文献类型：期刊文献

英文题名：Compact Polarimetric Response of Rape (Brassica napus L.) at C-Band: Analysis and Growth Parameters Inversion

作者：Zhang, Wangfei[1,2] Li, Zengyuan[1] Chen, Erxue[1] Zhang, Yahong[2] Yang, Hao[3] Zhao, Lei[1] Ji, Yongjie[2]

第一作者：Zhang, Wangfei

通信作者：Chen, EX[1]

机构：[1]Chinese Acad Forestry, Inst Forest Resource Informat Tech, Beijing 100091, Peoples R China;[2]Southwest Forestry Univ, Coll Forestry, Kunming 650224, Peoples R China;[3]Beijing Acad Agr & Forestry Sci, Beijing Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China

年份：2017

卷号：9

期号：6

外文期刊名：REMOTE SENSING

收录：;WOS:【SCI-EXPANDED(收录号:WOS:000404623900082)】；

基金：This work was supported in part by the National Basic Research Program of China (Grant No. 2013CB733404), the project of The Technique of Accurate Surface Parameters Inversion Using GF-3 Images (Grant No. 03-Y20A11-9001-15/16) and National Natural Science Foundation of China (41401477). The authors would also like to thank the four anonymous referees who have helped improve the original manuscript.

语种：英文

外文关键词：compact polarimetric (CP) SAR; rape; Radarsat-2; day after sowing (DAS); random forest; Stokes parameters; polarimetric decomposition; backscatter coefficients

摘要：Growth parameters like biomass, leaf area index ( LAI) and stem height play an import role for crop monitoring and yield prediction. Compact polarimetric (CP) SAR has shown great potential and similar performance to fully-polarimetric (FP) SAR in crop mapping and phenology retrieval, but its potential in growth parameters inversion has not been fully explored. In this paper, a time series of images of CP SAR was simulated from five FP SAR data gathered during the entire growth season of rape. CP response of 27 parameters, relying on Stokes parameters and their child parameters, decomposition parameters and backscattering coefficients, were extracted and investigated as a function of days after sowing (DAS) during the whole rape growth cycle to interpret their sensitivity to each growth parameter. Then, random forest (RF) was chosen as an automatic approach for the growth parameters inversion method, and its results were compared with traditional single-parameter regression models. Most of the CP parameters showed high sensitivity with growth parameters and great potential for growth parameters inversion. Among all of the regression models, the quadratic regression model showed the best performance for all of the growth parameters inversion, the best result for biomass inversion was the third component of the Stokes parameters (g3) with R-2 of 0.765 and RMSE of 73.20 g/m(2). For LAI and stem height was one of the Stokes child parameters, the circular polarization ratio (U-c), with R-2 of 0.857 and 0.923 and RMSE of 0.66 and 18.71 cm, respectively. RF showed the highest accuracy and smallest RMSE for all of three growth parameters inversion; R-2 for biomass, LAI and stem height were 0.93, 0.96 and 0.95, respectively; RMSE were 46.24 g/m(2), 0.25 and 13.5 cm, respectively. However, there are also some CP parameters, which showed low sensitivity to growth parameters, that had high importance for RF inversion. The results confirmed the potential of CP data and the RF method in growth parameters inversion, but they also confirmed that it was difficult to give a physical interpretation for the RF inversion model.