基于多光谱遥感图像的青海湖流域土壤有机质估算初探
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摘要
土壤有机质是土壤固相部分的重要组成成分,也是陆地表层重要的碳库,其含量的快速、准确测定关乎农牧业生产活动安排与地表过程研究中关键参数的获取效率。为了探寻适合青藏高原高寒地区土壤有机质遥感反演的响应波段及遥感模型,实现区域像元尺度上的土壤表层有机质估算,本文利用Landsat8-OLI多光谱遥感数据与实地采样数据对青海湖流域表层(0～20 cm)土壤进行了有机质含量反演研究。结果表明:Landsat8-OLI影像的第5、6和7波段是青海湖流域土壤有机质含量的特征波段,基于这3个波段构建的土壤有机质遥感反演三元回归模型(R~2=0.704,P<0.001),经实测点验证(RMSE=8.66)与相关文献研究结果验证(RMSE=8.85),精度高、稳定性强、预测趋势平稳。本研究不仅为高寒地区土壤有机质含量快速测定提供了一定的技术支持,也为高寒地区的碳库计算、土壤肥力评价、土壤碳循环、农作物估产、草地退化监测等提供了参考。
Soil organic matter(SOM) is an important component of soil solid phase, and it is also an important carbon pool of terrestrial ecosystem. At regionalscale, rapidly and accurately determining SOM content is critical for production activities of agriculture-animal husbandry and the efficiency for obtaining the key parameters of earth surface processes. To explore the remote sensing(RS) bands containing SOM information in multi-spectral RS data and to estimate SOM with RS technology over Qinghai-Tibet Plateau(QTP), the Landsat-8 OLI multi-spectral RS data and the actual sample data were used to construct SOM estimation model with regression analysis method. The results showed that the characteristic bands of SOM in Landsat8-OLI image were band 5, band 6 and band 7. Based on these three bands, the model forestimating SOM was constructed(R~2= 0.704,P<0.001). Through precision analysis of actual measured points(RMSE=8.66) and previous study results(RMSE = 8.85), this model was proved with high precision and strong stability. This study provides not only the technical support for rapid determination SOM over QTP, but also the reference for soil fertility evaluation, carbon pool calculation, soil carbon cycle, crop yield estimation and grassland degradation monitoring in alpine region.
Soil organic matter(SOM) is an important component of soil solid phase, and it is also an important carbon pool of terrestrial ecosystem. At regionalscale, rapidly and accurately determining SOM content is critical for production activities of agriculture-animal husbandry and the efficiency for obtaining the key parameters of earth surface processes. To explore the remote sensing(RS) bands containing SOM information in multi-spectral RS data and to estimate SOM with RS technology over Qinghai-Tibet Plateau(QTP), the Landsat-8 OLI multi-spectral RS data and the actual sample data were used to construct SOM estimation model with regression analysis method. The results showed that the characteristic bands of SOM in Landsat8-OLI image were band 5, band 6 and band 7. Based on these three bands, the model forestimating SOM was constructed(R~2= 0.704,P<0.001). Through precision analysis of actual measured points(RMSE=8.66) and previous study results(RMSE = 8.85), this model was proved with high precision and strong stability. This study provides not only the technical support for rapid determination SOM over QTP, but also the reference for soil fertility evaluation, carbon pool calculation, soil carbon cycle, crop yield estimation and grassland degradation monitoring in alpine region.
引文
[1]武彦清,张柏,宋开山,等.松嫩平原土壤有机质含量高光谱反演研究[J].中国科学院研究生院学报,2011,28(2):187-194
[2]尚斌,邹焱,徐宜民,等.贵州中部山区植烟土壤有机质含量与海拔和成土母质之间的关系[J].土壤,2014,46(3):446-451
[3]吴乐知,蔡祖聪.中国土壤有机质含量变异性与空间尺度的关系[J].地球科学进展,2006,20(9):965-972
[4]刘云香.土壤有机质不同测定方法的比较[J].农村科技,2007,23(6):28
[5]吴才武,夏建新,段峥嵘.土壤有机质测定方法述评与展望[J].土壤,2015,57(3):453-460
[6]田永超,张娟娟,姚霞,等.基于近红外光声光谱的土壤有机质含量定量建模方法[J].农业工程学报,2012,28(1):145-152
[7]于雷,洪永胜,周勇,等.连续小波变换高光谱数据的土壤有机质含量反演模型构建[J].光谱学与光谱分析,2016,35(5):1428-1433
[8]王琼,陈兵,王方永,等.基于HJ卫星的棉田土壤有机质空间分布格局反演[J].农业工程学报,2016,31(1):174-180
[9]周华坤,赵新全,周立,等.青藏高原高寒草甸的植被退化与土壤退化特征研究[J].草业学报,2005,14(3):31-40
[10]张枝枝,张福平,燕玉超,等.渭河两岸缓冲带的土壤有机质含量分布特征及其影响因子[J].土壤,2017,49(2):393-399
[11]柳富坤,袁知洋,孙志国,等.基于GIS的武功山山地草甸土壤有机质空间变异研究[J].资源环境与工程,2017,31(2):158-164
[12]吴才武,张月丛,夏建新.基于地统计与遥感反演相结合的有机质预测制图研究[J].土壤学报,2016,53(6):1568-1575
[13]Leemans R.Scientific challenges for anthropogenic research in the 21th century:Problems of scale//Earth System Science in the Anthro-pocene[C].Berlin:Springer,2006:249-262
[14]曾远文,陈浮,王雨辰,等.采煤矿区表层土壤有机质含量遥感反演[J].水土保持通报,2013,32(2):169-172
[15]Krishnan P,Alexander J D,Butler B J,et al.Reflectance technique for predicting soil organic matter[J].Soil Society of American Journal,1980,44(6):1280-1285
[16]Gunsaulis F R,Kocher M F,Griffis C L.Surface structure effects on close-range reflectance as a function of soil organic matter content[J].American Society of Agricultural Engineer,1991,34(2):641-649
[17]刘焕军,张柏,赵军,等.黑土有机质含量高光谱模型研究[J].土壤学报,2007,44(1):27-32
[18]卢艳丽,白由路,杨俐苹,等.基于主成分回归分析的土壤有机质高光谱预测与模型验证[J].植物营养与肥料学报,2008,14(6):1076-1082
[19]刘炜,常庆瑞,郭曼,等.土壤导数光谱小波去噪与有机质吸收波段特征提取[J].光谱学与光谱分析,2011,31(1):100-104
[20]刘磊,沈润平,丁国香.基于高光谱的土壤有机质含量估算研究[J].光谱学与光谱分析,2011,31(3):762-766
[21]沈润平,丁国香,魏国栓,等.基于人工网络的土壤有机质含量高光谱反演[J].土壤学报,2009,46(3):391-397
[22]张凡,祁彪,温飞,等.不同利用程度高寒干旱草地碳储量的变化特征分析[J].草业学报,2011,20(4):11-18
[23]袁子茹,任灵,陈建纲,等.祁连山不同草地类型土壤有机质与全氮分布的关系[J].草原与草坪,2016,36(3):12-16
[24]方精云,刘国华,徐嵩龄.中国陆地生态系统的碳库//王庚辰,温玉璞.温室气体浓度和排放监测及相关过程[C].北京:中国环境科学出版社,1996:109-128
[25]朱延龙,韩昆,王芳.青海湖流域气候变化特点及水文生态响应[J].中国水利水电科学研究院学报,2012,9(4):260-266
[26]邓书斌,陈秋锦,杜会建,等.ENVI遥感图像处理方法[M].2版.北京:科学出版社,2017:277-312
[27]张玉君.Landsat8简介[J].国土资源遥感,2013,22(1):176-177
[28]Webster R.Statistics to support soil research and theirpresentation[J].European Journal of Soil Science,2001,52:331-340
[29]宋立生,赵之重,徐剑波,等.基于TM遥感影像的玛多县草地土壤有机质的时空格局反演[J].草业科学,2011,27(12):2069-2073
[30]王琼,陈兵,王方永,等.基于HJ卫星的棉田土壤有机质空间分布格局反演[J].农业工程学报,2016,31(1):174-180
[31]程励励,高以信,高坤林.草毡寒冻雏形土的有机质组成特征[J].土壤通报,1996,39(6):243-244
[32]孙宁,常庆瑞.青海高寒区土壤光谱特性研究[J].干旱地区农业研究,2011,29(1):80-83
[33]杨扬,高小红,贾伟,等.三江源区不同土壤类型有机质含量高光谱反演[J].遥感技术与应用,2015,29(1):186-198
[34]青海省农业资源区划办公室.青海土壤[M].北京:中国农业出版社,1995:24-142
[35]李欣宇,宇万太,李秀珍.基于TM影像的表层土壤有机碳空间格局[J].生态学杂志,2008,26(3):333-338
[36]Jenkinson D S,Rayner J H.The turnover of soil organic matter in soil of the Rothamsted classical experiment[J].Soil Science,1977(123):298-305
[37]董智君,赵英.黑土有机质含量与土壤水分蒸发关系的研究[J].农业系统科学与综合研究,2000,15(2):145-148
[38]张帅普,邵明安.绿洲边缘土壤水分与有机质空间分布及变异特征[J].干旱区研究,2014,30(5):812-818
[39]张法升,曲威,尹光华,等.基于多光谱遥感影像的表层土壤有机质空间格局反演[J].应用生态学报,2010,20(4):883-888
[40]Chen F,Kissel D E,West L T.Field-scale mapping of surface soil organic carbon using remotely sensed imagery[J].Soil Science Society of America Journal,2000,64(2):746-753
[2]尚斌,邹焱,徐宜民,等.贵州中部山区植烟土壤有机质含量与海拔和成土母质之间的关系[J].土壤,2014,46(3):446-451
[3]吴乐知,蔡祖聪.中国土壤有机质含量变异性与空间尺度的关系[J].地球科学进展,2006,20(9):965-972
[4]刘云香.土壤有机质不同测定方法的比较[J].农村科技,2007,23(6):28
[5]吴才武,夏建新,段峥嵘.土壤有机质测定方法述评与展望[J].土壤,2015,57(3):453-460
[6]田永超,张娟娟,姚霞,等.基于近红外光声光谱的土壤有机质含量定量建模方法[J].农业工程学报,2012,28(1):145-152
[7]于雷,洪永胜,周勇,等.连续小波变换高光谱数据的土壤有机质含量反演模型构建[J].光谱学与光谱分析,2016,35(5):1428-1433
[8]王琼,陈兵,王方永,等.基于HJ卫星的棉田土壤有机质空间分布格局反演[J].农业工程学报,2016,31(1):174-180
[9]周华坤,赵新全,周立,等.青藏高原高寒草甸的植被退化与土壤退化特征研究[J].草业学报,2005,14(3):31-40
[10]张枝枝,张福平,燕玉超,等.渭河两岸缓冲带的土壤有机质含量分布特征及其影响因子[J].土壤,2017,49(2):393-399
[11]柳富坤,袁知洋,孙志国,等.基于GIS的武功山山地草甸土壤有机质空间变异研究[J].资源环境与工程,2017,31(2):158-164
[12]吴才武,张月丛,夏建新.基于地统计与遥感反演相结合的有机质预测制图研究[J].土壤学报,2016,53(6):1568-1575
[13]Leemans R.Scientific challenges for anthropogenic research in the 21th century:Problems of scale//Earth System Science in the Anthro-pocene[C].Berlin:Springer,2006:249-262
[14]曾远文,陈浮,王雨辰,等.采煤矿区表层土壤有机质含量遥感反演[J].水土保持通报,2013,32(2):169-172
[15]Krishnan P,Alexander J D,Butler B J,et al.Reflectance technique for predicting soil organic matter[J].Soil Society of American Journal,1980,44(6):1280-1285
[16]Gunsaulis F R,Kocher M F,Griffis C L.Surface structure effects on close-range reflectance as a function of soil organic matter content[J].American Society of Agricultural Engineer,1991,34(2):641-649
[17]刘焕军,张柏,赵军,等.黑土有机质含量高光谱模型研究[J].土壤学报,2007,44(1):27-32
[18]卢艳丽,白由路,杨俐苹,等.基于主成分回归分析的土壤有机质高光谱预测与模型验证[J].植物营养与肥料学报,2008,14(6):1076-1082
[19]刘炜,常庆瑞,郭曼,等.土壤导数光谱小波去噪与有机质吸收波段特征提取[J].光谱学与光谱分析,2011,31(1):100-104
[20]刘磊,沈润平,丁国香.基于高光谱的土壤有机质含量估算研究[J].光谱学与光谱分析,2011,31(3):762-766
[21]沈润平,丁国香,魏国栓,等.基于人工网络的土壤有机质含量高光谱反演[J].土壤学报,2009,46(3):391-397
[22]张凡,祁彪,温飞,等.不同利用程度高寒干旱草地碳储量的变化特征分析[J].草业学报,2011,20(4):11-18
[23]袁子茹,任灵,陈建纲,等.祁连山不同草地类型土壤有机质与全氮分布的关系[J].草原与草坪,2016,36(3):12-16
[24]方精云,刘国华,徐嵩龄.中国陆地生态系统的碳库//王庚辰,温玉璞.温室气体浓度和排放监测及相关过程[C].北京:中国环境科学出版社,1996:109-128
[25]朱延龙,韩昆,王芳.青海湖流域气候变化特点及水文生态响应[J].中国水利水电科学研究院学报,2012,9(4):260-266
[26]邓书斌,陈秋锦,杜会建,等.ENVI遥感图像处理方法[M].2版.北京:科学出版社,2017:277-312
[27]张玉君.Landsat8简介[J].国土资源遥感,2013,22(1):176-177
[28]Webster R.Statistics to support soil research and theirpresentation[J].European Journal of Soil Science,2001,52:331-340
[29]宋立生,赵之重,徐剑波,等.基于TM遥感影像的玛多县草地土壤有机质的时空格局反演[J].草业科学,2011,27(12):2069-2073
[30]王琼,陈兵,王方永,等.基于HJ卫星的棉田土壤有机质空间分布格局反演[J].农业工程学报,2016,31(1):174-180
[31]程励励,高以信,高坤林.草毡寒冻雏形土的有机质组成特征[J].土壤通报,1996,39(6):243-244
[32]孙宁,常庆瑞.青海高寒区土壤光谱特性研究[J].干旱地区农业研究,2011,29(1):80-83
[33]杨扬,高小红,贾伟,等.三江源区不同土壤类型有机质含量高光谱反演[J].遥感技术与应用,2015,29(1):186-198
[34]青海省农业资源区划办公室.青海土壤[M].北京:中国农业出版社,1995:24-142
[35]李欣宇,宇万太,李秀珍.基于TM影像的表层土壤有机碳空间格局[J].生态学杂志,2008,26(3):333-338
[36]Jenkinson D S,Rayner J H.The turnover of soil organic matter in soil of the Rothamsted classical experiment[J].Soil Science,1977(123):298-305
[37]董智君,赵英.黑土有机质含量与土壤水分蒸发关系的研究[J].农业系统科学与综合研究,2000,15(2):145-148
[38]张帅普,邵明安.绿洲边缘土壤水分与有机质空间分布及变异特征[J].干旱区研究,2014,30(5):812-818
[39]张法升,曲威,尹光华,等.基于多光谱遥感影像的表层土壤有机质空间格局反演[J].应用生态学报,2010,20(4):883-888
[40]Chen F,Kissel D E,West L T.Field-scale mapping of surface soil organic carbon using remotely sensed imagery[J].Soil Science Society of America Journal,2000,64(2):746-753