基于时刻独立脉冲耦合神经网络的高空间分辨率摇感影像分割

高空间分辨率遥感影像中地物目标内部光谱信息复杂性的增强,使得传统基于光谱特征值的数据处理方法效果不再显著,影像分割为解决这一问题提供了一种思路,成为当前高空间分辨率遥感影像处理的研究焦点.时刻独立脉冲耦合神经网络具有状态相近、空间相邻神经元相互耦合同步脉冲激发和区域之间神经元脉冲激发时刻独立两大特点,已被应用于非遥感影像分割中,并取得较好效果.本文结合高空间分辨率遥感影像特点,通过对网络参数进行实验和分析,提出一个基于时刻独立脉冲耦合神经网络的高空间分辨率遥感影像分割方法,并利用空间分辨率0.3m的航空影像进行了数据试验,将分割结果进行讨论并与现有时刻独立脉冲耦合神经网络方法和ISODATA方法分割结果进行对比分析.结果表明:时刻独立脉冲耦合神经网络在高空间分辨率遥感影像分割处理中具有很好的应用前景.     

遥感影像特征提取与选择及在影像分类中的应用

利用模式识别中特征提取和特征选择的相关理论对遥感影像的纹理特征进行遴选和变换处理,得到描述纹理的二次特征。实验证明这些新特征能够提高影像分类精度和分类效率。     

基于LBV变换的遥感影像多步骤分类法研究

面对与日俱增的遥感数据,如何快速准确地进行影像分类成为遥感领域亟待解决的问题。本文在前人的基础上提出了一种基于LBV变换的遥感影像多步骤分类方法。L:地物的总辐射水平,集中反映了裸地的信息;B:地物的可见-红外光辐射平衡,是地面水分状况和水体存在的一个良好指标;V:地物辐射随波段变化的方向和速度向量,能集中反映地面植被状况。多步骤分类法遵循由易到难的原则,能克服类别之间的互相影响,从而提高分类精度。文章结合LBV变换和多步骤分类法的优点对影像进行了分类,结果表明该方法简单易行,且能达到良好的分类精度。     

遥感图像线性影纹理解专家系统设计与实现

线性影纹信息是遥感图像中的一类重要信息,线性影纹信息自动提取是遥感图像智能解译的重要研究领域。笔者采用基于特征对象的专家系统技术来完成线性影纹信息的简单类别提取,设计并实现了线性影纹理解专家系统;阐明了系统结构,解译规则获取、表达,基于消息的不确定性推理机及解释机的设计;最后利用系统做了线性影纹类别提取实验,结果表明基于特征对象的专家系统用于线性影纹类别自动提取是切实可行的,并具有较高的提取精度。     

Approaches for comparative evaluation of raster GIS-based landslide susceptibility zonation maps

Evaluation of maps generated from different conceptual models or data processing approaches at spatial level has importance in many geoenvironmental applications. This paper addresses the spatial comparison of different landslide susceptibility zonation (LSZ) raster maps of the same area derived from various procedures.     

Estimating Influence of Crystallizing Latent Heat on Cooling-Crystallizing Process of a Granitic Melt and Its Geological Implications

Based on the theory of thermal conductivity, in this paper we derived a formula to estimate the prolongation period （AtL） of cooling-crystallization process of a granitic melt caused by latent heat of crystallization as follows：△tL=QL×△tcol/（TM-TC）×CP where TM is initial temperature of the granite melt, Tc crystallization temperature of the granite melt, Cp specific heat, △tcol cooling period of a granite melt from its initial temperature （TM） to its crystallization temperature （Tc）, QL latent heat of the granite melt.
The cooling period of the melt for the Fanshan granodiorite from its initial temperature （900℃） to crystallization temperature （600℃） could be estimated -210,000 years if latent heat was not considered. Calculation for the Fanshan melt using the above formula yields a AtL value of -190,000 years, which implies that the actual cooling period within the temperature range of 900°-600℃ should be 400,000 years. This demonstrates that the latent heat produced from crystallization of the granitic melt is a key factor influencing the cooling-crystallization process of a granitic melt, prolongating the period of crystallization and resulting in the large emplacement-crystallization time difference （ECTD） in granite batholith.     

A framework of region-based spatial relations for non-overlapping features and its application in object based image analysis

Object based image analysis (OBIA) is an approach increasingly used in classifying high spatial resolution remote sensing images. Object based image classifiers first segment an image into objects (or image segments), and then classify these objects based on their attributes and spatial relations. Numerous algorithms exist for the first step of the OBIA process, i.e. image segmentation. However, less research has been conducted on the object classification part of OBIA, in particular the spatial relations between objects that are commonly used to construct rules for classifying image objects and refining classification results. In this paper, we establish a context where objects are areal (not points or lines) and non-overlapping (we call this “single-valued” space), and propose a framework of binary spatial relations between segmented objects to aid in object classification. In this framework, scale-dependent “line-like objects” and “point-like objects” are identified from areal objects based on their shapes. Generally, disjoint and meet are the only two possible topological relations between two non-overlapping areal objects. However, a number of quasi- topological relations can be defined when the shapes of the objects involved are considered. Some of these relations are fuzzy and thus quantitatively defined. In addition, we define the concepts of line-like objects (e.g. roads) and point-like objects (e.g. wells), and develop the relations between two line-like objects or two point-like objects. For completeness, cardinal direction relations and distance relations are also introduced in the proposed context. Finally, we implement the framework to extract roads and moving vehicles from an aerial photo. The promising results suggest that our methods can be a valuable tool in defining rules for object based image analysis.     

改进的边缘角度直方图在遥感图像检索中的应用

针对基于形状的遥感图像检索中区域分割困难这个问题,本文提出利用边缘角度直方图作为形状特征对遥感图像进行检索;针对遥感影像分辨率和颜色反差对检索性能的影响,本文提出采用多尺度分析的思想,提取图像在多个尺度上的边缘角度直方图特征进行检索。通过单一尺度边缘角度直方图特征和多尺度边缘角度直方图特征检索的对比实验,揭示了本文所提出的改进方案使遥感图像的检索精度提高了约31个百分点。     

基于AHP和BP神经网络的深部地热水可持续开发能力评价

采用资料完整性、开采潜力、回灌量、平均水压下降速率、地面沉降速率、水温、水质、地热井布局8项指标构建天津地热可持续开发能力评价指标体系;运用层次分析法确定了各项指标的权重,建立起评价因素集和评语集,给出了归一化数值;建立了天津地热可持续开发能力的BP神经网络模型,以层次分析法得出的结果作为样本,对BP网络进行了训练和测试,实例评价结果表明了AHP和BP神经网络方法的可行性,为地热资源的可持续开发能力评价提供了一种新的评价方法。     

ASTER多光谱波段与SPOT全色波段融合方法研究

遥感图像融合可以发挥多源遥感数据的优势。但由于不同传感器的遥感数据有着不同的特征,不同数据所采用的融合方法也应不同。文章探讨了ASTER多光谱波段与SPOT全色波段数据融合的方法,通过对PCA融合、IHS融合和基于小波的IHS融合方法的对比研究,得出基于小波的IHS融合法在提高空间分辨率的同时较好地保持了地物的多光谱信息。