基于无人机遥感数据与作物模型同化的冬油菜生长监测与估产方法研究

我国油菜生长常年所面临的“北旱南涝”威胁是制约油菜丰产保收的重要因素。准确、快速的获取油菜生长信息与产量预报对农田生产管理、保证粮油安全以及国家经济健康发展具有重要的意义。基于数据同化算法耦合的遥感与作物模型系统能够实现两者的优势互补，在准确描述作物生长状态的同时又能够提高作物区域估产精度。本课题拟以冬油菜为研究对象，油菜生长机理和过程机制模拟为基础，采用田间观测和模型数值模拟相结合的方法，开展不同尺度(叶片、单株和冠层)与时间序列的作物生长状态变量监测。从油菜播期、关键生育期以及多状态变量无人机遥感数据识别与反演、冬油菜生长过程机理模型研究和优化、以及多变量多参数多同化算法协同应用等方面，对同化系统的构建与实现进行系统研究。建立冬油菜产量估测同化框架，明确有效提高单产估测精度的同化方案，为促进农业信息监测研究的发展提供重要理论基础。

The threat of rapeseed production in ‘north drought with south flood’ and inefficiency growth monitoring in China is the important factors restricting the high yield harvest. Accurately and rapidly obtains winter rapeseed growth states, grain yield is great significance for field management, food and oil storage, and national economic development. Assimilating remote sensing data and crop model can complement and eliminate the advantages and drawbacks of both methods and eliminate drawbacks, which can accurately describe crop growth and improve crop yield estimation in a regional scale. Based on the different sowing dates and seeding density during three consecutive growing seasons of winter rapeseed (Brassica napus), our study will comprehensively analyze crop growth mechanism and process, using various equipment for rapeseed growth states monitoring at different scales (leaf, plant, and canopy) and time series(continuous growing season). By combining field observation with crop model numerical simulation, this study mainly focuses on the effect of detection model for sowing dates and growth stages in rapeseed and retrieving multiple states variables using UAV remote sensing spectral data; development and evaluation of multiple famous rapeseed growth mechanism model with atmosphere, crop and soil for simulating crop growth and production; establishing assimilation system by assimilating multiple state variables, parameters, and algorithm, analyzing the effect of different assimilation schemes on the accuracy of crop yield estimation, and proposing the optimum method for improving yield estimation accuracy. This project will provide an important theoretical basis for promoting the development of agricultural information application.