Study on northern japonica rice yield model based on canopy date of NDVI

doi:10.3969/j.issn.1004-1524.2016.10.22

›› 2016, Vol. 28 ›› Issue (10): 1790-1795.DOI: 10.3969/j.issn.1004-1524.2016.10.22

• Biosystems Engineering • Previous Articles Next Articles

Study on northern japonica rice yield model based on canopy date of NDVI

XU Tong-yu^{1, 2}, HONG Xue², CHEN Chun-ling^{1, 2, *}, ZHOU Yun-cheng^{1, 2}, CAO Ying-li^{1, 2}, YU Feng-hua², LI Na²

1. Agricultural Information Engineering Technology Center in Liaoning Province, Shenyang Agricultural University, Shenyang 110161, China;
2. College of Information and Electrical Engineering, Shenyang Agricultural University, Shenyang 110161, China

Received:2016-03-16 Online:2016-10-15 Published:2016-11-20

Abstract

Abstract: In the present study, experimental field in Shenyang Agricultural University was selected as study region, and unmanned aerial vehicle (UAV) remote sensing technology and manual analysis was combined to collect canopy NDVI data of the whole growth of japonica rice in the summer of 2015. Firstly, dual distance variable correlation analysis was applied to reveal the relationships between NDVI data of single day, ten day or each month and yield. Then, the yield and NDVI data which showed good correlations were adopted to build models via linear regression and Square or Cubic curve, and validation test of the constructed regression model and precision comparison were carried out. It was shown that it was better to build model with Square or Cubic curve than linear regress when only one variable was used. The model consisted of data collected in June 11^th to 20^th and August 1^st to 10^th was ideal to predict the yield, of which the determination coefficient (R²), relative error(RE), and root mean square error (RMSE) were 0.771, 4.06% and 0.474 t·hm^-2, respectively. It was of high precision and feasibility. Thus, it was suggested that the most suitable time for japonica rice yield prediction in Northern China was June 11^th to 20^th and August 1^st to 10^th.

Key words: japonica rice, NDVI, correlation, regression analysis

CLC Number:

S127

XU Tong-yu, HONG Xue, CHEN Chun-ling, ZHOU Yun-cheng, CAO Ying-li, YU Feng-hua, LI Na. Study on northern japonica rice yield model based on canopy date of NDVI[J]. , 2016, 28(10): 1790-1795.

References

[1] 黄敬峰, 杨忠恩, 王人潮, 等. 基于GIS的水稻遥感估产模型研究[J]. 遥感技术与应用, 2002, 17(3):125-128.
HUANG J F, YANG Z E, WANG R C, et al. The rice production forecasting models using NOAA/AVHRR data based on GIS [J]. Remote Sensing Technology and Application , 2002, 17(3): 125-128. (in Chinese with English abstract)
[2] 陈温福, 潘文博, 徐正进. 我国粳稻生产现状及发展趋势[J]. 沈阳农业大学学报, 2006, 37(6): 801-805.
CHEN W F, PAN W B, XU Z J. Current situation and trends in production of japonica rice in China [J]. Journal of Shenyang Agricultural University , 2006, 37(6): 801-805. (in Chinese with English abstract)
[3] 李卫国, 李花. 水稻卫星遥感估产研究现状与对策[J].江苏农业学报,2010 (5):444-445.
LI W G, LI H. Status and countermeasures on research of estimating rice yield by satellite remote sensing[J]. Jiangsu Agricultural Sciences , 2010 (5): 444-445. (in Chinese with English abstract)
[4] 李德仁, 李明. 无人机遥感系统的研究进展与应用前景[J].武汉大学学报(信息科学版),2014,39(5):505-513.
LI D R, LI M. Research advance and application prospect of unmanned aerial vehicle remote sensing system [J]. Geomatics and Information Science of Wuhan University , 2014, 39(5): 505-513. (in Chinese with English abstract)
[5] 刘刚, 许宏健, 马海涛, 等. 无人机航测系统在应急服务保障中的应用与前景[J]. 测绘与空间地理信息, 2011, 34(4):177-179.
LIU G, XU H J, MA H T, et al. Unmanned aerial system applications and prospects in the protection of emergency services[J]. Geomatics & Spatial Information Technology , 2011, 34(4): 177-179. (in Chinese with English abstract)
[6] MKHABELA M S, BULLOCK P, RAJ S, et al. Crop yield forecasting on the Canadian Prairies using MODIS NDVI data[J]. Agricultural & Forest Meteorology , 2011, 151(3):385-393.
[7] BECKER-RESHEF I, VERMOTE E, LINDEMAN M, et al. A generalized regression-based model for forecasting winter wheat yields in Kansas and Ukraine using MODIS data[J]. Remote Sensing of Environment , 2010, 114(6):1312-1323.
[8] GOWARD S N, TUCKER C J, DYE D G. North American vegetation patterns observed with the NOAA-7 advanced very high resolution radiometer[J]. Vegetatio , 1985, 64(1):3-14.
[9] MUÑOZ J D, FINLEY A O, GEHL R, et al. Nonlinear hierarchical models for predicting cover crop biomass using normalized difference vegetation index[J]. Remote Sensing of Environment , 2010, 114(12):2833-2840.
[10] FLYNN E S, DOUGHERTY C T, WENDROTH O. Assessment of pasture biomass with the normalized difference vegetation index from active ground-based sensors[J]. Agronomy Journal , 2008, 100(1): 114-121.
[11] KALUBARME M H, POTDAR M B, MANJUNATH K R, et al. Growth profile based crop yield models: a case study of large area wheat yield modelling and its extendibility using atmospheric corrected NOAA AVHRR data[J]. International Journal of Remote Sensing , 2003, 24(10):2037-2054.
[12] THENKABAIL P S. Biophysical and yield information for precision farming from near-real-time and historical Landsat TM images[J]. International Journal of Remote Sensing , 2003, 24(14):2879-2904.
[13] BAEZGONZALEZ A D, KINIRY J R, MAAS S J, et al. Large-area maize yield forecasting using leaf area index based yield model[J]. Agronomy Journal , 2005, 97(2):418-425.
[14] 冯美臣, 肖璐洁, 杨武德, 等. 基于遥感数据和气象数据的水旱地冬小麦产量估测[J]. 农业工程学报, 2010, 26(11):183-188.
FENG M C, XIAO L J, YANG W D, et al. Predicting grain yield of irrigation-land and dry-land winter wheat based on remote sensing data and meteorological data[J]. Journal of Agricultural Engineering , 2010, 26(11): 183-188. (in Chinese with English abstract)
[15] 曹卫彬, 刘姣娣, 赵良斌,等. 北疆棉花遥感估产最佳时相选择研究[J]. 中国棉花, 2007, 34(3):10-11.
CAO W B, LIU J D, ZHAO L B, et al. Phase selection for cotton yield estimation in Northern Xinjiang based on remote sensing[J]. China Cotton , 2007, 34(3): 10-11. (in Chinese)
[16] 李飞, 杨小平, 毛晖. 基于MODIS-NDVI数据的甘肃临夏州的春小麦遥感估产[J]. 陕西农业科学, 2014, 60(10): 74-77.
LI F, YANG X P, MAO H. Spring wheat yield estimation in Linxiazhou, Gansu based on MODIS_NDVI data by remote sensing[J]. Shaanxi Journal of Agricultural Sciences , 2014, 60(10): 74-77. (in Chinese)
[17] 高中灵, 徐新刚, 王纪华,等. 基于时间序列NDVI相似性分析的棉花估产[J]. 农业工程学报, 2012, 28(2):148-153.
GAO Z L, XU X G, WANG J H, et al. Cotton yield estimation based on similarity analysis of time-series NDVI[J]. Transactions of the Chinese Society of Agricultural Engineering , 2012, 28(2): 148-153. (in Chinese with English abstract)
[18] 陈鹏飞, 杨飞, 杜佳. 基于环境减灾卫星时序归一化植被指数的冬小麦产量估测[J]. 农业工程学报, 2013, 29(11):124-131.
CHEN P F, YANG F, DU J. Yield forecasting for winter wheat using time series NDVI from HJ satellite[J]. Transactions of the Chinese Society of Agricultural Engineering , 2013, 29(11): 124-131. (in Chinese with English abstract)
[19] 黄敬峰, 王人潮, 蒋亨显, 等. 基于GIS的浙江省水稻遥感估产最佳时相选择[J]. 应用生态学报, 2002, 13(3):290-294.
HUANG J F, WANG R C, JIANG H X, et al. Selection of optimum periods for rice estimation using remote sensing data based on GIS[J]. Chinese Journal of Applied Ecology , 2002, 13(3): 290-294. (in Chinese with English abstract)
[20] 金伟, 葛宏立, 杜华强, 等. 无人机遥感发展与应用概况[J]. 遥感信息, 2009(1):88-92.
JIN W, GE H L, DU H Q, et al. A review on unmanned aerial vehicle remote sensing and its application[J]. Remote Sensing Information , 2009(1): 88-92. (in Chinese with English abstract)
[21] 吴文斌, 杨鹏, 唐华俊,等. 基于NDVI数据的华北地区耕地物候空间格局[J]. 中国农业科学, 2009, 42(2):552-560.
WU W B, YANG P, TANG H J, et al. Monitoring spatial patterns of cropland phenology in North China based on NOAA NDVI Data[J]. Scientia Agricultura Sinica , 2009, 42(2): 552-560. (in Chinese with English abstract)
[22] 白文龙, 张福平. 基于SPOT VGT/NDVI的陕西省关中地区冬小麦遥感估产[J]. 资源开发与市场, 2012, 28(6):483-485.
BAI W L, ZHANG F P. Estimation of winter wheat yield in Guanzhong area of Shaanxi Province using SPOT VGT/NDVI[J]. Resource Development & Market , 2012, 28(6): 483-485. (in Chinese with English abstract)

Study on northern japonica rice yield model based on canopy date of NDVI

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