聚集指数CI(Clumping Index)是植被冠层的一个重要结构参数,对植被冠层的辐射截获,以及全球碳、水循环的研究均有重要作用。现有星载CI产品的估算主要是基于CI-NDHD(Normalized Difference between Hotspot and Dark spot)线性模型方法...聚集指数CI(Clumping Index)是植被冠层的一个重要结构参数,对植被冠层的辐射截获,以及全球碳、水循环的研究均有重要作用。现有星载CI产品的估算主要是基于CI-NDHD(Normalized Difference between Hotspot and Dark spot)线性模型方法,由于针叶林和阔叶林在叶片尺度上存在聚集层级的差异,该模型对它们分别采用了不同的模型系数。但是,该模型对中粗分辨率的针阔混交林像元通常采用阔叶林的CI反演系数,因此,理论上会导致该类型CI的高估。为此,本文提出了一种动态选取混交林像元端元CI组分的方法,以改进针阔混交林植被聚集指数的估算精度。首先,通过国际地圈—生物圈计划(IGBP)的地表类型和描述二向性反射分布函数BRDF(Bidirectional Reflectance Distribution Function)特征的地表各向异性平整指数AFX(Anisotropic Flat Index)进行双重约束,逐像元地计算端元CI值;然后,结合高分辨率的土地覆盖分类数据确定端元在像元中的面积比例,并估算MODIS针阔混交林像元的聚集指数MFCI(Mixed Forest CI);最后,将方法应用于研究区MODIS数据的MFCI估算,并通过地面实测数据进行精度评价。结果表明:目前的MODIS产品算法高估了针阔混交林像元的CI值,而MFCI估算方法在CI-NDHD算法的基础上,可以较显著地改善该类型聚集指数的估算精度,当针叶林树种成数达到60%时,精度改善可达28.03%,其中,改进结果的均方根误差(RMSE)和偏差(Bias)各降低约84%和175%。研究表明,MFCI方法对针阔混合像元的端元组分的变化敏感,在高分辨率地表分类已知的条件下,MFCI方法为针阔混交林CI产品生产和精度提高提供了可行的解决方案。展开更多
In order to study the mechanism of steam explosion caused by the interactionbetween coolant and melted metal drops with high temperature,the process of explosion generated by water following interaction with molten me...In order to study the mechanism of steam explosion caused by the interactionbetween coolant and melted metal drops with high temperature,the process of explosion generated by water following interaction with molten metal drops is carried out.In the experiment,liquid aluminum and water with different ratios and different temperatures were evaluated,and the influence of different water temperatures on the steam explosion was studied.The corresponding rules of steam explosion at the different experimental conditions were derived.The difference between experiment resultants was analyzed.The experimental results show that when the ratios of liquid aluminum to water are within a certain range,explosions maybe happen,and the higher the temperature of water is,the less likely explosions will occur while other conditions remain the same.The research results would provide an insight into controlling steam explosion.展开更多
文摘聚集指数CI(Clumping Index)是植被冠层的一个重要结构参数,对植被冠层的辐射截获,以及全球碳、水循环的研究均有重要作用。现有星载CI产品的估算主要是基于CI-NDHD(Normalized Difference between Hotspot and Dark spot)线性模型方法,由于针叶林和阔叶林在叶片尺度上存在聚集层级的差异,该模型对它们分别采用了不同的模型系数。但是,该模型对中粗分辨率的针阔混交林像元通常采用阔叶林的CI反演系数,因此,理论上会导致该类型CI的高估。为此,本文提出了一种动态选取混交林像元端元CI组分的方法,以改进针阔混交林植被聚集指数的估算精度。首先,通过国际地圈—生物圈计划(IGBP)的地表类型和描述二向性反射分布函数BRDF(Bidirectional Reflectance Distribution Function)特征的地表各向异性平整指数AFX(Anisotropic Flat Index)进行双重约束,逐像元地计算端元CI值;然后,结合高分辨率的土地覆盖分类数据确定端元在像元中的面积比例,并估算MODIS针阔混交林像元的聚集指数MFCI(Mixed Forest CI);最后,将方法应用于研究区MODIS数据的MFCI估算,并通过地面实测数据进行精度评价。结果表明:目前的MODIS产品算法高估了针阔混交林像元的CI值,而MFCI估算方法在CI-NDHD算法的基础上,可以较显著地改善该类型聚集指数的估算精度,当针叶林树种成数达到60%时,精度改善可达28.03%,其中,改进结果的均方根误差(RMSE)和偏差(Bias)各降低约84%和175%。研究表明,MFCI方法对针阔混合像元的端元组分的变化敏感,在高分辨率地表分类已知的条件下,MFCI方法为针阔混交林CI产品生产和精度提高提供了可行的解决方案。
文摘In order to study the mechanism of steam explosion caused by the interactionbetween coolant and melted metal drops with high temperature,the process of explosion generated by water following interaction with molten metal drops is carried out.In the experiment,liquid aluminum and water with different ratios and different temperatures were evaluated,and the influence of different water temperatures on the steam explosion was studied.The corresponding rules of steam explosion at the different experimental conditions were derived.The difference between experiment resultants was analyzed.The experimental results show that when the ratios of liquid aluminum to water are within a certain range,explosions maybe happen,and the higher the temperature of water is,the less likely explosions will occur while other conditions remain the same.The research results would provide an insight into controlling steam explosion.
