Grid pattern recognition in road networks using the C4.5 algorithm

Pattern recognition in road networks can be used for different applications, including spatiotemporal data mining, automated map generalization, data matching of different levels of detail, and other important research topics. Grid patterns are a common pattern type. This paper proposes and implements a method for grid pattern recognition based on the idea of mesh classification through a supervised learning process. To train the classifier, training datasets are selected from worldwide city samples with different cultural, historical, and geographical environments. Meshes are subsequently labeled as composing or noncomposing grids by participants in an experiment, and the mesh measures are defined while accounting for the mesh’s individual characteristics and spatial context. The classifier is generated using the C4.5 algorithm. The accuracy of the classifier is evaluated using Kappa statistics and the overall rate of correctness. The average Kappa value is approximately 0.74, which corresponds to a total accuracy of 87.5%. Additionally, the rationality of the classifier is evaluated in an interpretation step. Two other existing grid pattern recognition methods were also tested on the datasets, and comparison results indicate that our approach is effective in identifying grid patterns in road networks.     

矿床成矿系列——五论矿床的成矿系列问题

矿床的成矿系列(简称成矿系列)是矿床学领域的一个理论性概念,由五级序次组成。矿床成矿系列是成矿系列的第二序次,是成矿系列的核心部分。矿床成矿系列的划分,以岩浆、沉积、变质、表生和流体(非岩浆-非变质成因流体)5种成矿作用为基本原则,以成矿地质环境为基础,结合成矿的时段与形成的矿床组合进行划分。本文对矿床成矿系列时空范围、时空组成结构、矿化强度与演化、成矿区带内不同矿床成矿系列之间的演化、叠加和复合作用及对指导找矿的意义进行了论述。     

基于面向对象分类的稀土开采区遥感信息提取方法研究

离子吸附型稀土矿是我国宝贵的矿产资源,运用遥感影像分类技术提取稀土开采区可以准确地实现对稀土开采状况的监测,但仅利用光谱信息往往难以保证分类精度。本文以江西寻乌稀土矿区为研究区,以IKONOS影像为数据源,应用面向对象分类方法提取了稀土开采区的遥感信息。针对稀土开采区的分布特点,选择基于边缘的分割算法进行影像分割;结合地形信息、光谱信息及几何信息建立规则集,进行特征提取;最后采用隶属度函数法实现面向对象分类,并与传统的光谱角填图分类进行对比分析。研究结果表明,面向对象分类法提取稀土开采区的总体精度为92.49%,Kappa系数为0.857 6,与传统监督分类方法相比有了很大的提高。     

Objective Analysis on Large-scale Circulation Type and Its Links to Precipitation over China

Atmospheric circulation anomaly is a direct cause of weather and climate change. In the past, most researches for the relationship between Weather Type (WT) and precipitation have mainly focused on the subjective classification and diagnosis. Compared to the subjective analysis, objective classification uses more consistent index and standard unification, thus, we can get more WTs, and it has been widely used in many areas. By using daily 12UTC Sea Level Pressure (SLP), Precipitable Water (PW), and 700 hPa wind speed (UV700) data from ECMWF’s Interim Reanalysis, the classification of WTs over China was performed with the method of obliquely rotated T-mode principle component analysis. WT and its link to precipitation over China were further analyzed. The results show that the influence of different WTs on precipitation is not uniform over China, and also show distinctly difference in different seasons. A common feature is that WTs great impact on the regions and months with large precipitation, while less impact on regions and months have with less precipitation. In addition, precipitation trends originating from WT intensity changes are much more deterministic, significant, and predictable than trends from WT frequency changes.     

基于支持向量机的喀斯特山区土壤环境质量评价——以贵州北部一茶叶园区为例

以贵州北部一茶叶园区80个表层土壤样品为研究对象,对其Hg、As、Cd、Pb、Cr和Cu含量进行测定,在MATLAB中应用支持向量机构建土壤环境质量评价模型,并与模糊综合评价法和内梅罗综合污染指数法的评价结果对比分析,探究支持向量机模型在喀斯特山区土壤环境质量评价中的适用性,其结果表明:研究区土壤质量Ⅰ类与Ⅱ类样品比例为33∶7,土壤环境质量大多数为I类;支持向量机方法的评价结果与模糊综合评价法和内梅罗综合污染指数法结果的相同率分别达到82.5%和80.0%,并分析结果有差异的样品,发现支持向量机评价结果更符合实际情况,这说明该模型适用于土壤环境质量的评价。      

Detection and mapping of bracken fern weeds using multispectral remotely sensed data: a review of progress and challenges

Bracken fern is one of the major invasive plants distributed all over the world currently threatening socio-economic and ecological systems due to its ability to swiftly colonize landscapes. The study aimed at reviewing the progress and challenges in detecting and mapping of bracken fern weeds using different remote sensing techniques. Evidence from literature have revealed that traditional methods such as field surveys and modelling have been insufficient in detecting and mapping the spatial distribution of bracken fern at a regional scale. The applications of medium spatial resolution sensors have been constrained by their limited spatial, spectral and radiometric capabilities in detecting and mapping bracken fern. On the other hand, the availability of most of these data-sets free of charge, large swath width and their high temporal resolution have significantly improved remote sensing of bracken fern. The use of commercial satellite data with high resolution have also proven useful in providing fine spectral and spatial resolution capabilities that are primarily essential to offer precise and reliable data on the spatial distribution of invasive species. However, the application of these data-sets is largely restricted to smaller areas, due to high costs and huge data volumes. Studies on bracken fern classification have extensively adopted traditional classification methods such as supervised maximum likelihood classifier. In studies where traditional methods performed poorly, the combination of soft classifiers such as super resolution analysis and traditional methods of classification have shown an improvement in bracken fern classification. Finally, since high spatial resolution sensors are expensive to acquire and have small swath width, the current study recommends that future research can also consider investigating the utility of the freely available recently launched sensors with a global footprint that has the potential to provide invaluable information for repeated measurement of invasive species over time and space.     

Object- and pixel-based classifications of macroalgae farming area with high spatial resolution imagery

Macroalgae plays an important role in coastal ecosystems. The accurate delineation of macroalgae areas is important for environmental management. This study compared the pixel- and object-based methods using Gaofen satellite no. 2 image to explore an efficient classification approach. Expert system rules and nearest neighbour classifier were adopted for object-based classification, whereas maximum likelihood classifier was implemented in the pixel-based approach. Normalized difference vegetation index, normalized difference water index, mean value of the blue band and geometric characteristics were selected as features to distinguish macroalgae farms by considering the spectral and spatial characteristics. Results show that the object-based method achieved a higher overall accuracy and kappa coefficient than the pixel-based method. Moreover, the object-based approach displayed superiority in identifying Porphyra class. These findings suggest that the object-based method can delineate macroalgae farming areas efficiently and be applied in the future to monitor the macroalgae farms with high spatial resolution imagery.     

综合物探法在砂岩型铀矿中深部找矿中的实践与分析——以新疆昭苏盆地为例

为了探查新疆昭苏盆地砂岩型铀矿的异常信息,选择可控源音频大地电磁测量、高精度磁测和土壤氡气测量三种物探方法,并简要介绍各方法的工作原理。通过分析昭苏盆地的地质特征、物性特征和本区的找矿难点,对昭苏盆地综合物探数据所蕴含的信息进行地质-物探综合解译。实践证明:可控源音频大地电磁测量对低阻和高阻体均有良好的电性响应,可以划分地层、推断断裂构造;高精度磁测可以推断氧化还原界面,辅助解释断裂构造;土壤氡气测量可辅助解释断裂构造,对地下铀矿体有指示作用,三种方法的技术特性相互补充,提高了物探解释的准确性。突破了伊犁盆地以往600 m的找矿深度,并以电性稳定的中阻厚层、磁测异常、氡异常偏高晕和峰-谷状曲线作为预测标志,解决了深埋藏条件下赋矿地质体的圈定难点,在昭苏盆地砂岩型铀矿中、深部找矿工作中取得了良好的效果。     

ANALYSIS OF PILES USED FOR SLOPE STABILIZATION

Piles used for the stabilization of slopes have to be adequately designed to resist the induced lateral loads due to the movement of the unstable slope. In this paper, a numerical method is presented for the analysis of this problem. In this approach, the piles are modelled using beam finite elements. The soil response at the individual piles is modelled using the modulus of subgrade reaction and pile–soil–pile interaction considered using the theory of elasticity. Two case histories, one for single pile and the other for pile group, are analysed which show that the numerical model can predict the general characteristics of the piles reasonably well. The study suggests that the design of the piles based on the computed response from single pile analysis, ignoring group effects, may be unduly conservative.     

A STUDY ON A NEW MECHANICAL MODEL FOR FOUNDATIONS AND ITS ELASTIC SETTLEMENT RESPONSE

In the present paper, a new foundation model has been proposed by introducing a stretched rough elastic membrane in the Pasternak shear layer sandwiched between two spring layers which is an extension of Kerr model. Considering the equilibrium of different elements, the equations governing the elastic settlement response of the model are derived. Finite difference scheme has been employed to solve the governing equations. The parametric studies carried out show the effect of several parameters on the elastic settlement response of the model. The proposed model is well suited for idealizing the behavior of geosynthetic-reinforced granular fill—soft soil system besides other applications.