排序方式： 共有33条查询结果，搜索用时 171 毫秒
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我国新型自主的极轨气象卫星风云3号A星（简称FY-3A）上搭载的中分辨率光谱成像仪（MERSI）为大面积雪监测提供了新的遥感数据源。以中国西北祁连山区为例,分析FY-3A/MERSI传感器积雪与其它地物的图谱特征差异,建立了适用于FY-3A/MERSI的归一化差分积雪指数（NDSI）,以此为基础,构建了综合利用多光谱判别指标及土地覆盖类型（LULC）定类辅助的积雪判识模型,生成250 m分辨率的日积雪制图产品。模型通过逐步逼近的树状判别结构,去除了易和积雪混淆的部分乔木林、云、云阴影、水体、湖冰、沙（盐）地等地物,并提出应考虑积雪下覆地表特性的影响,调整设定不同LULC类型的积雪判别阈值约束,实时结合区域LULC影像进行积雪的最终判定与优化。对祁连山区2010-2011年积雪季FY-3A/MERSI影像的积雪制图应用结果表明,该资料能够客观精细地反映积雪的空间分布与动态发展过程。同时利用气象台站积雪观测记录及Terra/MODIS积雪判识结果进行对比验证,结果表明基于FY-3A/MERSI建立的积雪判识模型具有较高的精度和稳定性,特别是提高了云雪区分的效能。 相似文献
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Mohsin Jamil Butt 《水文研究》2012,26(24):3689-3698
Estimation of snow cover characteristics (snow grain size, snow contamination, snow depth and liquid water content) from satellite data are important components for many hydrological models used for the water resource management. This research aimed to use Landsat ETM+ (Enhanced Thematic Mapper Plus) data to estimate the snow pack characteristics in northern Pakistan. The Normalized Difference Snow Index (NDSI), Snow Contamination Index (SCI) and Snow Grain Size Index (SGI) are applied to estimate the snow cover characteristics in northern Pakistan for the first time. Qualitative maps are generated to show the snow cover distribution, snow contamination concentration and snow grain size distribution over snow cover area. Our results show that NDSI, SCI and SGI can be effectively used to identify snow area, contaminated snow and ageing snow. Furthermore, the results of the current study indicate that in the HKH region 99.8% of the snow is least contaminated whereas 94.50% of the area has fine snow grain size. As no such attempt in the past has been made in northern Pakistan, it is envisaged that the results of this study will be helpful in planning remote sensing data for the water resource management and in characterizing the snow cover for the climate change applications in the region. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
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基于NDVI背景场的雪盖制图算法探索 总被引：5，自引：0，他引：5
NDSI算法提取MSS雪盖面积时,受到MSS影像缺少短波红外波段的局限。为充分精确提取MSS影像的雪盖面积,本文探索一种以NDVI为背景场的雪盖制图新思路。该方法首先在辐射校正时利用6S模型反演地表反射率,然后根据各地物的光谱特性差异和NDVI特性差异,在ENVI软件SPECTRAL模块中创建冰雪光谱阈值查找表。通过ETM＋和TM影像的三个例证,详细阐明该算法流程以及查找表的创建,并以NDSI对其雪盖制图进行精度验证。结果一致表明,与常规的分类方法（最大似然法）相比较,本文探索的NDVI背景场算法有更高的总体精度和Kappa系数。 相似文献
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The Cordillera Blanca, located in the central zone of the Andes Mountains in Peru, has shown a retreat in its glaciers. This paper presents a trend analysis of the glacier area over the groups of Nevados Caullaraju-Pastoruri from 1975 to 2010 using Landsat-5 Thematic Mapper (TM) imagery. In the case of the Nevados Pastoruri/Tuco, the study period was extended back to 1957 by using an aerial photograph taken that year. The extent of clean glacier ice was estimated using Normalized Difference Snow Index (NDSI) thresholds. Moreover, the estimation of debris-covered glacier ice was retrieved by means of a decision tree classification method using NDSI, Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST). Area estimations derived from Landsat imagery were compared to the glacier ground-truth data in 1975 and 2010. Results show a statistically significant (p < 0.05) decreasing trend over the whole study area. Total glacier area decreased at a rate of 4.5 km2 per decade from 1975 to 2010, with a total loss of 22.5 km2 (58%). Lower decreasing rates were found for the period 1987–2010: 3.5 km2 per decade with a total loss of 7.7 km2 (32.5%). In the case of the Nevados Pastoruri/Tuco, decreasing rates of clean ice extent were constant for the periods 1957–2010, 1975–2010 and 1987–2010, with values close to 1.4 km2 per decade and a total loss between 1957 and 2010 estimated at about 5 km2 (54%). This work shows an evident area decrease in the Caullaraju-Pastoruri tropical glaciers, which needs to be included in a future hydrological scenario of local adaptability and water management. 相似文献
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纳木那尼峰地区冰川信息的综合提取方法 总被引：1，自引：0，他引：1
以喜马拉雅山脉西段的纳木那尼峰地区为例,基于ASTER遥感数据,采用波段比值法、ND-SI指数法等多种方法,自动提取冰川信息,对比分析各方法在山体阴影与非阴影区冰川提取的优势和局限,并集成各方法的优势综合提取该地区的冰川.结果表明,在阴影区ASTER3/AsTER4波段比值法提取的冰川信息更准确,而在非阴影区,NDSI指数法的提取结果较准确.综合波段比值法和NDSI指数法在阴影区和非阴影区的优势,分别提取阴影区和非阴影区的冰川,集成两部分结果,并采用掩膜方法剔除高海拔基岩区的积雪,得到了研究区的冰川数据. 相似文献
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以木孜塔格峰地区为研究区,从不同坡度、坡向的样方内测量雪深和采集光谱,通过分析归一化差分雪盖指数（Normalized Difference Snow Index,NDSI）、反照率、HJ-1卫星的红外波段反射率与雪深的相关关系,建立了适用于HJ-1星的积雪深度反演模型,估算出2012年4月14日-25日木孜塔格峰地区的雪深时空变化,并结合实测数据进行验证。结果表明:反照率反演模型的复相关系数为0.992;通过NDSI阈值区分混合雪盖像元和积雪像元,雪深估测精度可达92.78%。冰川区的反照率、NDSI与海拔的相关系数分别为0.626和0.733,且高海拔带反照率值明显高于低海拔带的反照率值。受西风带降雪的影响,非冰川区的北坡雪深值较大;西坡、南坡次之;东坡最小,且雪深最大值出现在坡度约等于10°处。雪深估测的相对误差随着样地的坡度增大而增加,坡度为15°时相对误差较大。 相似文献
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利用TM图像提取玛纳斯河流域上游积雪信息的方法研究 总被引：1，自引：0，他引：1
在我国干旱地区,天山是融水占年径流量比重较大的山区,在天山地区,冰雪为许多河流和生态环境的生存发展提供水资源,所以对冰雪的定量监测非常重要。通过对TM图像云和雪的光谱特征分析以及几种常用积雪信息提取方法的比较,以及对玛纳斯河流域上游地区的积雪进行实际检测,认为雪盖指数法是TM图像提取积雪的较佳技术手段。 相似文献
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以山东省为研究区域,利用2009年9月MODIS的8 d合成波段反射率产品MOD09,选择特征变量植被指数(NDVI、EVI)、NDWI、NDMI、NDSI及辅助信息DEM,通过选取其中的影像特征组合来确定分类方案,构建各波段组合的CART决策树,对MODIS影像进行分类,得到CART决策树的最优波段组合。结果表明,特征变量DEM、NDVI、EVI对分类结果贡献较大;将CART决策树的分类结果与其相对应的最大似然分类结果进行比较可知,基于影像多特征的CART决策树分类方法能明显提高分类精度。 相似文献
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Snow‐covered areas (SCAs) are the fundamental source of water for the hydrological cycle for some region. Accurate measurements of river discharge from snowmelt can help manage much needed water required for hydropower generation and irrigation purposes. This study aims to apply the snowmelt runoff model (SRM) in the Upper Indus basin by the Astore River in northern Pakistan for the years 2000 to 2006. The Shuttle Radar Topographic Mission (SRTM) data are used to generate the Digital Elevation Model (DEM) of the region. Various variables (snow cover depletion curves (SCDCs), temperature and precipitation) and parameters (degree‐day factor, recession coefficient, runoff coefficients, time lag, critical temperature and temperature lapse rate) are used as input in the SRM. However, snow cover data are direct and an important input to the SRM. Satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS) are used to estimate the SCA. Normalized difference snow index (NDSI) algorithm is applied for snow cover mapping and to differentiate snow from other land features. Nash–Sutcliffe coefficient of determination (R2) and volume difference (DV) are used for quality assessment of the SRM. The results of the current research show that for the study years (2000–2006), the average value of R2 is 0·87 and average volume difference DV is 1·18%. The correlation coefficient between measured and computed runoff is 0·95. The results of the study further show that a high level of accuracy can be achieved during the snowmelt season. The simulation results endorse that the SRM in conjunction with MODIS snow cover product is very useful for water resource management in the Astore River and can be used for runoff forecasts in the Indus River basin in northern Pakistan. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献