Thermo-acoustic sound generation in the interaction of pulsed proton and laser beams with a water target

The generation of hydrodynamic radiation in interactions of pulsed proton and laser beams with matter is explored. The beams were directed into a water target and the resulting acoustic signals were recorded with pressure sensitive sensors. Measurements were performed with varying pulse energies, sensor positions, beam diameters and temperatures. The obtained data are matched by simulation results based on the thermo-acoustic model with uncertainties at a level of 10%. The results imply that the primary mechanism for sound generation by the energy deposition of particles propagating in water is the local heating of the medium. The heating results in a fast expansion or contraction and a pressure pulse of bipolar shape is emitted into the surrounding medium. An interesting, widely discussed application of this effect could be the detection of ultra-high energetic cosmic neutrinos in future large-scale acoustic neutrino detectors. For this application a validation of the sound generation mechanism to high accuracy, as achieved with the experiments discussed in this article, is of high importance.     

济南地区黄土成因分析及工程地质特征

通过对济南地区黄土的成因类型、分布范围及工程地质特征进行分析,并对济南西部和东部不同地区黄土的物理力学性质进行对比,总结黄土湿限对工程建设产生的危害性并提出防治措施和建议。     

Operationalizing measurement of forest degradation: Identification and quantification of charcoal production in tropical dry forests using very high resolution satellite imagery

Quantification of forest degradation in monitoring and reporting as well as in historic baselines is among the most challenging tasks in national REDD+ strategies. However, a recently introduced option is to base monitoring systems on subnational conditions such as prevalent degradation activities. In Tanzania, charcoal production is considered a major cause of forest degradation, but is challenging to quantify due to sub-canopy biomass loss, remote production sites and illegal trade. We studied two charcoal production sites in dry Miombo woodland representing open woodland conditions near human settlements and remote forest with nearly closed canopies. Supervised classification and adaptive thresholding were applied on a pansharpened QuickBird (QB) image to detect kiln burn marks (KBMs). Supervised classification showed reasonable detection accuracy in the remote forest site only, while adaptive thresholding was found acceptable at both locations. We used supervised classification and manual digitizing for KBM delineation and found acceptable delineation accuracy at both sites with RMSEs of 25–32% compared to ground measurements. Regression of charcoal production on KBM area delineated from QB resulted in R²s of 0.86–0.88 with cross-validation RMSE ranging from 2.22 to 2.29 Mg charcoal per kiln. This study demonstrates, how locally calibrated remote sensing techniques may be used to identify and delineate charcoal production sites for estimation of charcoal production and associated extraction of woody biomass.     

全极化SAR图像边缘检测的随机距离法

提出了一种基于复Wishart分布随机距离的PolSAR图像边缘检测方法,将统计学中的随机距离理论引入PolSAR图像边缘检测中,依据的主要原理是边缘两侧类别之间随机距离的大小与边缘的方向和两侧类别差异的高度相关性。通过模拟数据对随机距离检测边缘的性能进行了全面分析,表明随机距离具有准确的边缘定向和定位能力。并利用基于复Wishart分布随机数生成器模拟的PolSAR图像和一景机载全极化SAR图像进行了验证。试验结果证实了该方法检测边缘的效果。     

采用最优生成树的正射影像镶嵌线快速智能检测

针对高分辨率遥感影像提出了一种基于最优生成树的镶嵌线快速智能检测方法。该方法利用影像亮度差异和梯度构建重叠区域差分影像并视其为带权无向图,以Bottleneck模型为基础,采用最优生成树生成方法智能检测最佳镶嵌线。该方法回避了迭代搜索过程,具有速度快、效率高的优点。试验结果表明,所提出的方法能够在保证镶嵌线质量的同时具有较高的效率,可有效解决正射影像镶嵌过程中镶嵌线的自动选择问题。     

结合LOG算子和大津法的遥感影像边缘检测方法

针对遥感影像具有丰富的细节和混合噪声,采用传统高斯拉普拉斯(LOG)算子难以有效地提取遥感影像地物边缘信息,文章提出一种结合LOG算子和大津法(Otsu法)的遥感影像地物边缘信息提取算法。此算法采用中值滤波对原始影像进行消噪,利用Otsu算法对滤波后影像进行自适应阈值分割得到目标影像,采用LOG算子对目标影像进行边缘信息提取。以安宁某区域的遥感影像为例,实验结果表明,提出的算法与传统LOG算子相比,具有更高的提取精度,能有效地提取出遥感影像的真实边缘、减少伪边缘。     

基于自适应支撑区域的特征点检测算法

针对已有的特征点检测算法的不足,文章提出了一种基于自适应支撑区域(ROS)的算法,该算法针对目前特征点检测中的支撑区域选择,提出了一种自适应单调检测方法,改变了传统支撑区域选择过于单一的难点,自适应性强;并对于曲率的非极大值抑制易造成误检的问题,给出了三次扫描算法,即分析误检产生机理筛选候选特征点。通过支撑区域的自适应选择和三次扫描,实现了算法的自适应性和鲁棒性,检测精度高。试验结果表明,该算法无需先验参数,运行效率高,算法复杂度低。     

高分遥感影像与矢量数据结合的变化检测方法

针对高分辨率遥感影像与矢量数据配准套合之后存在的不一致性问题,该文探讨了多尺度分割算法获取同质像斑的方法。在此基础上,发展了一种基于最近邻分类算法的分类后处理变化检测方法。结果表明,通过多尺度分割算法能够获取"类内光谱相同"和"类间光谱相异"的像斑;分类后处理变化检测方法能够正确检测出80%以上的变化区域,在获取变化检测结果的同时能够获取变化像斑的类别,而且检测精度较高,具有较高的应用价值。     

基于超宽带雷达及支持向量机的灾后人体呼吸信号识别方法与试验研究

与常规雷达相比,超宽带雷达具有距离分辨力高、近距离盲区小、穿透性强、目标识别率高等特点,已被广泛应用于灾后搜寻、救援工作中,以对受困生命体征目标进行生命探测。为实现使用超宽带雷达对受困生命体征目标的识别定位,本研究提出基于信号多特征提取技术及支持向量机模型的人体呼吸信号识别方法。首先,使用经验模态分解、变分模态分解及希尔伯特变换提取雷达探测信号的微多普勒特征,使用傅里叶变换提取宏观频谱特征,使用相关分析获取相关性特征;然后,以提取的信号特征为输入,使用支持向量机模型对信号进行分类,进而对人体呼吸信号进行识别,对人体位置进行定位。不同障碍物场景下的试验结果表明,本方法可有效识别砖墙、建筑楼板等遮挡物下的受困生命体征目标,并提供其位置信息。     

ALOS卫星图像分析与预处理实证研究

通过实证研究的方法对高分辨率ALOS卫星数据进行质量分析,结合ALOS数据特点,提出了ALOS原始影像数据的预处理方法和处理流程。研究结果表明： ALOS数据预处理工作量较大,且预处理方法要求较为严格,因此,在开展大规模、大范围、大区域、大精度、短周期的图件更新、动态监测等应用时,应考虑将ALOS卫星图像与其它卫星图像结合使用。