The Yield Estimation Research About Winter Wheat Of Longkou City Based On MODIS

Winter wheat is one of the main food crops in China, and in north has a pivotal status. Especially in recent years population increasing all the time, while cultivated land resources in constant decrease, and the graim problem increasingly serious. So growing monitoring and yield estimation when the winter wheat stages of growth are very important to national and the government.Crop yield prediction research also obtained fast development along with the satellite remote sensing technology and the development of computer technology. As crop monitoring and estimation of a new scientific methods, yield estimation techniques combined with remote sensing and GIS, is much accounted of government departments at all levels and decision-making departments for its macro, rapid, objective and so on. Terra/MODIS is a new kind of satellite sensor, coverring wide-ranging, and monitoring period is short, while once a day to the ground covered, and provides new opportunities for the remote sensing monitoring and yield estimation crop. This thesis subsidized by"Sino-german science and technology exchange and cooperation projects"(2007DFB70200)and"Shandong natural science fund"(Y2008E10). This paper reviews the research status of both domestic and foreign remote-sensing estimates, and explains the research content and meaning. The voerseas for yield estimation research for the 2010 winter wheat is used the 12-minute phase high spectral resolution EOS composed multi-temporal MODIS images. Extraction winter wheat planting area based on the optirnal remote sensing images. Analysised and studied the relation between leaf area index and vegetation index, we get the winter wheat crop, and establish yield model. In winter wheat growth condition analysis research, we discussed on winter wheat growing quantitative analysis method. Research shows that the performance of different period of winterwheat leaf area index LAI, by establishing relation model of winter wheat from the main vegetation index biophysical parameters in Longkou City. Results show that EVI inversion of winter wheat biological physical parameters is better than NDVI effect. Determine the winter wheat crop township use EVI, and establish yield model. Finally built the winter wheat yield model, and budget production of longkou city in 2010, and precision analysis according to the field data collection. Results show that the method is feasible of using MODIS to winter wheat planting area of extraction and total output forecast. But in the research area of smaller cases can cause much error. Overall in the study area are the error output forecast in the control of 10%. At the end of the paper I summarized the main conclusion and achievemented obtined, and looked forward to the work in the future needs further solve the problem.