植被光合有效辐射吸收比例FPAR (Fraction of absorbed Photosynthetically Active Radiation)是碳循环光能利用率模型中的关键参数之一。高分系列卫星的发射,为反演定量遥感产品提供了高时空分辨率的卫星遥感数据,基于高分数据的植被...植被光合有效辐射吸收比例FPAR (Fraction of absorbed Photosynthetically Active Radiation)是碳循环光能利用率模型中的关键参数之一。高分系列卫星的发射,为反演定量遥感产品提供了高时空分辨率的卫星遥感数据,基于高分数据的植被光合有效辐射吸收比例产品能够为生态系统碳循环的分析评估提供更加精细、精度更高的输入参数产品。本文发展了一种基于深度学习的光合有效辐射吸收比例反演方法。该方法利用SAIL(Scattering by Arbitrarily Inclined Leaves)模型模拟多种太阳入射角度、观测角度、大气条件下的植被冠层光合有效辐射吸收比例及冠层反射率,形成海量输入—输出模拟数据集,具有鲁棒性及更好的普适性;基于深度信念网络对数据集进行训练,得到高分一号(GF-1)卫星光合有效辐射吸收比例遥感反演模型。利用中国科学院怀来遥感综合试验站及黑河流域地表过程综合观测网FPAR地面站点连续观测数据对玉米作物、芦苇草地等下垫面反演的FPAR进行了对比验证,RMSE分别为0.15和0.17。本方法以辐射传输模型模拟的多维大气及地表输入—植被冠层输出作为深度学习的训练样本库,弥补了训练样本数量不足及观测数据不全带来的深度学习训练过程中的误差,从而使得模型兼具机理性和高效性。同时,反演的输入为具有太阳角度、观测角度信息的地表反射率产品,降低了输入参数获取的难度,减少输入参数误差传递的影响,有利于实现产品的业务化生产。展开更多
The properties of functionally graded(FG) cellular structures vary spatially, and the varying properties can meet the requirements of different working environments. In this study, we fabricated FG cellular structures...The properties of functionally graded(FG) cellular structures vary spatially, and the varying properties can meet the requirements of different working environments. In this study, we fabricated FG cellular structures with shape memory effect by 4D printing and evaluated the compressive performance and shape memory behavior of these structures with temperature through experimental analysis and finite element simulations. The results show that the maximum energy absorption gradually decreases but the compressive modulus gradually increases with increasing gradient parameters. Moreover, the finite element simulations also show that the compressive deformation mode of the structure shifts from uniform to non-uniform deformation with increasing gradient parameters. The compressive modulus and compressive strength of 4D printed FG structures decrease with increasing temperature due to the influence of the shape memory polymer, and they exhibit outstanding shape recovery capability under high-temperature stimulus. The proposed 4D printed FG structures with such responsiveness to stimulus shed light on the design of intelligent energy-absorbing devices that meet specific functional requirements.展开更多
蒸散发是水循环和能量平衡的重要组成,在地下水监测、农业灌溉等研究中发挥重要作用,但非均匀下垫面会导致遥感估算的水热通量产生空间尺度误差。以Sentinel数据作为基础数据,利用EFAF(Evaporative Fraction and Area Fraction)方法和...蒸散发是水循环和能量平衡的重要组成,在地下水监测、农业灌溉等研究中发挥重要作用,但非均匀下垫面会导致遥感估算的水热通量产生空间尺度误差。以Sentinel数据作为基础数据,利用EFAF(Evaporative Fraction and Area Fraction)方法和温度降尺度法校正水热通量偏差,并且对比两种方法的差异。研究结果表明:EFAF方法和温度降尺度法的精度不相上下,决定系数R^(2)约为0.86,平均偏差MBE约为18 W/m^(2),均方根误差RMSE约为64 W/m^(2),两种方法的精度都高于未校正潜热通量的精度,对于校正非均匀下垫面造成的潜热通量偏差有一定的效果。EFAF方法估算的潜热通量在像元尺度上的分布与土地分类数据一致,在区域尺度上和未校正的潜热通量分布一致。温度降尺度法估算的潜热通量在像元尺度上与地表温度的分布高度相似,其空间细节信息更加丰富,局部特征明显。展开更多
中国属于太阳能资源丰富的国家之一,光伏装机量位居世界第一,未来其装机量仍会不断增加。本文拟利用遥感技术获取区域太阳能资源的时空分布,采用多因子评价模型对中国地区大型光伏电站区域适宜性进行评估,以期为光伏电站的选址提供科学...中国属于太阳能资源丰富的国家之一,光伏装机量位居世界第一,未来其装机量仍会不断增加。本文拟利用遥感技术获取区域太阳能资源的时空分布,采用多因子评价模型对中国地区大型光伏电站区域适宜性进行评估,以期为光伏电站的选址提供科学依据。结合太阳总辐射、日照时数的稳定程度、离路网的距离、离城镇的距离和坡向5个因子,通过设定海拔以及土地覆盖类型对应的限制区域,利用Mu Sy Q辐射产品、DEM、道路网数据、VIIRS夜间灯光数据、土地覆盖产品得到因子图层,使用层次分析法确定各因子在模型中的权重,借助GIS进行叠加分析并分为"低适宜"、"较适宜"、"适宜"、"非常适宜"和"限制区"5类,得到光伏电站建设的空间适宜性分布。研究结果表明,西北地区的适宜区占全国的53.0%,"非常适宜"区占全国的47.3%,其累计光伏电站装机量占全国的45.6%。建设光伏电站的"适宜"和"非常适宜"区面积的大小与装机量的多少没有明显的线性关系。"非常适宜"区作为光伏电站的最佳建设场所,光伏发电潜力大于2016年全国发电量的5倍。同时,国家政策制定的装机规模指标以及光电补贴政策对光伏电站的选址也起了一定的指向作用。展开更多
To satisfy the requirement of surface energy budget research on the meso-and micro-scale,a parameterization is developed to calculate high spatial resolution,clear-sky downward longwave radiation(DLR)from HJ-1B therma...To satisfy the requirement of surface energy budget research on the meso-and micro-scale,a parameterization is developed to calculate high spatial resolution,clear-sky downward longwave radiation(DLR)from HJ-1B thermal data.The DLR algorithm is established based on extensive radiative transfer simulation and statistical analysis.To address the problem that HJ-1B has a single thermal channel and lacks atmospheric information,the brightness temperature of HJ-1B and water vapor content are used in the algorithm.An accuracy evaluation and error analysis for the algorithm is conducted using a simulated radiation dataset.The result shows that the algorithm performs well in most circumstances,but there is obvious underestimation when water vapor content is greater than 4g/cm2 .Error analysis indicates the accuracy of estimated DLRs is affected by uncertainties in input parameters,including water vapor content and top-of-atmosphere radiance.It is also affected by the difference between ground and near-surface air temperature.The algorithm is applied to actual HJ-1B data,and validated by ground data from six stations in the Heihe River and Haihe River basins.The estimated DLRs have good consistency with measured data except at Huazhaizi,and root mean square errors at most sites are around 20W/m2 ,which is slightly better than the result of MODIS. There is significant overestimation of DLR at Huazhaizi during summer,which is mainly produced by the large ground-air temperature difference.A correction process based on temperature difference is proposed and applied at Huazhaizi.The result shows that the positive bias is largely diminished after correction.展开更多
文摘植被光合有效辐射吸收比例FPAR (Fraction of absorbed Photosynthetically Active Radiation)是碳循环光能利用率模型中的关键参数之一。高分系列卫星的发射,为反演定量遥感产品提供了高时空分辨率的卫星遥感数据,基于高分数据的植被光合有效辐射吸收比例产品能够为生态系统碳循环的分析评估提供更加精细、精度更高的输入参数产品。本文发展了一种基于深度学习的光合有效辐射吸收比例反演方法。该方法利用SAIL(Scattering by Arbitrarily Inclined Leaves)模型模拟多种太阳入射角度、观测角度、大气条件下的植被冠层光合有效辐射吸收比例及冠层反射率,形成海量输入—输出模拟数据集,具有鲁棒性及更好的普适性;基于深度信念网络对数据集进行训练,得到高分一号(GF-1)卫星光合有效辐射吸收比例遥感反演模型。利用中国科学院怀来遥感综合试验站及黑河流域地表过程综合观测网FPAR地面站点连续观测数据对玉米作物、芦苇草地等下垫面反演的FPAR进行了对比验证,RMSE分别为0.15和0.17。本方法以辐射传输模型模拟的多维大气及地表输入—植被冠层输出作为深度学习的训练样本库,弥补了训练样本数量不足及观测数据不全带来的深度学习训练过程中的误差,从而使得模型兼具机理性和高效性。同时,反演的输入为具有太阳角度、观测角度信息的地表反射率产品,降低了输入参数获取的难度,减少输入参数误差传递的影响,有利于实现产品的业务化生产。
基金supported by the National Natural Science Foundation of China (Grant Nos.12072094 and 12172106)。
文摘The properties of functionally graded(FG) cellular structures vary spatially, and the varying properties can meet the requirements of different working environments. In this study, we fabricated FG cellular structures with shape memory effect by 4D printing and evaluated the compressive performance and shape memory behavior of these structures with temperature through experimental analysis and finite element simulations. The results show that the maximum energy absorption gradually decreases but the compressive modulus gradually increases with increasing gradient parameters. Moreover, the finite element simulations also show that the compressive deformation mode of the structure shifts from uniform to non-uniform deformation with increasing gradient parameters. The compressive modulus and compressive strength of 4D printed FG structures decrease with increasing temperature due to the influence of the shape memory polymer, and they exhibit outstanding shape recovery capability under high-temperature stimulus. The proposed 4D printed FG structures with such responsiveness to stimulus shed light on the design of intelligent energy-absorbing devices that meet specific functional requirements.
文摘蒸散发是水循环和能量平衡的重要组成,在地下水监测、农业灌溉等研究中发挥重要作用,但非均匀下垫面会导致遥感估算的水热通量产生空间尺度误差。以Sentinel数据作为基础数据,利用EFAF(Evaporative Fraction and Area Fraction)方法和温度降尺度法校正水热通量偏差,并且对比两种方法的差异。研究结果表明:EFAF方法和温度降尺度法的精度不相上下,决定系数R^(2)约为0.86,平均偏差MBE约为18 W/m^(2),均方根误差RMSE约为64 W/m^(2),两种方法的精度都高于未校正潜热通量的精度,对于校正非均匀下垫面造成的潜热通量偏差有一定的效果。EFAF方法估算的潜热通量在像元尺度上的分布与土地分类数据一致,在区域尺度上和未校正的潜热通量分布一致。温度降尺度法估算的潜热通量在像元尺度上与地表温度的分布高度相似,其空间细节信息更加丰富,局部特征明显。
文摘中国属于太阳能资源丰富的国家之一,光伏装机量位居世界第一,未来其装机量仍会不断增加。本文拟利用遥感技术获取区域太阳能资源的时空分布,采用多因子评价模型对中国地区大型光伏电站区域适宜性进行评估,以期为光伏电站的选址提供科学依据。结合太阳总辐射、日照时数的稳定程度、离路网的距离、离城镇的距离和坡向5个因子,通过设定海拔以及土地覆盖类型对应的限制区域,利用Mu Sy Q辐射产品、DEM、道路网数据、VIIRS夜间灯光数据、土地覆盖产品得到因子图层,使用层次分析法确定各因子在模型中的权重,借助GIS进行叠加分析并分为"低适宜"、"较适宜"、"适宜"、"非常适宜"和"限制区"5类,得到光伏电站建设的空间适宜性分布。研究结果表明,西北地区的适宜区占全国的53.0%,"非常适宜"区占全国的47.3%,其累计光伏电站装机量占全国的45.6%。建设光伏电站的"适宜"和"非常适宜"区面积的大小与装机量的多少没有明显的线性关系。"非常适宜"区作为光伏电站的最佳建设场所,光伏发电潜力大于2016年全国发电量的5倍。同时,国家政策制定的装机规模指标以及光电补贴政策对光伏电站的选址也起了一定的指向作用。
基金supported by Knowledge Innovation Program of the Chinese Academy of Sciences(Grant No.KZCX2-YW-Q10-2-2)National Natural Science Foundation of China(Grant No.40971204)+1 种基金National High-tech R&D Program of China(Grant No.2012AA12A304)R&D Special Fund for Public Welfare Industry(Meteorology)(Grant No.GYHY200706046-1)
文摘To satisfy the requirement of surface energy budget research on the meso-and micro-scale,a parameterization is developed to calculate high spatial resolution,clear-sky downward longwave radiation(DLR)from HJ-1B thermal data.The DLR algorithm is established based on extensive radiative transfer simulation and statistical analysis.To address the problem that HJ-1B has a single thermal channel and lacks atmospheric information,the brightness temperature of HJ-1B and water vapor content are used in the algorithm.An accuracy evaluation and error analysis for the algorithm is conducted using a simulated radiation dataset.The result shows that the algorithm performs well in most circumstances,but there is obvious underestimation when water vapor content is greater than 4g/cm2 .Error analysis indicates the accuracy of estimated DLRs is affected by uncertainties in input parameters,including water vapor content and top-of-atmosphere radiance.It is also affected by the difference between ground and near-surface air temperature.The algorithm is applied to actual HJ-1B data,and validated by ground data from six stations in the Heihe River and Haihe River basins.The estimated DLRs have good consistency with measured data except at Huazhaizi,and root mean square errors at most sites are around 20W/m2 ,which is slightly better than the result of MODIS. There is significant overestimation of DLR at Huazhaizi during summer,which is mainly produced by the large ground-air temperature difference.A correction process based on temperature difference is proposed and applied at Huazhaizi.The result shows that the positive bias is largely diminished after correction.
