Weng Yongling,Qi Haoping,Fang Hongbin,et al.PLSR-based hyperspectral remote sensing retrieval of soil salinity of Chaka-Gonghe Basin in Qinghai province[J].Acta Pedologica Sinca,2010,47(6):1255-1263.
[19]娄明静,邢前国,施平.海岸带高光谱遥感与近海高光谱成像仪(HICO)[J].遥感技术与应用,2013,28(4):627-632.Lou Mingjing,Xing Qianguo,Shi Ping.Hyperspectral remote sensing for coastal zone and hyperspectral imager for the coastal ocean[J].Remote Sensing Technology and Application,2013,28(4):627-632.
[20]Gitelson A A,Gao Bocai,Li Rongrong,et al.Estimation of chlorophyll aconcentration in productive turbid waters using a hyperspectral imager for the coastal ocean-the Azov sea case study[J].Environmental Research Letters,2011,6(2):024023.
[21]范晓梅,刘高焕,唐志鹏,等.黄河三角洲土壤盐渍化影响因素分析[J].水土保持学报,2010,24(1):139-144.Fan Xiaomein,Liu Gaohuan,Tang Zhipeng,et al.Analysis on main contributors influencing soil salinization of Yellow River Delta[J].Journal of Soil and Water Conservation,2010,24(1):139-144.
[22]关元秀,刘高焕,王劲峰.基于GIS的黄河三角洲盐碱地改良分区[J].地理学报,2001,56(2):198-205.Guan Yuanxiu,Liu Gaohuan,Wang Jinfeng.Regionalization of salt-affected land for amelioration in the Yellow river delta based on GIS[J].Acta Geographica Sinica,2001,56(2):198-205.
[23]Chang Chengwen,Laird D A,Mausbach M J,et al.Near-infrared reflectance spectroscopy-principal components regression analysis of soil properties[J].Soil Science Society of America Journal,2001,65(2):480-490.
[24]Rao B R M,Sharma R C,Sankar T R,et al.Spectral behavior of salt-affected soils[J].International Journal of Remote Sensing,1995,16(12):2125-2136.
[25]李晓明,韩霁昌,李娟.典型半干旱区土壤盐分高光谱特征反演[J].光谱学与光谱分析,2014,34(4):1081-1084.Li Xiaoming,Han Jichang,Li Juan.Research on hyperspectral inversion of soil salinity in typical semiarid area[J].Spectroscopy and Spectral Analysis,2014,34(4):1081-1084.
[2]Dwivedi R S,Rao B R M.The selection of the best possible landsat TM band combination for delineating salt affected soils[J].International Journal of Remote Sensing,1992,13(11):2051-2058.
[3]李百红,赵庚星,秦元伟,等.黄河三角洲滨海盐碱退化土地变化遥感监测研究[J].江西农业大学学报,2009,31(6):1166-1171.Li Baihong,Zhao Gengxing,Qing Yuanwei,et al.A study of remote sensing detection of salt-affected coastal Land degradation in the Yellow River Delta[J].Acta Agriculturae Universitatis Jiangxiensis,2009,31(6):1166-1171.
[4]李晋,赵庚星,常春燕,等.基于HSI高光谱和TM图像的土地盐渍化信息提取方法[J].光谱学与光谱分析,2014,34(2):520-525.Li Jin,Zhao Gengxing,Chang Chunyan,et al.Land salinization information extraction method based on HSI hyper-spectral and TM imagery[J].Spectroscopy and Spectral Analysis,2014,34(2):520-525.
[5]Liu Ya,Pan Xianzhang,Wang Changkun,et al.Can subsurface soil salinity be predicted from surface spectral information?-From the perspective of structural equation modelling[J].Biosystems Engineering,2016,152:138-147.
[6]Bouaziz M,Matschullat J,Gloaguen R.Improved remote sensing detection of soil salinity from a semi-arid climate in northeast brazil[J].Comptes Rendus Geoscience,2011,343(11/12):795-803.
[7]陈红艳,赵庚星,陈敬春,等.基于改进植被指数的黄河口区盐渍土盐分遥感反演[J].农业工程学报,2015,31(5):107-112,114.Chen Hongyan,Zhao Gengxing,Chen Jingchun,et al.Remote sensing inversion of saline soil salinity based on modified vegetation index in estuary area of Yellow River[J].Transactions of the Chinese Society of Agricultural Engineering,2015,31(5):107-112,114.
[8]蒲瑞良,宫鹏.高光谱遥感及其应用[M].北京:高等教育出版社,2000.Pu Ruiliang,Gong Peng.Hyperspectral Remote Sensing and Its Application[M].Beijing:Higher Education Press,2000.
[9]Ben-Dor E,Patkin K,Banin A,et al.Mapping of several soil properties using DAIS-7915hyperspectral scanner data.A case study over soils in Israel[J].International Journal of Remote Sensing,2002,23(6):1043-1062.
[10]张飞,塔西甫拉提·特依拜,丁建丽,等.塔里木河流域中游渭干河-库车河绿洲盐渍土水盐信息光谱特征研究[J].地理与地理信息科学,2012,28(1):65-70.Zhang Fei,Tashpolat獉Tiyip,Ding Jianli,et al.Study on water-salt information and Spectral characteristics of saline soil in the Weigan and Kuqa River delta oasis of the middle[J].Geography and Geo-Information Science,2012,28(1):65-70.
[11]丁建丽,伍漫春,刘海霞,等.基于综合高光谱指数的区域土壤盐渍化监测研究[J].光谱学与光谱分析,2012,32(7):1918-1922.Ding Jianli,Wu Manchun,Liu Haixia,et al.Study on the soil salinization monitoring based on synthetical hyper-spectral index[J].Spectroscopy and Spectral Analysis,2012,32(7):1918-1922.
[12]王静,刘湘南,黄方,等.基于ANN技术和高光谱遥感的盐渍土盐分预测[J].农业工程学报,2009,25(12):161-166.Wang Jing,Liu Xiangnan,Huang Fang,et al.Salinity forecasting of saline soil based on ANN and hyperspectral remote sensing[J].Transactions of the CSAE,2009,25(12):161-166.
[13]杨佳佳,姜琦刚,赵静,等.基于环境减灾卫星高光谱数据的盐碱地等级划分[J].农业工程学报,2011,27(10):118-124.Yang Jiajia,Jiang Qigang,Zhao Jing,et al.Quantitative retrieval and classification of saline soil using HJ-1Ahyperspectral data[J].Transactions of the CSAE,2011,27(10):118-124.
[14]Farifteh J,Van der Meer F,Atzberger C,et al.Quantitative analysis of salt-affected soil reflectance spectra:a comparison of two adaptive methods(PLSR and ANN)[J].Remote Sensing of Environment,2007,110(1):59-78.
[15]任广波,张杰,马毅.基于HJ-1A高光谱的黄河口碱蓬和柽柳盖度反演模型研究[J].海洋学报,2015,37(9):51-58.Ren Guangbo,Zhang Jie,Ma Yi.Suaeda-salsa and tamarisk fractional cover inversion models by HJ-1Ahyperspectral remote sensing image in Yellow River Estuary[J].Haiyang Xuebao,2015,37(9):51-58.
[16]Xing Qianguo,Lou Mingjing,Chen Chuqun,et al.Using in situ and Satellite hyperspectral data to estimate the surface suspended sediments concentrations in the Pearl River Estuary[J].IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2013,6(2):731-738.
[17]An Deyu,Zhao Gengxing,Chang Chunyan,et al.Hyperspectral field estimation and remote-sensing inversion of salt content in coastal saline soils of the Yellow river delta[J].International Journal of Remote Sensing,2016,37(2):455-470.
[18]翁永玲,戚浩平,方洪宾,等.基于PLSR方法的青海茶卡-共和盆地土壤盐分高光谱遥感反演[J].土壤学报,2010,47(6):1255-1263.Weng Yongling,Qi Haoping,Fang Hongbin,et al.PLSR-based hyperspectral remote sensing retrieval of soil salinity of Chaka-Gonghe Basin in Qinghai province[J].Acta Pedologica Sinca,2010,47(6):1255-1263.
[19]娄明静,邢前国,施平.海岸带高光谱遥感与近海高光谱成像仪(HICO)[J].遥感技术与应用,2013,28(4):627-632.Lou Mingjing,Xing Qianguo,Shi Ping.Hyperspectral remote sensing for coastal zone and hyperspectral imager for the coastal ocean[J].Remote Sensing Technology and Application,2013,28(4):627-632.
[20]Gitelson A A,Gao Bocai,Li Rongrong,et al.Estimation of chlorophyll aconcentration in productive turbid waters using a hyperspectral imager for the coastal ocean-the Azov sea case study[J].Environmental Research Letters,2011,6(2):024023.
[21]范晓梅,刘高焕,唐志鹏,等.黄河三角洲土壤盐渍化影响因素分析[J].水土保持学报,2010,24(1):139-144.Fan Xiaomein,Liu Gaohuan,Tang Zhipeng,et al.Analysis on main contributors influencing soil salinization of Yellow River Delta[J].Journal of Soil and Water Conservation,2010,24(1):139-144.
[22]关元秀,刘高焕,王劲峰.基于GIS的黄河三角洲盐碱地改良分区[J].地理学报,2001,56(2):198-205.Guan Yuanxiu,Liu Gaohuan,Wang Jinfeng.Regionalization of salt-affected land for amelioration in the Yellow river delta based on GIS[J].Acta Geographica Sinica,2001,56(2):198-205.
[23]Chang Chengwen,Laird D A,Mausbach M J,et al.Near-infrared reflectance spectroscopy-principal components regression analysis of soil properties[J].Soil Science Society of America Journal,2001,65(2):480-490.
[24]Rao B R M,Sharma R C,Sankar T R,et al.Spectral behavior of salt-affected soils[J].International Journal of Remote Sensing,1995,16(12):2125-2136.
[25]李晓明,韩霁昌,李娟.典型半干旱区土壤盐分高光谱特征反演[J].光谱学与光谱分析,2014,34(4):1081-1084.Li Xiaoming,Han Jichang,Li Juan.Research on hyperspectral inversion of soil salinity in typical semiarid area[J].Spectroscopy and Spectral Analysis,2014,34(4):1081-1084.