基于多角度高光谱遥感的冬小麦叶片含水率估算模型
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摘要
准确的作物水分监测对于旱情评估具有重要意义。在分析研究区冬小麦多角度光谱特征后,利用不同水分处理下冬小麦实测叶片含水率和实测多角度光谱数据,基于植被光谱指数法,建立不同观测角度下冬小麦光谱植被指数、水分敏感波段光谱指数与叶片含水率之间的数学模型。结果显示,相对方位角与相对天顶角越小时,观测到的光谱指数与叶片含水率的相关关系越优;敏感波段组合构建的光谱指数中,1450nm波段分别与其他波段组合的NDSI、RSI指数与叶片含水率相关性在各观测角度条件下均较好,1 450 nm波段是冬小麦叶片含水率研究的最佳敏感波段;选取常见的4种植被指数(NDVI、EVI、WI和NDII)中WI和NDVI在各观测角度下与叶片含水率的相关性优于其他两种指数,决定系数R2均在0.83以上,P<0.01呈极显著相关;综上建立的多角度光谱叶片含水率估算模型,平均相对误差MRE均小于0.154、均方根误差RMSE均小于0.098,拟合效果较好,尤其是光谱指数NDSI1160,1450、NDSI980,1450和植被指数NDVI、WI;基于以上4种指数建立的最优观测角度(0°,30°)模型,其中植被指数WI的估算效果最好,相关系数在各角度均达到5%的相关显著水平,MRE<0.03,可作为最优观测角度反演研究的最优植被指数。
Accurate crop moisture monitoring is great importance for drought assessment. Based on the analysis of multi-angle spectral characteristics of winter wheat under different water treatments, we analyzed the leaf moisture content and measure the multi-angle spectral data of winter wheat under different water treatments, then by using the vegetation spectral index method, and established the mathematical models of spectral indices and leaf water content under different observation angles. The results showed that the smaller the relative azimuth and relative zenith angle, the better the correlation between the observed spectral index and leaf moisture content. The spectral indexes of the sensitive band combination were the NDSI and RSI index of the 1 450 nm band combined with other bands, and the correlation with the water content of the leaves was good under various observation angles, so the 1 450 nm band was the best sensitive band for the study of leaf water content of winter wheat. The common 4 planting indexes(NDVI, EVI, WI, NDII) were selected for WI and NDVI, the correlation between the water content and the leaf moisture content were better than that of the other two indexes. The determination coefficient R2 was above 0.83, P<0.01 was extremely significant correlation. From the multi-angle spectral leaf moisture estimation model, the error MRE was less than 0.154, the root mean square error RMSE was less than 0.098, and the fitting effect was good, especially the spectral indexes NDSI1160,1450, NDSI980,1450 and vegetation index NDVI, WI. From the optimal observation angle(0 °, 30 °) model, the vegetation index WI is the best estimation effect, and the correlation coefficient reached 5% significant level at all angles, the MRE is less than 0.03, it can be used as the optimal vegetation index for the inversion of optimal observation angle.
Accurate crop moisture monitoring is great importance for drought assessment. Based on the analysis of multi-angle spectral characteristics of winter wheat under different water treatments, we analyzed the leaf moisture content and measure the multi-angle spectral data of winter wheat under different water treatments, then by using the vegetation spectral index method, and established the mathematical models of spectral indices and leaf water content under different observation angles. The results showed that the smaller the relative azimuth and relative zenith angle, the better the correlation between the observed spectral index and leaf moisture content. The spectral indexes of the sensitive band combination were the NDSI and RSI index of the 1 450 nm band combined with other bands, and the correlation with the water content of the leaves was good under various observation angles, so the 1 450 nm band was the best sensitive band for the study of leaf water content of winter wheat. The common 4 planting indexes(NDVI, EVI, WI, NDII) were selected for WI and NDVI, the correlation between the water content and the leaf moisture content were better than that of the other two indexes. The determination coefficient R2 was above 0.83, P<0.01 was extremely significant correlation. From the multi-angle spectral leaf moisture estimation model, the error MRE was less than 0.154, the root mean square error RMSE was less than 0.098, and the fitting effect was good, especially the spectral indexes NDSI1160,1450, NDSI980,1450 and vegetation index NDVI, WI. From the optimal observation angle(0 °, 30 °) model, the vegetation index WI is the best estimation effect, and the correlation coefficient reached 5% significant level at all angles, the MRE is less than 0.03, it can be used as the optimal vegetation index for the inversion of optimal observation angle.
引文
[1]曹卫星.作物栽培学总论[M].2版.科学出版社,2011.
[2]李合生.现代植物生理学[M].3版.北京:高等教育出版社,2012.
[3]雷艳,张富仓,寇雯萍,等.不同生育期水分亏缺和施氮对冬小麦产量及水分利用效率的影响[J].西北农林科技大学学报(自然科学版),2010,38(5):167-174.
[4]魏永霞,马瑛瑛,冯鼎瑞,等.调亏灌溉下滴灌玉米根冠生长与水分动态响应特征[J].农业机械学报,2017,48(7):180-188.
[5]李东晓,王红光,张迪,等.水分亏缺对不同小麦品种矿质元素吸收分布及水分利用的影响[J].中国生态农业学报,2017,25(10):1475-1484.
[6]赵丽英,邓西平,山仑.水分亏缺下作物补偿效应类型及机制研究概述[J].应用生态学报,2004,15(3):523-526.
[7]米慧聪,谢双泽,李跃,等.水分亏缺对小麦灌浆中后期穗部光合特性和14C-同化物转运的影响[J].作物学报,2017,43(1):149-154.
[8]王毅.干旱胁迫对作物影响研究概况[J].现代农业,2015(4):28-29.
[9]祁有玲,张富仓,李开峰.水分亏缺和施氮对冬小麦生长及氮素吸收的影响[J].应用生态学报,2009,20(10):2399-2405.
[10]赵叶萌.基于产量响应的冬小麦水分亏缺诊断指标及其阈值研究[D].北京:中国农业科学院,2016.
[11]HASSANLI A M,AHMADIRAD S,BEECHAM S.Evaluation of the influence of irrigation methods and water quality on sugar beet yield and water use efficiency[J].Agr Water Manage,2010,97(2):357-362.
[12]DONG B D,SHI L,SHI C H,et al.Grain yield and water use efficiency of two types of winter wheat cultivars under different water regimes[J].Agr Water Manage,2011,99(1):103-110.
[13]ILBEYI A,USTUN H,OWEIS T,et al.Wheat water productivity and yield in a cool highland environment:Effect of early sowing with supplemental irrigation[J].Agr Water Manage,2006,82(3):399-410.
[14]LóPEZ-URREA R,MONTORO A,GONZáLEZ-PIQUERAS J,et al.Water use of spring wheat to raise water productivity[J].Agr Water Manage,2009,96(9):1305-1310.
[15]薛利红,罗卫红,曹卫星,等.作物水分和氮素光谱诊断研究进展[J].遥感学报,2003,7(1):73-80.
[16]贾雯晴.基于高光谱的小麦水分状况监测研究[D].南京:南京农业大学,2013.
[17]DEFRIES R S,TOWNSHEND J R G.NDVI-derived land cover classifications at a global scale[J].Int J Remote Sens,1994,15(17):3567-3586.
[18]MCFEETERS S K.The use of the Normalized Difference Water Index(NDWI)in the delineation of open water features[J].Int J Remote Sens,1996,17(7):1425-1432.
[19]PE?UELAS J,FILELLA I,BIEL C,et al.The reflectance at the 950-970 nm region as an indicator of plant water status[J].Int J Remote Sens,1993,14(10):1887-1905.
[20]王强.高光谱数据进行混合像元分解研究[D].哈尔滨:东北林业大学,2006.
[21]邓兵,杨武年,慕楠,等.基于光谱分析与角度斜率指数的植被含水量研究[J].光谱学与光谱分析,2016,36(8):2546-2552.
[22]SEELIG H D,HOEHN A,STODIECK L S,et al.The assessment of leaf water content using leaf reflectance ratios in the visible,near-,and short-wave-infrared[J].Int J Remote Sens,2008,29(13):3701-3713.
[23]JONES H G.Remote detection of crop water"stress"and distinguishing it from other stresses[C]//XXVIII International Horticultural Congress on Science and Horticulture for People(IHC2010):International Symposium on CLIMWATER 2010:Horticultural Use of Water in a Changing Climate,2010.
[24]邓孺孺,何颖清,秦雁,等.近红外波段(900:2500nm)水吸收系数测量[J].遥感学报,2012,16(1):192-206.
[25]THOMAS J R,NAMKEN L N,OERTHER G F,et al.Estimating leaf water content by reflectance measurements1[J].Agron J,1971,63(6):845-847.
[26]JONES C L,WECKLER P R,MANESS N O,et al.Estimating water stress in plants using hyperspectral sensing[C]//2004 ASAE Annual Meeting.American Society of Agricultural and Biological Engineers,Ottawa,2004.
[27]王纪华,赵春江,郭晓维,等.用光谱反射率诊断小麦叶片水分状况的研究[J].中国农业科学,2001,34(1):104-107.
[28]DISNEY M,LEWIS P,SAICH P.3D modelling of forest canopy structure for remote sensing simulations in the optical and microwave domains[J].Remote Sens Environ,2006,100(1):114-132.
[29]申广荣,王人潮.基于神经网络的水稻双向反射模型研究[J].遥感学报,2002,6(4):252-258.
[30]STRAHLER A H.Vegetation canopy reflectance modeling:recent developments and remote sensing perspectives[J].Remote Sens Rev,1997,15(1/2/3/4):179-194.
[31]COMAR A,BARET F,VIéNOT F,et al.Wheat leaf bidirectional reflectance measurements:Description and quantification of the volume,specular and hot-spot scattering features[J].Remote Sens Environ,2012,121(2):26-35.
[32]肖春华,李少昆,王克如,等.叶片垂直分布对小麦冠层方向光谱响应研究[J].中国农业科学,2008,41(8):2271-2278.
[33]李莉.高光谱和多角度遥感提取植被冠层水分信息研究[D].北京:中国气象科学研究院,2008.
[34]MBOW C.Proposition of a method for early fires planning using ground and satellite(NDVI/NOAA-AVHRR)data from Niokolo Koba National Park(Southeast Senegal)[C]//Proceedings of the Second International Symposium on Operationalization of Remote Sensing,Enschede,1999.
[35]丁丽霞,王志辉,葛宏立.基于包络线法的不同树种叶片高光谱特征分析[J].浙江林学院学报,2010,27(6):809-814.
[36]BACH H,MAUSER W.Modelling and model verification of the spectral reflectance of soils under varying moisture conditions[C]//Proceedings of IGARSS'94-1994 IEEEInternational Geoscience and Remote Sensing Symposium.Pasadena,1994.
[37]刘斌.基于敏感波段筛选的多源遥感数据作物生物量估算研究[D].北京:中国农业科学院,2016.
[38]YAMAMOTO H,MIURA T,TSUCHIDA S.Advanced Spaceborne Thermal Emission and Reflection Radometer(ASTER)Enhanced Vegetation Index(EVI)products from Global Earth Observation(GEO)Grid:An assessment using Moderate Resolution Imaging Spectroradiometer(MODIS)for synergistic applications[J].Remote Sens,2012,4(8):2277-2293.
[39]郭超凡,郭逍宇.基于可见光波段包络线去除的湿地植物叶片叶绿素估算[J].生态学报,2016,36(20):6538-6546.
[40]CARTER G A.Primary and secondary effects of water content on the spectral reflectance of leaves[J].Am J Bot,1991,78(7):916-924.
[41]王纪华,赵春江,郭晓维,等.用光谱反射率诊断小麦叶片水分状况的研究[J].中国农业科学,2001,34(1):104-107.
[42]HUNTJR E,ROCK B.Detection of changes in leaf water content using Near-and Middle-Infrared reflectances[J].Remote Sens Environ,1989,30(1):43-54.
[43]CURCIO J A,PETTY C C.The near infrared absorption spectrum of liquid water[J].J Opt Soc Am A,1951,41(5):302-304.
[2]李合生.现代植物生理学[M].3版.北京:高等教育出版社,2012.
[3]雷艳,张富仓,寇雯萍,等.不同生育期水分亏缺和施氮对冬小麦产量及水分利用效率的影响[J].西北农林科技大学学报(自然科学版),2010,38(5):167-174.
[4]魏永霞,马瑛瑛,冯鼎瑞,等.调亏灌溉下滴灌玉米根冠生长与水分动态响应特征[J].农业机械学报,2017,48(7):180-188.
[5]李东晓,王红光,张迪,等.水分亏缺对不同小麦品种矿质元素吸收分布及水分利用的影响[J].中国生态农业学报,2017,25(10):1475-1484.
[6]赵丽英,邓西平,山仑.水分亏缺下作物补偿效应类型及机制研究概述[J].应用生态学报,2004,15(3):523-526.
[7]米慧聪,谢双泽,李跃,等.水分亏缺对小麦灌浆中后期穗部光合特性和14C-同化物转运的影响[J].作物学报,2017,43(1):149-154.
[8]王毅.干旱胁迫对作物影响研究概况[J].现代农业,2015(4):28-29.
[9]祁有玲,张富仓,李开峰.水分亏缺和施氮对冬小麦生长及氮素吸收的影响[J].应用生态学报,2009,20(10):2399-2405.
[10]赵叶萌.基于产量响应的冬小麦水分亏缺诊断指标及其阈值研究[D].北京:中国农业科学院,2016.
[11]HASSANLI A M,AHMADIRAD S,BEECHAM S.Evaluation of the influence of irrigation methods and water quality on sugar beet yield and water use efficiency[J].Agr Water Manage,2010,97(2):357-362.
[12]DONG B D,SHI L,SHI C H,et al.Grain yield and water use efficiency of two types of winter wheat cultivars under different water regimes[J].Agr Water Manage,2011,99(1):103-110.
[13]ILBEYI A,USTUN H,OWEIS T,et al.Wheat water productivity and yield in a cool highland environment:Effect of early sowing with supplemental irrigation[J].Agr Water Manage,2006,82(3):399-410.
[14]LóPEZ-URREA R,MONTORO A,GONZáLEZ-PIQUERAS J,et al.Water use of spring wheat to raise water productivity[J].Agr Water Manage,2009,96(9):1305-1310.
[15]薛利红,罗卫红,曹卫星,等.作物水分和氮素光谱诊断研究进展[J].遥感学报,2003,7(1):73-80.
[16]贾雯晴.基于高光谱的小麦水分状况监测研究[D].南京:南京农业大学,2013.
[17]DEFRIES R S,TOWNSHEND J R G.NDVI-derived land cover classifications at a global scale[J].Int J Remote Sens,1994,15(17):3567-3586.
[18]MCFEETERS S K.The use of the Normalized Difference Water Index(NDWI)in the delineation of open water features[J].Int J Remote Sens,1996,17(7):1425-1432.
[19]PE?UELAS J,FILELLA I,BIEL C,et al.The reflectance at the 950-970 nm region as an indicator of plant water status[J].Int J Remote Sens,1993,14(10):1887-1905.
[20]王强.高光谱数据进行混合像元分解研究[D].哈尔滨:东北林业大学,2006.
[21]邓兵,杨武年,慕楠,等.基于光谱分析与角度斜率指数的植被含水量研究[J].光谱学与光谱分析,2016,36(8):2546-2552.
[22]SEELIG H D,HOEHN A,STODIECK L S,et al.The assessment of leaf water content using leaf reflectance ratios in the visible,near-,and short-wave-infrared[J].Int J Remote Sens,2008,29(13):3701-3713.
[23]JONES H G.Remote detection of crop water"stress"and distinguishing it from other stresses[C]//XXVIII International Horticultural Congress on Science and Horticulture for People(IHC2010):International Symposium on CLIMWATER 2010:Horticultural Use of Water in a Changing Climate,2010.
[24]邓孺孺,何颖清,秦雁,等.近红外波段(900:2500nm)水吸收系数测量[J].遥感学报,2012,16(1):192-206.
[25]THOMAS J R,NAMKEN L N,OERTHER G F,et al.Estimating leaf water content by reflectance measurements1[J].Agron J,1971,63(6):845-847.
[26]JONES C L,WECKLER P R,MANESS N O,et al.Estimating water stress in plants using hyperspectral sensing[C]//2004 ASAE Annual Meeting.American Society of Agricultural and Biological Engineers,Ottawa,2004.
[27]王纪华,赵春江,郭晓维,等.用光谱反射率诊断小麦叶片水分状况的研究[J].中国农业科学,2001,34(1):104-107.
[28]DISNEY M,LEWIS P,SAICH P.3D modelling of forest canopy structure for remote sensing simulations in the optical and microwave domains[J].Remote Sens Environ,2006,100(1):114-132.
[29]申广荣,王人潮.基于神经网络的水稻双向反射模型研究[J].遥感学报,2002,6(4):252-258.
[30]STRAHLER A H.Vegetation canopy reflectance modeling:recent developments and remote sensing perspectives[J].Remote Sens Rev,1997,15(1/2/3/4):179-194.
[31]COMAR A,BARET F,VIéNOT F,et al.Wheat leaf bidirectional reflectance measurements:Description and quantification of the volume,specular and hot-spot scattering features[J].Remote Sens Environ,2012,121(2):26-35.
[32]肖春华,李少昆,王克如,等.叶片垂直分布对小麦冠层方向光谱响应研究[J].中国农业科学,2008,41(8):2271-2278.
[33]李莉.高光谱和多角度遥感提取植被冠层水分信息研究[D].北京:中国气象科学研究院,2008.
[34]MBOW C.Proposition of a method for early fires planning using ground and satellite(NDVI/NOAA-AVHRR)data from Niokolo Koba National Park(Southeast Senegal)[C]//Proceedings of the Second International Symposium on Operationalization of Remote Sensing,Enschede,1999.
[35]丁丽霞,王志辉,葛宏立.基于包络线法的不同树种叶片高光谱特征分析[J].浙江林学院学报,2010,27(6):809-814.
[36]BACH H,MAUSER W.Modelling and model verification of the spectral reflectance of soils under varying moisture conditions[C]//Proceedings of IGARSS'94-1994 IEEEInternational Geoscience and Remote Sensing Symposium.Pasadena,1994.
[37]刘斌.基于敏感波段筛选的多源遥感数据作物生物量估算研究[D].北京:中国农业科学院,2016.
[38]YAMAMOTO H,MIURA T,TSUCHIDA S.Advanced Spaceborne Thermal Emission and Reflection Radometer(ASTER)Enhanced Vegetation Index(EVI)products from Global Earth Observation(GEO)Grid:An assessment using Moderate Resolution Imaging Spectroradiometer(MODIS)for synergistic applications[J].Remote Sens,2012,4(8):2277-2293.
[39]郭超凡,郭逍宇.基于可见光波段包络线去除的湿地植物叶片叶绿素估算[J].生态学报,2016,36(20):6538-6546.
[40]CARTER G A.Primary and secondary effects of water content on the spectral reflectance of leaves[J].Am J Bot,1991,78(7):916-924.
[41]王纪华,赵春江,郭晓维,等.用光谱反射率诊断小麦叶片水分状况的研究[J].中国农业科学,2001,34(1):104-107.
[42]HUNTJR E,ROCK B.Detection of changes in leaf water content using Near-and Middle-Infrared reflectances[J].Remote Sens Environ,1989,30(1):43-54.
[43]CURCIO J A,PETTY C C.The near infrared absorption spectrum of liquid water[J].J Opt Soc Am A,1951,41(5):302-304.
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