干旱区生态环境知识资源中心(Arid): 亚洲中部干旱区积雪时空变异遥感分析

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	亚洲中部干旱区积雪时空变异遥感分析
其他题名	Spatial-temproal variability of snow cover in arid regions of Central Asia
	陈文倩 1; 丁建丽1 ; 马勇刚 1; 张喆 1; 周杰 2
来源期刊	水科学进展
ISSN	1001-6791
出版年	2018
卷号	29 期号:1 页码:11-19
中文摘要	亚洲中部干旱区的大尺度遥感积雪信息研究,可在跨界河流水资源分配利用方面提供数据支持,对国家重大战略的生态安全保障有重要作用。采用数据融合方法,将MOD10A2和MYD10A2数据进行融合去云处理,结合气象站点积雪数据评估去云后的积雪识别精度;提取积雪覆盖率( SCP)与积雪日数( SCD)信息,分析SCP与SCD年际、年内变化差异;结合数字高程模型,分析不同高程带下SCP的时空变化规律。结果表明: ① MOD10A2与MYD10A2融合去云处理,可有效去除云的干扰,准确提取亚洲中部干旱区积雪变化信息。②年内SCP最大值范围为55.7%~ 77.4%,最小值范围为1.6 %~ 2.9%,融雪期SCP下降速率具有明显地域差异,总体SCP呈缓慢增加趋势。③总体SCD呈略微下降趋势,32.2%的区域呈下降趋势,30.9%的区域呈增加趋势,36.9%的区域保持稳定不变。④海拔1 000 m以下,SCP年内随季节变化呈U型,年际变化显著; 1 000~ 4 000 m区域,SCP年内均随季节的变化呈现出V型,年际变化呈现出稳定性波动; 6 000 m以上为永久性积雪,季节、时空变化差异性均不明显。
英文摘要	Remote sensing of snow information in arid regions of Central Asia can provide data support for the allocation and utilization of water resources in transboundary rivers and play an important role in the ecological security of major national strategies. In this paper,data fusion method was used to merge MOD10A2 and MYD10A2 data for cloud removal and extraction of snow cover. Snow cover data from meteorological stations were used to evaluate the snow recognition accuracy after cloud removal. Information of snow cover percentage ( SCP) and snow day ( SCD) was extracted and analyzed. Temporal and spatial variation of SCP under different elevation zones was analyzed by using digital elevation model ( DEM) . The results showed that: ① The fusion of MOD10A2 and MYD10A2 data can effectively remove cloud and improves the accuracy of snow information extraction. ② During a year,the maximum SCP ranged from 55.7% to 77.4% and the minimum ranged from 1.6% to 2.9%. There was a clear regional difference in the rate of the decline of SCP during the snowmelt period,and the overall SCP showed a slowly increasing trend. ③ The overall SCD showed a slight downward trend,32.2% region showed a downward trend,30.7% region showed an upward trend,36.9% of the region remained stable. ④ Under the altitude of 1 000 m,the annual variation of SCP during the year is U-shaped and the annual variation is significant. In the regions of 1 000-4 000 m,the variation of seasons is V-shaped during the year of SCP,and the annual variation shows a steady fluctuation; permanent snow, temporal and spatial variation of SCP are not obvious.
中文关键词	亚洲中部干旱区 ; 大尺度遥感 ; 时空变异
英文关键词	MOD10A2 MYD10A2 arid regions of Central Asia large-scale in remote sensing MOD10A2 MYD10A2 temporal and spatial variation
语种	中文
国家	中国
收录类别	CSCD
WOS类目	METEOROLOGY ATMOSPHERIC SCIENCES
WOS研究方向	Meteorology & Atmospheric Sciences
CSCD记录号	CSCD:6226167
来源机构	中国科学院新疆生态与地理研究所 ; 新疆大学
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/238247
作者单位	1.新疆大学资源与环境科学学院;;绿洲生态教育部重点实验室, 智慧城市与环境建模自治区普通高校重点实验室;;绿洲生态教育部重点实验室, 乌鲁木齐;;乌鲁木齐, 新疆;;新疆 830046;;830046, 中国; 2.中国科学院新疆生态与地理研究所, 乌鲁木齐, 新疆 830011, 中国
推荐引用方式 GB/T 7714	陈文倩,丁建丽,马勇刚,等. 亚洲中部干旱区积雪时空变异遥感分析[J]. 中国科学院新疆生态与地理研究所, 新疆大学,2018,29(1):11-19.
APA	陈文倩,丁建丽,马勇刚,张喆,&周杰.(2018).亚洲中部干旱区积雪时空变异遥感分析.水科学进展,29(1),11-19.
MLA	陈文倩,et al."亚洲中部干旱区积雪时空变异遥感分析".水科学进展 29.1(2018):11-19.