Comparative of remote sensing estimation models of winter wheat biomass based on random forest algorithm

Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering

Volumn 32, Issue 18, 2016, Pages 175-182

  Yue, Jibo ^a,b   Yang, Guijun ^b,c,d,e   Feng, Haikuan ^b,c,d,e  

^a HENAN POLYTECHNIC UNIVERSITY   (China)

^b BEIJING RESEARCH CENTER FOR INFORMATION TECHNOLOGY IN AGRICULTURE   (China)

^c NATIONAL ENGINEERING RESEARCH CENTER FOR INFORMATION TECHNOLOGY IN AGRICULTURE   (China)

^d Key Laboratory of Urban Agriculture (North) of Ministry of Agriculture   (China)

^e Beijing Engineering Research Center of Agricultural Internet of Things   (China)

Author keywords

Biomass; Grey relational analysis; Model; Random forest algorithm; Remote sensing; Winter wheat

Indexed keywords

AGRICULTURAL MACHINERY; AGRICULTURE; ARTIFICIAL INTELLIGENCE; BACKSCATTERING; BIOMASS; CROPS; DATA FLOW ANALYSIS; DATA REDUCTION; DECISION MAKING; DECISION TREES; LEARNING ALGORITHMS; LEARNING SYSTEMS; MEAN SQUARE ERROR; MODELS; RADAR; REFLECTION; REMOTE SENSING; SYNTHETIC APERTURE RADAR; VEGETATION;

AGRICULTURE PRODUCTIONS; CORRELATION COEFFICIENT; DETERMINATION COEFFICIENTS; GREY RELATIONAL ANALYSES (GRA); GREY RELATIONAL ANALYSIS; RANDOM FOREST ALGORITHM; REMOTE SENSING ESTIMATIONS; WINTER WHEAT;

PARAMETER ESTIMATION;

EID: 84988640511     PISSN: 10026819     EISSN: None     Source Type: Journal    
DOI: 10.11975/j.issn.1002-6819.2016.18.024     Document Type: Article

References (30)

1. Wu Suxia, Feng Shuqing, Mao Renzhao, et al. The estimating model of chlorophyll relative content in leaves of winter wheat by remote sensing[J]. Agricultural Research in the Arid Areas, 2006, 24(05): 137-140. (in Chinese with English abstract)
2. Sui Xueyan, Zhu Zhenlin, Li Shaokun, et al. Extracting winter wheat planting area based on cropping system with MODIS data[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2010, 26(Supp.1): 225-229. (in Chinese with English abstract)
3. Tan Changwei, Wang Jihua, Zhao Chunjiang, et al. Monitoring wheat main growth parameters at anthesis stage by Landsat TM[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2011, 27(5): 224-230. (in Chinese with English abstract)
4. Yang Fuqin, Feng Haikuan, Li Zhenhai, et al. Hyperspectral estimation of leaf area index for winter wheat based on Akaike's information criterion[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2016, 32(3): 163-168. (in Chinese with English abstract)
5. Zhang Kai, Wang Runyuan, Wang Xiaoping, et al. Correlations between leaf area index and hyperspectral vegetation index of spring wheat on Loess Plateau[J]. Chinese Journal of Ecology, 2008, 27(10): 1692-1697. (in Chinese with English abstract)
6. Li Fenling, Wang Li, Liu Jing, et al. Remote sensing estimation of SPAD value for wheat leaf based on GF-1 Data[J]. Transactions of the Chineses Society for Agricultural Machinery, 2015, 46(9): 273-281. (in Chinese with English abstract)
7. Wu Bingfang, Zhang Feng, Liu Chenglin, et al. An integrated method for crop condition monitoring[J]. Journal of Remote Sensing, 2004, 8(6): 498-514. (in Chinese with English abstract)
8. Feng Haikuan, Yang Fuqin, Li Zhenhai, et al. Hyperspectral estimation of leaf total phosphorus content in apple tree based on optimal weights combination model[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2016, 32(7): 173-180. (in Chinese with English abstract)
9. Yang Fuqin, Feng Haikuan, Li Zhenhai, et al. Estimation of leaf area index of winter wheat based on akaike's information criterion[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2015, 46(11): 112-120. (in Chinese with English abstract)
10. Wang Beizhan, Feng Xiao, Wen Nuan, et al. Monitoring Biomass and N Accumulation at Jointing Stage in Winter Wheat Based on SPOT-5 Images[J]. Scientia Agricultura Sinica, 2012, 45(15): 3049-3057. (in Chinese with English abstract)
11. Li Weiguo, Zhao Chunjiang, Wang Jihua, et al. Monitoring the growth condition of winter wheat in jointing stage based on land sat TM image[J]. Journal of Triticeae Crops, 2007, 27(3): 523-527. (in Chinese with English abstract)
12. Breiman Leo. Random Forests[J]. Machine Learning, 2001, 45(1): 5-32.
13. Han Zhaoying, Zhu Xicun, Fang Xianyi, et al. Hyperspectral estimation of apple tree canopy LAI based on SVM and RF regression[J]. Spectroscopy and spectral analysis, 2016, 36(3): 800-805. (in Chinese with English abstract)
14. Breiman Leo. Out-of-bag estimation[R]. Citeseer, Technical Report, 1996.
15. Liu Sifeng, Cai Hua, Yang Yingjie, et al. Advanced in grey incidence analysis modeling[J]. Systems Engineering-Theory & Practice, 2013, 32(8): 2041-2046. (in Chinese with English abstract)
16. Yuan Jinguo, Niu Zheng, Wang Xiping. Atmospheric correction of hyperion hyperspectral image based on FLAASH[J]. Spectroscopy & Spectral Analysis, 2009, 29(5): 1181-1185. (in Chinese with English abstract)
17. Lee Jong Sen, Pottier Eric. Polarimetric Radar Imaging: From Basics to Applications[M]. BocaRaton: CRC Press, 2009.
18. Kim Yunjin, van Zyl Jakob J. A time-series approach to estimate soil moisture using polarimetric radar data[J]. Ieee Transactions on Geoscience and Remote Sensing, 2009, 47(8): 2519-2527.
19. Jin Xiuliang, Yang Guijun, Xu Xingang, et al. Combined multi-temporal optical and radar parameters for estimating LAI and biomass in winter wheat using HJ and RADARSAR-2 Data[J]. Remote Sensing, 2015, 7(10): 13251-13272.
20. Rouse J W, Haas R H, Schell J A, et al. Monitoring the vernal advancement of retrogradation (green wave effect) of natural vegetation[R]. Greenbelt: NASA/GSFC, Type III, Final Report, 1974.
21. Pearson R L, Miller L D. Remote mapping of standing crop biomass for estimation of the productivity of the shortgrass prairie[J]. International Journal of Powder Metallurgy, 2012, 48(6): 7-18.
22. Huete A. A soil-adjusted vegetation index (SAVI)[J]. Remote Sensing of Environment, 1988, 25(3): 295-309.
23. Rondeaux G, Baret F, Steven M. Optimization of soil-adjusted vegetation indices[J]. Remote Sensing of Environment, 1996, 55(2): 95-107.
24. Liu Hui Qing, Huete A. A feedback based modification of the NDVI to minimize canopy background and atmospheric noise[J]. IEEE Transactions on Geoscience & Remote Sensing, 1995, 33(2): 457-465.
25. Haboudane D, Miller J R, Pattey E, et al. Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture[J]. Remote Sensing of Environment, 2004, 90(3): 337-352.
26. Fang Kuangnan, Wu Jianbin, Zhu Jianping, et al. A review of technologies on random forests[J]. Statistics & Information Forum, 2011, 26(3): 32-38. (in Chinese with English abstract)
27. Tibshirani Robert. Bias, variance and prediction error for classification rules[R]. Citeseer, Technical Report, 1996.
28. Mao Xuesen, Zhang Yongqiang, Shen Yanjun. Effects of water stress in different stages on winter wheat vegetation index and NDVI's dynamic[J]. Agricultural Reseach in the Arid Areas, 2002, 20(1): 69-71. (in Chinese with English abstract)
29. Cheng Xiaojuan, Xu Xingang, Chen Tianen, et al. The new method monitoring crop water content Based on NIR-Red spectrum feature space[J]. Spectroscopy & Spectral Analysis, 2014, 34(6): 1542-1547. (in Chinese with English abstract)
30. Gao Shuai, Niu Zheng, Huang Ni, et al. Estimating the leaf area index, height and biomass of maize using HJ-1 and RADARSAT-2[J]. International Journal of Applied Earth Observation and Geoinformation, 2013, 24(1): 1-8.