基于AMSR2被动微波积雪参量高精度反演方法研究

doi:10.7522/j.issn.1000-0240.2016.0017

摘要/Abstract

摘要： 以新疆为研究区域建立了被动微波遥感积雪深度高精度反演模型,采用高空间和时间分辨率AMSR2被动微波遥感数据(2012年11月-2015年3月逐日数据),结合研究区域海拔高度、坡度、坡向、沙漠,荒漠和地表粗糙度等地形、地貌特征,考虑冰川、水体、林地等地表覆盖类型和不同季节的新雪、干雪和湿雪等积雪属性的微波辐射特征,以决策树阈值法为基础,通过采集样本分类建立起多种雪深判识阈值,在此基础上建立AMSR2高精度积雪深度反演综合模型,分类分析不稳定积雪和冰川信息,从而实现雪深在60cm以内的积雪深度AMSR2反演的主要原理、思路及方法,并对模型的反演结果跟台站实测或者野外观测积雪值以时间和空间角度进行检验.结果表明:该综合模型能够定量判识研究区域复杂地形地貌条件下的1~60cm积雪厚度,检验的复相关系数为0.74~0.88,均方根误差为2.92~6.14cm,平均绝对偏差指数为3~4cm,雪深误差<5cm的精度为91%~94%,雪深误差<2.5cm的精度为81%~87%.

关键词: AMSR2, 积雪辐射特性, 雪深判识模型, 复杂地形地貌

Abstract: This study aims to establish a model of deriving high-precision snow parameters from passive microwave remote sensing data, taken Xinjiang Uygur Autonomous Region as a case. In this paper, firstly high-resolution spatial and temporal data in the research region by means of AMSR2 passive microwave remote sensing were collected from November, 2010 to March, 2015. Then terrain features, such as altitude, slope, aspect, desert and surface roughness, had also been investigated. Other factors, such as variation of surfaces ranging from glacier, paddy field and forest, and microwave radiations of new snow, dry snow and wet snow in various seasons had also been taken into account. After that, a variety of threshold values to assess snow depth were worked out by classifying the collected samples. Finally, a deriving model of snow depth from AMSR2 high-precision sensing data was set up on the basis of decision tree threshold method. The model was then adopted to analyze and classify unstable snow cover and glaciers to establish a deriving method from AMSR2 data targeting at the snow depth of no more than 60 cm. The result of the test was reexamined with those data which were collected from stations or expeditions. The research approves the workability of the new model in identifying the snow depth ranging from 1 to 60 cm in the areas with complicated landforms, with multiple correlation coefficients ranging from 0.74 to 0.88, root mean square error ranging from 2.92 to 6.14 cm, the mean absolute deviation index ranging from 3 to 4 cm. When the snow depth error less than 5 cm, the accuracy of the test ranges from 91% to 94%; when the snow depth error less than 2.5 cm, the accuracy ranges from 81% to 87%.

Key words: AMSR2, snow radiation, snow depth assessing model, varied topography

中图分类号:

P426.63+5

沙依然·外力, 毛炜峄. 基于AMSR2被动微波积雪参量高精度反演方法研究[J]. 冰川冻土, 2016, 38(1): 145-158.

Sayran Wayli, MAO Weiyi. A research on the method of deriving high precision snow parameters from AMSR2 passive microwave remote sensing data[J]. JOURNAL OF GLACIOLOGY AND GEOCRYOLOGY, 2016, 38(1): 145-158.

参考文献

[1] Hofer R, Mätzler C. Investigations on snow parameters by radiometry in the 3- to 60-mm wavelength region[J]. Journal of Geophysical Research: Oceans, 1980, 85(C1): 453-460.
[2] Foster J L, Hall D K, Chang A T C, et al. An overview of passive microwave snow research and results[J]. Reviews of Geophysics, 1984, 22(2): 195-208.
[3] Chang A T C, Foster J L, Hall D K. Nimbus-7 SMMR derived global snow cover parameters[J]. Annals of glaciology, 1987, 9(9): 39-44.
[4] Cao Meisheng, Li Peiji, Robinson D A, et al. Evaluation and primary application of microwave remote sensing SMMR-derived snow cover in western China[J]. Remote sensing of Environment, 1993, 8(4): 260-269. [曹梅盛, 李培基, Robinson D A, 等. 中国西部积雪SMMR微波遥感的评价与初步应用[J]. 环境遥感, 1993, 8(4): 260-269.]
[5] Cao Meisheng, Li Peiji. Microwave remote sensing monitoring of snow cover in western China[J]. Mountain Research, 1994, 12(4): 230-234. [曹梅盛, 李培基. 中国西部积雪微波遥感监测[J]. 山地研究, 1994, 12(4): 230-234.]
[6] Che Tao, Li Xin . The development and prospect of estimating snow water equivalent using passive microwave remote sensing data[J]. Advance in Earth Sciences, 2004, 19(2): 204-210. [车涛, 李新. 被动微波遥感估算雪水当量研究进展与展望[J]. 地球科学进展, 2004, 19(2): 204-210.]
[7] Sun Zhiwen, Shi Jiancheng, Jiang Lingmei, et al. Development of snow depth and snow water equivalent algorithm in western China using passive microwave remote sensing data[J]. Advances in Earth Science, 2004, 21(12): 1364-1369. [孙知文, 施建成, 蒋玲梅, 等. 被动微波遥感反演中国西部地区雪深、雪水当量算法初步研究[J]. 地球科学进展, 2004, 21(12): 1364-1369.]
[8] Chang A T C, Foster J L, Hall D K, et al. Snow water equivalent estimation by microwave radiometry[J]. Cold Regions Science and Technology, 1982, 5(3): 259-267.
[9] Foster J L, Chang A T C, Hall D K. Comparison of snow mass estimates from a prototype passive microwave snow algorithm, a revised algorithm and a snow depth climatology[J]. Remote sensing of environment, 1997, 62(2): 132-142.
[10] Kelly R E, Chang A T, Tsang L, et al. A prototype AMSR-E global snow area and snow depth algorithm[J]. Geoscience and Remote Sensing, IEEE Transactions on, 2003, 41(2): 230-242.
[11] Tsang L, Chen Chite, 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(3): 731-749.
[12] Li Xin, Che Tao. A review on passive microwave remote sensing of snow cover[J]. Journal of Glaciology and Geocryology, 2007, 29(3): 487-496. [李新, 车涛. 积雪被动微波遥感研究进展[J]. 冰川冻土, 2007, 29(3): 487-496.]
[13] Foster J L, Sun C, Walker J P, et al. Quantifying the uncertainty in passive microwave snow water equivalent observations[J]. Remote Sensing of environment, 2005, 94(2): 187-203.
[14] Sturm M, Holmgren J, Liston G E. A seasonal snow cover classification system for local to global applications[J]. Journal of Climate, 1995, 8(5): 1261-1283.
[15] Grody N C, Basist A N. Global identification of snowcover using SSM/I measurements[J]. Geoscience and Remote Sensing, IEEE Transactions on, 1996, 34(1): 237-249.
[16] Bin Chanjia, Qiu Yubao, Shi Lijuan, et al. Comparative validation of snow depth algorithms using AMSR-E passive microwave data in China[J]. Journal of Glaciology and Geocryology, 2013, 35(4): 801-813. [宾婵佳, 邱玉宝, 石利娟, 等. 我国主要积雪区AMSR-E被动微波雪深算法对比验证研究[J]. 冰川冻土, 2013, 35(4): 801-813.]
[17] Chen Wenqian, Ding Jianli, Sun Yongmeng, et al. Retrieval of snow cover area based on NDSI-NDVI feature space[J]. Journal of Glaciology and Geocryology, 2015, 37(4): 1059-1066. [陈文倩, 丁建丽, 孙永猛, 等. 基于NDSI-NDVI特征空间的积雪面积反演研究[J]. 冰川冻土, 2015, 37(4): 1059-1066.]
[18] Sun Yanhua, Huang Xiaodong, Wang Wei, et al. Spatio- temporal changes of snow cover and snow water equivalent in the Tibetan Plateau during 2003-2010[J]. Journal of Glaciology and Geocryology, 2014, 36(6): 1337-1344. [孙燕华, 黄晓东, 王玮, 等. 2003-2010年青藏高原积雪及雪水当量的时空变化[J].冰川冻土, 2014, 36(6): 1337-1344.]
[19] Chen An'an, Chen Wei, Wu Hongbo, et al. The variations of firn line altitude on the Binglinchuan Glacier, Ulugh Muztagh during 2000-2013[J]. Journal of Glaciology and Geocryology, 2014, 36(5): 1069-1078. [陈安安, 陈伟, 吴红波, 等. 2000-2013年木孜塔格冰鳞川冰川粒雪线高度变化研究[J]. 冰川冻土, 2014, 36(5): 1069-1078.]
[20] Zhou Qiming, Liu Xuejun. Digital terrain analysis[M]. Beijing: Science Press, 2006: 200-300. [周启明, 刘学军. 数字地形分析[M]. 北京: 科学出版社, 2006: 200-300.]
[21] Bi Xiaoling, Li Xiaojuan, Hu Zhuowei,et al. Analysis on the influence of DEM grid size on the accuracy of topographical factors[J]. Science of Surveying and Mapping, 2012, 37(6): 150-152. [毕晓玲, 李小娟, 胡卓玮, 等. DEM网格尺寸对地形因子精度的影响分析[J]. 测绘科学, 2012, 37(6): 150-152.]
[22] Li Sanmei, Fu Hua, Huang Zhen, et al. Snow depth retrieval using EOS/MODIS[J]. Arid Land Geography, 2006, 29(5): 718-724. [李三妹, 傅华, 黄镇, 等. 用EOS/MODIS资料反演积雪深度参量[J]. 干旱区地理, 2006, 29(5): 718-724.]
[23] Liu Yujie, Yang Zhongdong. The theory and algorithm of remote sensing information processing using EOS/MODIS data[M]. Beijing: Science Proess, 2001: 183-198. [刘玉洁, 杨忠东. MODIS遥感信息处理原理预算法[M]. 北京: 科学出版社, 2001: 183-198.]
[24] Wei Wenshou, Qin Dahe, Liu Mingzhe. Properties and structure of the seasonal snow cover in the northwest regions of China[J]. Arid Land Geography, 2001, 24(4): 310-313. [魏文寿, 秦大河, 刘明哲. 中国西北地区季节性积雪的性质与结构[J]. 干旱区地理, 2001, 24(4): 310-313.]
[25] Woodhouse I H. Introduction to microwave remote sensing[M]. Dong Xiaolong, Xu Xing'ou, Xu Xiyu, trans. Beijing: Science Press, 2014: 122-140. [Iain H. Woodhouse. 微波遥感导论[M]. 董晓龙, 徐星欧, 徐曦煜, 译. 北京: 科学出版社, 2014: 122-140.]
[26] Cao Meisheng, Li Xin, Chen Xianzhang, et al. Remote sensing of cryosphere[M]. Beijing: Science Press, 2006: 92-121. [曹梅盛, 李新, 陈贤章, 等.冰冻圈遥感[M]. 北京: 科学出版社, 2006: 92-121.]