云南地震重点监视防御区民众地震科普认知分析

云南地处云贵高原,地震活动频繁,是一个多震多灾的省份。当地民众对地震灾害的认知程度和自救互救能力,对于保护生命财产安全,减轻地震灾害损失,显得尤为重要。本文选取云南地震重点监视防御区为样本区域,对民众的地震科普知识认知情况和互联网信息智慧化推送接受程度等进行了调研。根据调查结果分析评价,10个样本区域民众的地震科普知识整体认知水平不高,“优秀”等级的州市为0,“良好”等级的州市有6个,“差”的州市有4个;对互联网智慧化推送的民众接受程度存在比较明显的群体差异。     

2008年初持续雨雪灾害过程分析

利用地面实况资料与长沙单站探空等观测资料,对2008年1月中下旬至2月上旬初发生在湖南的低温、雨雪、冻雨灾害天气过程的影响实况和成因进行了分析.结果表明:中高纬阻高的建立、崩溃、重建导致其前部的鄂霍茨克海低涡不断引导冷空气南下,是产生低温、雨雪、冻雨的大气环流背景;南支锋区上强盛的西南气流带来了充沛的水汽,与北支锋区上南下的冷空气结合时,出现了持续的冻雨,当冻雨形成后逆温的强弱、融化层厚度及暖层温度高低、冷却层厚度、700 hPa西南气流强弱、日平均气温与日雨量的变化都与冻雨厚度变化密切相关;当高空南支有低槽分裂东移,中低层西南大风核上强烈的水汽辐合与阻高崩溃横槽转竖带来的冷空气共同作用影响时,为南方大范围暴雪过程提供了动力、水汽和凝结条件.     

一种新的针对反射波的逆时偏移真振幅成像条件

真振幅成像是一种代表性的定量估计模型参数扰动高波数部分的地震波成像方法.经典的真振幅成像方法在高频近似和理想照明假设条件下求取显式对角Hessian逆矩阵作为偏移振幅加权算子,用以校正波传播过程中的几何扩散效应,得到模型参数扰动的带限估计.真振幅保真成像方法在利用逆时偏移（RTM）框架实现时会产生低波数噪声,影响对高波数参数估计的精度.本文给出了一种新的基于RTM框架的真振幅保真成像条件,该成像条件针对反射波数据,在高频近似下散射模式对应正问题及Bayes反问题框架下导出.与传统基于高频渐进反演的波动方程成像方法类似,利用本文提出RTM成像条件能够保证计算结果与高频近似下反演结果的一致性.同时,利用本文提出RTM真振幅成像条件能够在成像过程中自动保真的消除传统真振幅RTM算法中存在低波数噪声,模型数值实验结果验证了本文方法的正确性和有效性.     

On A Low Cloud Phenomenon At The Breidamerkurjökull Glacier, Iceland

An impressive cloud wall has frequently been observed on the southern slopes of the Vatnajökull ice sheet, which is located in south-eastern Iceland. Its optical and dynamic features suggest a delicate balance of the atmospheric agents involved. This has been confirmed by a thorough analysis of a well documented event and by statistics covering a whole summer season. As an exemplary event, the regional development of the associated cloud has basically been documented with synchronous surface data along a suitable transect of the glacier. Data from tethered balloons, radiosoundings and routine synoptic data have also been exploited extensively. Cloud development was generally aided by a high moisture potential because of proximity to the open seas and the remnants of a frontal system. Furthermore the occurrence of the cloud phenomenon was associated with onshore (southerly) surface winds, assisting advection and lifting of the associated air masses above the slopes of the ice sheet. Northward protrusion of the associated cloud was apparently opposed by continuous katabatic winds and topographically induced lee effects.     

格尔木地磁Z分量静日变化特征与前兆异常分析

研究了格尔木地震台1996-2006年地磁模拟资料和2008-2011年的数字化资料,通过对台站磁静日低点时间、日变幅度、日变形态的分析,确认地磁z分量磁静日低点时间在地方时12时左右;日变幅月均值呈现明显的波浪式起伏变化,其年均值与太阳黑子数保持一致;地磁日变形态较为规则,有1个低点和2个高点;在前兆异常分析中,认为低点时间异常和日变形态双低点异常与周边强震具有一定的对应关系。     

孟连回林低温热液构造角砾岩型金多金属矿

对矿化蚀变带进行分析研究,矿床位于中-下石炭统接触裂隙破碎带中,总结成矿规律,建立找矿标志,为该区的地质找矿指明方向。     

Scaling of Canadian low flows

Scaling properties of Canadian low flows, namely annual minimum mean 1-, 5- and 7-day flows, are evaluated across Canada and in its sub-climatic regions. Across the entire country, the log relationship between the kth product moments (PMs, E[Q_i^k]) of low flows and drainage area (A_i) can be represented by: ln(E[Q_i^k])=a_k+b_kln(A_i)and b_k=k, with = 0.86, 0.94 and 0.93 for annual minimum mean 1-, 5- and 7-day flows, respectively. The log linear relationships between the kth probability weighted moments (PWMs, ) and A_i are ln()=c_k+Hln(A_i), in which H is constant and is independent of k. The values of H are 0.87, 0.97, and 0.96 for annual minimum mean 1-, 5- and 7-day flows, respectively, which are almost the same as the values. The coefficients of variation (Cv) are almost independent of drainage area. These results demonstrate that Canadian low flows generally exhibit simple scaling and drainage area alone describes most of the variability in the moments of the low flows. Low flows in each of the sub-climatic regions also obey a simple scaling law. The values of , H and Cv are different in each region, which may stem from physiographical and climatological differences among these regions. The finding lays a basis for applying the index flood method to conduct regional low flow frequency analysis as simple scaling is equivalent to the index flood method.Acknowledgements The authors thank Prof. Thian Yew Gan of University of Alberta, Canada for providing additional pristine data sites for regions 4 and 10. A constructive comments provided by an anonymous reviewer improved the quality of the paper.     

Detail focused fusion of hyperspectral and multispectral imagesEI北大核心CSCD

Hyperspectral image (HSI) and multispectral image (MSI) are two types of images widely used in the field of remote sensing. These images are useful in certain applications, such as environmental monitoring, target detection, and mineral exploration. HSI contains a large amount of spectral information. Photons are typically collected in a larger spatial area on the sensor to ensure a sufficiently high signal-to-noise ratio (SNR). Accordingly, the HSI spatial resolution is much lower compared with MSI. This low spatial resolution greatly affects the practicality of HSI. Accordingly, fusing a low-spatial resolution HSI (LR-HSI) with a high-spatial resolution MSI (HR-MSI) in the same scene to obtain a high-resolution HSI (HR-HSI) is a method for solving such problems, which resolves the contradiction that the spatial resolution and the spectral resolution cannot simultaneously maintain a high level. From the analysis of fusion effect, the spatial and spectral reconstruction errors of the existing algorithms are mainly reflected in the edge and detail areas. The method proposed in this work was a fusion algorithm for dictionary construction and image reconstruction based on detail attention. In terms of maintaining spectral characteristics, the spectral distribution in the detail area is complex and diverse because of the proximity effect of the image. This work proposes to perform dictionary learning on the image and detail layers. The detail perception error terms and a constraint of edge adaptive directional total variation are proposed for spatial characteristic enhancement, which is combined with a local low rank constraint in the same fusion framework to estimate the sparse coefficient. Experiments were conducted on two datasets, namely, Pavia University and Indian Pine, to verify the effectiveness of the proposed method. The quantitative evaluation metrics contain peak SNR, relative dimensionless global error in synthesis, spectral angle map, and universal image quality index. Based on the experimental comparison, the fusion result of the algorithm proposed in this work is significantly improved compared with those of the other algorithms in terms of spatial and spectral characteristics. This work uses dictionary learning to propose a fusion algorithm for dictionary construction and image reconstruction with attention to details through the analysis of the existing hyperspectral and multispectral image fusion algorithms. A hierarchical dictionary learning algorithm is proposed to address the problem of large reconstruction error in the detail part of the existing algorithms. The detail perception error term and the direction adaptive full variational regularization term are used to improve the spectral dictionary solution and coefficient estimation, respectively. The result of the fusion is the error in the spectral characteristics and spatial texture of the detail, which achieves an accurate representation of the edge detail. © 2022 National Remote Sensing Bulletin. All rights reserved.     

模拟退火算法在室内定位中的应用

随着室内定位技术的广泛应用,如何高效、精准、低成本地实现室内定位尤为重要。本文分析了现有室内定位算法的不足,结合室内定位问题与模拟退火算法的特点,通过室内定位问题的数学抽象与建模,提出一种基于模拟退火算法的室内定位方法,给出了可行解邻域的选取方式与二范数的目标函数。实验结果表明该算法可实现高效、精准、低成本的定位效果,并且具有较好的鲁棒性和平差效果。     

Combining AVHRR imagery with CORINE Land Cover data to observe forest fires and to assess their consequences

This paper describes an operational application of AVHRR satellite imagery in combination with the satellite-based land cover database CORINE Land Cover (CLC) for the comprehensive observation and follow-up of 10000 fire outbreaks and of their consequences in Greece during summer 2000. In the first stage, we acquired and processed satellite images on a daily basis with the aim of smoke-plume tracking and fire-core detection at the national level. Imagery was acquired eight times per day and derived from all AVHRR spectral channels. In the second stage, we assessed the consequences of fire on vegetation by producing a burnt-area map on the basis of multi-annual normalised vegetation indices using AVHRR data in combination with CLC. In the third stage we used again CLC to assess the land cover of burnt areas in the entire country. The results compared successfully to available inventories for that year. Burnt area was estimated with an accuracy ranging from 88% to 95%, depending on the predominant land cover type. These results, along with the low cost and high temporal resolution of AVHRR satellite imagery, suggest that the combination of low-resolution satellite data with harmonised CLC data can be applied operationally for forest fire and post-fire assessments at the national and at a pan-European level.