基于小波变换的全色和多光谱遥感图像融合

基于多分辨率小波变换,针对高分辨率全色图像和多光谱图像的融合,提出了一种基于方向可调滤波器的区域能量测量的小波变换融合算法.将此方法与HIS和传统小波的融合方法比较,结果表明,该方法在保留多光谱图像光谱信息的同时,能够更好地保留高分辨率图像的空间信息,融合效果有较大改善.     

丽江市地质灾害易发性遥感影像判译

丽江市地质灾害多发,在滇西北旅游城市中较典型。应用遥感技术对丽江市地质灾害易发性的遥感研究,可突破传统方法,发挥宏观、综合、直观、快速特点,取得较好效果。     

像素级遥感图像融合方法研究

多传感器遥感图像融合按信息表征层次的不同,可以分为像素级融合、特征级融合和决策级融合。本文介绍了像素级层次上的多种遥感图像融合方法,阐述了其融合原理和实现过程,分析了它们适用性和优缺点,并给出了遥感图像融合的一般评价指标。     

构建基于GIS的房产管理

阐述了基于GIS房产管理的关键是建立统一的数据分类与编码标准,核心是建立房屋的空间地理属性信息、自然属性信息、社会人文属性信息的链接,基础是建立房产地理信息数据库。并提出了建立房产地理信息数据库的方法、设计思路和方式。     

城市形象资源和地域文化传统特色研究

城市是人类的一种社会组织结构形式,与其他任何组织形式一样,城市的发展也需要核心竞争力,核心竞争力依赖于城市核心资源系统的开发和创造。通过城市形象的塑造再创城市新型的核心资源,这已经是一个既成事实,城市形象可以在更高层次保护城市传统资源要素,使其发挥更大的作用。     

Automated Kerogen Classification in Microscope Images of Dispersed Kerogen Preparation

We develop the classification part of a system that analyses transmitted light microscope images of dispersed kerogen preparation. The system automatically extracts kerogen pieces from the image and labels each piece as either inertinite or vitrinite. The image pre-processing analysis consists of background removal, identification of kerogen material, object segmentation, object extraction (individual images of pieces of kerogen) and feature calculation for each object. An expert palynologist was asked to label the objects into categories inertinite and vitrinite, which provided the ground truth for the classification experiment. Ten state-of-the-art classifiers and classifier ensembles were compared: Naïve Bayes, decision tree, nearest neighbour, the logistic classifier, multilayered perceptron (MLP), support vector machines (SVM), AdaBoost, Bagging, LogitBoost and Random Forest. The logistic classifier was singled out as the most accurate classifier, with an accuracy greater than 90. Using a 10 times 10-fold cross-validation provided within the Weka software, we found that the logistic classifier was significantly better than five classifiers (p<0.05) and indistinguishable from the other four classifiers. The initial set of 32 features was subsequently reduced to 6 features without compromising the classification accuracy. A further evaluation of the system alerted us to the possible sensitivity of the classification to the ground truth that might vary from one human expert to another. The analysis also revealed that the logistic classifier made most of the correct classifications with a high certainty.     

雾灵山森林公园旅游形象设计

引入反馈调节设计理念，构建了旅游形象设计体系；运用该体系对雾灵山森林公园的旅游形象进行了多方案设计，拟在广泛征询意见的基础上最终裁定该公园的旅游形象方案。     

A Comparison of Sediment Varves (1950–2003 AD) in Two Adjacent Lakes in Northern Sweden

Koltjärnen and Nylandssjön are two closely situated lakes (<2 km apart) in northern Sweden. During the past century, distinct varved sediments have formed in these lakes. Nylandssjön has two varved, deep basins. Since lake and catchment characteristics superficially appear very similar for the two lakes and they are exposed to the same climate, one would expect the sediment varves to be similar. This investigation compares the varves in the two deep basins of Nylandssjön, and in the two lakes. The comparison of basins of Nylandssjön shows that varve thickness, water content and annual accumulation rates of organic matter and nitrogen are correlated for the period (1970–2003). The grey-scale curves are only clearly similar in about 50% of the varves. In the between-lake comparison varve thickness, water content and annual accumulation rates of organic matter and nitrogen are correlated for the period (1950–1996). However, the annual accumulation rates of dry mass, minerogenic matter and biogenic silica differ between the lakes, as well as within-varve successions in grey-scale. A general explanation to the differences is that the prerequisites for varve formation are not totally similar because of differences in catchment size, catchment- to-lake material fluxes, lake productivity and land-use influence. This study illustrates the complex relationships that exist between a lake, its catchment, in-lake productivity and formation of sediment varves. As a consequence, we must not apply a too simplistic view of the potential of varves as past climatic indicators, especially if the lakes are affected by land-use.     

Traction image method for irregular free surface boundaries in finite difference seismic wave simulation

In this study, we propose a new numerical method, named as Traction Image method, to accurately and efficiently implement the traction-free boundary conditions in finite difference simulation in the presence of surface topography. In this algorithm, the computational domain is discretized by boundary-conforming grids, in which the irregular surface is transformed into a 'flat' surface in computational space. Thus, the artefact of staircase approximation to arbitrarily irregular surface can be avoided. Such boundary-conforming gridding is equivalent to a curvilinear coordinate system, in which the first-order partial differential velocity-stress equations are numerically updated by an optimized high-order non-staggered finite difference scheme, that is, DRP/opt MacCormack scheme. To satisfy the free surface boundary conditions, we extend the Stress Image method for planar surface to Traction Image method for arbitrarily irregular surface by antisymmetrically setting the values of normal traction on the grid points above the free surface. This Traction Image method can be efficiently implemented. To validate this new method, we perform numerical tests to several complex models by comparing our results with those computed by other independent accurate methods. Although some of the testing examples have extremely sloped topography, all tested results show an excellent agreement between our results and those from the reference solutions, confirming the validity of our method for modelling seismic waves in the heterogeneous media with arbitrary shape topography. Numerical tests also demonstrate the efficiency of this method. We find about 10 grid points per shortest wavelength is enough to maintain the global accuracy of the simulation. Although the current study is for 2-D P-SV problem, it can be easily extended to 3-D problem.     

基于粗糙集的K--均值聚类算法在遥感影像分割中的应用

结合粗糙集理论和K——均值聚类算法，提出一种遥感影像的粗糙聚类分割方法。根据遥感影像中特征属性的相互依赖关系，应用粗糙集理论的等价关系。求出K——均值聚类所需要的初始类的个数和均值。然后采用聚类算法对图像进行分割。实验结果表明该方法比随机选取聚类的中心点和个数减少了运算量．提高了分类精度和准确性。