FY-3微波数据RFI订正及我国典型地区地表微波发射率反演研究

项目名称： FY-3微波数据RFI订正及我国典型地区地表微波发射率反演研究

项目编号： No.41305033

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 天文学、地球科学

项目作者： 吴莹

作者单位： 南京信息工程大学

项目金额： 25万元

中文摘要： 微波地表发射率，是表示地表特征的一个参数，在卫星遥感反演地表、大气参数中非常重要。然而，由于地表发射率的不确定性，卫星资料所包含的大气温、湿信息难以更好地提取和有效地应用。我国风云三号（FY-3）卫星微波成像仪（MWRI）资料的处理和使用更是如此。近年来由于无线电频谱资源使用日益加剧，在某些特定微波频率处的无线电波已经对卫星遥感形成"无线电频率干扰（RFI）"，明显增加卫星观测亮温，从而显著降低地表发射率反演的准确性。本项目将研究FY-3 MWRI资料的RFI检测、识别和订正算法，并选取我国干旱、半干旱、湿润等典型地表地区，创新性地利用RFI订正以后的FY-3 MWRI多通道资料，用一维变分法反演地表发射率，为我国建立新的微波地表发射率数据库。本项目将进一步丰富微波地表发射率遥感理论和技术，促进我国气象卫星遥感技术的开发和资料的应用。

中文关键词： 微波遥感；；无线电频率干扰（RFI）；一维变分反演（1-DVAR）；地表发射率；土壤质地

英文摘要： The Microwave land surface emissivity is a very important parameter for describing the characteristics of the land, and it is also a key factor for retrieving the parameters of land and atmosphere. However, du to the uncertainty of land surface emissivity, the satellite data containing the temperature and humidity information can not be better applied in numerical weather prediction. Moreover, so it is especially to the measurements of the Microwave Radiation Imager (MWRI) loaded on the Chinese FengYun-3 (FY-3) satellite. Additionally, in recent years, due to an increasing using of the radio spectrum, the radio-frequency interference (RFI) which can evidently increase brightness temperature at some special microwave channels has become a serious problem for microwave radiometry, and significantly reduces the accuracy of emissivity retrievals. Therefore, in this study, a new algorithm is expected to be proposed for RFI detection and correction of FY-3 MWRI brightness temperatures. And also, with one-dimensional variational retrieval (1DVAR) method, a new land emissivity data base of typical land surface (e.g. arid, semiarid, and humid regions) in China using FY-3 microwave data after RFI-contaminated data are detected and corrected is expected to be developed. The results will further enrich the remote sensing th

英文关键词： microwave remote sensing；radio-frequency interference (RFI)；one dimensional variational retrieval (1-DVAR)；land emissivity；soil texture