基于GIS和RS的蓄滞洪区和谐发展的技术路线

应用遥感与地理信息系统技术构建基于GIS模型的蓄滞洪区空间数据库,对蓄滞洪区内的基础地理数据进行存储、管理,并对空间数据进行可视化和空间分析等操作;运用RS技术对蓄滞洪区内的土地利用、生态环境变化等情况进行动态监测,建立蓄滞洪区发展指标体系;探求蓄滞洪区的和谐发展模式,为蓄滞洪区的可持续发展提供科学依据。     

一种SAR与可见光图像压缩感知融合增强方法

针对机载多传感器成像战场态势感知的问题，提出了一种合成孔径雷达(Synthetic Aperture Radar，SAR)与可见光图像压缩感知融合增强方法。该方法首先对SAR与可见光图像分别进行压缩感知测量，得到压缩测量值，然后通过基于局部权值的融合方法实现对压缩测量值的融合，再利用有序度最优分割法提取SAR图像的强散射目标，最后对融合测量值重建得到初步融合图像，初步融合图像通过目标对比度增强得到最终融合图像。对多组图像进行了仿真分析，视觉及数值结果表明该方法能显著增强融合图像的目标对比度，提升了图像纹理清晰度，较大程度降低了图像融合过程中的数据计算量。     

剖线强度梯度变化的作物软硬变化区精确划分

[目的]软硬变化区的划分是进行遥感变化检测技术识别农作物的基础。为解决人工判读方法中存在人为主观因素影响以及自动判别和交互式判别方法对不同研究区的适用性问题,该文提出基于剖线梯度变化(Profile based Gradient Change Magnitude,PGCM)进行软硬变化区划分的方法。[方法]该研究选择破碎农业景观种植区域为研究区,计算拔节期Quick Bird影像和播种期模拟影像两个时相的变化强度,从作物地块内部向外绘制剖线,利用剖线强度的梯度变化确定硬变化区(Hard change region,HCR)、软变化区(Soft change region,SCR)和未变化区(Non change region,NCR)3者间的划分阈值。[结果]从识别结果来看,PGCM能够有效在地块边界处探测到软变化像元,进而确定HCR、SCR。像元分辨率在5~60 m不同尺度下,识别HCR区混入比例为11%~16%,混入比例随着分辨率下降而降低;NCR区混入比例为3%~4%,受分辨率尺度影响不大;SCR区识别比例为74%~86%,识别精度较高,识别结果与冬小麦空间分布结果保持一致。[结论]PGCM方法能够自动、便捷地确定阈值,摆脱人工判定的主观性,有效地划分出HCR、SCR和NCR 3个区域,为进一步HCR、SCR区内的作物识别提供基础。     

无人机遥感系统的研究进展与应用前景

对于无人机遥感来说,融合了无人机技术与遥感技术。在无人机遥感技术应用的过程中,涵盖了诸多不同类型的先进技术,比如,无人机驾驶飞行技术、通讯技术、遥感传感器技术等,存在着显著的智能化、自动化等不同方面的特征,能够迅速得到相关资源,并且系统掌握国土、环境等不同方面的信息,然后加以实时化处理,通过建模与科学分析,能够制定出无人机遥感技术运用的具体策略,凸显出其良好的功效。本文针对无人机遥感系统的研究进展进行了详细地分析,同时说明了无人机遥感系统的应用前景,进而对有关研究人员形成一定的启发。     

Remote sensing-based detection of agricultural land losses around Greater Cairo since the Egyptian revolution of 2011

Over the last four decades, the loss of agricultural land has been observed in Egypt at high rates. However, the highest rates of losses have occurred since the January 25th revolution in 2011. Greater Cairo (GC), which is the largest metropolitan in Egypt, has witnessed a massive loss of agricultural land since the 2011 revolution. However, until now, no study or official report has revealed the volume of agricultural land losses in this region. This study quantifies agricultural land losses around the GC using Landsat satellite images from 2010 and 2018. Supervised classification was performed using the maximum likelihood algorithm in QGIS software. A post-classification comparison method was applied to detect the land use/land cover changes between the classified images; then, the loss of agricultural land was quantified using Arc GIS software. Visualizations of the gains and losses in agricultural land and the spatial trends of agricultural land losses were created using TerrSet software. The results show that 9600 ha of agricultural land were converted to urban use during 2010–2018, which means that the annual rate of agricultural land loss has tripled and now reaches approximately 1200 ha per year. Decay of executive authority, rapid population growth, real estate market speculation and fragmentation of agricultural land were the main driving factors of agricultural land losses during this period. The results of this research may help decision makers understand the current high rate of agricultural land loss. Hence, appropriate strategies may be adopted to prevent future losses of this valuable land.     

基于信息辅助块稀疏贝叶斯学习的直扩通信窄带干扰抑制

现有基于Nyquist-Shannon采样定理的窄带干扰(Narrowband Interference,NBI)抑制方法存在应用受限于采样率较高的问题。应用压缩感知(Compressive Sensing,CS)理论解决上述问题，利用NBI在频域表现出的块稀疏特性以及直接序列扩频(Direct Sequence Spread Spectrum,DSSS)信号的类噪声特性，提出了基于块稀疏贝叶斯学习(Block Sparse Bayesian Learning,BSBL)框架的DSSS通信NBI抑制模型。实现干扰抑制后，利用传统的CS重构算法实现DSSS信号的压缩域解调。为进一步提高算法性能，将NBI稀疏分块的块内自相关矩阵建模为单位矩阵，提出了信息辅助BSBL(Aid BSBL,ABSBL)算法，设计了基于ABSBL的DSSS通信NBI抑制算法。该算法在保持较好NBI抑制性能的条件下，提高了运算效率并且不依赖NBI的稀疏结构。仿真验证和对比分析结果表明，所提方法能够有效抑制DSSS通信中的NBI，在干扰强度相同的条件下，NBI带宽越小、压缩率越大，算法对NBI的抑制性能越好。     

基于图形小波变换的遥感图像表示与去噪

离散小波变换（Discrete Wavelet Transform，DWT）通常用于图像的表示。然而，对于具有不规则形状边缘的图像，尤其是对于纹理和细节信息较多的遥感图像，DWT却很难有效表示，进而影响后续去噪效果。针对该问题，提出了一种基于图形小波变换（Graphic Wavelet Transform，GWT）的图像去噪方法。首先，将图像表示为图形信号，并通过该图形信号的谱表示构造相应的变换矩阵；然后，设计了一种改进自适应阈值的图像去噪方法，在GWT变换域内对图像去噪。实验结果表明，与常用的图像去噪方法相比，所提算法能够提供更好的图像主观质量。采用均方根误差（Root Mean Square Error，RMSE）和峰值信噪比（Peak Signal-to-Noise Ratio，PSNR）作为客观指标，结果表明，采用所提方法得到的重建图像客观质量更优。     

War and economy. Rediscovering the eighteenth-century military entrepreneur

Abstract

The detrimental effects traditionally assigned to warfare in the development of pre-industrial economies have obscured the prominent role that military entrepreneurs played in economic development in this period. Historiography minimises the extent to which war and the concomitant strengthening of the central state provided a whole new range of opportunities for capital investment, a tendency that has been strengthened by the paradigm of Redlich’s ‘decline of the soldier-entrepreneur’ and the technological determinism of the debate on the Military Revolution among others. The aim of this introduction is to look into the background of this relative lack of interest and to reaffirm the mutual dependence of eighteenth-century state-formation and the business of war.