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基于被动微波遥感的青藏高原雪深反演及其结果评价
引用本文:柏延臣,冯学智,李新,陈贤章.基于被动微波遥感的青藏高原雪深反演及其结果评价[J].遥感学报,2001,5(3):161-165.
作者姓名:柏延臣  冯学智  李新  陈贤章
作者单位:1. 中国科学院地理科学与资源研究所,北京 100101
2. 南京大学城市与资源学系,南京 210093
3. 中国科学院寒区旱区环境与工程研究所,兰州 730000
基金项目:国家自然科学基金项目“青藏高原积雪和冻土的微波遥感监测研究”(49971060)和“我国积雪遥感综合定量分析系统研究(49471058)资助。
摘    要:采用修正的张氏雪深反演算法,用SSM/I37GHz和19GHz水平极化亮温值计算了青藏高原及其毗邻地区的积雪深度,对其精度进行了评价,并对误差来源进行了分析,结果显示,此算法能够较好地反映研究区的雪深分布,但局部地区误差较大,总体上雪深被高估,其误差主要来源于冻土,深霜层,植被以及雪层中液态水含量,雪粒的形状和粒径的变化带来的影响,SSM/I数据较低的分辨率和研究区复杂的地形使反演的雪深与观测的雪深缺少可比性,给精度的评价带来影响。

关 键 词:积雪深度  被动微波遥感  SSM/I数据  评价  青藏高原  高温数据
文章编号:1007-4619 (2001) 03-0161-05
收稿时间:6/8/2000 12:00:00 AM
修稿时间:2000年6月8日

The Retrieval of Snow Depth in Qinghai_Xizang (Tibet) Plateau from Passive Microwave Remote Sensing Data and Its Results Assessment
BO Yan-chen,FENG Xue-zhi,LI Xin and CHEN Xian-zhang.The Retrieval of Snow Depth in Qinghai_Xizang (Tibet) Plateau from Passive Microwave Remote Sensing Data and Its Results Assessment[J].Journal of Remote Sensing,2001,5(3):161-165.
Authors:BO Yan-chen  FENG Xue-zhi  LI Xin and CHEN Xian-zhang
Abstract:Snow cover extension and snow depth information may be useful indicators of regional and global climate change and of basin_scale water storage in mountainous areas as well as snow disaster monitoring, forecasting and the loss assessment in pastoral areas. Thus, it is important to ensure that they are accurate and as free as possible of any known biases.Though it is practical to get snow extension from the visible and infrared remotely sensed data such as NOAA_AVHRR, TM and the like, it is nearly impossible to get snow depth information from such data set. Passive microwave remotely sensed data such as SMMR and SSM/I make it possible to derive snow depth in a large_scale area. Some algorithms have been developed to retrieve the snow depth from SMMR and SSM/I data, but those algorithms didn't perform well in many studies.In this paper, using a revised Chang's algorithm and SSM/I 37GHz and 19GHz horizontally polarized brightness temperature, we retrieved the snow depth distribution in Qinghai_Xizang (Tibet) plateau, assessed the results' accuracy, and analyzed their error sources. It showed that the revised Chang's algorithm described the general trend of snow depth of this area, in spite of overestimation in whole and large errors in local areas. The errors are mainly from the effects of the existence of frozen ground, depth_hoar, vegetation cover and the lacking of considering the effects of the liquid water content of snow and the changing of shape and grain size of snow. The coarse spatial resolution of SSM/I remotely sensed data makes the retrieved snow depth hard to compare with the ones from ground observation, thus, makes it difficult to \{evaluate\} the accuracy. Some suggestions for further investigation were put forward at last.
Keywords:snow depth  passive microwave remote sensing  SSM/I data  results assessment
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