[1] 任鑫.多极化多角度SAR土壤水分反演算法研究[D].北京: 中国科学院遥感应用研究所, 2003

Ren Xin. A Surface Moisture Inversion Teclmique Using Multi-Polarization and Multi-Angle Radar Images[D]. Beijing: Institute of Remote Sensing Application, Chinese Academy of Sciences, 2003
[2] 魏小兰, 李震, 陈权. S波段雷达数据反演土壤水分的模拟分析和验证[J].地球信息科学学报, 2008, 10(1):97-101 doi:  10.3969/j.issn.1560-8999.2008.01.016

Wei Xiaolan, Li Zhen, Chen Quan. The Simulation Analysis and Validation of Soil Moisture Retrieval Using S-band Radar[J]. Geo-information Science, 2008, 10(1):97-101 doi:  10.3969/j.issn.1560-8999.2008.01.016
[3] Bourgeau-Chavez L L, Leblon B, Charbonneau F, et al. Evaluation of Polarimetric Radarsat-2 SAR Data for Development of Soil Moisture Retrieval Algorithms over a Chronosequence of Black Spruce Boreal Forests[J]. Remote Sensing of Environment, 2013, 132(1):71-85 http://www.sciencedirect.com/science/article/pii/S0034425713000187
[4] Wiseman G, McNairn H, Homayouni S, et al. Radarsat-2 Polarimetric SAR Response to Crop Biomass for Agricultural Production Monitoring[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014, 7(11):4461-4471 doi:  10.1109/JSTARS.2014.2322311
[5] Adams J R, Berg A A, McNairn H, et al. Sensitivity of C-band SAR Polarimetric Variables to Unvegetated Agricultural Fields[J]. Canadian Journal of Remote Sensing, 2013, 39(1):1-16 doi:  10.5589/m13-003
[6] Baghdadi N, Dubois-Fernandez P, Dupuis X, et al. Sensitivity of Main Polarimetric Parameters of Multifrequency Polarimetric SAR Data to Soil Moisture and Surface Roughness over Bare Agricultural Soils[J]. IEEE Geoscience and Remote Sensing Letters, 2013, 10(4):731-735 doi:  10.1109/LGRS.2012.2220333
[7] Cloude S R, Pottier E. An Entropy Classification Scheme for Land Applications of Polarimetric SAR Data[J]. IEEE Transactions on Geoscience and Remote Sensing, 1997, 35:68-78 doi:  10.1109/36.551935
[8] Notarnicola C, Angiulli M, Posa F. Soil Moisture Retrieval from Remotely Sensed Data:Neural Network Approach Versus Bayesian Method[J]. IEEE Transactions on Geoscience and Remote Sensing, 2008, 46(2):547-557 doi:  10.1109/TGRS.2007.909951
[9] Ahmad S, Kalra A, Stephen H. Estimating Soil Moisture Using Remote Sensing Data:A Machine Learning Approach[J]. Advances in Water Resources, 2010, 33(1):69-80 doi:  10.1016/j.advwatres.2009.10.008
[10] Breiman L. Random Forest[J]. Machine Learning, 2001, 45(1):5-32 http://d.old.wanfangdata.com.cn/Periodical/nygcxb201505028
[11] Baghdadi N, Cresson R, El-Hajj M, et al. Estimation of Soil Parameters over Bare Agriculture Areas from C-band Polarimetric SAR Data Using Neural Networks[J]. Hydrology and Earth System Scien-ces, 2012, 16:1607-1621 doi:  10.5194/hess-16-1607-2012
[12] Pasolli L, Notarnicola C, Bruzzone L, et al. Polarimetric Radarsat-2 Imagery for Soil Moisture Rtrieval in Alpine Areas[J]. Canadian Journal of Remote Sensing, 2011, 37:535-547 https://www.researchgate.net/publication/258489714_Polarimetric_RADARSAT2_imagery_for_soil_moisture_retrieval_in_Alpine_areas
[13] Srivastava P K, Han D, Ramirez M R, et al. Machine Learning Techniques for Downscaling SMOS Satellite Soil Moisture Using MODIS Land Surface Temperature for Hydrological Application[J]. Water Resources Management, 2013, 27:3127-3144 doi:  10.1007/s11269-013-0337-9
[14] Karjalainen M, Kankare V, Vastaranta M, et al. Prediction of Plot-Level Forest Variables Using TerraSAR-X Stereo SAR Data[J]. Remote Sensing of Environment, 2012, 117:338-347 doi:  10.1016/j.rse.2011.10.008
[15] Baghdadi N, Cerden O, Zribi M, et al. Operational Performance of Current Synthetic Aperture Radar Sensors in Mapping Soil Surface Characteristics in Agricultural Environments:Application to Hydrological and Erosion Modelling[J]. Hydrological Processes, 2008, 22:9-20 doi:  10.1002/(ISSN)1099-1085
[16] Yang Guijun, Shi Yuechan, Zhao Chunjiang, et al. Estimation of Soil Moisture from Multi-Polarized SAR Data over Wheat Coverage Areas[C]. The First International Conference on Agro-Geoinformatics, Shanghai, China, 2012
[17] Freeman A, Durden S L. A Three-Component Scattering Model for Polarimetric SAR Data[J]. IEEE Transactions on Geoscience and Remote Sensing, 1998, 36(3):963-973 doi:  10.1109/36.673687
[18] Krogager E. A New Decomposition of the Radar Target Scattering Matrix[J]. Electronics Letter, 1990, 26(18):1525-1526 doi:  10.1049/el:19900979
[19] Srivastava P, Han D, Ramirez M R, et al. Machine Learning Techniques for Downscaling SMOS Satellite Soil Moisture Using MODIS Land Surface Temperature for Hydrological Application[J]. Water Resource Management, 2013, 27:3127-3144 doi:  10.1007/s11269-013-0337-9
[20] Shataee S, Kalbi S, Fallah A, et al. Forest Attri-bute Imputation Using Machine-Learning Methods and ASTER Data:Comparison of K-NN, SVR and Random Forest Regression Algorithms[J]. International Journal of Remote Sensing, 2012, 33:6254-6280 doi:  10.1080/01431161.2012.682661