遥感定量反演华北平原地区冬小麦含水量
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摘要
针对现有植被水分反演算法在华北平原地区适用性差、反演精度低、不能实施有效监测的问题,该文基于地面实测冬小麦植被含水量(VWC)数据,基于归一化型和比值型植被水分指数这两种常见的指数类型,提出调节植被水分指数以削弱土壤背景的影响,使用多个波段反射率数据反演VWC,提高拟合精度80%以上,发展适用于华北平原的农作物水分含量反演模型。拟合冬小麦植被含水量的决定系数为0.51,均方根误差为0.95(kg·m~(-2))。结果表明:调节植被水分指数能够削弱土壤背景影响,大幅度提高植被水分反演精度;同一种指数计算形式中,在水汽吸收谷内,基于更长波段反射率的植被水分指数反演精度更高;归一化型和比值型植被水分指数在反演精度方面无明显优劣,归一化型植被水分指数反演精度。
Aiming at the problem that the vegetation moisture retrieval algorithm in the North China plain has the problem of poor applicability,low precision and cannot be effectively monitored,the adjust vegetation water index that weakening soil background was proposed based on wheat moisture in-situ measurements collected in the North China plain in 2015 in this paper,and the precision of inversion was improved up to 80%.The coefficient of determination is 0.51,and the root mean square error is 0.95(kg·m~(-2)).The results showed that:1)adjusted vegetation water index could weaken the influence of soil background and improve the precision of vegetation water inversion;2)for a fixed spatial resolution and indices with same form,the longer wavelength remote sensing data were used,the better reversion performance would be achieved;3)normalized difference type water indexes showed a slight superiority to ratio type water indexes.
Aiming at the problem that the vegetation moisture retrieval algorithm in the North China plain has the problem of poor applicability,low precision and cannot be effectively monitored,the adjust vegetation water index that weakening soil background was proposed based on wheat moisture in-situ measurements collected in the North China plain in 2015 in this paper,and the precision of inversion was improved up to 80%.The coefficient of determination is 0.51,and the root mean square error is 0.95(kg·m~(-2)).The results showed that:1)adjusted vegetation water index could weaken the influence of soil background and improve the precision of vegetation water inversion;2)for a fixed spatial resolution and indices with same form,the longer wavelength remote sensing data were used,the better reversion performance would be achieved;3)normalized difference type water indexes showed a slight superiority to ratio type water indexes.
引文
[1]HUANG J,CHEN D,COSH M H.Sub-pixel reflectance unmixing in estimating vegetation water content and dry biomass of corn and soybeans cropland using normalized difference water index(NDWI)from satellites[J].International Journal of Remote Sensing,2009,30(8):2075-2104.
[2]王丽涛,王世新,周艺,等.基于多光谱数据的植被水分反演及其在旱情评估中的应用分析[J].光谱学与光谱分析,2011(10):2804-2808.(WANG Litao,WANG Shixin,ZHOU Yi,et al.Vegetation moisture inversion based on multi-spectral data and its application in drought assessment[J].Spectroscopy and Spectral Analysis,2011(10):2804-2808.)
[3]DANSON F M,BOWYER P.Estimating live fuel moisture content from remotely sensed reflectance[J].Remote Sensing of Environment,2004,92(3):309-321.
[4]CARTER G A.Primary and secondary effects of water content on the spectral reflectance of leaves[J].American Journal of Botany,1991,78(7):916-924.
[5]GAUSMAN H W,ALLEN W A.Optical parameters of leaves of 30plant species[J].Plant Physiology,1973,52(1):57-62.
[6]CECCATO P,GOBRON N,FLASSE S,et al.Designing a spectral index to estimate vegetation water content from remote sensing data:part 1:theoretical approach[J].Remote Sensing of Environment,2002,82(2/3):188-197.
[7]GAO B C.NDWI-A normalized difference water index for remote sensing of vegetation liquid water from space[C]∥Imaging Spectrometry.International Society for Optics and Photonics.[S.l.]:[s.n.],1995:225-236.
[8]ZARCO P J.Water content estimation in vegetation with MODIS reflectance data and model inversion methods[J].Remote Sensing of Environment,2003,85(1):109-124.
[9]PEUELAS J,FILELLA I,BIEL C,et al.The reflectance at the 950~970nm region as an indicator of plant water status[J].International Journal of Remote Sensing,1993,14(10):1887-1905.
[10]GAO B C.NDWI-A normalized difference water index for remote sensing of vegetation liquid water from space[J].Remote Sensing of Environment,1996,58(3):257-266.
[11]ZHANG Y J,LI J,GUO Z,et al.Simulated responses of winter wheat yield and soil moisture to different conservation tiliage practices in Weibei Highlands,Northwest China[J].Chinese Journal of Applied Ecology,2015,26(3):800.
[12]WANG L,QU J J.NMDI:A normalized multi-band drought index for monitoring soil and vegetation moisture with satellite remote sensing[J].Geophysical Research Letters,2007,34(20):117-131.
[13]HUETE A R.A soil-adjusted vegetation index(SA-VI)[J].Remote Sensing of Environment,1988,25(3):295-309.
[14]BARET F,GUYOT G,MAJOR D J.TSAVI:a vegetation index which minimizes soil brightness effects on lai and APAR estimation[C]∥Symposium on Geoscience&Remote Sensing Symposium.Vancover,Canada:IEEE,1989:1355.
[2]王丽涛,王世新,周艺,等.基于多光谱数据的植被水分反演及其在旱情评估中的应用分析[J].光谱学与光谱分析,2011(10):2804-2808.(WANG Litao,WANG Shixin,ZHOU Yi,et al.Vegetation moisture inversion based on multi-spectral data and its application in drought assessment[J].Spectroscopy and Spectral Analysis,2011(10):2804-2808.)
[3]DANSON F M,BOWYER P.Estimating live fuel moisture content from remotely sensed reflectance[J].Remote Sensing of Environment,2004,92(3):309-321.
[4]CARTER G A.Primary and secondary effects of water content on the spectral reflectance of leaves[J].American Journal of Botany,1991,78(7):916-924.
[5]GAUSMAN H W,ALLEN W A.Optical parameters of leaves of 30plant species[J].Plant Physiology,1973,52(1):57-62.
[6]CECCATO P,GOBRON N,FLASSE S,et al.Designing a spectral index to estimate vegetation water content from remote sensing data:part 1:theoretical approach[J].Remote Sensing of Environment,2002,82(2/3):188-197.
[7]GAO B C.NDWI-A normalized difference water index for remote sensing of vegetation liquid water from space[C]∥Imaging Spectrometry.International Society for Optics and Photonics.[S.l.]:[s.n.],1995:225-236.
[8]ZARCO P J.Water content estimation in vegetation with MODIS reflectance data and model inversion methods[J].Remote Sensing of Environment,2003,85(1):109-124.
[9]PEUELAS J,FILELLA I,BIEL C,et al.The reflectance at the 950~970nm region as an indicator of plant water status[J].International Journal of Remote Sensing,1993,14(10):1887-1905.
[10]GAO B C.NDWI-A normalized difference water index for remote sensing of vegetation liquid water from space[J].Remote Sensing of Environment,1996,58(3):257-266.
[11]ZHANG Y J,LI J,GUO Z,et al.Simulated responses of winter wheat yield and soil moisture to different conservation tiliage practices in Weibei Highlands,Northwest China[J].Chinese Journal of Applied Ecology,2015,26(3):800.
[12]WANG L,QU J J.NMDI:A normalized multi-band drought index for monitoring soil and vegetation moisture with satellite remote sensing[J].Geophysical Research Letters,2007,34(20):117-131.
[13]HUETE A R.A soil-adjusted vegetation index(SA-VI)[J].Remote Sensing of Environment,1988,25(3):295-309.
[14]BARET F,GUYOT G,MAJOR D J.TSAVI:a vegetation index which minimizes soil brightness effects on lai and APAR estimation[C]∥Symposium on Geoscience&Remote Sensing Symposium.Vancover,Canada:IEEE,1989:1355.