Regional yield estimation for winter wheat with MODIS-NDVI data in Shandong, China

文献类型： 外文期刊

第一作者： Ren, Jianqiang

作者： Ren, Jianqiang;Chen, Zhongxin;Zhou, Qingbo;Tang, Huajun;Ren, Jianqiang;Chen, Zhongxin;Zhou, Qingbo;Tang, Huajun

作者机构：

关键词： Remote sensing;Regional yield estimation;Winter wheat;MODIS;NDVI;China

期刊名称：INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION （ 影响因子：5.933； 五年影响因子：6.225 ）

ISSN： 0303-2434

年卷期： 2008 年 10 卷 4 期

页码：

收录情况： SCI

摘要： The significance of crop yield estimation is well known in agricultural management and policy development at regional and national levels. The primary objective of this study was to test the suitability of the method, depending on predicted crop production, to estimate crop yield with a MODIS-NDVI-based model on a regional scale. In this paper, MODIS-NDVI data, with a 250 m resolution, was used to estimate the winter wheat (Triticum aestivum L.) yield in one of the main winter-wheat-growing regions. Our study region is located in Jining, Shandong Province. In order to improve the quality of remote sensing data and the accuracy of yield prediction, especially to eliminate the cloud-contaminated data and abnormal data in the MODIS-NDVI series, the Savitzky-Golay filter was applied to smooth the 10-day NDVI data. The spatial accumulation of NDVI at the county level was used to test its relationship with winter wheat production in the study area. A linear regressive relationship between the spatial accumulation of NDVI and the production of winter wheat was established using a stepwise regression method. The average yield was derived from predicted production divided by the growing acreage of winter wheat on a county level. Finally, the results were validated by the ground survey data, and the errors were compared with the errors of agro-climate models. The results showed that the relative errors of the predicted yield using MODIS-NDVI are between -4.62% and 5.40% and that whole RMSE was 214.16 kg ha(-1) lower than the RMSE (233.35 kg ha(-1)) of agro-climate models in this study region. A good predicted yield data of winter wheat could be got about 40 days ahead of harvest time, i.e. at the booting-heading stage of winter wheat. The method suggested in this paper was good for predicting regional winter wheat production and yield estimation. (C) 2007 Elsevier B.V. All rights reserved.

分类号：

  • 相关文献

[1]EXTRACTING SPATIAL INFORMATION OF HARVEST INDEX FOR WINTER WHEAT BASED ON MODIS NDVI IN NORTH CHINA. Ren, Jianqiang,Chen, Zhongxin,Tang, Huajun,Ren, Jianqiang,Chen, Zhongxin,Tang, Huajun,Liu, Xingren. 2010

[2]Remote-Sensing Based Winter Wheat Growth Dynamic Changes and the Spatial-Temporal Relationship with Meteorological Factor. Huang Qing,Zhou Qingbo,Wu Wenbin,Li Dandan. 2014

[3]Application of EOS/MODIS-NDVI at Different Time Sequences on Monitoring Winter Wheat Acreage in Henan Province. Cheng Deng-fa. 2009

[4]Regional yield prediction for winter wheat based on crop biomass estimation using multi-source data. Ren, Jianqiang,Chen, Zhongxin,Zhou, Qingbo,Tang, Huajun,Ren, Jianqiang,Chen, Zhongxin,Zhou, Qingbo,Tang, Huajun,Li, Su. 2007

[5]Land surface phenology of China's temperate ecosystems over 1999-2013: Spatial-temporal patterns, interaction effects, covariation with climate and implications for productivity. Wu, Chaoyang,Peng, Dailiang,Xu, Shiguang,Hou, Xuehui,Gonsamo, Alemu,Gonsamo, Alemu.

[6]Effects of meteorological factors on different grades of winter wheat growth in the Huang-Huai-Hai Plain, China. Huang Qing,Wang Li-min,Chen Zhong-xin,Liu Hang. 2016

[7]Selecting the Optimal NDVI Time-Series Reconstruction Technique for Crop Phenology Detection. Wei, Wei,Wu, Wenbin,Li, Zhengguo,Yang, Peng,Zhou, Qingbo. 2016

[8]VALIDATION OF MODIS FAPAR PRODUCTS IN HULUNBER GRASSLAND OF CHINA. Li, Gang,Xin, Xiaoping,Zhang, Hongbin,Li, Gang,Xin, Xiaoping,Zhang, Hongbin,Wang, Daolong,Zhang, Hua,Xin, Xiaoping,Zhang, Hongbin,Liu, Shimin. 2010

[9]Is Time Series Smoothing Function Necessary for Crop Mapping? - Evidence from Spectral Angle Mapper After Empirical Analysis. Chen, Ailian,Zhao, Hu,Pei, Zhiyuan. 2016

[10]An approach for desertification monitoring in Hulun Buir grassland of Inner Mongolia, China. Qin, Zhihao,Xu, Bin,Gao, Maofang. 2007

[11]Crop discrimination in Northern China with double cropping systems using Fourier analysis of time-series MODIS data. Zhang Mingwei,Zhou Qingbo,Chen Zhongxin,Liu Jia,Zhou Yong,Cai Chongfa. 2008

[12]Topdressing nitrogen recommendation for early rice with an active sensor in south China. Xue, Lihong,Yang, Linzhang,Xue, Lihong,Yang, Linzhang,Li, Ganghua,Qin, Xia,Zhang, Hailin. 2014

[13]A new method of spatialization of crop area statistical data supported by remote sensing technology. Ren, Jianqiang,Chen, Zhongxin,Chen, Zhongxin,Tang, Huajun,Liu, Xingren. 2012

[14]Developing a photosynthetic sterility model to estimate CO2 fixation through the crop yield in Asia with the aid of MODIS data. Kaneko, Daijiro,Yeh, P. J. -F.,Kumakura, Toshiro,Yang, Peng. 2010

[15]Crop growth condition monitoring and analyzing in county scale by time series MODIS medium-resolution data. Yu, Kun,Wang, Zhiming,Sun, Ling,Shan, Jie,Mao, Liangjun. 2013

[16]Estimation of Regional Leaf Area Index by Remote Sensing Inversion of PROSAIL Canopy Spectral Model. Li Shu-min,Li Hong,Zhou Lian-di,Sun Dan-feng. 2009

[17]Spatio-Temporal Dynamics of Land-Use and Land-Cover in the Mu Us Sandy Land, China, Using the Change Vector Analysis Technique. Karnieli, Arnon,Panov, Natalya,Qin, Zhihao,Wu, Bo,Yan, Feng. 2014

[18]EVALUATION OF ARABLE LAND YIELD POTENTIAL THROUGH REMOTE SENSING MONITORING. Song Xiaoyu,Gu Xiaohe,Chang Hong. 2014

[19]SPATIAL VARIABILITY OF WINTER WHEAT GROWTH BASED ON THE INDIVIDUAL INDEX AND THE POPULATION INDEX. Cui, Bei,Song, Xiaoyu,Feng, Meichen. 2014

[20]Monitoring quality of winter wheat based on the HJ satellite images. Wang Yan,Li Cunjun. 2012

作者其他论文 更多>>

微信小程序