利用影像重定位和遍历检测的遥感影像水印算法

针对遥感影像数据,提出了一种基于影像重定位和遍历检测的盲水印算法。实验结果表明,该方法可以有效抵抗压缩、滤波等常见的图像处理攻击,还能有效抵抗裁剪攻击。     

B/S党务信息管理系统方案研究与设计

电子党务信息管理系统是实现党务管理信息化、规划化的有效途径,能够辅助完成党务管理中的各项工作,本文在分析当前党务信息管理的前提下,给出了建设党务信息管理系统的总体结构框架设计及具体功能设计方案,为党务信息管理系统的建设提供思路。     

宁津县国土数字档案管理信息系统的设计与实现

传统县级国土资源档案管理方式落后,条目式管理不能适应国土资源档案管理的要求,现有的地籍系统、土地利用系统和土地交易系统的数据分散于三个独立系统中,数据格式多样,给土地归档工作带来不便,需把各个部门各个系统的相关数据进行统一归档管理.本文结合宁津县国土数字档案管理信息系统的设计与实现过程,阐述了整个系统的总体设计思想,系统的功能模块划分、数据整理建库以及系统功能模块的设计实现,为县(市)级档案管理系统的建设提供了参考方案.     

隧道施工现场监控量测的控制

主要介绍了净空变形量测和拱顶下沉量测在隧道施工中的应用,为隧道施工提供了重要依据。     

城市规划管理系统空间数据更新技术研究

数据的现势性是城市规划管理数据的生命力所在,因此,必须研究快速、准确、高效的数据更新方法。针对城市规划数据的特点和质量控制需求,本文对基于版本和工作流技术的数据更新方法进行了探讨和研究。通过胶南市土地规划网格化管理系统检验表明这种方法是行之有效的。     

线纹计量器具检定系统表修订建议

JJG 2001-1987《线纹计量器具检定系统》是我国线纹计量器具进行量值传递的检定系统表,但其存在着许多不足,已无法满足当今计量检定的需要。此处对该检定系统表进行详细分析后给出修订建议,并介绍了目前国际上有关动向,提出了一些有益建议。     

中国煤炭资源供应格局演变及流动路径分析

利用1949—2008年的相关统计数据,分析中国煤炭资源供应格局和流动路径,结果表明:(1)国家政策变动对中国煤炭资源消费规模影响深刻,每一次政策变化都会造成能源消费规模的波动,近年来强烈的能源需求使得我国煤炭供应不得不面临进口的现实;(2)受能源需求和资源禀赋的双重压力,大规模、跨区域、长距离的煤炭运输成为我国能源运输体系的重要特征;(3)尽管煤炭运输方式在向铁路、水路和公路组合并用的多元化发展,但仍然不能满足旺盛的能源需求,煤炭运输瓶颈始终存在,变输煤为输电是缓解当前煤炭运输困难的一个途径。     

我国省域工业主导产业的遴选与发展

工业主导产业在国民经济发展中起着决定性和指向性的作用。主导产业的选择是经济发展阶段的重要课题。依据6个量化指标,从4个维度对"十一五"期间主导产业进行遴选,发现以能源及相关产业为代表的重化工业是各省的重点,高新技术产业成为主导产业的省份较少,劳动密集型产业依然是东部发达省市的重点,预期中的产业转移并未实现;以行业为变量对各省份的主导产业进行聚类分析,可将31个省份划分为5类,反映了我国各省份主导产业布局特点;在此基础上,依据产业生命周期理论和各地区"十二五"发展趋势,提出了相应的对策建议。     

Assessment of CMIP3 climate models and projected changes of precipitation and temperature in the Yangtze River Basin, China

The projected changes of precipitation and temperature in the Yangtze River Basin in the 20th Century from 20 models of the CMIP3 (phase 3 of the Coupled Model Inter-comparison Project) dataset are analyzed based on the observed precipitation and temperature data of 147 meteorological stations in the Yangtze River Basin. The results show that all models tend to underestimate the annual mean temperature over the Yangtze River Basin, and to overestimate the annual mean precipitation. The temporal changes of simulated annual mean precipitation and temperature are broadly comparable with the observations, but with large variability among the results of the models. Most of the models can reproduce maximum precipitation during the monsoon season, while all models tend to underestimate the mean temperature of each month over the Yangtze River Basin. The Taylor diagram shows that the differences between modeled and observed temperature are relatively smaller as compared to differences in precipitation. For a detailed investigation of regional characteristics of climate change in the Yangtze River Basin during 2011–2050, the multi-model ensembles produced by an upgraded REA method are carried out for more reliable projections. The projected precipitation and temperature show large spatial variability in the Yangtze River Basin. Mean precipitation will increase under the A1B and B1 scenarios and decrease under the A2 scenario, with linear trends ranging from ?21 to 28.5?mm/decade. Increasing mean temperature can be found in all scenarios with linear trends ranging from 0.15 to 0.48°C/decade. Grids in the head region of the Jingshajiang catchment show distinct increasing trends for all scenarios. Some physical processes associated with precipitation are not well represented in the models.     

Subarea characteristics of the long-range correlations and the index χ for daily temperature records over China

Daily temperature records including daily minimum, maximum, and average temperature from 190 meteorological stations over China during 1951–2000 are analyzed from two perspectives: (a) long-term persistence in direction of time varies, and (b) standard deviation in direction of amplitude varies. By employing the detrended fluctuation analysis (DFA), we find all the temperature records are long-term correlated, while the exponent α obtained from DFA varies from different districts of China due to different climate conditions, such as the southwest monsoon, subtropical high, northeast cold vortex, and the Tibetan plateau, etc. After we take the standard deviation into account, a new index χ?=?α?×?σ, which has been proposed recently, can be obtained. By further rescaling it as $ \chi = \overline \chi - {{1} \left/ {5} \right.} \times {\sigma_{{\overline \chi }}} $ , we find an obvious change of χ for these three kinds of time series, from which the whole China can be divided into two groups, which are comparatively consistent with dry/wet distributions in the south–north areas over China.