Wheat Yield Forecasting at County Scale Based on Time Series Vegetation Temperature Condition Index

WANG Lei; WANG Pengxin; LI Li; ZHANG Shuyu; BAI Xuejiao; XIE Yi

doi:10.13203/j.whugis20160391

Volume 43 Issue 10

Oct. 2018

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Geomatics and Information Science of Wuhan University > 2018 > 43(10): 1566-1573. > DOI: 10.13203/j.whugis20160391

WANG Lei, WANG Pengxin, LI Li, ZHANG Shuyu, BAI Xuejiao, XIE Yi. Wheat Yield Forecasting at County Scale Based on Time Series Vegetation Temperature Condition Index[J]. Geomatics and Information Science of Wuhan University, 2018, 43(10): 1566-1573. DOI: 10.13203/j.whugis20160391

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Wheat Yield Forecasting at County Scale Based on Time Series Vegetation Temperature Condition Index

WANG Lei^{1, 2,},
WANG Pengxin^{1, 2, ,},
LI Li^{1, 2},
ZHANG Shuyu³,
BAI Xuejiao^{1, 2},
XIE Yi^{1, 2}

1.
College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
2.
Key Laboratory of Remote Sensing for Agri-Hazards, Ministry of Agriculture and Rural Affairs, Beijing 100083, China
3.
Shaanxi Provincial Meteorological Bureau, Xi'an 710014, China

Funds:

The National Natural Science Foundation of China 41371390

The National Natural Science Foundation of China 41811530303

More Information

Author Bio:
WANG Lei, PhD candidate, specializes in quantitative remote sensing and its application in drought forecasting. E-mail: leiwangciee2015@cau.edu.cn
Corresponding author:
WANG Pengxin, professor, PhD supervisor. E-mail: wangpx@cau.edu.cn
Received Date: March 18, 2017
Published Date: October 04, 2018

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Abstract

Abstract

Selecting the drought monitoring results of remotely sensed vegetation temperature condition index (VTCI) for winter wheat at the ten-day intervals from 2008 to 2016 in the Guanzhong Plain, the weights of drought impact on wheat yields at the 4 main growth stages were determined by applying the best weighting method. Linear regression analysis was employed to study the correlation between the weighted VTCIs and wheat yields of counties, and the yield prediction was carried out at 1-, 2-and 3-ten day intervals between 2008 and 2016 by using the monitored VTCIs and forecasted ones by the autoregressive integrated moving average models. The results show that the weights of drought impact on wheat yields at the turning green stage, the elongation stage, the heading-filling stage and the dough stage are 0.035, 0.489, 0.427 and 0.049 respectively based on the best combination weighting approach of the improved analytic hierarchy method and the entropy method. There is a significant correlation between the weighted VTCIs and the ground-measured yields published in the related statistical yearbooks, indicating the accuracy of the estimated yields is high. The forecasted yield accuracies are quite high and decreased with the increase of the forecasting intervals.

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