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

文献类型： 外文期刊

第一作者： Zhang, Wangfei

作者： Zhang, Wangfei;Li, Zengyuan;Chen, Erxue;Zhao, Lei;Zhang, Wangfei;Zhang, Yahong;Ji, Yongjie;Yang, Hao

作者机构：

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

期刊名称：REMOTE SENSING （ 影响因子：4.848； 五年影响因子：5.353 ）

ISSN： 2072-4292

年卷期： 2017 年 9 卷 6 期

页码：

收录情况： SCI

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.

分类号：

  • 相关文献

[1]Agricultural crop harvest progress monitoring by fully polarimetric synthetic aperture radar imagery. Yang, Hao,Zhao, Chunjiang,Yang, Guijun,Yuan, Lin,Yang, Xiaodong,Xu, Xingang,Yang, Hao,Li, Zengyuan,Chen, Erxue. 2015

[2]Temporal Polarimetric Behavior of Oilseed Rape (Brassica napus L.) at C-Band for Early Season Sowing Date Monitoring. Yang, Hao,Li, Zengyuan,Chen, Erxue,Feng, Qi,Yang, Hao,Zhao, Chunjiang,Yang, Guijun,Casa, Raffaele,Pignatti, Stefano. 2014

[3]Potential of Fully Polarimetric SAR Data for Crops Biophysical Parameters Retrieval. Yang, Hao,Yang, Xiaodong,Xu, Xingang,Gao, Zhongling,Li, Cunjun,Wang, Jihua,Zhao, Chunjiang. 2012

[4]Mapping Plastic-Mulched Farmland with C-Band Full Polarization SAR Remote Sensing Data. Hasituya,Li, Fei,Hongmei,Hasituya,Li, Fei,Hongmei,Hasituya,Li, Fei,Hongmei,Chen, Zhongxin,Chen, Zhongxin. 2017

[5]RESEARCHES OF OPTIMUM LEAF AREA INDEX DYNAMIC MODELS FOR RAPE(BRASSICA NAPUS L.). Cao, Hongxin,Jin, Zhiqing,Zhu, Dawei,Wei, Xiufang,Li, Guangming,Zhang, Baojun,Zhang, Baojun,Zhao, Suolao,Wang, Baoqing,Zhu, Dawei. 2009

[6]Investigations into the Effects of Microcystin-LR on the Growth and Antioxidant Enzymes in Chinese cabbage and Rape. Xue Yanfeng, I,Li Youqin, II,Shi Zhiqi,Yi Neng, III. 2010

[7]Effects of temperature and rainfall on date of release of ascospores of Leptosphaeria maculans (phoma stem canker) from winter oilseed rape (Brassica napus) debris in the UK. Huang, Y. J.,Liu, Z.,West, J. S.,Todd, A. D.,Hall, A. M.,Fitt, B. D. L..

[8]A comparison of methods for drying seeds: vacuum freeze-drier versus silica gel. Hu, XR,Zhang, YL,Hu, CL,Tao, M,Chen, SP. 1998

[9]Determination of Multiresidues in Rapeseed, Rapeseed Oil, and Rapeseed Meal by Acetonitrile Extraction, Low-Temperature Cleanup, and Detection by Liquid Chromatography with Tandem Mass Spectrometry. Jiang, Yaping,Li, Yanjie,Jiang, Yuting,Pan, Canping,Li, Jianguo.

[10]Allelopathic effects of Conyza canadesis the germination and growth of wheat, sorghum, cucumber, rape and radish. Gao, Xingxiang,Li, Mei,Gao, Zongyun,Zhang, Hongjun,Sun, Zuowen.

[11]Estimation and Mapping of Winter Oilseed Rape LAI from High Spatial Resolution Satellite Data Based on a Hybrid Method. Wei, Chuanwen,Huang, Jingfeng,Mansaray, Lamin R.,Liu, Weiwei,Han, Jiahui,Wei, Chuanwen,Huang, Jingfeng,Mansaray, Lamin R.,Liu, Weiwei,Han, Jiahui,Mansaray, Lamin R.,Li, Zhenhai. 2017

[12]Mapping regional cropping patterns by using GF-1 WFV sensor data. Song Qian,Zhou Qing-bo,Wu Wen-bin,Hu Qiong,Lu Miao,Liu Shu-bin. 2017

[13]Deciphering the Routes of invasion of Drosophila suzukii by Means of ABC Random Forest. Fraimout, Antoine,Debat, Vincent,Fellous, Simon,Hufbauer, Ruth A.,Foucaud, Julien,Loiseau, Anne,Estoup, Arnaud,Hufbauer, Ruth A.,Pudlo, Pierre,Marin, Jean-Michel,Price, Donald K.,Cattel, Julien,Chen, Xiao,Depra, Marindia,Duyck, Pierre Francois,Guedot, Christelle,Kenis, Marc,Kimura, Masahito T.,Loeb, Gregory,Martinez-Sanudo, Isabel,Pascual, Marta,Richmond, Maxi Polihronakis,Shearer, Peter,Singh, Nadia,Tamura, Koichiro,Zhang, Jinping.

[14]Prediction of soil organic carbon in an intensively managed reclamation zone of eastern China: A comparison of multiple linear regressions and the random forest model. Zhang, Huan,Wu, Pengbao,Yang, Xiaohui,Gao, Chao,Yin, Aijing,Zhang, Ming.

[15]In-Season Crop Mapping with GF-1/WFV Data by Combining Object-Based Image Analysis and Random Forest. Song, Qian,Hu, Qiong,Zhou, Qingbo,Xiang, Mingtao,Tang, Huajun,Wu, Wenbin,Hovis, Ciara. 2017

[16]Land use and land cover change in Inner Mongolia - understanding the effects of China's re-vegetation programs. Yin, He,Pflugmacher, Dirk,Hostert, Patrick,Li, Ang,Li, Zhengguo,Hostert, Patrick. 2018

[17]Identification and apportionment of the drivers of land use change on a regional scale: Unbiased recursive partitioning-based stochastic model application. Wang, Qi,Ren, Qingfu,Ren, Qingfu,Liu, Jianfeng.

[18]Characterizing and modeling regional-scale variations in soil salinity in the arid oasis of Tarim Basin, China. Ma, Ligang,Yang, Shengtian,Feng, Juan,Ding, Jianli,Ma, Ligang,Yang, Shengtian,Feng, Juan,Ding, Jianli,Ma, Fenglan,Li, Jiadan,Gu, Qing,Wu, Di.

[19]Interpreting RADARSAT-2 Quad-Polarization SAR Signatures From Rice Paddy Based on Experiments. Yang, Shenbin,Zhao, Xiaoyan,Hua, Guoqiang,Li, Bingbai. 2012

[20]Wheat lodging monitoring using polarimetric index from RADARSAT-2 data. Yang, Hao,Chen, Erxue,Li, Zengyuan,Zhao, Lei,Yang, Hao,Zhao, Chunjiang,Yang, Guijun,Pignatti, Stefano,Casa, Raffaele. 2015

作者其他论文 更多>>

微信小程序