%0 Conference Proceedings
%T The Estimation of Winter Wheat Yield Based on MODIS Remote Sensing Data
%+ Anhui University [Hefei]
%+ National Engineering Research Center for Information Technology in Agriculture [Beijing] (NERCITA)
%A Huang, Linsheng
%A Yang, Qinying
%A Liang, Dong
%A Dong, Yansheng
%A Xu, Xingang
%A Huang, Wenjiang
%Z Part 1: GIS, GPS, RS and Precision Farming
%< avec comitÃ© de lecture
%( IFIP Advances in Information and Communication Technology
%B 5th Computer and Computing Technologies in Agriculture (CCTA)
%C Beijing, China
%Y Daoliang Li
%Y Yingyi Chen
%I Springer
%3 Computer and Computing Technologies in Agriculture V
%V AICT-369
%P 496-503
%8 2011-10-29
%D 2011
%R 10.1007/978-3-642-27278-3_51
%K LAI
%K remote sensing
%K yield estimation
%K regression model
%K ArcGIS Server
%Z Computer Science [cs]Conference papers
%X A yield estimation method by remote sensing was used to estimate the yield of winter wheat in Jiangsu province, China. The first step of this study was to extract the planting area of winter wheat from environmental satellite images and land -use map of Jiangsu province, meanwhile, correlation analyses were performed by using 8-day of composite Leaf Area Index (LAI) data from Moderate Resolution Imaging Spectroradiometer (MODIS) and statistical yield of corresponding counties. Secondly, the average LAI was calculated at the optimal growth period, and the statistical yields of wheat for all counties were collected, in which the former was chosen as the independent variable and the latter was the dependent variable, and the regression model was established. Finally, the accuracy and stability of the regression model were validated using the data of another year. The results indicated that the yield estimation model at provincial level was reliable, the Root Mean Square Error (RMSE) and the Mean Absolute Error (MAE) of the model was 12.1% and 9.7%, respectively. In addition, the yield estimation system of winter wheat in Jiangsu province was constructed and published based on ArcMap and ArcGIS Server.
%G English
%Z TC 5
%Z WG 5.14
%2 https://inria.hal.science/hal-01361021/document
%2 https://inria.hal.science/hal-01361021/file/978-3-642-27278-3_51_Chapter.pdf
%L hal-01361021
%U https://inria.hal.science/hal-01361021
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-TC5
%~ IFIP-WG5-14
%~ IFIP-CCTA
%~ IFIP-AICT-369