多源数据小麦病害遥感识别与监测方法研究

项目名称： 多源数据小麦病害遥感识别与监测方法研究

项目编号： No.41271412

项目类型： 面上项目

立项/批准年度： 2013

项目学科： 天文学、地球科学

项目作者： 黄文江

作者单位： 北京市农林科学院

项目金额： 75万元

中文摘要： 全球变化引起病虫害对农业生产造成的损失日益加剧，目前我国农业植保部门对病害的监测方法主要是目测手查法，这种传统的以"点"代"面"的工作模式费时、费力，且无法获取大面积的病害发生程度和蔓延信息。综合遥感、植保和气象多源数据的作物病害监测和预报成为重要趋势。项目针对目前病害遥感监测中病害与其它胁迫类型易混淆，基于卫星的病害监测方法欠缺，病害预测主要基于气象数据预测空间尺度过大等突出问题，以小麦主要病害白粉病和条锈病为对象，设置控制实验，研究小麦病害和营养、干旱等胁迫在光谱、时序等多维特征上的差异，构建小麦病害特征知识库，发展病害遥感识别和严重度监测方法；研究基于混合调谐匹配滤波分析的融合中、高分辨率卫星影像光谱、空间、时间等多维特征的大范围病害识别监测方法；构建综合气象、农学、植保、遥感数据的小麦病害预测预报模型。对保障我国粮食安全和指导适时、合理施药保护环境具有重要意义。

中文关键词： 光谱吸收特征；病虫害监测预警；数据同化；尺度效应；

英文摘要： The yield loss of crops due to crop diseases and pests are increasing under the context of global climate change. For monitoring of crop diseases and pests, the traditional methods that are adopted by major plant protection department of our country are still through manually inspection and field sampling. However, these methods are not only time consuming, labor intensive, but are also unable to obtain information about disease occurrence and dispersal over vast areas. Nowadays, incorporating datasets from multi-sources for disease monitoring and forecasting, such as remote sensing data, agricultural data as well as meteorological data, is becoming an important tendency. The present proposal aims at solving a series of problems in crop diseases monitoring and forecasting. These problems include: how to separate crop diseases from other stressors？how to utilize satellite images for monitoring? and how to forecast crop diseases at a finer spatial scale? Two important diseases of wheat, powdery mildew and yellow rust, are adopted as the objects of our study. A control experiment is planned to simulate wheat plants under different stresses (e.g. diseases, nutrient stress and drought). The divergence between wheat diseases and other stresses can be analyzed at different dimensions (e.g. spectral, temporal, etc.). Ba

英文关键词： Spectral absorption features；Crop pests and diseases monitoring and forecastin；Data assimilation；Scale effect；