Arid
Study on Yield Estimation of Spring Wheat basing on Hyperspectral data under Different Meteorological Condition in Semi-Arid Rain Fed Region
Sha Sha1; Wang Xiaoping1; Li Qiaozhen2; Li Weidong3
通讯作者Sha Sha
会议名称5th International Conference on Agro-Geoinformatics (Agro-Geoinformatics)
会议日期JUL 18-20, 2016
会议地点Tianjin, PEOPLES R CHINA
英文摘要

Statistically relating vegetation index to yield is a common wheat yield estimation method. In this paper, we investigate the relationship between a variety of spectral vegetation indices and yield factors for spring wheat in a semiarid, rain-fed, agricultural region under different meteorological conditions on the basis of relevant ground observations. We also analyze the yield estimation factor of remote sensing for spring wheat by regression method under different meteorological conditions. Results are as follows. 1) The theoretical yield per unit area, thousand-kernel weight, grains per ear, and number of productive tillers per square meters at the milk stage of maturity are relatively small. These data exhibit flat variation trends with spectral vegetation indices under drought conditions. By contrast, the trends under non-drought conditions are significantly changing. 2) Meanwhile, the spectral vegetation indices under drought and non-drought conditions are appreciably associated with the theoretical yields at the booting (0.01) and heading stages (0.001). 3) In the meteorological droughts, the aggregate value of the semi-arid water index at the booting and heading stages is suitable for use as the yield estimation factor for spring wheat. However, under the meteorological non-droughts, the RVI(p 780/p1750) at the booting stage is used as the yield estimation factor for spring wheat. The mean absolute percentage errors of the yield estimations in the two cases are 70.9% and 84.2%, respectively.


英文关键词Meteorological Condition Spring Wheat Dingxi
来源出版物2016 FIFTH INTERNATIONAL CONFERENCE ON AGRO-GEOINFORMATICS (AGRO-GEOINFORMATICS)
ISSN2334-3168
出版年2016
页码242-247
EISBN*****************
出版者IEEE
类型Proceedings Paper
语种英语
国家Peoples R China
收录类别CPCI-S
WOS记录号WOS:000391252300048
WOS关键词MODIS ; NDVI
WOS类目Agriculture, Multidisciplinary ; Computer Science, Information Systems
WOS研究方向Agriculture ; Computer Science
资源类型会议论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/305329
作者单位1.CMA, Inst Arid Meteorol, Key Lab Arid Climate Change & Reducing Disaster G, Key Open Lab Arid Climate Change & Disaster Reduc, Lanzhou, Peoples R China;
2.Meteorol Bur Dingxi Gansu Prov, Dingxi, Peoples R China;
3.Gansu Prov Meteorol Bur, Lanzhou, Peoples R China
推荐引用方式
GB/T 7714
Sha Sha,Wang Xiaoping,Li Qiaozhen,et al. Study on Yield Estimation of Spring Wheat basing on Hyperspectral data under Different Meteorological Condition in Semi-Arid Rain Fed Region[C]:IEEE,2016:242-247.
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