HDD扩孔钻具组合三维小挠度运动规律浅析

以HDD铺设管道直线段轨迹中的扩孔钻具组合为研究对象,将扩孔钻具简化为质量均匀分布的转子模型,对扩孔钻具进行了详细的受力分析。以转子动力学理论为基础,通过对扩孔钻具所受力及力矩表示并建立了力和力矩平衡方程,采用矢量分析方法推导出了在小挠度情况下扩孔钻具的三维控制微分方程。     

自动剪断线算法的设计与实现

结合相关几何学原理,阐述了线段之间存在的空间拓扑关系,并结合当前线段相交算法的优缺点,提出了判断线段间有唯一实交点的混合判断方法,并在此基础上完成了对自动剪断线算法的设计与实现。     

基于乘积模型的极化SAR滤波

提出了一种基于乘积模型的极化SAR滤波方法。首先基于乘积模型分离纹理信息和极化信息,然后分别独立地进行滤波,最后再合成协方差矩阵。实验表明,本方法有效可行,有较好的极化保持性能。     

改进的OIF和SVM结合的高光谱遥感影像分类

文章提出了一种结合改进的最佳指数法(OIF)和支持向量机(SVM)进行高光谱遥感影像分类新方法.利用本文提出的稳定系数进行波段初选择,根据相关系数选择波段组合生成新影像,并对新影像进行OIF计算,得到OIF值最大的波段组合为最佳波段组合;构建SVM分类器,对最佳波段组合分类;最后将分类结果与其他监督分类方法比较,并在相同核函数下与PCA和SVM结合的方法进行精度比较分析.实验结果表明,本文方法能够有效提取最佳波段组合,在SVM算法下获得较高分类精度.     

Impact of feature selection on the accuracy and spatial uncertainty of per-field crop classification using Support Vector Machines

Crop mapping is one major component of agricultural resource monitoring using remote sensing. Yield or water demand modeling requires that both, the total surface that is cultivated and the accurate distribution of crops, respectively is known. Map quality is crucial and influences the model outputs. Although the use of multi-spectral time series data in crop mapping has been acknowledged, the potentially high dimensionality of the input data remains an issue. In this study Support Vector Machines (SVM) are used for crop classification in irrigated landscapes at the object-level. Input to the classifications is 71 multi-seasonal spectral and geostatistical features computed from RapidEye time series. The random forest (RF) feature importance score was used to select a subset of features that achieved optimal accuracies. The relationship between the hard result accuracy and the soft output from the SVM is investigated by employing two measures of uncertainty, the maximum a posteriori probability and the alpha quadratic entropy. Specifically the effect of feature selection on map uncertainty is investigated by looking at the soft outputs of the SVM, in addition to classical accuracy metrics. Overall the SVMs applied to the reduced feature subspaces that were composed of the most informative multi-seasonal features led to a clear increase in classification accuracy up to 4.3%, and to a significant decline in thematic uncertainty. SVM was shown to be affected by feature space size and could benefit from RF-based feature selection. Uncertainty measures from SVM are an informative source of information on the spatial distribution of error in the crop maps.     

SAR polarimetric change detection for flooded vegetation

Abstract

Due to spatial and temporal variability an effective monitoring system for water resources must consider the use of remote sensing to provide information. Synthetic Aperture Radar (SAR) is useful due to timely data acquisition and sensitivity to surface water and flooded vegetation. The ability to map flooded vegetation is attributed to the double bounce scattering mechanism, often dominant for this target. Dong Ting Lake in China is an ideal site for evaluating SAR data for this application due to annual flooding caused by mountain snow melt causing extensive changes in flooded vegetation. A curvelet-based approach for change detection in SAR imagery works well as it highlights the change and suppresses the speckle noise. This paper addresses the extension of this change detection technique to polarimetric SAR data for monitoring surface water and flooded vegetation. RADARSAT-2 images of Dong Ting Lake demonstrate this curvelet-based change detection technique applied to wetlands although it is applicable to other land covers and for post disaster impact assessment. These tools are important to Digital Earth for map updating and revision.     

基于虚拟日变台进行地磁矢量数据日变通化方法

流动地震地磁矢量观测是一种获取地震前兆异常的方法,试验研究和观测实例表明,地震孕育引起的地磁场异常变化量级较小,因此在观测、数据处理过程中都要尽可能消除误差提高精度.本文主要从地磁矢量数据日变通化精度方面开展讨论,首先使用反距离加权插值法由泰安、武汉、崇明、杭州4个地磁台观测资料计算出蒙城地磁台相应的虚拟地磁数据,其磁偏角、水平分量、垂直分量三个要素与真实观测值的相关系数分别高达0.9987、0.9946和0.9806,验证了反距离加权插值方法对地磁观测数据空间插值的有效性.其次,选择东部和西部测区分别使用反距离加权插值方法建立各地磁矢量测点位置的虚拟日变台并用其进行通化,实例计算结果表明,该方法可有效提高日变通化精度,对于地磁台站稀疏地区更具实际应用价值.     

Prediction of Anopheles minimus habitat in India—a tool for malaria management

This paper reports research to predict the distribution of An. minimus, a malaria vector in forest fringe areas using GIS to support precision surveys for malaria control. Because An. minimus is a forest‐associated species, generalized thematic maps (1:6?000?000) of forest cover, soil type, altitude, rainfall and temperature were used. Digitization, overlaying, integration and analysis of thematic maps were done using Arc/Info 8.1 NT and Arc/View 3.2 (GIS, ESRI) software. GIS delineated favourable areas for An. minimus where the species is likely to be found, and precision surveys can be conducted. Precision field surveys in selected locations of favourable/non‐favourable areas were carried out. The species could be found in all locations designated as a favourable area and was absent in non‐favourable areas. In two districts, one where the species is reported to have disappeared in the early 1950s and the other where it was not reported in earlier surveys, GIS helped in precision surveys, and An. minimus was found. The technique can quickly cover vast and inaccessible areas and is easy to duplicate in other parts of the world to assist cost‐effective control of malaria. It can also delineate areas favourable for any species of flora and fauna to help precision surveys.     

Assessment of sliver polygons in geographical vector data

As positional error is a major issue in the assessment of spatial data quality, its propagation has been studied widely in map overlaying. However, few studies deal with a manifest consequence of positional error in map overlaying, namely sliver polygons. Sliver polygons are generally treated as awkward by-products that need to be removed quickly. Nevertheless, as they represent spurious areas, their nature and properties carry useful information, for example, for land use/cover assessment. Therefore, next to sliver removal, there is a need for intelligent detection and eventually further analysis of sliver polygons. This article proposes a general, semi-automated method for the assessment of slivers in vector polygon layers. A case study in Flanders (Belgium) illustrates a possible application in area estimation evaluation of land use allocation classes.