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摘要： Chang算法及改进算法是被动微波遥感雪深反演算法中较简单的经验算法。为了评价改进的Chang算法在东北地区的适用性,对改进的Chang算法进行分析与验证。从空间上,选取了84个野外数据采样点和48个气象站点对改进的Chang算法进行分析与验证。结果表明:森林下垫面改进的Chang算法会低估雪深3.6 cm,而农田下垫面改进的Chang算法会高估雪深1.5 cm。从时间序列上,选取五营、呼中、庆安和巴彦4个气象站点2012年11月15日~2013年2月28日的时间序列雪深数据,对改进的Chang算法进行分析与验证。结果表明:森林下垫面改进的Chang算法会低估雪深,五营站点低估雪深13.7 cm,呼中站点低估雪深8.3 cm,农田下垫面改进的Chang算法会高估雪深,庆安站点高估雪深3.4 cm,巴彦站点高估雪深0.8 cm。无论从空间上还是时间序列上,验证结果都表明,农田下垫面时改进的Chang算法的精度比森林下垫面时要高。此外,站点雪深不变而改进的Chang算法反演的雪深却在增大,这可能是由于期间雪粒径不断增大的缘故。 关键词： 雪深;  遥感;  被动微波;  微波成像仪;  东北地区     Abstract: Chang algorithm and improved Chang algorithm are the simple empirical algorithms of snow depth inversion algorithms of passive microwave remote sensing.In order to evaluate the applicability of the improved Chang algorithm in Northeast China,this paper analyzed and validated improved Chang algorithm.In spatial analysis,this study selected 84 field sampling points and 48 meteorological stations to analyze and validate the improved Chang algorithm.The results showed that when the underlying surface is forest improved Chang algorithm underestimated the snow depth of 3.6 cm,however when the underlying surface is farmland improved Chang algorithm overestimated the snow depth of 1.5cm.In the time series analysis,this study selected snow depth data of four meteorological stations from 15 November 2012 to 28 February 2013 to analyze and validate the improved Chang algorithm,and four meteorological stations are Wuying,Huzhong,Qingan and Bayan respectively.The results showed that when the underlying surface was forest improved Chang algorithm underestimated the snow depth.It underestimated the snow depth of 13.7 cm for Wuying and 8.3 cm for Huzhong.However when the underlying surface was farmland improved Chang algorithm overestimated the snow depth.It overestimated the snow depth of 3.4 cm for Qingan and 0.8 cm for Bayan.The results also showed that when the underlying surface is farmland the accuracy of the improved Chang algorithm is better than that when the underlying surface is forest in spatial analysis and in the time series analysis.Moreover,the snow depth of improved Chang algorithm inversion was increasing and the depth of meteorological stations was constant.The possible cause was that snow grain size was increasing.

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