SNOW WETNESS ESTIMATES OF VEGETATED TERRAIN FROM SATELLITE PASSIVE MICROWAVE DATA

The Special Sensor Microwave/Imager (SSM/I) radiometer is a useful tool for monitoring snow wetness on a large scale because water content has a significant effect on the microwave emissions at the snowpack surface. To date, SSM/I snow wetness algorithms, based on statistical regression analysis, have been developed only for specific regions. Inadequate ground-based snow wetness measurements and the non-linearity between SSM/I brightness temperatures (T_Bs) and snow wetness over varied vegetation covered terrain has impeded the development of a general model. In this study, we used a previously developed linear relationship between snowpack surface wetness (% by volume) and concurrent air temperature (°C) to estimate the snow wetness at ground weather stations. The snow condition (snow free, dry, wet or refrozen snow) of each SSM/I pixel (a 37 × 29 km area at 37.0 GHz) was determined from ground-measured weather data and the T_B signature. SSM/I T_Bs of wet snow were then linked with the snow wetness estimates as an input/output relationship. A single-hidden-layer back-propagation (backprop) artificial neural network (ANN) was designed to learn the relationships. After training, the snow wetness values estimated by the ANN were compared with those derived by regression models. Results show that the ANN performed better than the existing regression models in estimating snow wetness from SSM/I data over terrain with different amounts of vegetation cover.     

Effect of altitude error on position precision of double-star position system

IntroductionDouble-Star is to use two stationary orbit satellitesto locate the target which is located in the overlayarea of the the satellites’wave-beam. The two sat-ellites can only supply two equations. In order toget the three-dimensional position of…     

Mini-inflation prior to the cosmic confinement transition?

The onset of the confinement transition in the early universe is studied within the Friedmann model. Exploiting a bag model equation of state for the deconfined matter, which is generalized to include also metastable states, the possibility of a mini-inflationary epoch is demonstrated. A criterion of metastability is derived to estimate parameters of this mini-inflation.     

1:10 000基础测绘数字产品的质量控制

从生产实际出发,对1:10000基础测绘数字产品DLG,DEM,DOM,E00质量控制的主要内容和方法进行了较全面的阐述,并提出了一些影响测绘产品质量的问题。     

基于DEM分形特征的坡度尺度变换模型

利用DEM提取坡度具有明显的尺度依赖性,探求DEM在不同尺度下表现出的规律关系,建立多尺度变换模型,以实现不同尺度间的转换是地形分析研究的热点和难点。本文阐释了DEM表面与地表粗糙度分形维数值的地学意义及内在关系,并利用分形对象的自相似性原理,建立了一种基于DEM分形特征的坡度尺度变换模型。选取四川丘陵地区某小流域为研究区,进行坡度尺度变换实验和误差分析,结果表明该模型能有效实现坡度尺度变换:在非平坦地区(坡度>1°)一般重采样方法变换得到的坡度误差为该方法的1.86倍;从信息熵理论分析,经该方法转换后的坡度信息得到了显著恢复。对于无1︰1万及以上精度地形数据的西南山区,利用该方法获取高精度坡度数据具有重要的理论价值和现实意义。     

The use of cartographic control points in the harmonization and revision of MRDBs

The main purpose of the research is to achieve fully automated approach for supplying multi-resolution databases with linear objects in each scale. Moreover, the proposed solutions maintain the repeatability and accuracy of output data wherever possible according to the input scale. These properties are achieved by keeping the minimal object dimensions as well as the appropriate data pre-processing, based on the classification of source points. The classification distinguishes three classes of points: constant (unchangeable), temporary, and inherited. These classes build a structure of cartographic control points. Based on these solutions, the authors proposed an algorithm for linear object simplification based on minimal object dimensions and cartographic control points. It was also confirmed that the simplification between constant points does not cause geometry discrepancies in relation to the global simplification of the whole line.     

基于贝叶斯正则化BP神经网络的DEM趋势面逼近

趋势面从宏观上揭示了研究对象的特性,在各领域发挥着重要作用。BP神经网络可以对复杂系统进行无限逼近,进而进行预测。建立了基于贝叶斯正则化BP神经网络的数字高程模型趋势面,与二次多项式建立的数字高程模型趋势面进行比较分析,证明了该方法的可行性和有效性。     

网络3维地球软件客户端缓存动态管理设计与实现

本地缓存机制能够显著减少数据请求,提高网络数据传输与可视化效率。本文探讨了多线程模式下的网络3维地球软件客户端空间数据访问与缓存替换流程,针对性设计并实现了一种基于内外双缓存及单一大数据文件模式的空间数据缓存动态管理机制,通过实验验证了方法的有效性。     

直接数字频率合成技术在声学释放器中的应用

直接数字频率合成技术(DDS)是一种新的频率合成方法,它具有转换时间短、相位变化连续、全数字可编程等优点.文中介绍了ADI公司生产的AD7008芯片作为频率信号源在声学释放器中的应用.     

基于数字频率合成技术的任意波形发生器设计与应用

介绍了直接数字合成技术的原理及其在任意波形发生器上的应用,设计了任意波形发生器和多类信号的 混合发生软件.并对任意波形发生器的性能进行了测试.测试结果表明,该仪器频率信号发生准确、可靠.将该仪器用于漆包线信号传输特性分析.得到了漆包线的频率特性.