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Estimation of Crop Biomass Using GF-3 Polarization SAR Data Based on Genetic Algorithm Feature Selection 被引量:5

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摘要 In recent years,Polarization SAR(PolSAR)has been widely used in the filed of crop biomass estimation.However,high dimensional features extracted from PolSAR data will lead to information redundancy which will result in low accuracy and poor transfer ability of the estimation model.Aiming at this problem,we proposed a estimation method of crop biomass based on automatic feature selection method using genetic algorithm(GA).Firstly,the backscattering coefficient,the polarization parameters and texture features were extracted from PolSAR data.Then,these features were automatically pre-selected by GA to obtain the optimal feature subset.Finally,based on this subset,a support vector regression machine(SVR)model was applied to estimate crop biomass.The proposed method was validated using the GaoFen-3(GF-3)QPSΙ(C-band,quad-polarization)SAR data.Based on wheat and rape biomass samples acquired from a synchronous field measurement campaign,the proposed method achieve relative high validation accuracy(over 80%)in both crop types.For further analyzing the improvement of proposed method,validation accuracies of biomass estimation models based on several different feature selection methods were compared.Compared with feature selection based on linear correlation,GA method has increased by 5.77%in wheat biomass estimation and 11.84%in rape biomass estimation.Compared with the method of recursive feature elimination(RFE)selection,the proposed method has improved crops biomass estimation accuracy by 3.90%and 5.21%,respectively.
出处 《Journal of Geodesy and Geoinformation Science》 2020年第4期126-136,共11页 测绘学报(英文版)
基金 National Key R&D Program of China(No.2017YFB0502700) Project of The Technique of Accurate Surface Parameters Inversion Using GF-3 Images(No.03-Y20A11-9001-15/16) National Natural Science Foundation of China(No.41801289)。
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  • 1Thorp K R, Wang G, West A L, et al. Estimating crop bio- physical properties from remote sensing data by inverting linked radiative transfer and ecophysiological models[J]. Re- mote Sensing of Environment, 2012,124 : 224-233.
  • 2Attema E P W, Ulaby F T. Vegetation modeled as a water cloud [J]. Radio Science ,1978,13(2) :357-364.
  • 3Ulaby F T, Allen C T, Eger G, et al. Relating the microwave backscattering coefficient to leaf area index [J]. Remote Sens- ing of Environment, 1984,14 (1) : 113-133.
  • 4Prevot L,Charapion I,Guyot G. Estimating surface soil mois- ture and leaf area index of a wheat canopy using a dual-fre- quency (C and X bands) scatter meter [J]. Remote Sensing of Environment,1993,46(3) :331-339.
  • 5Taconet O,Vidal-Madjar D,Erablanch C,etal. Taking into ac- count vegetation effects to estimate soil moisture from C-band radar measureraents [J]. Remote Sensing of Environment, 1996,56(1) :52 -56.
  • 6Champion I, Prevot L, Guyot G. Generalized semi-empirical modeling of wheat radar response [J]. International Journal of Remote Sensing, 2000,21 (9) : 1945-1951.
  • 7Inoue Y, Kurosu T, Maeno H, et al. Season-long daily meas- urements of multifrequency (Ka, Ku, X, C, and L) and full- polarization backscatter signatures over paddy rice field and their relationship with biological variables[J]. Remote Sens- ing of Environment, 2002,81 (2) : 194-204.
  • 8Svoray T, Shoshany M. SAR-based estimation of areal aboveground biomass (AAB) of herbaceous vegetation in the semi-arid zone: a modification of the water-cloud model [J]. International Journal of Remote Sensing, 2002, 23 ( 19 ) :4089-4100.
  • 9Svoray T,Shoshany M. Herbaceous biomass retrieval in hab- itats of complex composition: A model merging SAR images with unmixed Landsat TM data EJ]. IEEE Transactions on Geoscience and Remote Sensing, 2003,41 (7) : 1592-1601.
  • 10Beriaux E, Lucau-Danila C, Auquiere E, et al. Multiyear inde- pendent validation of the water cloud model for retrieving maize leaf area index from SAR time series [J]. International Journal of Remote Sensing ,2013,34(12) :4156-4181.

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