Please wait a minute...
img

官方微信

遥感技术与应用  2009, Vol. 24 Issue (6): 715-721    DOI: 10.11873/j.issn.1004-0323.2009.6.715
技术研究与图像处理     
AMSR-E数据散射与极化指数检测2008年1月中国南方冰雪灾害
金亚秋1,陈  昊1,谷松岩2
   
  
1.复旦大学波散射与遥感信息教育部重点实验室,上海  200433;
2.国家卫星气象中心,北京  100081
Detection of Snow and Frost in Southern China,January 2008 Using AMSR-E Scattering and Polarization Indices
JIN Ya-qiu1,CHEN Hao1,GU Song-yan2
1.Key Laboratory of Wave Scattering and Remote Sensing Information (MOE)Fudan University, Shanghai 200433,China;
2.Center for Satellite Meteorology,Beijing 100081,China
       
 全文: PDF(3775 KB)  
摘要:

全天候全天时微波遥感是监测自然灾害的重要手段。星载被动微波遥感测量的多通道辐射亮度温度对全球和区域性天气与气候、大气降水、陆地水文、海面风场等物理信息的获取已发挥了重要的作用。2008年初中国通常温暖的南方发生暴雪和冰冻灾害,用业务运行的多通道辐射亮度温度算法产品却无法识别这一冰雪灾害。通过对积雪层的矢量辐射传输模拟,根据多通道微波扫描辐射计AMSR-E数据的散射与极化特征指数、往年同时期同地区正常条件下的平均特征指数以及先时特征指数的变化,构成新的判据流程,能有效地识别中国南方区域性冰雪自然灾害。
     

关键词: 被动微波遥感 多通道TB 极化指数 散射指数 积雪冰冻 判据流程    
Abstract:

All weather and all time microwave remote sensing is one of most effective means to monitor natural disasters.Multi-channel brightness temperature from satellite-borne passive microwave remote sensing has played important role to retrieve quantitative physical information on global and regional weather and climate,atmospheric precipitation,land hydrology,oceanic surface winds,etc. However,during serious snowing and frost in usually warming southern China,January 2008,the operational algorithm of multi-channel brightness temperature failed to detect the snowing.In this paper,based on simulation of vector radiative transfer of a layer of snow,we present the characteristic indices of scattering and polarization differences,average indices in previous year under normal situation,and change of antecedent index.A new logic tree is presented to effectively detect the regional snow and frost disaster in southern China.

Key words:      Passive microwave remote sensing    Multi-channel TB    Polarization index    Scattering index    Snowpack and frost    Detection logic tree 
收稿日期: 2009-08-24 出版日期: 2012-01-06
基金资助:

国家自然科学基金项目(40637033)。

作者简介: 金亚秋(1946-),男,美国MIT博士、 IEEE院士、国家973项目首席科学家,主要从事电磁散射与辐射传输、空间微波遥感信息理论与技术、计算机电磁学等方面的研究。E-mail:yqjin@fudan.ac.cn。
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章  
金亚秋
陈昊
谷松岩

引用本文:

金亚秋, 陈昊, 谷松岩. AMSR-E数据散射与极化指数检测2008年1月中国南方冰雪灾害[J]. 遥感技术与应用, 2009, 24(6): 715-721.

JIN Ya-Qiu, CHEN Hao, GU Song-Yan. Detection of Snow and Frost in Southern China,January 2008 Using AMSR-E Scattering and Polarization Indices. Remote Sensing Technology and Application, 2009, 24(6): 715-721.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2009.6.715        http://www.rsta.ac.cn/CN/Y2009/V24/I6/715

1] Kawanishi T,Sezai T,Ito Y,et al.The Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E),NASDA’s Contribution to the EOS for Global Energy and Water Cycle Studies[J].IEEE Transactions on Geoscience and Remote Sensing,2003,41(2):184-194.
 [2] Shibata A,Imaoka K,Koike T.AMSR/AMSR-E Level 2 and 3 Algorithm Developments and Data Validation Plans of NASDA[J].IEEE Transactions on Geoscience and Remote Sensing,2003,41(2):195-203.
 [3] Bauer P,Grody N C.The Potential of Combining SSM/I and SSM/T2 Measurements to Improve the Identification of Snowcover and Precipitation[J].IEEE Transactions on Geoscience and Remote Sensing,1995,33(2):252-261.
 [4] Ferraro R R,Wen F,Grody N C,et al.An Eight-year (1987-1994) Time Series of Rainfall,Clouds,Water Vapor,Snow Cover,and Sea Ice Derived from SSM/I Measurements[J].Bulletin of the American Meteorological Society,1996,77(5):891-905.
 [5] Jin Yaqiu.Theory and Method for Data Validation of Space-borne Microwave Remote Sensing[M].Beijing:Science Press,2005.[金亚秋.空间微波遥感数据验证的理论与方法[M].北京:科学出版社,2005.]
 [6] www.nsmc.cma.gov.cn[Z/OL].中国气象局卫星气象中心发布.
 [7] www.nsidc.net[DB/OL].美国国家冰雪数据中心发布AMSR-E数据和SSM/I数据产品.
 [8] Grody N C,Basist A N.Global Identification of Snowcover Using SSM/I Measurements[J].IEEE Transactions on Geoscience and Remote Sensing,1996,34(1):237-249.
 [9] Jin Yaqiu.Remote Sensing Theory of Electromagnetic Scattering and Thermal Emission[M].Beijing:Science Press,1993.[金亚秋.电磁散射和热辐射的遥感理论[M].北京:科学出版社,1993.]
10] Jin Y Q.Electromagnetic Scattering Modelling for Quantitative Remote Sensing[C].Singapore:World Scientific,1994.
11] Tsang L,Chen C T,Chang A T C,et al.Dense Media Radiative Transfer Theory Based on Quasicrystalline Approximation with Applications to Passive Microwave Remote Sensing of Snow[J].Radio Science,2000,35(5):731-749.
12] Jin Y Q.Theory and Approach of Information Retrievals from Electromagnetic Scattering and Remote Sensing[M].Berlin Heidelberg New York:Springer,2005.

[13] Jin Y Q,Yan F H.A Change Detection Algorithm for Terrain Surface Moisture Mapping Based on Multi-year Passive Microwave Remote Sensing (Examples of SSM/I and TMI Channels)[J].Hydrological Processes,2007,21:1918-1924. 

[1] 邱玉宝,郭华东,石利娟,施建成. 基于AMSR-E的全球陆表被动微波发射率数据集[J]. 遥感技术与应用, 2016, 31(4): 809-819.
[2] 王琦,柴琳娜,赵少杰,张涛. 基于多角度微波辐射亮温数据反演冬小麦光学厚度[J]. 遥感技术与应用, 2015, 30(3): 424-430.
[3] 陈修治,陈水森,苏泳娴,李 丹,韩留生. 基于被动微波遥感的2008年广东省春季低温与典型作物寒害研究[J]. 遥感技术与应用, 2012, 27(3): 387-395.
[4] 顾玲嘉,赵凯,孙健,郑兴明. 被动微波遥感数据超分辨率增强与混合像元分解研究综述[J]. 遥感技术与应用, 2012, 27(1): 1-6.
[5] 李欣欣,张立新,蒋玲梅,赵少杰,赵天杰. 地形坡面对被动微波遥感影响的试验研究[J]. 遥感技术与应用, 2011, 26(1): 74-81.
[6] 顾玲嘉,赵凯,孙健,郑兴明. 被动微波遥感数据超分辨率增强与混合像元分解研究综述[J]. 遥感技术与应用, 2011, 27(1): 1-7.
[7] 陈昊, 金亚秋 . 星载微波辐射计对玉树地震岩石破裂辐射异常的初步检测[J]. 遥感技术与应用, 2010, 25(6): 860-866.
[8] 白云洁, 卢 玲, 李 新, 车 涛. 积雪微波辐射亮温对积雪参数的敏感性分析——以多层积雪微波辐射模型为例[J]. 遥感技术与应用, 2009, 24(5): 622-630.
[9] 吴季,刘浩,阎敬业,孙伟英,张成,潘碑. 干涉式被动微波成像技术[J]. 遥感技术与应用, 2009, 24(1): 1-12.
[10] 金亚秋,法文哲,徐 丰. 月球表面微波主被动遥感的建模模拟与反演[J]. 遥感技术与应用, 2007, 22(2): 129-134.
[11] 孙知文,施建成,杨 虎,蒋玲梅,彭 亮. 风云三号微波成像仪积雪参数反演算法初步研究[J]. 遥感技术与应用, 2007, 22(2): 264-267.
[12] 高 峰, 车涛, 王介民, 文军 . 被动微波遥感指数及其应用[J]. 遥感技术与应用, 2005, 20(6): 551-557.
[13] 何文英, 陈洪滨, 周毓筌. 微波被动遥感陆面降水统计反演算式的比较[J]. 遥感技术与应用, 2005, 20(2): 221-227.
[14] 吴 季, 刘 浩, 孙伟英, 姜景山. 综合孔径微波辐射计的技术发展及其应用展望[J]. 遥感技术与应用, 2005, 20(1): 24-29.
[15] 钟若飞, 郭华东, 王为民. 被动微波遥感反演土壤水分进展研究[J]. 遥感技术与应用, 2005, 20(1): 49-57.