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联合Sentinel-1与Sentinel-2的高时空分辨率玉米叶面积指数反演

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遥感信息 2024年第1期39卷 73-82页

作者：于慧男王昶景刘国祥屈永华尹高飞西南交通大学地球科学与环境工程学院成都610031 北京师范大学遥感科学国家重点实验室北京100875 北京师范大学地理科学学部遥感与工程研究院北京100875

叶面积指数(leaf area index,LAI)是单位地表面积上总叶面积的一半,是影响光合作用、蒸腾作用和能量平衡等地表过程的关键生物物理变量。鉴于光学遥感数据易受天气的影响,雷达遥感数据易受土壤等的影响,二者在叶面积指数反演方面各有利... 详细信息

叶面积指数(leaf area index,LAI)是单位地表面积上总叶面积的一半,是影响光合作用、蒸腾作用和能量平衡等地表过程的关键生物物理变量。鉴于光学遥感数据易受天气的影响,雷达遥感数据易受土壤等的影响,二者在叶面积指数反演方面各有利弊,提出了一种考虑不同数据反演结果不确定性的融合方法。研究测试了多种机器学习模型在中国张掖地区的玉米农田上估算LAI的性能。结果表明,光学和雷达两种数据分别作为模型输入进行LAI反演时,高斯过程回归(Gaussian process regression,GPR)的表现均为最优。随后,基于Sentinel-1雷达数据和Sentinel-2光学数据,使用GPR模型生成了研究区2019年的两种LAI及不确定性时空分布图。考虑不同数据反演结果的差异,使用加权滤波方法将两种LAI融合,实现了高时空分辨率玉米LAI制图。通过定性和定量分析,融合后的LAI时间序列分布图变化连贯,空间分布均匀,精度相较于融合之前有了明显改善。

关键词：叶面积指数 Sentinel-1 Sentinel-2 协同玉米

A long-term Global LAnd Surface Satellite(GLASS)data-set for environmental studies

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International Journal of Digital Earth 2013年第S1期6卷 5-33页

作者： Shunlin Liang Xiang Zhao Suhong Liu Wenping Yuan Xiao Cheng Zhiqiang Xiao Xiaotong Zhang Qiang Liu Jie Cheng Hairong Tang yonghua qu Yancheng Bo Ying qu Huazhong Ren Kai Yu John Townshend The State Key Laboratory of Remote Sensing Science Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing Applications of Chinese Academy of SciencesBeijingChina College of Global Change and Earth System Sciences Beijing Normal UniversityBeijingChina Department of Geographical Sciences University of MarylandMDUSA School of Geography Beijing Normal UniversityBeijingChina Institute of Electronics Chinese Academy of SciencesBeijingChina

Recently,five Global LAnd Surface Satellite(GLASS)products have been released:leaf area index(LAI),shortwave broadband albedo,longwave broadband emissivity,incident short radiation,and photosynthetically active radiation(PAR).The first three products cover the years 19822012(LAI)and 19812010(albedo and emissivity)at 15 km and 8-day resolutions,and the last two radiation products span the period 20082010 at 5 km and 3-h resolutions.These products have been evaluated and validated,and the preliminary results indicate that they are of higher quality and accuracy than the existing products.In particular,the first three products have much longer time series,and are therefore highly suitable for various environmental studies.This paper outlines the algorithms,product characteristics,preliminary validation results,potential applications and some examples of initial analysis of these products.

关键词： earth observation global environmental change remote sensing

Internet of Things to network smart devices for ecosystem monitoring

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Science Bulletin 2019年第17期64卷 1234-1245页

作者： Xin Li Ning Zhao Rui Jin Shaomin Liu Xiaomin Sun Xuefa Wen Dongxiu Wu Yan Zhou Jianwen Guo Shiping Chen Ziwei Xu Mingguo Ma Tianming Wang yonghua qu Xinwei Wang Fangming Wu Yuke Zhou Institute of Tibetan Plateau Research Chinese Academy of Sciences Beijing 100101 China State Key Laboratory of Remote Sensing Science Faculty of Geographical Science Beijing Normal University Beijing 100875 China State Key Laboratory of Remote Sensing Science Institute of Remote Sensing and Digital Earth Chinese Academy o f Sciences Beijing 100101 China Center for Excellence in Tibetan Plateau Earth Sciences Chinese Academy o f Sciences Beijing 100101 China Key Laboratory of Remote Sensing of Gansu Province Heihe Remote Sensing Experimental Research Station Cold and Arid Regions Environmental and Engineering Research Institute Chinese Academy of Sciences Lanzhou 730000 China State Key Laboratory of Earth Surface Processes and Resource Ecology Faculty o f Geographical Science Beijing Normal University Beijing 100875 China Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 China State Key Laboratory of Vegetation and Environmental Change Institute of Botany Chinese Academy of Sciences Beijing 100093 China Optoelectronics System Laboratory Institute of Semiconductors Chinese Academy of Sciences Beijing 100083 China Research Base of Karst Eco-environments at Nanchuan in Chongqing Ministry of Nature Resources School of Geographical Sciences Southwest University Chongqing 400715 China Ministry of Education Key Laboratory for Biodiversity Science and Engineering Monitoring and Research Center for Amur Tigers and Amur Leopards National Forestry and Grassland Administration & College of Life Sciences Beijing Normal University Beijing 100875 China

Smart, real-time, low-cost, and distributed ecosystem monitoring is essential for understanding and managing rapidly changing ecosystems. However, new techniques in the big data era have rarely been introduced into operational ecosystem monitoring, particularly for fragile ecosystems in remote areas.We introduce the Internet of Things(IoT) techniques to establish a prototype ecosystem monitoring system by developing innovative smart devices and using IoT technologies for ecosystem monitoring in isolated environments. The developed smart devices include four categories: large-scale and nonintrusive instruments to measure evapotranspiration and soil moisture, in situ observing systems for CO2 and d13 C associated with soil respiration, portable and distributed devices for monitoring vegetation variables, and Bi-CMOS cameras and pressure trigger sensors for terrestrial vertebrate monitoring. These new devices outperform conventional devices and are connected to each other via wireless communication networks. The breakthroughs in the ecosystem monitoring IoT include new data loggers and longdistance wireless sensor network technology that supports the rapid transmission of data from devices to wireless networks. The applicability of this ecosystem monitoring IoT is verified in three fragile ecosystems, including a karst rocky desertification area, the National Park for Amur Tigers, and the oasis-desert ecotone in China. By integrating these devices and technologies with an ecosystem monitoring information system, a seamless data acquisition, transmission, processing, and application IoT is created. The establishment of this ecosystem monitoring IoT will serve as a new paradigm for ecosystem monitoring and therefore provide a platform for ecosystem management and decision making in the era of big data.

关键词： Ecosystem monitoring Fragile ecosystem Internet of Things Wireless sensor network Smart device

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国产电容器的质量评价方法

电子与封装 2024年第3期24卷 10-15页

作者：张永华曲芳何浒澄江南计算技术研究所江苏无锡214083

电容器作为电路系统中广泛使用的基本元件,其质量直接影响到电路性能的发挥。面向信息领域国产化替代需求,系统研究和探讨了开展国产电容器(器件级)验证评价时可选择的质量检测和可靠性评价方法,以及可参考的通用评价准则。同时,结合实... 详细信息

电容器作为电路系统中广泛使用的基本元件,其质量直接影响到电路性能的发挥。面向信息领域国产化替代需求,系统研究和探讨了开展国产电容器(器件级)验证评价时可选择的质量检测和可靠性评价方法,以及可参考的通用评价准则。同时,结合实践案例,重点阐述了国产电容器在实施验证过程中和实际使用中的注意事项,为相关领域工程师开展国产电容器的可用性和可靠性评价工作提供了参考范例。

关键词：电容器质量检测可靠性试验寿命预测

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液氢温区材料拉伸测试装置研制及仿真分析

真空与低温 2024年第2期30卷 134-142页

作者：王干缘夏莉承磊屈莎莎黄永华上海交通大学制冷与低温工程研究所上海200240 广东省特种设备检测研究院广东佛山528251 上海精密计量测试研究所上海201109

为了满足当前液氢工程领域对材料力学性能测试的需求,以两台G-M制冷机为冷源、氦气为载冷介质,设计和研制了一台低温材料拉伸测试装置。该装置可实现14~300 K温区内各类固体材料的拉伸试验。采用液氮预冷的方式,样品降温至14 K用时仅7 ... 详细信息

为了满足当前液氢工程领域对材料力学性能测试的需求,以两台G-M制冷机为冷源、氦气为载冷介质,设计和研制了一台低温材料拉伸测试装置。该装置可实现14~300 K温区内各类固体材料的拉伸试验。采用液氮预冷的方式,样品降温至14 K用时仅7 h。对试验腔内试件的温度分布进行仿真模拟,结果表明试件的温度梯度主要存在于纵向,而横向没有明显的温差。对316 L不锈钢试样进行多工况拉伸性能测试,可重复性高于97.8%。所得304和316 L不锈钢材料的屈服强度和抗拉强度测试数据与文献数据相比最大相对偏差仅为6.3%,该深冷温区拉伸测试装置具有较高的可靠性和准确性。

关键词：低温 G-M制冷机温度分布均匀性拉伸测试装置

结合光照信息的多尺度K-均值植被几何光学四分量提取算法

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地球信息科学学报 2023年第5期25卷 1037-1049页

作者：冯耀伟屈永华北京师范大学地理科学学部北京师范大学遥感科学国家重点实验室北京100875 北京市陆表遥感数据产品工程技术研究中心北京师范大学地理科学学部遥感科学与工程研究院北京100875

遥感几何光学模型利用传感器视场内植被、土壤组分随着光照与观测几何的变化模拟冠层多角度反射率。在近地遥感中,向下观测相机图像中的光照土壤、阴影土壤、光照植被和阴影植被这4种像元类型(称为植被几何光学四分量,简称四分量)是几... 详细信息

遥感几何光学模型利用传感器视场内植被、土壤组分随着光照与观测几何的变化模拟冠层多角度反射率。在近地遥感中,向下观测相机图像中的光照土壤、阴影土壤、光照植被和阴影植被这4种像元类型(称为植被几何光学四分量,简称四分量)是几何光学模型的重要输入参数。本文基于低成本成像传感器的RGB图像,提出一种结合光照信息和多尺度图像分层模型的K-均值四分量提取算法(MSI-Kmeans),首先通过综合利用颜色指数构成聚类空间,之后利用图像的光照分量和阴影分量子图分别构建多尺度图像分层模型,再在多尺度图像分层模型中进行K-均值聚类得到植被分量和土壤分量结果,最后将得到的四分量结果组合输出,从而实现植被几何光学四分量提取。对不同自然光照条件下获取的52幅多种植被冠层图像进行实验,结果表明:(1)在与多种常见算法的精度比较中,本文方法在四分量的分类中制图精度与用户精度均表现良好,综合评价Kappa系数最高(0.82);(2) MSI-Kmeans算法在不同冠层覆盖度和太阳高度角连续变化的条件下均可得到良好稳定的分类效果,具有应用于长期植被监测和单日内连续监测植被四分量变化的潜力。本算法的优势在于提高了阴影分量的分类精度和解决了高植被覆盖度下四分量的提取问题,后续的改进方向在于减小计算代价,提高算法在复杂场景下的适用性。本文研究成果对于利用数字相机进行植被几何光学四分量的提取和植被结构参数的估计具有较为重要的理论与应用价值。

关键词：几何光学模型四分量提取光照信息多尺度图像分层模型 K-均值聚类植被监测

ALGORITHM OF PRETREATMENT ON AUTOMOBILE BODY POINT CLOUD

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Chinese Journal of Mechanical Engineering 2007年第4期20卷 71-74页

作者： GAO Feng ZHOU Yu DU Farong qu Weiwei XIONG yonghua Department of Automobile Engineering Beihang University Beijing 100083 China

As point cloud of one whole vehicle body has the traits of large geometric dimension, huge data and rigorous reverse precision, one pretreatment algorithm on automobile body point cloud is put forward. The basic idea of the registration algorithm based on the skeleton points is to construct the skeleton points of the whole vehicle model and the mark points of the separate point cloud, to search the mapped relationship between skeleton points and mark points using congruence triangle method and to match the whole vehicle point cloud using the improved iterative closed point （ICP） algorithm. The data reduction algorithm, based on average square root of distance, condenses data by three steps, computing datasets＇ average square root of distance in sampling cube grid, sorting order according to the value computed from the first step, choosing sampling percentage. The accuracy of the two algorithms above is proved by a registration and reduction example of whole vehicle point cloud of a certain light truck.

关键词： Reverse engineering Point cloud registration Skeleton point Iterative closed point（ICP） Data reduction

Efficacy and mechanisms of Dingxian pill(定痫丸)combined with valproic acid on pentylenetetrazol-induced chronic epilepsy in rats

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Journal of Traditional Chinese Medicine 2023年第2期43卷 286-294页

作者： qu Dongxiao GE Yiqin ZHUO Limin CHEN Liji XUE yonghua CHENG Jiwei TAO Jie LI Guoyi ZHU Yudan XIAO Qian Department of Neurology and Central Laboratory Putuo HospitalShanghai University of Traditional Chinese MedicineShanghai 200062China Department of Neurosurgery Jiading Branch of Shanghai General HospitalShanghai Jiao Tong University School of MedicineShanghai 201803China Department of Neurology and Central Laboratory Putuo Clinical Medical SchoolAnhui Medical UniversityShanghai 200062China College of Sciences Shanghai UniversityShanghai 200442China

OBJECIVE:To investigate the efficacy and mechanisms of Dingxian pill(定痫丸)combined with valproic acid(VPA)on pentylenetetrazol-induced chronical epilepsy in rats.METHODS:A rat model of epilepsy was established by administering pentylenetetrazol(PTZ)water solution(35 mg/kg).Rats were divided into 4 groups,among which three groups were treated with different drugs once a day for 28 d including Dingxian pill(2.4 g/kg),VPA(0.2 g/kg),or a combination of Dingxian pill(2.4 g/kg)and VPA(0.2 g/kg)respectively,and the control group was given the same volume of saline.Rats in different groups were compared based on animal behavior,electroencephalograms,Morris water maze,immunohistochemistry,transcriptomics and real-time polymerase chain reaction.RSULTS:The combination therapy of Dingxian pill and VPA inhibited PTZ-induced seizure-like behavior and reduced seizure grades more significantly than VPA alone.Compared with the control group,the learning and memory ability of chronic PTZ-induced epileptic rats was improved in all the drug treatment groups,especially in the group that received both Dingxian pill and VPA.Similar to the results of MWM tests,expression of the neuroexcitability marker gene c-Fos was reduced after Dingxian pill and/or VPA treatment,and the effect was most pronounced in the combined treatment group.Transcriptomic analysis revealed that gene expression in the rodent hippocampus,which is involved in epilepsy,was upregulated by combined treatment with Dingxian pill and VPA,compared with VPA treatment alone.CONCLUSION:Our results not only highlight the antiepileptic effects of combined Dingxian pill and VPA treatment,but also shed light on the underlying molecular mechanisms and provide a way to apply Traditional Chinese Medicine in the treatment of epilepsy.

关键词： epilepsy Valproic Acid learning memory transcriptome Dingxian pill

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智能手机农作物叶面积指数测量算法改进

遥感学报 2023年第2期27卷 441-455页

作者：汪梓鑫屈永华方红亮北京师范大学遥感科学国家重点实验室北京100875 北京市陆表遥感数据产品工程技术研究中心北京师范大学地理科学学部遥感与工程研究院北京100875 中国科学院地理科学与资源研究所资源与环境信息系统国家重点实验室北京100101 中国科学院大学资源与环境学院北京100049

叶面积指数LAI(Leaf Area Index)是表征植被冠层结构特征的一个重要参数,已经成为多个对地观测系统的陆表参数标准产品,也是定量遥感模型的重要输入参数。快速、准确地获取植被LAI对于开展遥感产品验证、促进遥感模型的发展具有极为重... 详细信息

叶面积指数LAI(Leaf Area Index)是表征植被冠层结构特征的一个重要参数,已经成为多个对地观测系统的陆表参数标准产品,也是定量遥感模型的重要输入参数。快速、准确地获取植被LAI对于开展遥感产品验证、促进遥感模型的发展具有极为重要的意义。随着传感器性能与应用软件功能扩展,智能手机已经成为植被LAI测量的新选择。然而,由于手机成像传感器窄视场角的限制,现有算法依赖于叶倾角分布函数为球型分布的假设,即G函数(单位叶面积在垂直于观测天顶角的平面上的投影)恒等于0.5。因而,传统算法无法解决植被叶倾角分布未知的情况。本文提出了一种基于形状匹配的G函数估算方法,基于有限长度方法和多幅影像间隙率,计算样方内的植被冠层聚集指数,利用泊松分布模型分别得到了植被冠层有效叶面积指数(LAI_(eff))和真实叶面积指数(LAI_(tru)),并用黑龙江海伦农场两种农作物类型(玉米和大豆)的破坏性测量得到的时间序列真实LAI数据(LAI_(des))对算法进行了验证。结果表明,算法改进之前的均方根误差(RMSE)分别是0.84(垂直拍摄)和1.33(倾斜57°拍摄),改进后LAI_(eff)(有效LAI)和LAI_(tru)(真实LAI)的RMSE为分别为0.58(垂直拍摄)和0.56(垂直拍摄)。新算法得到的LAI值在时间序列变化趋势上与实测值更为一致。本文算法扩展了农作物LAI测量方法,为从智能手机影像中快速、准确提取植被LAI提供了可能。后续研究将会从分析外部光照环境变化对测量结果的影响和增加不同植被类型的验证数据两个方向进一步开展工作。

关键词：遥感智能手机叶面积指数多角度间隙率 G函数聚集指数有效叶面积指数