青海省积雪监测与青南牧区雪灾预警研究
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摘要
季节性雪被对水文过程和气候具有重要的作用。积雪覆盖面积的动态变化对水体和能量循环以及社会经济和生态环境均具有重大的影响。而且积雪融水是干旱、半干旱地区生态系统的重要水源。冬春季降雪是制约我国牧区畜牧业发展的重要因素。积雪不仅会掩埋牧草,造成畜牧草料供应不足,而且在没有饲草储备或储备不足的牧区,造成大批家畜因冻饿而死亡的情况,从而发生“雪灾”。青海草原辽阔,草原面积3647×104ha,其中可利用草地面积3161×104ha,是我国六大牧区之一。雪灾是青海牧区冬春季节的主要自然灾害,每年10月至次年4月这一时段,青海牧区玉树、果洛、黄南南部、海南南部、祁连山等地区极易出现局地或区域的强降雪天气过程,加之气温较低,积雪难以融化,时常造成大雪封山、冻死、饿死牲畜,使牧区人民生命财产遭受巨大损失。
应用遥感技术动态监测积雪的覆盖面积和反演积雪深度对牧区雪灾监测与评价具有重要意义。本文首先利用可见光MODIS每日积雪产品具有较高空间分辨率(500m)和被动微波AMSR-E SWE不受云影响的特点,合成具有较高积雪识别率的用户自定义每日积雪产品,用于监测青海积雪覆盖面积；其次用被动微波AMSR-E BT每日产品,结合气象地面台站数据,反演青海积雪深度；然后利用MODIS EVI数据结合地面实测,反演青南牧区草地地上生物量；最后依据前面研究得到的积雪覆盖面积、积雪深度、草地载畜量结合青南牧区其他数据库,对建立青南牧区雪灾预警及风险评估模型作方法性研究,以期为青海积雪监测和青南牧区雪灾预警提供科学依据。
通过本文的研究,可以得出如下结论：1)以青海省为研究区,用MODIS/Terra和MODIS/Aqua的每日积雪产品合成新的积雪影像(MOYD10A1),该影像的图像云量比MOD10A1、MYD10A1减少了大约14%。青海用户自定义合成的积雪影像MOYD10A1在各种天气条件下的积雪分类精度为43.7%(MOD10A1的积雪分类精度为43.5%,MYD10A1的积雪分类精度为27.7%)。用MOYD10A1和AMSR-E SWE用户自定义合成积雪影像MAl0A1的积雪分类精度为54.5%,陆地分类精度为89.2%,总分类精度(雪+陆地)为85.5%。2)利用2003-2008年5个积雪季(10-3月)降轨AMSR-E 18和36 GHz波段的水平和垂直极化亮温数据,结合43个气象台站的实测雪深、日最高温等气象数据,分析青海省影响雪深反演的因子,发现湿雪、融雪、大型水体、深霜层等因素严重影响雪深模型的建立,其中深霜层的影响最大。根据剔除不合理数据后的639对有效样本,用不同的亮温差和实测雪深值作回归分析,建立青海省基于AMSR.E亮度温度数据的雪深反演模型SD=0.43(Tb18V—Tb36V)+2.06,用2002-2003年10-3月104对雪深大于3cm的样本,对得到的线性回归模型的反演精度进行评价。结果表明,公式反演的雪深值和实测值之间的各项误差均比较小,可以用于监测研究区雪深。3)以青南牧区为研究区,利用2006年8月和2007年8月的植被指数(MODIS-EVI)和草地地面样方实测值,建立草地地上生物量遥感反演模型,y=297.15e4.9492x(R2=0.5626,N=396)。用2008年草地地面样方实测值代入该公式得出的估测值对比,平均误差为21.06%,其精度为78.94%。依据陈全功的关键场理论,计算出2006年-2008年青南牧区14个县的草地地上生物量、采食牧草总量、理论载畜量、冬春场载畜量和夏秋场载畜量。4)从草地畜牧业角度考虑青南牧区雪灾情况,利用遥感和地理信息技术结合本文第二章、第三章、第四章的结果及研究区统计资料,对青南牧区的积雪、草地、家畜三者之间的关联性进行分析,建立雪灾预警分级指标,最后通过对雪灾发生前的草地抗灾力和家畜承灾体的监测,建立青南牧区的雪灾预警判别模型和风险评估模型,对青南牧区的雪灾预警判别模型和风险评估模型作了方法性研究。
Seasonal snow cover has an important meaning for hydrological process and climate change. The dynamic change of snow cover area influences aquatic system, energy cycle, social economy and ecological system significantly. In addition, snowmelt is primary water source for arid and semiarid ecological system. Winter-spring snowfall is an important restrictive factor of animal husbandry development. Snow cover has some harmful effects, for example, burying forage, shortage of forage. Moreover, snow cover maybe cause snow disaster, because of freezing a large number of livestock to death in the pastoral area which have no or lack of forage storage. In this research, the study area is Qinghai, holding a large rangeland with 3647×104 ha and available pasture with 3161×104 ha, which made the pasture of Qinghai be one of the five six largest pastures in China. Snow disaster is the main natural hazards. In the period from October to April of the next year, because of the series snowfall and low temperature, heavy snow cover and freezing and starving of the livestock to death always happen in Yushu, Guoluo, the south part of Huangnan and Qilianshan, which make local herdsmen lost a lot property or even life.
Snow cover area monitor and snow depth inversion have important implications for snow hazard monitor and evaluation in the pasture. In this study, the combination of MODIS daily images for snow product (with the resolution of 500m) and passive microwave images (AMSR-E SWE) which are not affected by clouds are combined into user-defined daily snow images with higher resolution firstly. Then, based on the passive microwave daily images (AMSR-E TB) and climate data, snow depth of Qinghai is inverted. Finally, using the combination of snow cover area and depth which is obtained in format researches, grazing capacity of the pasture and some other databases, the snow disast early warming and risk evaluation models were built. This study provided a scientifical basis for snow cover and snow disaster monitoring and estimation.
The results of this study indicated that:1) As the study area of Qinghai Province, the cloud cover of the combined image (MOYD10A1) of the MODIS/Terra and MODIS/Aqua daily image for snow product is about 14 percent less than that of MOD10A1 image or MYD10A1 image. For all the climate, the classification accuracy of the user-defined images (MOYD10A1) is 43.7%, compared with that of MOD10A1 (43.5%) and that of MYD10A1 (27.7%). The snow classification accuracy of MA10A1, composited by MOYD10A and AMSR-E SWE, is 54.5%, and the land classification accuracy and overall classification accuracy is 89.2% and 85.5%, respectively.2) The factors which affect the snow depth inversion is analyzed base on the AMSR-E 18 and 36 GHz data during the snow seasons (October to March, from 2003 to 2008) and the sampling data (including snow depth and daily maximum temperature) of 43 meteorological stations. The result shows that the factors like snowmelt, large water body and especially deep frost layer influence the building of snow depth model seriously. According to the 639 pairs data excluding the unreasonable records, the snow depth inversion model (SD= 0.43(Tb18V-Tb36V)+ 2.06) was built based on the regressional analysis of various brightness temperature difference data and snow depth samples. Then the 104 pairs data (the snow depth is over 3cm) from October to March in 2002-2003 was used to evaluate the linear regression model. The result of this evaluation reveals that the obtained inversion model can be used to monitor snow depth of the study area Based on MODIS-EVI and aboveground biomass samples of August 2006 and August 2007 in the south part of Qinghai, the aboveground biomass inversion model (y= 297.15e4.9492x, R2=0.5626, N=396) was built. According to the aboveground biomass samples of 2008, average error of the model is 21.06%. Based on the key pasture theory, the aboveground biomass, total consuming forage, theoretical capacity, winter-spring pasture capacity and summer-autumn capacity of 14 counties are calculated and analylized through 2006 to 2008 in the southern pasture of Qinghai.4) Based on remote sensing, GIS, statistics of the study area and the results of chapter 2, chapter 3 and chapter 4, the relationship among snow cover, rangeland and livestock was analyzed. And the snow disaster warning grade index was put forward. Finally, the snow disaster warning model and the risk assessment model were built based on monitoring the anti-calamity ability of pasture and livestock.
应用遥感技术动态监测积雪的覆盖面积和反演积雪深度对牧区雪灾监测与评价具有重要意义。本文首先利用可见光MODIS每日积雪产品具有较高空间分辨率(500m)和被动微波AMSR-E SWE不受云影响的特点,合成具有较高积雪识别率的用户自定义每日积雪产品,用于监测青海积雪覆盖面积；其次用被动微波AMSR-E BT每日产品,结合气象地面台站数据,反演青海积雪深度；然后利用MODIS EVI数据结合地面实测,反演青南牧区草地地上生物量；最后依据前面研究得到的积雪覆盖面积、积雪深度、草地载畜量结合青南牧区其他数据库,对建立青南牧区雪灾预警及风险评估模型作方法性研究,以期为青海积雪监测和青南牧区雪灾预警提供科学依据。
通过本文的研究,可以得出如下结论：1)以青海省为研究区,用MODIS/Terra和MODIS/Aqua的每日积雪产品合成新的积雪影像(MOYD10A1),该影像的图像云量比MOD10A1、MYD10A1减少了大约14%。青海用户自定义合成的积雪影像MOYD10A1在各种天气条件下的积雪分类精度为43.7%(MOD10A1的积雪分类精度为43.5%,MYD10A1的积雪分类精度为27.7%)。用MOYD10A1和AMSR-E SWE用户自定义合成积雪影像MAl0A1的积雪分类精度为54.5%,陆地分类精度为89.2%,总分类精度(雪+陆地)为85.5%。2)利用2003-2008年5个积雪季(10-3月)降轨AMSR-E 18和36 GHz波段的水平和垂直极化亮温数据,结合43个气象台站的实测雪深、日最高温等气象数据,分析青海省影响雪深反演的因子,发现湿雪、融雪、大型水体、深霜层等因素严重影响雪深模型的建立,其中深霜层的影响最大。根据剔除不合理数据后的639对有效样本,用不同的亮温差和实测雪深值作回归分析,建立青海省基于AMSR.E亮度温度数据的雪深反演模型SD=0.43(Tb18V—Tb36V)+2.06,用2002-2003年10-3月104对雪深大于3cm的样本,对得到的线性回归模型的反演精度进行评价。结果表明,公式反演的雪深值和实测值之间的各项误差均比较小,可以用于监测研究区雪深。3)以青南牧区为研究区,利用2006年8月和2007年8月的植被指数(MODIS-EVI)和草地地面样方实测值,建立草地地上生物量遥感反演模型,y=297.15e4.9492x(R2=0.5626,N=396)。用2008年草地地面样方实测值代入该公式得出的估测值对比,平均误差为21.06%,其精度为78.94%。依据陈全功的关键场理论,计算出2006年-2008年青南牧区14个县的草地地上生物量、采食牧草总量、理论载畜量、冬春场载畜量和夏秋场载畜量。4)从草地畜牧业角度考虑青南牧区雪灾情况,利用遥感和地理信息技术结合本文第二章、第三章、第四章的结果及研究区统计资料,对青南牧区的积雪、草地、家畜三者之间的关联性进行分析,建立雪灾预警分级指标,最后通过对雪灾发生前的草地抗灾力和家畜承灾体的监测,建立青南牧区的雪灾预警判别模型和风险评估模型,对青南牧区的雪灾预警判别模型和风险评估模型作了方法性研究。
Seasonal snow cover has an important meaning for hydrological process and climate change. The dynamic change of snow cover area influences aquatic system, energy cycle, social economy and ecological system significantly. In addition, snowmelt is primary water source for arid and semiarid ecological system. Winter-spring snowfall is an important restrictive factor of animal husbandry development. Snow cover has some harmful effects, for example, burying forage, shortage of forage. Moreover, snow cover maybe cause snow disaster, because of freezing a large number of livestock to death in the pastoral area which have no or lack of forage storage. In this research, the study area is Qinghai, holding a large rangeland with 3647×104 ha and available pasture with 3161×104 ha, which made the pasture of Qinghai be one of the five six largest pastures in China. Snow disaster is the main natural hazards. In the period from October to April of the next year, because of the series snowfall and low temperature, heavy snow cover and freezing and starving of the livestock to death always happen in Yushu, Guoluo, the south part of Huangnan and Qilianshan, which make local herdsmen lost a lot property or even life.
Snow cover area monitor and snow depth inversion have important implications for snow hazard monitor and evaluation in the pasture. In this study, the combination of MODIS daily images for snow product (with the resolution of 500m) and passive microwave images (AMSR-E SWE) which are not affected by clouds are combined into user-defined daily snow images with higher resolution firstly. Then, based on the passive microwave daily images (AMSR-E TB) and climate data, snow depth of Qinghai is inverted. Finally, using the combination of snow cover area and depth which is obtained in format researches, grazing capacity of the pasture and some other databases, the snow disast early warming and risk evaluation models were built. This study provided a scientifical basis for snow cover and snow disaster monitoring and estimation.
The results of this study indicated that:1) As the study area of Qinghai Province, the cloud cover of the combined image (MOYD10A1) of the MODIS/Terra and MODIS/Aqua daily image for snow product is about 14 percent less than that of MOD10A1 image or MYD10A1 image. For all the climate, the classification accuracy of the user-defined images (MOYD10A1) is 43.7%, compared with that of MOD10A1 (43.5%) and that of MYD10A1 (27.7%). The snow classification accuracy of MA10A1, composited by MOYD10A and AMSR-E SWE, is 54.5%, and the land classification accuracy and overall classification accuracy is 89.2% and 85.5%, respectively.2) The factors which affect the snow depth inversion is analyzed base on the AMSR-E 18 and 36 GHz data during the snow seasons (October to March, from 2003 to 2008) and the sampling data (including snow depth and daily maximum temperature) of 43 meteorological stations. The result shows that the factors like snowmelt, large water body and especially deep frost layer influence the building of snow depth model seriously. According to the 639 pairs data excluding the unreasonable records, the snow depth inversion model (SD= 0.43(Tb18V-Tb36V)+ 2.06) was built based on the regressional analysis of various brightness temperature difference data and snow depth samples. Then the 104 pairs data (the snow depth is over 3cm) from October to March in 2002-2003 was used to evaluate the linear regression model. The result of this evaluation reveals that the obtained inversion model can be used to monitor snow depth of the study area Based on MODIS-EVI and aboveground biomass samples of August 2006 and August 2007 in the south part of Qinghai, the aboveground biomass inversion model (y= 297.15e4.9492x, R2=0.5626, N=396) was built. According to the aboveground biomass samples of 2008, average error of the model is 21.06%. Based on the key pasture theory, the aboveground biomass, total consuming forage, theoretical capacity, winter-spring pasture capacity and summer-autumn capacity of 14 counties are calculated and analylized through 2006 to 2008 in the southern pasture of Qinghai.4) Based on remote sensing, GIS, statistics of the study area and the results of chapter 2, chapter 3 and chapter 4, the relationship among snow cover, rangeland and livestock was analyzed. And the snow disaster warning grade index was put forward. Finally, the snow disaster warning model and the risk assessment model were built based on monitoring the anti-calamity ability of pasture and livestock.
引文
[1]Pulliainen, J. Mapping of snow water equivalent and snow depth in boreal and sub-arctic zones by assimilating space-borne microwave radiometer data and ground-based observations. Remote Sensing of Environment,2006,101,257-269.
[2]延昊.利用MODIS和AMSR-E进行积雪制图的比较分析[J].冰川冻土,2005,27(4)：515-519.
[3]刘兴元,梁天刚,郭正刚.雪灾对草地畜牧业影响的评价模型及方法研究[J].西北植物学报,2004,24(1)：94-99.
[4]鲁安新,冯学智,曾群柱.地理信息系统在牧区雪灾研究中的应用[J].灾害学,1996,11(1)：25-29.
[5]裴浩,韩经纬,李云鹏.利用气象卫星监测雪情的研究[J].干旱区资源与环境,1994,8(2)：95-100.
[6]李培基.我国牧区雪灾监测预报研究亟待加强[J].冰川冻土,1996,18(4)：374-375.
[7]陈全功.青海省玉树藏族自治州的雪灾及其防御对策[J].草业科学,1996,13(6)：60-63.
[8]史培军,陈晋.RS与GIS支持下的草地雪灾监测试验研究[J].地理学报,1996,51(4)：296-304.
[9]郝璐,王静爱,满苏尔,等.中国雪灾时空变化及畜牧业脆弱性分析[J].自然灾害学报,2002,11(4)：42-48.
[10]黄晓东,梁天刚.牧区雪灾遥感监测方法的研究[J].草业科学,2005,22(12)：10-16.
[11]王志伟,张学通,周兆叶,等.牧区积雪监测中卫星资料应用的研究现状[J].草业科学,2009,26(1)：32-39.
[12]马林,张青梅,赵春宁,王文英,李锡福,马元仓.青藏高原东部牧区春季雪灾天气的形成及其预报[J].自然灾害学报,2003,12(3)：61-68.
[13]周陆生,王青春,李海红,等.青藏高原东部牧区—暴雪过程雪灾灾情实时预评估方法的研究[J].自然灾害学报,2001,10(2)：58-65.
[14]梁天刚,高新华,刘兴元.阿勒泰地区雪灾遥感监测模型与评价方法[J].应用生 态学报,2004,15(12)：2272-2276.
[15]冯学智,鲁安新,曾群柱.中国主要牧区雪灾遥感监测评估模型研究[J].遥感学报,1997,1(2)：129-135.
[16]李培基.我国牧区雪灾监测预报研究亟待加强——“全国首届牧区雪灾气象服务工作研讨会”简介[J].冰川冻土,1996,18(4)：374-375.
[17]郝璐,王静爱,满苏尔,等.中国雪灾时空变化及畜牧业脆弱性分析[J].自然灾害学报,2002,11(4)：43-48.
[18]高卫东,刘明哲,魏文寿,等.新疆精(河)-伊(宁)铁路沿线雪害形成机制及其防治工程措施[J],山地学报,2005,23(1)：43-52.
[19]周陆生,李海红,王青春.青藏高原东部牧区—暴雪过程及雪灾分布的基本特征[J].高原气象,2000,19(4)：450-458.
[20]周陆生,王青春,李海红,等.青藏高原东部牧区—暴雪过程雪灾灾情实时预评估方法的研究[J].自然灾害学报,2001,10(2)：58-65.
[21]Hall D. K., Riggs, G. A., Salomonson, V. V., et al. MODIS snow-cover products. Remote Sensing of Environment,2002,83,181-194.
[22]Liang, T. G, Huang, X. D., Wu, C. X., et al. An application of MODIS data to snow cover monitoring in a pastoral area:A case study in Northern Xinjiang, China. Remote Sensing of Environment,2007, doi:10.1016/j.rse.2007.06.001.
[23]Rutger, D., Steven, M.,& De, J. Monitoring snow-cover dynamics in northern Fennoscandia with SPOT VEGETATION images. International Journal of Remote Sensing,2004,25(15):2933-2949.
[24]Xiao, X., Zhang, Q., Boles, S., et al. Mapping snow cover in the Pan-Arctic zone using multi-year (1998-2001) images from optical VEGETATION sensor. International Journal of Remote Sensing,2004,25(24),5731-5744.
[25]Cao, Y. G,& Liu, C. The development of snow-cover mapping from AVHRR to MODIS. Geography and Geo-Information Science,2005,21(5),15-19.
[26]曹云刚,刘闯.从AVHRR到MODIS的雪盖制图研究进展[J].地理与地理信息科学,2005,21(5)：15-19.
[27]Hall D. K., Riggs, G. A., Salomonson, V. V, et al. MODIS snow-cover products. Remote Sensing of Environment,2002,83,181-194.
[28]Hall, D. K., Riggs, G. A. Accuracy assessment of the MODIS Snow-cover products. Hydrological Processes,2007,21,1534-1547.
[29]Dagrun V, Rune S. Snow-cover mapping in forests by constrained linear spectral unmixing of MODIS data. Remote Sensing of Environment,2003,88:309-323.
[30]Dery, S. J., Salomonson, V. V., Stieglitz, M., Hall, D. K.,& Appel, I. An approach to using snow areal depletion curves inferred from MODIS and its application to land surface modelling in Alaska. Hydrological Processes,2005,19,2755-2774.
[31]Rodell, M., Houser P. Updating a land surface model with MODIS-derived snow cover. Journal of Hydrometeorology,2004,5:1064-1075.
[32]Zhou, X., Xie, H.,& Hendrickx, J. Statistical evaluation of MODIS snow cover products with constraints from streamflow and SNOTEL measurement. Remote Sensing of Environment,2005,94,214-231.
[33]Liang T, Gao X, Liu X. Snow disaster remote sensing monitoring model and evaluation method in Aletai region. Acta Botanica Boreali-Occidentalia Sin,2004,15(12):2272-2276.
[34]Liang T, Huang X, Wu C, Liu X, Li W, Guo Z, Ren J. An application of MODIS data to snow cover monitoring in a pastoral area:a case study in Northern Xinjiang, China.Remote Sensing of Environment,2008,112:514-1526.;
[35]Liang, T. G., Zhang, X. T., Xie, H.J, et al. Toward improved daily snow cover mapping with advanced combination of MODIS and AMSR-E measurements, Remote Sensing of Environment,2008b,112:3750-3761.
[36]Wulder, M. A., Nelson, T. A., Derksen, C., et al. Snow cover variability across central Canada (1978-2002) derived from satellite passive microwave data. Climatic Change,2007,82(1),113-130.
[37]F Foster JL, Chang A, Hall DK. Comparison of snow mass estimates from a prototype passive microwave snow algorithm, a revised algorithm and a snow depth climatology.Remote Sensing of Environment,1997,62:132-142.;
[38]Kelly, R. E., Chang, A. T. C., Foster J. L. Updated daily. AMSR-E/Aqua daily L3 global snow water equivalent EASE-Grids V001, November to March 2002-2005.
[39]Boulder, CO, USA:National Snow and Ice Data Center. Digital media.
[40]黄敬峰,王秀珍,王人潮,胡新博.天然草地牧草产量遥感综合监测预测模型研究[J].遥感学报,2001,5(1)：69-75.
[41]陈全功,卫亚星,梁天刚,李建龙.遥感技术在草地资源管理上的应用进展[J].国外畜牧学—草原与牧草,1994,1：1-12.
[42]鲁安新,冯学智,曾群柱.我国牧区雪灾遥感判别初步研究-以西藏那曲地区为 试验区[J].自然灾害学报,1994,3(4)：69-77.
[43]鲁安新,冯学智,曾群柱,王丽红.西藏那曲牧区雪灾因子主成分分析[J].冰川冻土,1997,19(2)：180-185.
[44]冯学智,鲁安新,曾群柱.中国主要牧区雪灾遥感监测评估模型研究[J].遥感学报,1997,1(2)：129-135.
[45]刘兴元,梁天刚,郭正刚,李立恒.阿勒泰地区草地畜牧业雪灾的遥感监测与评价[J].草业学报,2003,12(6)：115-120.
[46]刘兴元,梁天刚,郭正刚,张学通.北疆牧区雪灾预警与风险评估方法[J].应用生态学报,2008,19(1)：133-138.
[47]Stanley Q Kidder, Huey-Tzu Wu. A multispectral study of the St. Louis area under snowcovered conditions using NOAA-7 AVHRR data [J].Remote Sensing of Environment,1987,22(2):159-172.
[48]Simpson J J, Stitt J R, Sienko M. Improved estimates of the area extent of snow cover from AVHRR data[J]. Hydrology,1998,204:1-23.
[49]Metsamaki S, Vepsalainen J, Pulliainen J, et al. Improved linear interpolation method for the estimation of snow-covered area from optical data[J]. Remote Sensing of Environment,2002,82(1):64-78.
[50]Salomonson V, Appel I. Estimating fractional snow cover from MODIS using the normalized difference snow index[J]. Remote Sensing of Environment,2004, 89(3):351-360.
[51]曾群柱.黄河上游卫星雪盖监测与融雪径流研究总结[M].见：黄河流域典型地区遥感动态研究.北京：科学出版社,1990.
[52]马虹,仇家琪,徐俊荣.利用GIS复合AVHRR数据进行积雪信息提取方法的研究[J].冰川冻土,1996,18(??)：336-343.
[53]周咏梅,贾生海,刘萍.利用NOAA-AVHRR资料估算积雪参数[J].气象科学,2001,21(1)：117-121.
[54]季泉,孙龙祥,王勇,等.基于MODIS数据的积雪监测[J].遥感信息,2006,(3)：57-58.
[55]陆智,刘志辉,房世峰.MODIS数据的积雪密度遥感监测分析[J].水土保持与应用,2007,(3)：29-30.
[56]刘艳,张璞,李杨,等.基于MODIS数据的雪深反演——以天山北坡经济带为例[J].地理与地理信息科学,2005,21(6)：41-44.
[57]梁天刚,高新华,黄晓东,等.新疆北部MODIS积雪制图算法的分类精度[J].干旱区研究,2007,24(4)：446-451.
[58]惠凤鸣,田庆久,李英成,等.基于MODIS数据的雪情分析研究[J].遥感信息,2004,(4)：35-37.
[59]李甫,伏洋,肖建设,等.青海省2008年年初雪灾及雪情遥感监测与评估[J].青海气象,2008(2)：61-64.
[60]边多,董妍,边巴次仁,等.基于MODIS资料的西藏遥感积雪监测业务化方法[J].气象科技,2008,36(3)：345-348.
[61]Liang T G, Zhang X T, Xie H J, et al.Toward improved daily snow cover mapping with advanced combination of MODIS and AMSR-E measurements[J]. Remote Sensing of Environment,2008,112:3750-3761.
[62]Chang A T C, Foster J L, Hall D K. Nimbus-7 SMMR Derived Global Snow Cover Parameters[J]. Annals of Glaciology,1987,9:39-44.
[63]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,1997,62:132-142.
[64]Tait A. Estimation of Snow Water Equivalent Using Passive Microwave Radiation Data[J]. Remote Sensing of Environment,1998,64:286-291.
[65]Armstong R L, Brodzik M J. Hemispheric-scale comparison and evaluation of passive microwave snow algorithms [J]. Annals of Glaciology,2002,34:38-44.
[66]Biancamaria S, Mognard N M., Boone Aaron, et al. A satellite snow depth multi-year average derived from SSM/I for the high latitude regions [J].Remote Sensing of Environment,2008,112(5):2557-2568.
[67]Grippa M., Mognard N., Le Toana TV, et al. Siberia snow depth climatology derived from SSM/I data using a combined dynamic and static algorithm[J].Remote Sensing of Environment,2004,93(1-2):30-41.
[68]Mognard N M, Josberger E G. Northern Great Plains 1996/97seasonal evolution of snowpack parameters from satellite passive-microwave measurements [J].Annals of Glaciology,2002,34:15-23.
[69]Derksen C, Walker A E, LeDrew E,et al. Time-series analysis of passive-microwave-derived central North American snow water equivalent imagery [J]. Annals of Glaciology,2002,34:1-7.
[70]Derksen C. The contribution of AMSR-E 18.7 and 10.7 GHz measurements to improved boreal forest snow water equivalent retrievals[J].Remote Sensing of Environment,2008,112(5):2701-2710.
[71]Derksen C. The contribution of AMSR-E 18.7 and 10.7 GHz measurements to improved boreal forest snow water equivalent retrievals [J]. Remote Sensing of Environment,2008,112(5):2701-2710.
[72]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.
[73]李培基.中国西部积雪变化特征[J].地理学报,1993,48(6)：505-515.
[74]柏延臣,冯学智,李新,等.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.
[75]高峰,李新,Armstrong R L,等.被动微波遥感在青藏高原积雪业务监测中的初步应用[J].遥感技术与应用,2003,18(6)：360-363.
[76]车涛,李新,高峰.青藏高原积雪深度和雪水当量的被动微波遥感反演[J].冰川冻土,2004,26(3)：363-368.
[77]SUN Zhi-wen, SHI Jian-cheng, JIANG ling-mei, 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,2006, 21(12):1363-1368.
[78]延昊.利用MODIS和AMSR-E进行积雪制图的比较分析[J].冰川冻土,2005,27(4)：515-519.
[79]李晓静,刘玉洁,朱小祥,等.利用SSM/I数据判识我国及周边地区雪盖[J].应用气象学报,2007,18(1)：12-20.
[80]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,2008,26(1)：59-64.
[81]郝璐,高景民,杨春燕.草地畜牧业雪灾灾害系统及减灾对策研究[J].草业科学,2006,23(6)：48-54.
[1]Singer F S, Pohham R W. Non-meteorological observation from weather satellites [J].Astronautics and Aerospace Engineering.1963, 1(3):89-92.
[2]Matson M. NOAA satellite snow cover data.Palaeogeography and Palaeoecology[J].1991,90:213-218.
[3]Ramsay B. Prospects for the interactive multisensor snow and Ice Mapping System (IMS) [C].Proceedings of the 57th Eastern Snow Conference, Syracuse, NY, East Snow Conference.2000:161-170.
[4]Carroll T R. Operational airborne and satellite snow cover products of the National Operational Hydrologic Remote Sensing Center[C].Proceedings of the forty-seventh annual Eastern Snow Conference, Bangor, Maine, CRREL Special Report. June 7-8,1990:90-44.
[5]Rango A. Snow hydrology processes and remote sensing [J].Hydrological Processes.1993,7:121-138.
[6]Hall D K, Riggs G A, Salomonson V V. Development of methods for mapping global snow cover using moderate resolution imaging spectroradiometer data. Remote Sensing of Environment.1995,54:127-140.
[7]Xiao X, Shen Z, Qin X. Assessing the potential of VEGETATION sensor data for mapping snow and ice cover:a Normalized Difference Snow and Ice Index [J]. International Journal of Remote Sensing.2001,22(13):2479-2487.
[8]Xiao X, MooreⅢ B, Qin X, Shen Z, Stephen Boles. Large-Scale observations of alpine snow and ice cover in Asia:Using multi-temporal VEGETATION sensor data [J].International Journal of Remote Sensing.2002,23(11):2213-2228.
[9]Hall D K, Riggs G A, Salomonson V V, et al. MODIS snow-cover products [J]. Remote sensing of Environment.2002,83:181-194.
[10]Riggs G A, Hall D K, Salomonson V V. MODIS Snow Products User Guide Collection 5 [C].2006, http://modis-snow-ice.gsfc.nasa.gov/sugkc2.html.
[11]Bitner D, Carroll T, Cline D, et al. An assessment of the differences between three satellite snow cover mapping techniques[J].Hydrological Processes.2002, 16:3723-3733.
[12]Romanov P, Gutman G, Csiszar I. Automated monitoring of snow cover over North American with multispectral satellite data[J].Journal of Applied Meteorology.2000,39:1866-1880.
[13]Klein A, Barnett A C. Validation of daily MODIS snow maps of the Upper Rio Grande River
[14]Maurer M P, Rhoads J D, Dubayah R O, et al. Evaluation of the snow-covered area data product from MODIS[J].Hydrological Processes.2003,17:59-71.
[15]Lee S W, Klein A G, Over T M.A comparison of MODIS and NOHRSC snow-cover products for simulating streamflow using the Snowmelt Runoff Model[J].Hydrological Processes.2005,19:2951-2972.
[16]Zhou X, Xie H, Hendrickx J M H. Statistical evaluation of remotely sensed snow-cover products with constraints from streamflow and SNOTEL measurements [J]. Remote Sensing of Environment.2005,94:214-231.
[17]Hall D K, Riggs G A. Accuracy assessment of the MODIS snow products [J].Hydrological Processes.2007,21:1534-1547.
[18]傅华,沙依然,黄镇,等.MODIS积雪遥感监测系统的研制[J].气象.2007,33(3)：411-416.
[19]郝晓华,王建,李弘毅.MODIS雪盖制图中NDSI阈值的检验—以祁连山中部山区为例[J].冰川冻土.2008,30(10)：132-138.
[20]张学通,黄晓东,梁天刚,陈全功.新疆北部地区MODIS积雪遥感数据MOD10A1的精度分析[J].草业学报.2008,17(2)：110-117.
[21]Tian Gang Liang, Xiao Dong Huang, Cai Xia Wu, et al. An application of MODIS data to snow cover monitoring in a pastoral area:A case study in Northern Xinjiang, China [J].Remote Sensing of Environment.2008, 112:1514-1526.
[22]Xianwei Wang, Hongjie Xie, Tiangang Liang. Evaluation of MODIS snow cover and cloud mask and its application in Northern Xinjiang, China [J].Remote Sensing of Environment.2008,112:1497-1513.
[23]Nolin A W, Dozier J, Mertes L A K. Mappingalpine snow using a spectral mixture modeling technique[J].Ann. Glaciol.1993a,17:121-24.
[24]Rosenthal W, Dozier J. Automated mapping of montane snow cover at subpixel resolution from the Landsat Thematic Mapper [J].Water Resources Research.1996, 32(1):115-130.
[25]Painter T H, Robert D A, Green R O, et al.The effect of grain size on spectral mixture analysis of snow-covered area from AVIRIS data[J].Remote Sensing of Environment.1998,65(3):320-332.
[26]Painter T H, Dozier J, Roberts D A, et al. Retrieval of subpixel snow-covered area and grain size from imaging spectrometer data[J].Remote Sensing of Environment.2003,85(1):64-77.
[27]Barton J S, Hall D, Riggs G A. Remote sensing of fractional snow cover using Moderate Resolution Imaging Spectroradiometer (MODIS) data[C].Proceedings of the 57 Eastern Snow Conference, NY, USA.2000:171-183.
[28]Kaufman Y J, Kleidman R G, Hall D K, et al. Remote sensing of subpixel snow cover using 0.66 and 2.1 μm channels[J]. Geophys.Res.Lett.2002,29:1781. DOI:1029/2001GL013580.
[29]Salomonson V V, Appel I. Estimating the fractional snow covering using the normalized difference snow index [J].Remote Sensing of Environment.2004, 89:251-360.
[30]曹云刚,刘闯.一种简化的MODIS亚像元积雪信息提取方法[J].冰川冻土.2006,28(4)：562-567.
[31]金翠,张柏,刘殿伟,等.东北地区MODIS亚像元积雪覆盖率反演及验证[J].遥感技术与应用.2008,23(2)：195-202.
[32]Wang X., H. Xie, T. Liang, X. Huang. Comparison and Validation of MODIS Standard and New Combination of Terra and Aqua Snow Cover Products in Northern Xinjiang, China[J]. Hydrological Processes,2008, doi: 10.1002/hyp.7151.
[33]Liang, T. G, Zhang, X. T., Xie, H.J, et al.Toward improved daily snow cover mapping with advanced combination of MODIS and AMSR-E measurements, Remote Sensing of Environment 112:3750-3761.
[34]YANG Gao, Hongjie Xie, Ning Lu, et al. Toward advanced daily cloud-free snow cover and snow water equivalent products from Terra-Aqua MODIS and Aqua AMSR-E measurements [J]. Journal of Hydrology,2010, online.
[35]肖锋.青海省草地资源及保护利用对策[J].草业与畜牧,2006,132(11)：37-39.
[36]Barnes W L, Pagano T S, Salomonson V V. Prelaunch characteristics of the Moderate Resolution Imaging Spectroradiometer (MODIS) on EOS-AM1 [J]. IEEE Transaction on Geoscience and Remote Sensing.1998,36(4):1088-1100.
[37]Hall D K, Riggs G A, Salomonson V V. Algorithm Theoretical Basis Document(ATBD) for the MODIS Snow and Sea Ice-Mapping Algorithms[R].2001.
[3.8]Riggs G A, Hall D K, Salomonson V V. MODIS Snow Products User Guide Colletion 5[R].2006.
[39]Brown RD.2000. Northern Hemisphere snow cover variability and change, 1915-1997[J]. Journal of Climate 13:2339-2355.
[40]Bussieres N, de Seve D, Walker AE.2002. Evaluation of MODIS snow cover products over Canadian regions. In Proceedings of IGARSS.2002, Toronto.
[41]Klein A G, Barnett A,C. Validation of Daily MODIS Snow Cover Maps of the Upper Rio Grande River Basin for the 2000-2001 Snow Year[J]. Remote Sensing of Environment 2003,86:162-176.
[42]Simic A, Fernandes R, Brown R, et al. Validation of VEGETATION, MODIS, and GOES+SSM/I Snow-cover Products over Canada Based on Surface Snow Depth Observations[J]. Hydrological Process,2004,18:1089-1104.
[1]裴欢.基于MODIS数据的北疆积雪信息提取及其应用研究[D].新疆大学硕士研究生学位论文,2006.
[2]周陆生,李海红,王青春.青藏高原东部牧区—暴雪过程及雪灾分布的基本特征[J].高原气象,2000,19(4)：450-458.
[3]周陆生,王青春,李海红,等.青藏高原东部牧区—暴雪过程雪灾灾情实时预评估方法的研究[J].自然灾害学报,2001,10(2)：58-65.
[4]柯长青,李培基.青藏高原积雪分布与变化特征[J].地理学报,1998,53(3)：209-215.
[5]柯长青,李培基.用EOF方法研究青藏高原积雪深度分布与变化[J].冰川冻土,1998,20(1)：64-67.
[6]SUN Zhi-wen, SHI Jian-cheng, JIANG ling-mei, 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,2006, 21(12):1363-1368.
[7]延昊.利用MODIS和AMSR-E进行积雪制图的比较分析[J].冰川冻土,2005,27(4)：515-519.
[8]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,1997,62:132-142.
[9]Biancamaria Sylvain, Mognard Nelly M., Boone Aaron, et al. A satellite snow depth multi-year average derived from SSM/I for the high latitude regions[J].Remote Sensing of Environment,2008,112(5):2557-2568.
[10]Sylvain Biancamaria, Nelly M. Mognard, Aaron Boone, et al. A satellite snow depth multi-year average derived from SSM/I for the high latitude regions[J].Remote Sensing of Environment,2008,112(5):2557-2568.
[11]延昊,张佳.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,2008,26(1)：59-64.
[12]Chang A T C, Foster J L, Hall D K. Nimbus-7 SMMR Derived Global Snow Cover Parameters[J]. Annals of Glaciology,1987,9:39-44.
[13]Armstong R L, Brodzik M J. Hemispheric-scale comparison and evaluation of passive microwave snow algorithms [J].Annals of Glaciology,2002,34:38-44.
[14]Derksen C. The contribution of AMSR-E 18.7 and 10.7 GHz measurements to improved boreal forest snow water equivalent retrievals [J].Remote Sensing of Environment,2008,112(5):2701-2710.
[15]曹梅盛,李培基,Robinson D A,等.中国西部积雪SSMR微波遥感的评价与初步应用[J].环境遥感,1993,8(3)：260-269.
[16]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.
[17]李培基.中国西部积雪变化特征[J].地理学报,1993,48(6)：505-515.
[18]柏延臣,冯学智,李新,等.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.
[19]高峰,李新,Armstrong R L,等.被动微波遥感在青藏高原积雪业务监测中的初步应用[J].遥感技术与应用,2003,18(6)：360-363.
[20]车涛,李新.利用被动微波遥感数据反演我国积雪深度及其精度评价[J].遥感技术与应用,2004,19(5)：301-306.
[21]车涛,李新,高峰.青藏高原积雪深度和雪水当量的被动微波遥感反演[J].冰川冻土,2004,26(3)：363-368.
[22]李晓静,刘玉洁,朱小祥,等.利用SSM/I数据判识我国及周边地区雪盖[J].应用气象学报,2007,18(1)：12-20.
[23]Walker A E, Goodison B E. Discrimination of a wet snow cover using passive microwave satellite data[J]. Annals of Glaciology.,1993,17:307-311.
[1]田庆久,闵祥军.植被指数研究进展[J].地球科学进展,1998,13(4)：327-322.
[2]张登荣,赵元洪.土流失强度遥感快速调查方法[J].浙江大学学报(自然科学版),1997,31(6)：753-759.
[3]胡新博,王承军,顾祥,等.新疆荒漠、半荒漠草地的遥感应用研究[J].草食家畜,1996,3：33-37.
[4]张新跃,周俗,唐川江,等.四川省莎草、杂类草草地生产力遥感监测[J].草业科学,2009,26(6)：57-61.
[5]徐斌,杨秀春.东北草原区产草量和载畜平衡的遥感估算[J].地理研究,2009,28(2)：402-408.
[6]张俊华,张佳宝,贾科利.不同施肥条件下夏玉米光谱特征与叶绿素含量和LAI的相关性[J].西北植物学报,,2008,28(7)：1461-1467.
[7]王福民,黄敬峰,唐延林.采用不同光谱波段宽度的归一化植被指数估算水稻叶面积指数[J].应用生态学报,2007,18(11)：2444-2450.
[8]俞联平,李发弟,李新媛,等.基于3S技术的甘肃省甘州区荒漠草地生产力评价[J].草原和草坪,2008,5：36-39.
[9]秦元伟,赵庚星,姜曙千,等.基于中高分辨率卫星遥感数据的县域冬小麦估产[J].农业工程学报,2009,25(7)：118-123.
[10]王正兴,刘闯,A.Huete.植被指数研究进展：从AVHRR-NDVI到MODIS-EVI[J].生态学报,2003,23(5)：979-987.
[11]左丽君,张增祥,董婷婷,等.MODIS/NDVI和MODIS/EVI在耕地信息提取中的应用及对比分析[J].农业工程学报,2008,24(3)：167-172.
[12]王文种,张友静.半干旱区旱情监测指数应用分析[J].地球信息科学,2008,10(2)：273-278.
[13]于凤鸣,卓义,包玉海.基于BP神经网络和MODIS-EVI时间序列的土地覆被分类[J].测绘科学,2008,33：203-204.
[14]李红军,郑力,雷玉平等.基于EOS/MODIS数据的NDVI与EVI比较研究[J].地理科学进展,2007,26(1)：26-32.
[15]闫峰,史培军,武建军,等.基于MODIS-EVI数据的河北省冬小麦生育期特征[J].生态学报,2008,28(9)：4381-4387.
[16]王正兴,刘闯,赵冰茄,等.利用MODIS增强型植被指数反演草地地上生物量[J].兰州大学学报(自然科学版),2005,41(2)：11-16.
[17]于嵘,蔡博峰,温庆可,等.基于MODIS植被指数的西北农业灌溉区生物量估算[J].农业工程学报,2008,24(10)：141—144.
[18]李霞.北疆地区草地地上生物量遥感监测研究[D].兰州大学硕士研究生学位论文,2008.
[19]秦海蓉,孔庆秀.青南牧区草地生态环境现状及对策[J].青海草业,2005,14(1)：48-51.
[20]卓玛措.青南枚区雪灾危害及对策探讨[J].青海环境,1997,7(3)：138-140.
[21]冯蜀青,刘青春,金义安等.利用EOSMODIS进行牧草产量监测的研究[J].青海草业,2004,13(3)：6-10.
[22]陈乾.基于MOD13产品水稻遥感估产模型研究[J].农业工程学报,2006,22(3)：79-83.
[23]张霞,张兵,卫征等.MODIS光谱指数监测小麦长势变化研究[J].中国图像图形学报,2005,10(4)：420-425.
[24]王正兴,刘闯,赵冰茹.利用MODIS增强型植被指数反演草地地上生物量[J].兰州大学学报,2005,41(2)：10-16.
[25]陶伟国,徐斌,缪建明,等.草地遥感估产中不同尺度信息源关联方法对比及评价[J].中国草地学报,2006,28(4)：68-74.
[26]李永宏,莫文红,杨持,等.内蒙古主要草原植物群落地上生物量和理论载畜量及其与气候的关系[J].干旱区资源与环境,1994,(4)：43-50.
[27]陈全功.关键场与季节放牧及草地畜牧业的可持续发展[J].草业学报,2005,14(4)：29-34.
[28]任继周,王钦,胡自治,等.草原生产流程及季节畜牧业[J].中国农业科学,1978,(2)：87.
[29]任继周,胡自治,牟新待.关于草原生产能力及其评定的新指标——畜产品单位[J].中国畜牧杂志,1979,(2)：18-21.
[30]任继周,南志标,郝敦元.草业系统中的界面论[J].草业学报,2000,9(1)：1-8.
[31]任继周,万长贵.系统耦合与荒漠—绿洲草地农业系统—以祁连山—临泽剖面为例[J].草业学报,1994,3(3)：1-8.
[32]任继周,朱兴运.中国河西走廊草地农业的基本格局和它的系统相悖—草原退化的机理初探[J].草业学报,1995,4(1)：69-79.
[33]陈全功.中国草原监测的现状与发展J].草业科学,2008,25(2)：29-38.
[34]雷风.青南牧区草地载畜量对放牧家畜繁活率的影响[J].青海草业,2000,9(2)：13-16.
[1]冯学智,曾群柱,鲁安新,等.我国主要牧区雪灾遥感监测与评估研究[A].中国气象局气象服务与气候司,牧区雪灾的分析研究[C].北京：气象出版社,1998：95-97.
[2]顾钟炜,梁凤仙,曾群柱,等.我国积雪强度特征和牧区雪灾的分级标准、危险程度研究[A].中国科学院兰州冰川冻土研究所.兰州冰川冻土研究所集刊[C].北京：科学出版社,1995：1-7.
[3]黄朝迎.我国草原牧区雪灾及危害[J].灾害学,1988,13(4)：45-48.
[4]鲁安新,冯学智,曾群柱.我国牧区雪灾遥感判别初步研究——以西藏那曲地区为试验区[J].自然灾害学报,1994,3(4)：69-76.
[5]刘兴元,梁天刚,郭正刚,等.北疆牧区雪灾预警与风险评估方法[J].应用生态学报,2008,19(1)：133-138.
[6]冯学智,曾群柱,鲁安新,等.我国主要牧区雪灾遥感监测与评估研究[A].中国气象局气象服务与气候司,牧区雪灾的分析研究[C].北京：气象出版社,1998：95-97.
[7]鲁安新,冯学智,曾群柱.我国牧区雪灾遥感判别初步研究——以西藏那曲地区为试验区[J].自然灾害学报,1994,3(4)：69-76.
[8]仝川,雍世鹏,雍伟义,等.温带草原放牧场积雪灾害分级评价的遥感分析[J].内蒙古大学学报(自然科学版),1996,27(4)：531-537.
[9]冯学智,鲁安新,曾群柱.中国主要牧区雪灾遥感监测评估模型研究[J].遥感学报,1997,1(2)：129-134.
[10]鲁安新,冯学智,曾群柱,等.西藏那曲牧区雪灾因子主成分分析[J].冰川冻土,1997,19(2)：180-185.
[11]王希娟,时兴合,徐亮,等.青南高原雪灾模拟评估与服务对策[J].青海科技,2000,7(1)：12-15.
[12]周陆生,汪青春,李海红,等.青藏高原东部牧区大—暴雪过程雪灾灾情实时预评估方法的研究[J].自然灾害学报,2001,10(2)：58-65.
[13]李硕,冯学智,左伟.西藏那曲牧区雪灾区域危险度的模糊综合评价研究[J]. 自然灾害学报,2001,10(1)：86-91.
[14]郝璐,王静爱,满苏尔,等.中国雪灾时空变化及畜牧业脆弱性分析[J].自然灾害学报,2002,11(4)：42-48.
[15]刘兴元,陈全功,梁天刚,等.新疆阿勒泰牧区雪灾遥感监测体系构建与灾害评价系统研究[J].应用生态学报,2006,17(2)：215-220.
[16]梁天刚,刘兴元,郭正刚.基于3S技术的牧区雪灾评价方法[J].草业学报,2006,15(4)：122-128.
[17]梁天刚,高新华,刘兴元.阿勒泰地区雪灾遥感监测模型与评价方法[J].应用生态学报,2004,15(12)：2272-2276.
[18]刘兴元,梁天刚,郭正刚,等.阿勒泰地区草地畜牧业雪灾的遥感监测与评价[J].草业学报,2003,12(6)：115-120.
[19]刘兴元,梁天刚,郭正刚.雪灾对草地畜牧业影响的评价模型及方法研究[J].西北植物学报,2004,24(1)：94-99.
[20]赵燕宁,时兴合,秦宁生等.青海南部地区40多年来气候变化的特征分析[J].中国沙漠,2005,25(4)：529-534.
[21]王希娟,时兴合,徐亮,等.青海南部地区初冬雪灾变化及环流特征[J].气象科技,2007,35(3)：345-350.
[22]时兴合,秦宁生,李栋梁,等.青海南部冬季积雪和雪灾变化的特征及其预评估[J].山地学报,2007,25(3)：245-252.
[23]秦海蓉.青南牧区雪灾危害的防御[J].青海草业,2000,9(2)：16-18.
[24]时兴合,秦宁生,唐红玉,等.青海牧区冬春季雪灾预报方法研究[J].青海气象,1998,(4)：2-5.
[25]王劲峰.中国自然灾害影响评价方法研究[M].北京：北京科技出版社,1993.38-79.
[26]王春梅, 王金达,刘景双,等.东北地区森林资源生态风险评价研究[J].应用生态学报,2003,14(6)：867-870.
[27]王江山,周咏梅,赵强,等.青海省牧区雪灾预警模型研究[J].灾害学,1998,13(1)：30-33.
[28]王明涛.多指标综合评价中权系数确定的一种综合分析方法[J].系统工程,1999,8(8)：100-107.
[29]陈全功.青海省玉树藏族自治州的雪灾及其防御对策[J].草业科学,1996,13(6)：60-63.
[2]延昊.利用MODIS和AMSR-E进行积雪制图的比较分析[J].冰川冻土,2005,27(4)：515-519.
[3]刘兴元,梁天刚,郭正刚.雪灾对草地畜牧业影响的评价模型及方法研究[J].西北植物学报,2004,24(1)：94-99.
[4]鲁安新,冯学智,曾群柱.地理信息系统在牧区雪灾研究中的应用[J].灾害学,1996,11(1)：25-29.
[5]裴浩,韩经纬,李云鹏.利用气象卫星监测雪情的研究[J].干旱区资源与环境,1994,8(2)：95-100.
[6]李培基.我国牧区雪灾监测预报研究亟待加强[J].冰川冻土,1996,18(4)：374-375.
[7]陈全功.青海省玉树藏族自治州的雪灾及其防御对策[J].草业科学,1996,13(6)：60-63.
[8]史培军,陈晋.RS与GIS支持下的草地雪灾监测试验研究[J].地理学报,1996,51(4)：296-304.
[9]郝璐,王静爱,满苏尔,等.中国雪灾时空变化及畜牧业脆弱性分析[J].自然灾害学报,2002,11(4)：42-48.
[10]黄晓东,梁天刚.牧区雪灾遥感监测方法的研究[J].草业科学,2005,22(12)：10-16.
[11]王志伟,张学通,周兆叶,等.牧区积雪监测中卫星资料应用的研究现状[J].草业科学,2009,26(1)：32-39.
[12]马林,张青梅,赵春宁,王文英,李锡福,马元仓.青藏高原东部牧区春季雪灾天气的形成及其预报[J].自然灾害学报,2003,12(3)：61-68.
[13]周陆生,王青春,李海红,等.青藏高原东部牧区—暴雪过程雪灾灾情实时预评估方法的研究[J].自然灾害学报,2001,10(2)：58-65.
[14]梁天刚,高新华,刘兴元.阿勒泰地区雪灾遥感监测模型与评价方法[J].应用生 态学报,2004,15(12)：2272-2276.
[15]冯学智,鲁安新,曾群柱.中国主要牧区雪灾遥感监测评估模型研究[J].遥感学报,1997,1(2)：129-135.
[16]李培基.我国牧区雪灾监测预报研究亟待加强——“全国首届牧区雪灾气象服务工作研讨会”简介[J].冰川冻土,1996,18(4)：374-375.
[17]郝璐,王静爱,满苏尔,等.中国雪灾时空变化及畜牧业脆弱性分析[J].自然灾害学报,2002,11(4)：43-48.
[18]高卫东,刘明哲,魏文寿,等.新疆精(河)-伊(宁)铁路沿线雪害形成机制及其防治工程措施[J],山地学报,2005,23(1)：43-52.
[19]周陆生,李海红,王青春.青藏高原东部牧区—暴雪过程及雪灾分布的基本特征[J].高原气象,2000,19(4)：450-458.
[20]周陆生,王青春,李海红,等.青藏高原东部牧区—暴雪过程雪灾灾情实时预评估方法的研究[J].自然灾害学报,2001,10(2)：58-65.
[21]Hall D. K., Riggs, G. A., Salomonson, V. V., et al. MODIS snow-cover products. Remote Sensing of Environment,2002,83,181-194.
[22]Liang, T. G, Huang, X. D., Wu, C. X., et al. An application of MODIS data to snow cover monitoring in a pastoral area:A case study in Northern Xinjiang, China. Remote Sensing of Environment,2007, doi:10.1016/j.rse.2007.06.001.
[23]Rutger, D., Steven, M.,& De, J. Monitoring snow-cover dynamics in northern Fennoscandia with SPOT VEGETATION images. International Journal of Remote Sensing,2004,25(15):2933-2949.
[24]Xiao, X., Zhang, Q., Boles, S., et al. Mapping snow cover in the Pan-Arctic zone using multi-year (1998-2001) images from optical VEGETATION sensor. International Journal of Remote Sensing,2004,25(24),5731-5744.
[25]Cao, Y. G,& Liu, C. The development of snow-cover mapping from AVHRR to MODIS. Geography and Geo-Information Science,2005,21(5),15-19.
[26]曹云刚,刘闯.从AVHRR到MODIS的雪盖制图研究进展[J].地理与地理信息科学,2005,21(5)：15-19.
[27]Hall D. K., Riggs, G. A., Salomonson, V. V, et al. MODIS snow-cover products. Remote Sensing of Environment,2002,83,181-194.
[28]Hall, D. K., Riggs, G. A. Accuracy assessment of the MODIS Snow-cover products. Hydrological Processes,2007,21,1534-1547.
[29]Dagrun V, Rune S. Snow-cover mapping in forests by constrained linear spectral unmixing of MODIS data. Remote Sensing of Environment,2003,88:309-323.
[30]Dery, S. J., Salomonson, V. V., Stieglitz, M., Hall, D. K.,& Appel, I. An approach to using snow areal depletion curves inferred from MODIS and its application to land surface modelling in Alaska. Hydrological Processes,2005,19,2755-2774.
[31]Rodell, M., Houser P. Updating a land surface model with MODIS-derived snow cover. Journal of Hydrometeorology,2004,5:1064-1075.
[32]Zhou, X., Xie, H.,& Hendrickx, J. Statistical evaluation of MODIS snow cover products with constraints from streamflow and SNOTEL measurement. Remote Sensing of Environment,2005,94,214-231.
[33]Liang T, Gao X, Liu X. Snow disaster remote sensing monitoring model and evaluation method in Aletai region. Acta Botanica Boreali-Occidentalia Sin,2004,15(12):2272-2276.
[34]Liang T, Huang X, Wu C, Liu X, Li W, Guo Z, Ren J. An application of MODIS data to snow cover monitoring in a pastoral area:a case study in Northern Xinjiang, China.Remote Sensing of Environment,2008,112:514-1526.;
[35]Liang, T. G., Zhang, X. T., Xie, H.J, et al. Toward improved daily snow cover mapping with advanced combination of MODIS and AMSR-E measurements, Remote Sensing of Environment,2008b,112:3750-3761.
[36]Wulder, M. A., Nelson, T. A., Derksen, C., et al. Snow cover variability across central Canada (1978-2002) derived from satellite passive microwave data. Climatic Change,2007,82(1),113-130.
[37]F Foster JL, Chang A, Hall DK. Comparison of snow mass estimates from a prototype passive microwave snow algorithm, a revised algorithm and a snow depth climatology.Remote Sensing of Environment,1997,62:132-142.;
[38]Kelly, R. E., Chang, A. T. C., Foster J. L. Updated daily. AMSR-E/Aqua daily L3 global snow water equivalent EASE-Grids V001, November to March 2002-2005.
[39]Boulder, CO, USA:National Snow and Ice Data Center. Digital media.
[40]黄敬峰,王秀珍,王人潮,胡新博.天然草地牧草产量遥感综合监测预测模型研究[J].遥感学报,2001,5(1)：69-75.
[41]陈全功,卫亚星,梁天刚,李建龙.遥感技术在草地资源管理上的应用进展[J].国外畜牧学—草原与牧草,1994,1：1-12.
[42]鲁安新,冯学智,曾群柱.我国牧区雪灾遥感判别初步研究-以西藏那曲地区为 试验区[J].自然灾害学报,1994,3(4)：69-77.
[43]鲁安新,冯学智,曾群柱,王丽红.西藏那曲牧区雪灾因子主成分分析[J].冰川冻土,1997,19(2)：180-185.
[44]冯学智,鲁安新,曾群柱.中国主要牧区雪灾遥感监测评估模型研究[J].遥感学报,1997,1(2)：129-135.
[45]刘兴元,梁天刚,郭正刚,李立恒.阿勒泰地区草地畜牧业雪灾的遥感监测与评价[J].草业学报,2003,12(6)：115-120.
[46]刘兴元,梁天刚,郭正刚,张学通.北疆牧区雪灾预警与风险评估方法[J].应用生态学报,2008,19(1)：133-138.
[47]Stanley Q Kidder, Huey-Tzu Wu. A multispectral study of the St. Louis area under snowcovered conditions using NOAA-7 AVHRR data [J].Remote Sensing of Environment,1987,22(2):159-172.
[48]Simpson J J, Stitt J R, Sienko M. Improved estimates of the area extent of snow cover from AVHRR data[J]. Hydrology,1998,204:1-23.
[49]Metsamaki S, Vepsalainen J, Pulliainen J, et al. Improved linear interpolation method for the estimation of snow-covered area from optical data[J]. Remote Sensing of Environment,2002,82(1):64-78.
[50]Salomonson V, Appel I. Estimating fractional snow cover from MODIS using the normalized difference snow index[J]. Remote Sensing of Environment,2004, 89(3):351-360.
[51]曾群柱.黄河上游卫星雪盖监测与融雪径流研究总结[M].见：黄河流域典型地区遥感动态研究.北京：科学出版社,1990.
[52]马虹,仇家琪,徐俊荣.利用GIS复合AVHRR数据进行积雪信息提取方法的研究[J].冰川冻土,1996,18(??)：336-343.
[53]周咏梅,贾生海,刘萍.利用NOAA-AVHRR资料估算积雪参数[J].气象科学,2001,21(1)：117-121.
[54]季泉,孙龙祥,王勇,等.基于MODIS数据的积雪监测[J].遥感信息,2006,(3)：57-58.
[55]陆智,刘志辉,房世峰.MODIS数据的积雪密度遥感监测分析[J].水土保持与应用,2007,(3)：29-30.
[56]刘艳,张璞,李杨,等.基于MODIS数据的雪深反演——以天山北坡经济带为例[J].地理与地理信息科学,2005,21(6)：41-44.
[57]梁天刚,高新华,黄晓东,等.新疆北部MODIS积雪制图算法的分类精度[J].干旱区研究,2007,24(4)：446-451.
[58]惠凤鸣,田庆久,李英成,等.基于MODIS数据的雪情分析研究[J].遥感信息,2004,(4)：35-37.
[59]李甫,伏洋,肖建设,等.青海省2008年年初雪灾及雪情遥感监测与评估[J].青海气象,2008(2)：61-64.
[60]边多,董妍,边巴次仁,等.基于MODIS资料的西藏遥感积雪监测业务化方法[J].气象科技,2008,36(3)：345-348.
[61]Liang T G, Zhang X T, Xie H J, et al.Toward improved daily snow cover mapping with advanced combination of MODIS and AMSR-E measurements[J]. Remote Sensing of Environment,2008,112:3750-3761.
[62]Chang A T C, Foster J L, Hall D K. Nimbus-7 SMMR Derived Global Snow Cover Parameters[J]. Annals of Glaciology,1987,9:39-44.
[63]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,1997,62:132-142.
[64]Tait A. Estimation of Snow Water Equivalent Using Passive Microwave Radiation Data[J]. Remote Sensing of Environment,1998,64:286-291.
[65]Armstong R L, Brodzik M J. Hemispheric-scale comparison and evaluation of passive microwave snow algorithms [J]. Annals of Glaciology,2002,34:38-44.
[66]Biancamaria S, Mognard N M., Boone Aaron, et al. A satellite snow depth multi-year average derived from SSM/I for the high latitude regions [J].Remote Sensing of Environment,2008,112(5):2557-2568.
[67]Grippa M., Mognard N., Le Toana TV, et al. Siberia snow depth climatology derived from SSM/I data using a combined dynamic and static algorithm[J].Remote Sensing of Environment,2004,93(1-2):30-41.
[68]Mognard N M, Josberger E G. Northern Great Plains 1996/97seasonal evolution of snowpack parameters from satellite passive-microwave measurements [J].Annals of Glaciology,2002,34:15-23.
[69]Derksen C, Walker A E, LeDrew E,et al. Time-series analysis of passive-microwave-derived central North American snow water equivalent imagery [J]. Annals of Glaciology,2002,34:1-7.
[70]Derksen C. The contribution of AMSR-E 18.7 and 10.7 GHz measurements to improved boreal forest snow water equivalent retrievals[J].Remote Sensing of Environment,2008,112(5):2701-2710.
[71]Derksen C. The contribution of AMSR-E 18.7 and 10.7 GHz measurements to improved boreal forest snow water equivalent retrievals [J]. Remote Sensing of Environment,2008,112(5):2701-2710.
[72]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.
[73]李培基.中国西部积雪变化特征[J].地理学报,1993,48(6)：505-515.
[74]柏延臣,冯学智,李新,等.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.
[75]高峰,李新,Armstrong R L,等.被动微波遥感在青藏高原积雪业务监测中的初步应用[J].遥感技术与应用,2003,18(6)：360-363.
[76]车涛,李新,高峰.青藏高原积雪深度和雪水当量的被动微波遥感反演[J].冰川冻土,2004,26(3)：363-368.
[77]SUN Zhi-wen, SHI Jian-cheng, JIANG ling-mei, 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,2006, 21(12):1363-1368.
[78]延昊.利用MODIS和AMSR-E进行积雪制图的比较分析[J].冰川冻土,2005,27(4)：515-519.
[79]李晓静,刘玉洁,朱小祥,等.利用SSM/I数据判识我国及周边地区雪盖[J].应用气象学报,2007,18(1)：12-20.
[80]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,2008,26(1)：59-64.
[81]郝璐,高景民,杨春燕.草地畜牧业雪灾灾害系统及减灾对策研究[J].草业科学,2006,23(6)：48-54.
[1]Singer F S, Pohham R W. Non-meteorological observation from weather satellites [J].Astronautics and Aerospace Engineering.1963, 1(3):89-92.
[2]Matson M. NOAA satellite snow cover data.Palaeogeography and Palaeoecology[J].1991,90:213-218.
[3]Ramsay B. Prospects for the interactive multisensor snow and Ice Mapping System (IMS) [C].Proceedings of the 57th Eastern Snow Conference, Syracuse, NY, East Snow Conference.2000:161-170.
[4]Carroll T R. Operational airborne and satellite snow cover products of the National Operational Hydrologic Remote Sensing Center[C].Proceedings of the forty-seventh annual Eastern Snow Conference, Bangor, Maine, CRREL Special Report. June 7-8,1990:90-44.
[5]Rango A. Snow hydrology processes and remote sensing [J].Hydrological Processes.1993,7:121-138.
[6]Hall D K, Riggs G A, Salomonson V V. Development of methods for mapping global snow cover using moderate resolution imaging spectroradiometer data. Remote Sensing of Environment.1995,54:127-140.
[7]Xiao X, Shen Z, Qin X. Assessing the potential of VEGETATION sensor data for mapping snow and ice cover:a Normalized Difference Snow and Ice Index [J]. International Journal of Remote Sensing.2001,22(13):2479-2487.
[8]Xiao X, MooreⅢ B, Qin X, Shen Z, Stephen Boles. Large-Scale observations of alpine snow and ice cover in Asia:Using multi-temporal VEGETATION sensor data [J].International Journal of Remote Sensing.2002,23(11):2213-2228.
[9]Hall D K, Riggs G A, Salomonson V V, et al. MODIS snow-cover products [J]. Remote sensing of Environment.2002,83:181-194.
[10]Riggs G A, Hall D K, Salomonson V V. MODIS Snow Products User Guide Collection 5 [C].2006, http://modis-snow-ice.gsfc.nasa.gov/sugkc2.html.
[11]Bitner D, Carroll T, Cline D, et al. An assessment of the differences between three satellite snow cover mapping techniques[J].Hydrological Processes.2002, 16:3723-3733.
[12]Romanov P, Gutman G, Csiszar I. Automated monitoring of snow cover over North American with multispectral satellite data[J].Journal of Applied Meteorology.2000,39:1866-1880.
[13]Klein A, Barnett A C. Validation of daily MODIS snow maps of the Upper Rio Grande River
[14]Maurer M P, Rhoads J D, Dubayah R O, et al. Evaluation of the snow-covered area data product from MODIS[J].Hydrological Processes.2003,17:59-71.
[15]Lee S W, Klein A G, Over T M.A comparison of MODIS and NOHRSC snow-cover products for simulating streamflow using the Snowmelt Runoff Model[J].Hydrological Processes.2005,19:2951-2972.
[16]Zhou X, Xie H, Hendrickx J M H. Statistical evaluation of remotely sensed snow-cover products with constraints from streamflow and SNOTEL measurements [J]. Remote Sensing of Environment.2005,94:214-231.
[17]Hall D K, Riggs G A. Accuracy assessment of the MODIS snow products [J].Hydrological Processes.2007,21:1534-1547.
[18]傅华,沙依然,黄镇,等.MODIS积雪遥感监测系统的研制[J].气象.2007,33(3)：411-416.
[19]郝晓华,王建,李弘毅.MODIS雪盖制图中NDSI阈值的检验—以祁连山中部山区为例[J].冰川冻土.2008,30(10)：132-138.
[20]张学通,黄晓东,梁天刚,陈全功.新疆北部地区MODIS积雪遥感数据MOD10A1的精度分析[J].草业学报.2008,17(2)：110-117.
[21]Tian Gang Liang, Xiao Dong Huang, Cai Xia Wu, et al. An application of MODIS data to snow cover monitoring in a pastoral area:A case study in Northern Xinjiang, China [J].Remote Sensing of Environment.2008, 112:1514-1526.
[22]Xianwei Wang, Hongjie Xie, Tiangang Liang. Evaluation of MODIS snow cover and cloud mask and its application in Northern Xinjiang, China [J].Remote Sensing of Environment.2008,112:1497-1513.
[23]Nolin A W, Dozier J, Mertes L A K. Mappingalpine snow using a spectral mixture modeling technique[J].Ann. Glaciol.1993a,17:121-24.
[24]Rosenthal W, Dozier J. Automated mapping of montane snow cover at subpixel resolution from the Landsat Thematic Mapper [J].Water Resources Research.1996, 32(1):115-130.
[25]Painter T H, Robert D A, Green R O, et al.The effect of grain size on spectral mixture analysis of snow-covered area from AVIRIS data[J].Remote Sensing of Environment.1998,65(3):320-332.
[26]Painter T H, Dozier J, Roberts D A, et al. Retrieval of subpixel snow-covered area and grain size from imaging spectrometer data[J].Remote Sensing of Environment.2003,85(1):64-77.
[27]Barton J S, Hall D, Riggs G A. Remote sensing of fractional snow cover using Moderate Resolution Imaging Spectroradiometer (MODIS) data[C].Proceedings of the 57 Eastern Snow Conference, NY, USA.2000:171-183.
[28]Kaufman Y J, Kleidman R G, Hall D K, et al. Remote sensing of subpixel snow cover using 0.66 and 2.1 μm channels[J]. Geophys.Res.Lett.2002,29:1781. DOI:1029/2001GL013580.
[29]Salomonson V V, Appel I. Estimating the fractional snow covering using the normalized difference snow index [J].Remote Sensing of Environment.2004, 89:251-360.
[30]曹云刚,刘闯.一种简化的MODIS亚像元积雪信息提取方法[J].冰川冻土.2006,28(4)：562-567.
[31]金翠,张柏,刘殿伟,等.东北地区MODIS亚像元积雪覆盖率反演及验证[J].遥感技术与应用.2008,23(2)：195-202.
[32]Wang X., H. Xie, T. Liang, X. Huang. Comparison and Validation of MODIS Standard and New Combination of Terra and Aqua Snow Cover Products in Northern Xinjiang, China[J]. Hydrological Processes,2008, doi: 10.1002/hyp.7151.
[33]Liang, T. G, Zhang, X. T., Xie, H.J, et al.Toward improved daily snow cover mapping with advanced combination of MODIS and AMSR-E measurements, Remote Sensing of Environment 112:3750-3761.
[34]YANG Gao, Hongjie Xie, Ning Lu, et al. Toward advanced daily cloud-free snow cover and snow water equivalent products from Terra-Aqua MODIS and Aqua AMSR-E measurements [J]. Journal of Hydrology,2010, online.
[35]肖锋.青海省草地资源及保护利用对策[J].草业与畜牧,2006,132(11)：37-39.
[36]Barnes W L, Pagano T S, Salomonson V V. Prelaunch characteristics of the Moderate Resolution Imaging Spectroradiometer (MODIS) on EOS-AM1 [J]. IEEE Transaction on Geoscience and Remote Sensing.1998,36(4):1088-1100.
[37]Hall D K, Riggs G A, Salomonson V V. Algorithm Theoretical Basis Document(ATBD) for the MODIS Snow and Sea Ice-Mapping Algorithms[R].2001.
[3.8]Riggs G A, Hall D K, Salomonson V V. MODIS Snow Products User Guide Colletion 5[R].2006.
[39]Brown RD.2000. Northern Hemisphere snow cover variability and change, 1915-1997[J]. Journal of Climate 13:2339-2355.
[40]Bussieres N, de Seve D, Walker AE.2002. Evaluation of MODIS snow cover products over Canadian regions. In Proceedings of IGARSS.2002, Toronto.
[41]Klein A G, Barnett A,C. Validation of Daily MODIS Snow Cover Maps of the Upper Rio Grande River Basin for the 2000-2001 Snow Year[J]. Remote Sensing of Environment 2003,86:162-176.
[42]Simic A, Fernandes R, Brown R, et al. Validation of VEGETATION, MODIS, and GOES+SSM/I Snow-cover Products over Canada Based on Surface Snow Depth Observations[J]. Hydrological Process,2004,18:1089-1104.
[1]裴欢.基于MODIS数据的北疆积雪信息提取及其应用研究[D].新疆大学硕士研究生学位论文,2006.
[2]周陆生,李海红,王青春.青藏高原东部牧区—暴雪过程及雪灾分布的基本特征[J].高原气象,2000,19(4)：450-458.
[3]周陆生,王青春,李海红,等.青藏高原东部牧区—暴雪过程雪灾灾情实时预评估方法的研究[J].自然灾害学报,2001,10(2)：58-65.
[4]柯长青,李培基.青藏高原积雪分布与变化特征[J].地理学报,1998,53(3)：209-215.
[5]柯长青,李培基.用EOF方法研究青藏高原积雪深度分布与变化[J].冰川冻土,1998,20(1)：64-67.
[6]SUN Zhi-wen, SHI Jian-cheng, JIANG ling-mei, 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,2006, 21(12):1363-1368.
[7]延昊.利用MODIS和AMSR-E进行积雪制图的比较分析[J].冰川冻土,2005,27(4)：515-519.
[8]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,1997,62:132-142.
[9]Biancamaria Sylvain, Mognard Nelly M., Boone Aaron, et al. A satellite snow depth multi-year average derived from SSM/I for the high latitude regions[J].Remote Sensing of Environment,2008,112(5):2557-2568.
[10]Sylvain Biancamaria, Nelly M. Mognard, Aaron Boone, et al. A satellite snow depth multi-year average derived from SSM/I for the high latitude regions[J].Remote Sensing of Environment,2008,112(5):2557-2568.
[11]延昊,张佳.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,2008,26(1)：59-64.
[12]Chang A T C, Foster J L, Hall D K. Nimbus-7 SMMR Derived Global Snow Cover Parameters[J]. Annals of Glaciology,1987,9:39-44.
[13]Armstong R L, Brodzik M J. Hemispheric-scale comparison and evaluation of passive microwave snow algorithms [J].Annals of Glaciology,2002,34:38-44.
[14]Derksen C. The contribution of AMSR-E 18.7 and 10.7 GHz measurements to improved boreal forest snow water equivalent retrievals [J].Remote Sensing of Environment,2008,112(5):2701-2710.
[15]曹梅盛,李培基,Robinson D A,等.中国西部积雪SSMR微波遥感的评价与初步应用[J].环境遥感,1993,8(3)：260-269.
[16]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.
[17]李培基.中国西部积雪变化特征[J].地理学报,1993,48(6)：505-515.
[18]柏延臣,冯学智,李新,等.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.
[19]高峰,李新,Armstrong R L,等.被动微波遥感在青藏高原积雪业务监测中的初步应用[J].遥感技术与应用,2003,18(6)：360-363.
[20]车涛,李新.利用被动微波遥感数据反演我国积雪深度及其精度评价[J].遥感技术与应用,2004,19(5)：301-306.
[21]车涛,李新,高峰.青藏高原积雪深度和雪水当量的被动微波遥感反演[J].冰川冻土,2004,26(3)：363-368.
[22]李晓静,刘玉洁,朱小祥,等.利用SSM/I数据判识我国及周边地区雪盖[J].应用气象学报,2007,18(1)：12-20.
[23]Walker A E, Goodison B E. Discrimination of a wet snow cover using passive microwave satellite data[J]. Annals of Glaciology.,1993,17:307-311.
[1]田庆久,闵祥军.植被指数研究进展[J].地球科学进展,1998,13(4)：327-322.
[2]张登荣,赵元洪.土流失强度遥感快速调查方法[J].浙江大学学报(自然科学版),1997,31(6)：753-759.
[3]胡新博,王承军,顾祥,等.新疆荒漠、半荒漠草地的遥感应用研究[J].草食家畜,1996,3：33-37.
[4]张新跃,周俗,唐川江,等.四川省莎草、杂类草草地生产力遥感监测[J].草业科学,2009,26(6)：57-61.
[5]徐斌,杨秀春.东北草原区产草量和载畜平衡的遥感估算[J].地理研究,2009,28(2)：402-408.
[6]张俊华,张佳宝,贾科利.不同施肥条件下夏玉米光谱特征与叶绿素含量和LAI的相关性[J].西北植物学报,,2008,28(7)：1461-1467.
[7]王福民,黄敬峰,唐延林.采用不同光谱波段宽度的归一化植被指数估算水稻叶面积指数[J].应用生态学报,2007,18(11)：2444-2450.
[8]俞联平,李发弟,李新媛,等.基于3S技术的甘肃省甘州区荒漠草地生产力评价[J].草原和草坪,2008,5：36-39.
[9]秦元伟,赵庚星,姜曙千,等.基于中高分辨率卫星遥感数据的县域冬小麦估产[J].农业工程学报,2009,25(7)：118-123.
[10]王正兴,刘闯,A.Huete.植被指数研究进展：从AVHRR-NDVI到MODIS-EVI[J].生态学报,2003,23(5)：979-987.
[11]左丽君,张增祥,董婷婷,等.MODIS/NDVI和MODIS/EVI在耕地信息提取中的应用及对比分析[J].农业工程学报,2008,24(3)：167-172.
[12]王文种,张友静.半干旱区旱情监测指数应用分析[J].地球信息科学,2008,10(2)：273-278.
[13]于凤鸣,卓义,包玉海.基于BP神经网络和MODIS-EVI时间序列的土地覆被分类[J].测绘科学,2008,33：203-204.
[14]李红军,郑力,雷玉平等.基于EOS/MODIS数据的NDVI与EVI比较研究[J].地理科学进展,2007,26(1)：26-32.
[15]闫峰,史培军,武建军,等.基于MODIS-EVI数据的河北省冬小麦生育期特征[J].生态学报,2008,28(9)：4381-4387.
[16]王正兴,刘闯,赵冰茄,等.利用MODIS增强型植被指数反演草地地上生物量[J].兰州大学学报(自然科学版),2005,41(2)：11-16.
[17]于嵘,蔡博峰,温庆可,等.基于MODIS植被指数的西北农业灌溉区生物量估算[J].农业工程学报,2008,24(10)：141—144.
[18]李霞.北疆地区草地地上生物量遥感监测研究[D].兰州大学硕士研究生学位论文,2008.
[19]秦海蓉,孔庆秀.青南牧区草地生态环境现状及对策[J].青海草业,2005,14(1)：48-51.
[20]卓玛措.青南枚区雪灾危害及对策探讨[J].青海环境,1997,7(3)：138-140.
[21]冯蜀青,刘青春,金义安等.利用EOSMODIS进行牧草产量监测的研究[J].青海草业,2004,13(3)：6-10.
[22]陈乾.基于MOD13产品水稻遥感估产模型研究[J].农业工程学报,2006,22(3)：79-83.
[23]张霞,张兵,卫征等.MODIS光谱指数监测小麦长势变化研究[J].中国图像图形学报,2005,10(4)：420-425.
[24]王正兴,刘闯,赵冰茹.利用MODIS增强型植被指数反演草地地上生物量[J].兰州大学学报,2005,41(2)：10-16.
[25]陶伟国,徐斌,缪建明,等.草地遥感估产中不同尺度信息源关联方法对比及评价[J].中国草地学报,2006,28(4)：68-74.
[26]李永宏,莫文红,杨持,等.内蒙古主要草原植物群落地上生物量和理论载畜量及其与气候的关系[J].干旱区资源与环境,1994,(4)：43-50.
[27]陈全功.关键场与季节放牧及草地畜牧业的可持续发展[J].草业学报,2005,14(4)：29-34.
[28]任继周,王钦,胡自治,等.草原生产流程及季节畜牧业[J].中国农业科学,1978,(2)：87.
[29]任继周,胡自治,牟新待.关于草原生产能力及其评定的新指标——畜产品单位[J].中国畜牧杂志,1979,(2)：18-21.
[30]任继周,南志标,郝敦元.草业系统中的界面论[J].草业学报,2000,9(1)：1-8.
[31]任继周,万长贵.系统耦合与荒漠—绿洲草地农业系统—以祁连山—临泽剖面为例[J].草业学报,1994,3(3)：1-8.
[32]任继周,朱兴运.中国河西走廊草地农业的基本格局和它的系统相悖—草原退化的机理初探[J].草业学报,1995,4(1)：69-79.
[33]陈全功.中国草原监测的现状与发展J].草业科学,2008,25(2)：29-38.
[34]雷风.青南牧区草地载畜量对放牧家畜繁活率的影响[J].青海草业,2000,9(2)：13-16.
[1]冯学智,曾群柱,鲁安新,等.我国主要牧区雪灾遥感监测与评估研究[A].中国气象局气象服务与气候司,牧区雪灾的分析研究[C].北京：气象出版社,1998：95-97.
[2]顾钟炜,梁凤仙,曾群柱,等.我国积雪强度特征和牧区雪灾的分级标准、危险程度研究[A].中国科学院兰州冰川冻土研究所.兰州冰川冻土研究所集刊[C].北京：科学出版社,1995：1-7.
[3]黄朝迎.我国草原牧区雪灾及危害[J].灾害学,1988,13(4)：45-48.
[4]鲁安新,冯学智,曾群柱.我国牧区雪灾遥感判别初步研究——以西藏那曲地区为试验区[J].自然灾害学报,1994,3(4)：69-76.
[5]刘兴元,梁天刚,郭正刚,等.北疆牧区雪灾预警与风险评估方法[J].应用生态学报,2008,19(1)：133-138.
[6]冯学智,曾群柱,鲁安新,等.我国主要牧区雪灾遥感监测与评估研究[A].中国气象局气象服务与气候司,牧区雪灾的分析研究[C].北京：气象出版社,1998：95-97.
[7]鲁安新,冯学智,曾群柱.我国牧区雪灾遥感判别初步研究——以西藏那曲地区为试验区[J].自然灾害学报,1994,3(4)：69-76.
[8]仝川,雍世鹏,雍伟义,等.温带草原放牧场积雪灾害分级评价的遥感分析[J].内蒙古大学学报(自然科学版),1996,27(4)：531-537.
[9]冯学智,鲁安新,曾群柱.中国主要牧区雪灾遥感监测评估模型研究[J].遥感学报,1997,1(2)：129-134.
[10]鲁安新,冯学智,曾群柱,等.西藏那曲牧区雪灾因子主成分分析[J].冰川冻土,1997,19(2)：180-185.
[11]王希娟,时兴合,徐亮,等.青南高原雪灾模拟评估与服务对策[J].青海科技,2000,7(1)：12-15.
[12]周陆生,汪青春,李海红,等.青藏高原东部牧区大—暴雪过程雪灾灾情实时预评估方法的研究[J].自然灾害学报,2001,10(2)：58-65.
[13]李硕,冯学智,左伟.西藏那曲牧区雪灾区域危险度的模糊综合评价研究[J]. 自然灾害学报,2001,10(1)：86-91.
[14]郝璐,王静爱,满苏尔,等.中国雪灾时空变化及畜牧业脆弱性分析[J].自然灾害学报,2002,11(4)：42-48.
[15]刘兴元,陈全功,梁天刚,等.新疆阿勒泰牧区雪灾遥感监测体系构建与灾害评价系统研究[J].应用生态学报,2006,17(2)：215-220.
[16]梁天刚,刘兴元,郭正刚.基于3S技术的牧区雪灾评价方法[J].草业学报,2006,15(4)：122-128.
[17]梁天刚,高新华,刘兴元.阿勒泰地区雪灾遥感监测模型与评价方法[J].应用生态学报,2004,15(12)：2272-2276.
[18]刘兴元,梁天刚,郭正刚,等.阿勒泰地区草地畜牧业雪灾的遥感监测与评价[J].草业学报,2003,12(6)：115-120.
[19]刘兴元,梁天刚,郭正刚.雪灾对草地畜牧业影响的评价模型及方法研究[J].西北植物学报,2004,24(1)：94-99.
[20]赵燕宁,时兴合,秦宁生等.青海南部地区40多年来气候变化的特征分析[J].中国沙漠,2005,25(4)：529-534.
[21]王希娟,时兴合,徐亮,等.青海南部地区初冬雪灾变化及环流特征[J].气象科技,2007,35(3)：345-350.
[22]时兴合,秦宁生,李栋梁,等.青海南部冬季积雪和雪灾变化的特征及其预评估[J].山地学报,2007,25(3)：245-252.
[23]秦海蓉.青南牧区雪灾危害的防御[J].青海草业,2000,9(2)：16-18.
[24]时兴合,秦宁生,唐红玉,等.青海牧区冬春季雪灾预报方法研究[J].青海气象,1998,(4)：2-5.
[25]王劲峰.中国自然灾害影响评价方法研究[M].北京：北京科技出版社,1993.38-79.
[26]王春梅, 王金达,刘景双,等.东北地区森林资源生态风险评价研究[J].应用生态学报,2003,14(6)：867-870.
[27]王江山,周咏梅,赵强,等.青海省牧区雪灾预警模型研究[J].灾害学,1998,13(1)：30-33.
[28]王明涛.多指标综合评价中权系数确定的一种综合分析方法[J].系统工程,1999,8(8)：100-107.
[29]陈全功.青海省玉树藏族自治州的雪灾及其防御对策[J].草业科学,1996,13(6)：60-63.
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