[1]张显峰,包慧漪,刘 羽,等.基于微波遥感数据的雪情参数反演方法[J].山地学报,2014,(03):307.
　ZHANG Xianfeng,BAO Huiyi,LIU Yu,et al.Snow Parameter Estimation from Microwave Remote Sensing Data[J].Mountain Research,2014,(03):307.
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基于微波遥感数据的雪情参数反演方法()
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《山地学报》[ISSN:1008-2186/CN:51-1516]

卷:
期数:
2014年03期
页码:
307
栏目:
山地研究
出版日期:
2014-03-01

文章信息/Info

Title:
Snow Parameter Estimation from Microwave Remote Sensing Data
作者:
张显峰;  包慧漪; 刘 羽; 郑旭荣
1.北京大学遥感与地理信息系统研究所，北京 100871；
2.石河子大学水利建筑工程学院，新疆 石河子 832003
Author(s):
ZHANG Xianfeng;  BAO Huiyi;  LIU Yu;  ZHENG Xurong（313）
1. Institute of Remote Sensing and GIS, Peking University, Beijing 100871,China;
2. School of Water Conservancy, Shihezi University, Xinjiang 832003,China
关键词:
积雪深度; 被动微波; 亮温差; AMSR2; 新疆
Keywords:
snow depth;  passive microwave;  brightness temperature difference;  AMSR2;  Xinjiang
分类号:
TP722.5
文献标志码:
A
摘要:
微波遥感传感器在36.5 GHz通道会因雪深超过其穿透深度而出现信号饱和，从而导致雪深被低估。针对该问题，首先建立了18.7 GHz与36.5 GHz通道亮温差和10.7 GHz与18.7 GHz通道亮温差相结合的积雪深度分层反演新方法，然后利用GCOM-W1星上搭载的AMSR2传感器数据估算了2012年12月至2013年2月新疆每日积雪深度，结合同期的气象站点观测数据与野外实测数据对遥感反演结果进行了评价。结果表明，所建立模型能够很好识别新疆地区积雪的空间分布状况，雪深的估算结果明显优于常用的Chang模型。
Abstract:
The snow depth may be under estimated from the passive microwave remote sensing data at the frequency of 36.5 GHz due to the saturation of the microwave signal detected by the remote sensor, thus, a new segmental modeling approach for snow depth estimation was created by combining the brightness temperature differences between 18.7 GHz and 36.5 GHz channels and between 10.7 GHz and 18.7 GHz channels. Afterwards, the brightness temperature data acquired by the AMSR2 (Advanced Microwave Scanning Radiometer 2) sensor onboard the GCOM-W1 satellite were used to test the model and the snow depth of Xinjiang from December 2012 to February 2013 was estimated. The observations collected by the Xinjiang meteorological stations and field insitu measurements of snow depth were employed to assess the estimation. The results show that the segmental approach can identify the spatial distribution of snow covers and accurate estimation of snow depth can be achieved, which obviously outperforms the result using Chang’s algorithm.

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相似文献/References:

[1]延昊,张佳华.基于SSM/I被动微波数据的中国积雪深度遥感研究[J].山地学报,2008,(01):59.

备注/Memo

备注/Memo:
收稿日期(Received date)：2013-07-25；改回日期(Accepted): 2013-08-28。
基金项目（Foundation item）：国家科技支撑计划项目（No.2012BAH27B03 & 2012BAH27B02），国家自然科学
基金项目(No.41071257)。[Key project by the China Ministry of Science and Technology, No. 2012BAH27B03 & 2012BAH27B02；Research grant by National Natural Science Foundation of China,No.41071257.]
作者简介（Biography）：张显峰（1967-），男，四川达州人，副教授，博士，主要研究领域：生态与环境参数遥感反演、数据同化，灾害评价等。[Zhang Xianfeng (1967-), male and born in Dazhou, Sichuan Province, Associate Professor & Ph D, Main research interests: quantitative retrieval of ecological and environmental variables from remotely sensed data, data assimilation, and disaster assessment.]
更新日期/Last Update: 1900-01-01