Multiobjective PSO based adaption of neural network topology for pixel classification in satellite imagery

The proposed work involves the multiobjective PSO based adaption of optimal neural network topology for the classification of multispectral satellite images. It is per pixel supervised classification using spectral bands (original feature space). This paper also presents a thorough experimental analysis to investigate the behavior of neural network classifier for given problem. Based on 1050 number of experiments, we conclude that following two critical issues needs to be addressed: (1) selection of most discriminative spectral bands and (2) determination of optimal number of nodes in hidden layer. We propose new methodology based on multiobjective particle swarm optimization (MOPSO) technique to determine discriminative spectral bands and the number of hidden layer node simultaneously. The accuracy with neural network structure thus obtained is compared with that of traditional classifiers like MLC and Euclidean classifier. The performance of proposed classifier is evaluated quantitatively using Xie-Beni and β indexes. The result shows the superiority of the proposed method to the conventional one.     

Road Extraction from High Resolution Remote Sensing Image based on Shape Analysis with Gestalt Theory

Simulating the psychological experience of human vision，a road extraction model based on the format tower is proposed to extract the road in the high resolution remote sensing image from the perspective of morphology.Firstly，based on the spectral and texture information，the suspected road targets are extracted by using segmentation technology.Then these targets are classified according to their reliability and extract the road targets for each category.Finally，three types of identified road information are verified and merged，and the continuous smooth road extraction results are obtained.Experiments on real high resolution images show that the results are consistent with the visual perception of the human eye，and the overall classification accuracy is higher，indicating that the algorithm is effective and feasible and has good use value.     

小波变换在光谱特征提取方面的应用

人们在处理高光谱图像时一般要对一些典型地物进行光谱分析、特征波段的提取,以便提取出最大量的有效信息,剔除无用或冗余的信息,然后再进行分类识别.采用小波变换的分析方法,选用合适的小波进行分解,根据分解后的高频分量中包含的重要信息,利用局部相邻的正负极值点找出对应于原始光谱曲线上每个吸收带的左右边界;利用局部过零点,即可比较精确的提取出各个吸收带的中心波长.该方法比传统的光谱特征提取方法更简洁、有效,实验证明为一种比较理想的光谱特征提取方法.     

韩江三角洲海岸变迁遥感调查研究

利用1:10万TM影像，对广东东部韩江三角洲地区的海岸变迁及河道演变进行了调查研究。划分了不同时期的海岸界线和古河道遗迹，提出韩江三角洲的形成是河流动力和海洋动力共同作用的结果，对研究历史海平面变化及环境演变具重要意义。     

地壳应力场和密度场资料在油气检测中的应用

依据卫星轨道摄动测量结果反演的地壳区域构造应力场和密度场资料，可圈定油气区域构造圈闭和储集油气的低密度层。计算绘制了闽江口扇形洲区域构造应力场和密度卫星遥感图，图上显示出东海近海闽浙中拗陷含油气带与温东丽水油气构造带相接，敖江口官岭与闽江口川石储岛沥青苗等迹象都在此范围内，在闽江口扇形洲东部沿海沙泥沉积区，邻区东海宽长带深厚海沙软泥沉积区及本区北部罗源湾，用大地电磁CSAMT检测到1000－3000m深度范围内的低阻率地层，与本区卫星遥感图图低密度场相符。     

后遥感应用技术的提出与思考

本文在总结遥感技术应用于铀矿地质领域的实践和遥感技术最新进展的基础上。提出后遥感应用技术，并对其技术内涵、研究内容、建立试验样区、研究意义等进行了探讨。     

Mapping Turbidity, Surface Temperature and Water Circulation Patterns with the Aid of Satellite Imagery

Water turbidity, surface temperature and circulation of Barton and Wroxham Broads, two of the Norfolk Broads, were studied using one reflective (TM1) and the thermal (TM6) TM band. The results indicated that the through-flowing path of the River Ant in Barton Broad is the major influence on the distribution of these parameters. In Wroxham Broad, both turbidity and surface temperature displayed a uniform distribution. This could be explained by the absence of a predominant direction of flow.     

压电类智能层合结构的力学和计算模型综述

综述了压电类智能层合结构的力学和计算模型。基于大量国内外有关压电类智能层合结构的文献 ,根据各自采用的运动学假设、场变量的近似、压电层的表达法以及曲率和温度的影响 ,对压电层合结构的力学和计算模型进行了分类 ,阐述了各种理论的特点及一般形式。     

湿敏半导体材料电导率计算方法的研究

结合修正了的耗尽层理论和多孔湿敏半导体的特点，本文提出了一个简单的物理模型作为ｎ型湿敏半导体特征的一级近似。描述了多孔湿敏半导体的导电机理，并给出了湿度与宏观电导率的关系。