Study On Estimating Winter Wheat Growth And Fusarium Head Blight Using Satellite Remote Sensing

Under the environment of global warming and environmental degradation, the risks and diseases of winter wheat is increasing, which seriously affects it’s quality and yield, and even the whole world’s grain production. With the development of remote sensing technology and the advent of the information age, using multi-source remote sensing data forstudying on wheat growth and disease in information extraction and monitoring prediction, will gradually replace the traditional agriculture monitoring,which is the requirement of new agriculture to develop to healthy, green and sustainable, but also is the demand of modern agriculture, information technology development. This paper mainly using satellite remote sensing technology application in crop production as the research direction, using multi-source remote sensing data and field survey data, geographic data as the foundation, and do research on winter wheat growth and Fusarium head blightmonitoring.The main results include:1. Using images of China’s domestic satellite GF-1 and HJ-1, selected different spatial resolution imagesto fusion which producingat the same time and in the same area, respectively generating three different scale multi spectral imagesof spatial resolution 2m* 2m,8m* 8m and 16m* 16m, and comparingby the quality evaluation of fused image, spectrum analysis and unsupervised classification area precision values. The results showed that winter wheat planting area extraction accuracy of 16m* 16m fusion image is ideal, and the precision is 96.73%. The research shows that,16m* 16m spatial resolution remote sensing image is more suitable for the field distribution characteristics of winter wheat grown in Jiangsu Province and it is conducive to extract winter wheat planting area by remote sensing exactly.2. Through the comprehensive analysis of the quantitative relation betweengrowth parameters in winter wheat heading-flowering which are leaf area index, containing nitrogen content, chlorophyll content, biomass and the different vegetation index respectively, constructing and verifying the corresponding remote sensing inversion model, using HJ-1 multispectral remote sensing data of winter wheat in heading and flowering stage growth parameters for the quantitative inversion. Using ArcGIS to make the remote sensing monitoring information map of Jiangyan, realize the rapid transformation of "point" information to "face" information, and provide decision support for agricultural related departments.3. Investigatewinter wheat during the heading-flowering stage and on the day of the municipalities and satellite transit In Taixing, Jiangyan, Xinghua, sampled wheat by using diagonal determination method. Each city were selected 10 surveys, the survey ofwinter wheat leaf area index, chlorophyll content, the ground biomass, temperature and relative humidity. At the same time, conduct a survey of Fusarium Head Blight in the dough stage (10 days-15 days before harvest).Established monitoring model with the final disease index and the growth parameters and meteorological factors on the winter wheat heading-flowering,using the model and the parameter inversion model to make a remote sensing map of winter wheat scab disease classification information, which can reflect the information of the disease more clearly and provide the basis for agricultural decisions.