中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Rice Biomass Estimation Using Radar Backscattering Data at S-band

文献类型:期刊论文

作者Jia, Mingquan1; Tong, Ling1; Zhang, Yuanzhi2; Chen, Yan1
刊名IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
出版日期2014-02-01
卷号7期号:2页码:469-479
关键词Backscattering coefficients growth model ground-based radar scatterometer neural network rice biomass scatter model
英文摘要This paper presents an inversion method based on neural networks (NN) to estimate rice biomass in a paddy rice field with fully polarimetric (HH, HV, VH, VV) measurements at S-band. The backscattering coefficients are measured by a ground-based scatterometer system during the rice growth period from May to September 2010. The rice growth parameters including biomass, leaf-area index (LAI) and canopy structure are collected by random sampling at the same time. Data analyses show that the multi-temporal backscattering coefficients are very sensitive to the changes of biomass, LAI, canopy height and stem density. We also find that multi-temporal observations are suitable for paddy detection in the early growth period, and co-polarimetric observations perform well for monitoring rice status in the late growth period. According to the field measurements, a rice growth model was established as the function of rice age. The model made the parameters more representative and universal than limited random measurements over a given rice field. The scatter model of rice fields was simulated based on Monte Carlo simulations. The input parameters in the scatter model were generated by the rice growth model. The simulation results of the scatter model were composed as the NN training dataset, which was used for training and accessing the NN inversion algorithm. Two NN models, a simple training model (STM) and a related training model (RTM), were applied to estimate rice biomass. The obtained results show that the root mean square error (RMSE = 0.816 Kg/m(2)) of the RTM is better than that of the STM (RMSE = 1.226 kg/m(2)). The results suggest that the inversion model is able to estimate rice biomass with radar backscattering coefficients at S-band.
收录类别SCI
语种英语
WOS记录号WOS:000331457400009
源URL[http://ir.bao.ac.cn/handle/114a11/6495]  
专题国家天文台_月球与深空探测研究部
作者单位1.Univ Elect Sci & Technol China, Sch Automat, Chengdu 611731, Peoples R China
2.Chinese Acad Sci, Natl Astron Observ, Beijing 100012, Peoples R China
推荐引用方式
GB/T 7714
Jia, Mingquan,Tong, Ling,Zhang, Yuanzhi,et al. Rice Biomass Estimation Using Radar Backscattering Data at S-band[J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,2014,7(2):469-479.
APA Jia, Mingquan,Tong, Ling,Zhang, Yuanzhi,&Chen, Yan.(2014).Rice Biomass Estimation Using Radar Backscattering Data at S-band.IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,7(2),469-479.
MLA Jia, Mingquan,et al."Rice Biomass Estimation Using Radar Backscattering Data at S-band".IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 7.2(2014):469-479.

入库方式: OAI收割

来源:国家天文台

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