内蒙古、新疆、西藏、青海、甘肃和四川的草原区这6大牧区是中国重要的畜牧业生产基地,也是雪灾频发的区域,及时、准确地获取6大牧区雪情时空特征对于防灾减灾,指导畜牧业生产有着重要的现实意义。光学遥感与微波遥感各具优缺点,综合运用MODIS和AMSR-E数据构建草原积雪遥感监测模型,以日为监测单元,以旬为多日合成时段,对中国6大牧区在2008年10月上旬至2009年3月下旬间的草原积雪覆盖范围进行监测,并对监测结果进行检验,以此说明MODIS与AMSR-E数据在雪灾监测方面协同监测的可行性,为其他雪盖遥感监测研究提供参考。
The six main pastoral areas (Xinjiang, Tibet, Qinghai, Sichuan, Gansu, and Inner Mongolia) are the important production base of animal husbandry in China, and also the frequent snow disaster areas. To obtain snow conditions of these pastoral areas timely and accurately is valuable for disaster prevention and reduction. With higher spatial resolution and stronger interpretation, optical remote sensing is better for snow cover identification, but it is vulnerable to cloudy weather. Microwave remote sensing is not easy affected by cloud, but identification accuracy is not high. In this paper, we integrated the two kinds of data to identify snow covers. The MODIS data (optical) are used in cloud-free areas, while AMSR-E data (microwave) are used in the rest areas. According to the method, each single day is defined as monitoring unit, and every ten days compose the image combining unit. The monitoring area covers the six main pastoral areas of China. The monitoring duration is from October 1st, 2008 to March 31st, 2009. The main conclusions are as follows: 1) The grasslands Northern Xinjiang, eastern Tibet, south-west of Qinghai, central Gansu, northern Sichuan, the Xilin Gol, and Hulunbeier of Inner Mongolia are the areas with frequent snow cover. 2) The monitoring area possesses the smallest snow cover in December 10th to 20th, while it has the biggest snow cover in January 1st to 10th. 3) During the monitoring period, the fluctuation of snow-cover area can be concluded in three types: Xinjiang and Inner Mongolia have the single peaks, Tibet and Qinghai have three peaks and three valleys, and Sichuan and Gansu are relatively stable.
[1] Chang A T C,Wilheit T T.Remote sensing of atmospheric water vapor,liquid water and wind speed at ocean surface by passive microwave techniques from the Nimbus 5 satellite[J].Radio Science,1979,14 (5):793-802.
[2] 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.
[3] 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.
[4] 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.
[5] Derksen C,Walker A,Goodison B.Evaluation of passive microwave snow water equivalent retrievals across the boreal forest/tundra transition of western Canada[J].Remote Sensing of Environment,2005,96:315-327.
[6] 聂娟.业务化的雪灾遥感监测及预测[J].中国减灾,2005,5:40~41.
[7] 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.
[8] 延昊. NOAA16卫星积雪识别和参数提取[J].冰川冻土,2004,26(3):369~373.
[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] Hall D K,Riggs G A.Accuracy assessment of the MODIS Snow-cover products[J].Hydrological Processes,2007,21:1534-1547.
[11] Déry S J,Salomonson V V,Stieglitz M,et al. An approach to using snow areal depletion curves inferred from MODIS and its application to land surface modeling in Alaska[J].Hydrological Processes,2005,19:2755-2774.
[12] 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[J].International Journal of Remote Sensing,2004,25(24),5731-5744.
[13] 方墨人,田庆久,李英成,等.青藏高原MODIS图像冰雪信息挖掘与动态监测分析[J].地球信息科学,2005,7(4):10~14.
[14] 黄镇,崔彩霞.基于EOS/ MODIS的新疆积雪监测[J].冰川冻土,2006,28(3):343~346.
[15] 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.
[16] 曾严,鄢俊洁.MODIS数据在积雪检测中的应用[J].测绘与空间地理信息,2005,28(6):97~99.
[17] Pulliainen J.Mapping of snow water equivalent and snow depth in boreal and sub-arcticzones by assimilating space-borne microwave radiometer data and ground-based observations[J].Remote Sensing of Environment,2006,101:257-269.
[18] Wulder M A,Nelson T A,Derksen C,et al.Snow cover variability across central Canada (1978-2002) derived from satellite passive microwave data[J].Climatic Change,2007,82 (1):113-130.
[19] 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.
[20] Foster J L,Hall D K,Eylander J,et al.Blended visible,passive-microwave and scatter meter global snow products. Newfoundland:The 64th Eastern Snow Conference,2007.
[21] Parajka J,Blschl G.Spatio-temporal combination of MODIS images potential for snow cover mapping[J].Water Resources Research,2008,44,W03406.
[22] Liang T G,Zhang X T,Xie H,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.
[23] Gao Y,Xie H J, Lu N,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,2010,385:23-35.
[24] 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[J].Remote Sensing of Environment,2008,112:514-1526.
[25] Wang X,Xie H,Liang T G.Evaluation of MODIS snow cover and cloud mask and its application in northern Xinjiang,China [J].Remote Sensing of Environment,2008,112:1497-1513.
[26] Dressler K A,Leavesley G H,Bales R C,et al.Evaluation of gridded snow water equivalent and satellite snow cover products for mountain basins in a hydrologic model[J].Hydrological Processes,2006,20:673-688.
[27] 杨秀春,曹云刚,徐斌,等.中国北方草原区积雪遥感监测[J].地理研究,2008,27(5):1109~1117.
[28] 杨秀春,曹云刚,徐斌,等.多源遥感数据协同的我国草原积雪范围全天候实时监测[J].地理研究,2009,28(6):1704~1712.
[29] 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.
[30] 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.
[31] 曹云刚,杨秀春,徐斌,等.MODIS在青藏高原大范围积雪制图中的应用及存在的问题[J].科技导报,2007,25(21): 51~54.
[32] Ackerman S,Strabala K,Menzel P,et al.Discriminating clear-sky from cloud with MODIS algorithm theoretical basis document (MOD35).http://modis.gsfc.nasa.gov/data/atbd/atbd_mod06.Pdf.
