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高光谱遥感数据具有波段多、数据量大、处理复杂等特点, 基于GPU的高性能计算在遥感领域得到了快速发展, 为高光谱数据的快速处理提供了硬件和技术条件。采用GPU对高光谱遥感数据常用的SAM、PPI等处理算法进行应用实验, 验证基于GPU的高光谱遥感数据快速处理技术。实验采用新疆东天山地区的一景星载Hyperion数据, 利用支持IDL开发语言的GPULib、CUDA运行时API库进行算法效率的验证, 结果表明, 基于GPU的高光谱数据处理效率比常规的多核CPU主机处理效率有较大提升, 具有一定的应用推广价值。 相似文献
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Real‐time hybrid simulation (RTHS) is increasingly being recognized as a powerful cyber‐physical technique that offers the opportunity for system evaluation of civil structures subject to extreme dynamic loading. Advances in this field are enabling researchers to evaluate new structural components/systems in cost‐effective and efficient ways, under more realistic conditions. For RTHS, performance metric clearly needs to be developed to predict and evaluate the accuracy of various partitioning choices while incorporating the dynamics of the transfer system, and computational/communication delays. In addition, because of the dynamics of the transfer system, communication delays, and computation delays, the RTHS equilibrium force at the interface between numerical and physical substructures is subject to phase discrepancy. Thus, the transfer system dynamics must be accommodated by appropriate actuator controllers. In this paper, a new performance indicator, predictive performance indicator (PPI), is proposed to assess the sensitivity of an RTHS configuration to any phase discrepancy resulting from transfer system dynamics and computational/communication delays. The predictive performance indicator provides a structural engineer with two sets of information as follows: (i) in the absence of a reference response, what is the level of fidelity of the RTHS response? and (ii) if needed, what partitioning adjustments can be made to effectively enhance the fidelity of the response? Moreover, along with the RTHS stability switch criterion, this performance metric may be used as an acceptance criteria for conducting single‐degree‐of‐freedom RTHS. Copyright © 2014 John Wiley & Sons, Ltd. 相似文献
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针对无约束最小二乘混合像元分解算法提取地物端元丰度出现的局限性问题,通过野外实地采集的地物光谱数据建立研究区典型的地物波谱库,以Landsat OLI影像作为主要数据源,在经过Gram-Schmidt(GS)影像融合的基础上,利用纯净像元指数(PPI)及基于几何顶点的端元提取技术提取研究区典型地物端元,最后通过完全约束的最小二乘混合像元分解算法完成对研究区典型地物端元丰度的提取。结果较好地解决了无约束最小二乘混合像元分解算法提取的端元丰度信息出现负值的情况,并且提高了典型地物丰度信息提取的精度。完全约束最小二乘混合像元分解算法的RMSE误差均控制在0.174 913左右,在很大程度上提高了混合像元分解精度及实用性。 相似文献
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Spring greening in boreal forest ecosystems has been widely linked to increasing temperature, but few studies have attempted to unravel the relative effects of climate variables such as maximum temperature (TMX), minimum temperature (TMN), mean temperature (TMP), precipitation (PRE) and radiation (RAD) on vegetation growth at different stages of growing season. However, clarifying these effects is fundamental to better understand the relationship between vegetation and climate change. This study investigated spatio-temporal divergence in the responses of Finland’s boreal forests to climate variables using the plant phenology index (PPI) calculated based on the latest Collection V006 MODIS BRDF-corrected surface reflectance products (MCD43C4) from 2002 to 2018, and identified the dominant climate variables controlling vegetation change during the growing season (May–September) on a monthly basis. Partial least squares (PLS) regression was used to quantify the response of PPI to climate variables and distinguish the separate impacts of different variables. The study results show the dominant effects of temperature on the PPI in May and June, with TMX, TMN and TMP being the most important explanatory variables for the variation of PPI depending on the location, respectively. Meanwhile, drought had an unexpectedly positive impact on vegetation in few areas. More than 50 % of the variation of PPI could be explained by climate variables for 68.5 % of the entire forest area in May and 87.7 % in June, respectively. During July to September, the PPI variance explained by climate and corresponding spatial extent rapidly decreased. Nevertheless, the RAD was found be the most important explanatory variable to July PPI in some areas. In contrast, the PPI in August and September was insensitive to climate in almost all of the regions studied. Our study gives useful insights on quantifying and identifying the relative importance of climate variables to boreal forest, which can be used to predict the possible response of forest under future warming. 相似文献
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多普勒雷达速度图像识别及散度提取方法研究 总被引：2，自引：2，他引：2
大尺度风场往往是冷暖平流与大尺度辐合辐散运动相结合的结果,因此将大尺度风场的多普勒雷达速度特征提炼成以下4种类型:(1)暖平流与辐合迭加;(2)冷平流与辐合迭加;(3)暖平流与辐散迭加;(4)冷平流与辐散迭加。不同类型的风场引起零速度线不同的弯曲特征,对判断大尺度风场的辐合辐散有着指示作用。根据零速度线的弯曲程度以及一定距离圈上零速度点与雷达中心连线的夹角等,首先推导出定量计算大气辐合辐散值的算法,然后提出利用逐个调整法识别零速度点的方法。根据该算法,结合零速度点的识别技术,提出了图像识别原理与方法步骤。据此,能够从多普勒雷达基数据中提取出大气平均散度,得到大尺度天气系统不同高度的散度值,并进一步提出了散度平面位置显示(divergence PPI)的概念。通过实例,根据散度PPI与速度PPI的对比,分析了图像识别的效果,并将图像识别法提取的散度值与EVAD技术提取的散度值进行了对比分析。 相似文献
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利用高空、地面环流形势图、欧洲数值预报产品和大同地区C波段单多普勒雷达产品中的反射率因子、径向速度和VWP产品,对2009年11月9—10日发生在大同地区的暴雪天气过程进行综合分析。结果表明：地面回流和高低空急流是产生强降雪的主要原因;较大降雪回波与连续性降雨回波存在相同特点。利用大面积降水的多普勒雷达PPI径向速度零线的朝向、正负速度面积和径向速度值的大小定性判断辐合辐散图像特征与根据零速度线的弯曲程度、一定距离圈上零速度点与雷达中心连线夹角计算出的辐散值相比较,表明两种方法具有较好的一致性,可以在实际工作中对辐合、辐散快速判断。由重新处理的雷达原始资料求得每30 min的雷达风廓线资料,可以清楚地展示强降雪风场的垂直结构及其变化,直观地反映降水过程中的风场变化特征。 相似文献
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ALI 遥感数据在岩矿信息提取中的应用研究 总被引：1，自引：0，他引：1
论文对研究区ALI数据进行了纯净像元提取,在此基础上,对纯净像元进行N-D散点图分析,选择出不同端元并进行归类分析,作为后期分类识别的样本.这里采用决策树方法对研究区岩矿进行识别,研究发现:样本区在MNF变换后图像上的波谱(前几个波段)可分性远远大于其在变换前图像上的波谱可分性,基于此的决策树分类方法能够识别出岩矿. 相似文献
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713雷达数据判读与地学可视化 总被引：1，自引：1，他引：0
713型气象雷达为我国自主设计的固定式测雨雷达,目前我国西北部和中部地区的一些气象局仍在使用。文章简要介绍了713雷达的平面位置显示器(PPI)和距离高度显示器(RHI)两种数据的结构和格式,在充分解析后,采用Visual Basic.NET2005开发语言,完成了对两种雷达回波数据的准确判读。并结合GIS二次开发组件MapX,采用常规天气雷达数据产生回波图像的算法,提出并实现了极坐标系下的雷达平显回波图和高显回波图的地学线型与面型可视化,最大限度恢复了雷达数据中存储的回波信息,为准确分析区域降水提供了依据。 相似文献