被动微波雪深反演算法在东北地区的时空分析与验证  

The Space-time Analysis and Validation of Snow Depth Inversion Algorithm of Passive Microwave in Northeast China

作　　者：武黎黎 李晓峰[1,3] 赵凯[1,3] 郑兴明[1,3] 丁艳玲[1,2] 李洋洋[1,2] 任建华[1,2] 

机构地区：[1]中国科学院东北地理与农业生态研究所,吉林长春130102 [2]中国科学院大学,北京100049 [3]中国科学院长春净月潭遥感试验站,吉林长春130102

出　　处：《遥感技术与应用》2015年第3期565-572,共8页Remote Sensing Technology and Application

基　　金：国家863计划项目"遥感产品真实性检验关键技术及其试验验证"(2012AA12A305-5-2);国家自然科学基金项目"东北地区季节性积雪层中雪粒径的谱分布特征与微波(辐射;散射)特性研究"(41001201);国家自然科学基金项目"东北地区森林下雪深被动微波遥感反演的关键影响参数观测与研究"(41471289);国家自然科学基金项目"被动微波遥感土壤水分反演精度与空间异质特征的相关性研究"(41301369);吉林省科技发展计划项目"我国东北地区积雪与土壤湿度多源遥感数据产品的开发与应用"(20140101158JC)

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3.6cm,而农田下垫面改进的Chang算法会高估雪深1.5cm。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13.7cm,呼中站点低估雪深8.3cm,农田下垫面改进的Chang算法会高估雪深,庆安站点高估雪深3.4cm,巴彦站点高估雪深0.8cm。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。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 3.6cm,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 2012to 28 February 2013to 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 of13.7cm for Wuying and 8.3cm for Huzhong.However when the underlying surface was farmland improved Chang algorithm overestimated the snow depth.It overestimated the snow depth of 3.4cm for Qingan and 0.8cm 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.

关 键 词：雪深 遥感 被动微波 微波成像仪 东北地区 

分 类 号：TP722.6[自动化与计算机技术—检测技术与自动化装置]