高时空分辨率微波遥感信息与农作物模型同化研究

项目名称： 高时空分辨率微波遥感信息与农作物模型同化研究

项目编号： No.41271432

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： 陈劲松

作者单位： 中国科学院深圳先进技术研究院

项目金额： 75万元

中文摘要： 对农作物生长机理和过程的充分了解以及在农作物生长期及时准确地获取农作物生物物理参数信息是提高农作物估产精度的关键问题。本研究以华南多云雨地区水稻估产为研究重点,选择广东省雷州半岛水稻产区作为典型样区,通过地表散射计测量和高时空分辨率多极化微波遥感TerraSAR-X数据研究水稻的时域X波段微波后向散射特征和机理，建立散射模型定量反演水稻整个生长期的叶面积指数；并利用农作物生长模型研究水稻生长过程机理和水稻生物量及叶面积指数的动态变化。在此基础上进一步研究微波遥感信息和农作物模型的同化方法,将微波遥感信息与农作物模型耦合，以获取高精度的水稻估产结果。本研究旨在开发高时空分辨率微波遥感数据定量反演水稻生物物理参数的方法，探索微波散射机理和遥感信息与陆表过程模型的耦合方法，促进高时空分辨率主动微波遥感在南方多云雨地区中的应用，提高作物估产精度，为国家农业和区域可持续发展提供重要的科学依据。

中文关键词： 微波遥感；农作物模型；数据同化；农作物估产；

英文摘要： Fully understanding the mechanism and process of crop growth and obtaining timely and accurate crop biophysical parameters in the main stages of crop growth are key factors to improving the accuracy of crop yield estimation. The study aims to explore the mechanism of microwave scattering, develop methods of quantitative retrieval of biophysical parameters of crop using remote sensing data, further understand the coupling mechanism of remote sensing data and land surface process model and improve the accuracy of crop yield predictions. Most paddy rice crops grow in rainy and cloudy environment, for example, southern part of China. The regular acquisition of optical remote sensing data is hampered by frequent cloud cover. Radar can acquire remote sensing information with a high temporal resolution due to its all-weather capability. Crop growth models can be used to estimate crop growth state and yield. But the need of a large number of input parameters and nonoptimal and changing growing conditions hampers the application of such models at large spatial scale and limits the confidence in their output.In this study, with a focus on rice yield estimation in rainy and cloudy areas of Leizhou of Guangdong province in southern China, time series of high temporal and spatial resolution multi-polarization TerraSAR-X da

英文关键词： Microwave remote sensing；Crop growth model；Data assimilation；Crop yield estimation；