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基于HJ-1B数据的雪盖提取方法研究——以军塘湖流域为例
  • ISSN号:1000-6060
  • 期刊名称:《干旱区地理》
  • 时间:0
  • 分类:TP79[自动化与计算机技术—控制科学与工程;自动化与计算机技术—检测技术与自动化装置]
  • 作者机构:[1]新疆大学资源与环境科学学院,新疆乌鲁木齐830046, [2]新疆大学绿洲生态教育部重点实验室,新疆乌鲁木齐830046
  • 相关基金:新疆大学2009年博士启动基金(07020428040),国家自然科学基金(40871023)资助
中文摘要:

HJ-1A、1B卫星具有较高的时间和空间分辨率,适合小流域尺度的积雪动态监测研究。本文基于HJ-1B数据,选取军塘湖流域,针对同时具有HJ-1B/CCD、IRS数据和只有HJ-1B/CCD数据两种情况展开雪盖提取方法研究。对于第一种情况,因研究区南端有大面积森林覆盖,会影响雪像元识别,选用NDSI和田两种雪盖指数,并利用NDVI或TM影像反演的林区辅助判识积雪。结果表明:当有植被信息辅助分类时,两种雪盖指数均能较好提取出森林覆盖区的积雪,且提取结果基本一致,精度较高。对于第二种情况,因无法计算雪盖指数,采用光谱与纹理信息结合的SVM法提取雪盖,提取的面积和精度与上述方法相比略低,但很接近,说明在缺少IRS数据的情况下,仅利用CCD仍可提取出较为准确的雪盖,满足实际应用需求。

英文摘要:

In mid-to high-latitudes and alpine regions snow cover plays a vital role in regional climate. Area and spatial distribution of snow cover in alpine regions varies significantly over time, due to seasonal and interannual variations in climate. Therefore, there is a need for monitoring the area and spatial distribution of snow cover. Re- cently, remote sensing data become the most popular source for acquiring the snow cover information. There are many optical remote sensing data sources are used for extracting snow cover information, such as NOAA/AVHRR, EOS/MODIS, LandsatTM/ETM + and so on. Compared to these data sources, HJ -1A and HJ -1B satellites both have comparatively higher temporal and spatial resolution and it is more conducive to monitor the variations of snow cover at small watershed. At present, the study on the methods of extracting snow cover information based on HJ - 1 A and HJ - 1B data is less. In this paper we exploited the methods for extraction of snow cover information in two cases, both HJ - 1B/CCD and HJ - 1B/IRS data and just HJ - 1B/CCD data. The reason we chose the two cases is that, the two optical satellites HJ - 1A and HJ - 1 B, operating in constellation now, are capable of providing a whole-territory coverage period in visible light spectrum in two days, infrared in four days. So sometimes we can only obtain CCD image, which can not use the method of normalized snow index to extract snow cover information. Since a large area of forest distribute in the south of the study area, the snow pixels are difficult to identify, so for the first case, choose NDSI and $3 normalized snow indexes and assisted with the NDVI or forest area which re- trieved from TM image to extract snow cover. For NDSI, which uses reflectance values of red and SWIR spectral bands of HJ - 1B. And $3 index uses reflectance values of NIR, red and SWIR spectral bands. As it showed that, with the aid of vegetation information, the snow cover can be well extracted by two types of normalized snow index. Meanwhile, the r

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期刊信息
  • 《干旱区地理》
  • 北大核心期刊(2011版)
  • 主管单位:中国科学院出版委
  • 主办单位:中国科学院新疆生态与地理研究所 新疆地理学会
  • 主编:陈曦
  • 地址:乌鲁木齐北京南路818号
  • 邮编:830011
  • 邮箱:aridlg@ms.xjb.ac.cn
  • 电话:0991-7885506
  • 国际标准刊号:ISSN:1000-6060
  • 国内统一刊号:ISSN:65-1103/X
  • 邮发代号:58-45
  • 获奖情况:
  • 1994-1996、1997-1999年度科技期刊质量评比优秀期...,1999-2000年度科技期刊质量评比优秀期刊二等奖
  • 国内外数据库收录:
  • 英国农业与生物科学研究中心文摘,日本日本科学技术振兴机构数据库,中国中国科技核心期刊,中国北大核心期刊(2004版),中国北大核心期刊(2008版),中国北大核心期刊(2011版),中国北大核心期刊(2014版),中国北大核心期刊(2000版)
  • 被引量:18207