一种基于对象和多种特征整合的分类识别方法研究

遥感图像空间分辨率的提高，为目标物的纹理特征和形状特征的提取提供了客观基础，同时也使得传统的基于像元的分类识别方法受到了严重的挑战。因此，需要对传统的方法进行改进或发展新的方法。本文采用面向对象的分析思想，通过图像分割和分割对象的矢量化等一系列的预处理，并在此基础上实现了目标形状信息的提取，最后综合利用光谱特征和形状特征应用模糊分类器实现两种典型的人造目标的分类提取实验。识别的精度评价主要通过目视解译完成。分析表明，形状信息的提取大大丰富了目标识别的特征库，尤其在感兴趣目标与背景物具有相近的光谱反应而形状特征有明显差异的条件下，这种利用光谱与形状特征整合的提取方法能够大大提高目标的识别精度。     

综合分析技术在微细粒浸染型金矿金赋存状态研究中的应用

采用化学组分分析、物相分析、粒度筛析、X射线面扫描分析、矿物分离分析并结合数理统计分析等综合分析技术对微细粒浸染型金矿进行工艺矿物学研究,较为快速、准确地查明该金精矿金的赋存状态.几种分析方法互为补充,结果吻合.     

一个近地层中的三维随机扩散模式

利用横向Lagrange时间尺度T_(LY),与稳定度及高度的关系,本文建立了一个三维随机扩散模式,并用它模拟了近地层中地面源的扩散过程。模式计算结果表明:在稳定层结条件下该模式比取T_(LY)为常数得到的模式有明显的改进,而在不稳定条件下这一模式改进不大。     

Soil property variation mapping through data mining of soil category maps

Spatial information on soil properties is an important input to hydrological models. In current hydrological modelling practices, soil property information is often derived from soil category maps by the linking method in which a representative soil property value is linked to each soil polygon. Limited by the area‐class nature of soil category maps, the derived soil property variation is discontinuous and less detailed than high resolution digital terrain or remote sensing data. This research proposed dmSoil, a data‐mining‐based approach to derive continuous and spatially detailed soil property information from soil category maps. First, the soil–environment relationships are extracted through data mining of a soil map. The similarity of the soil at each location to different soil types in the soil map is then estimated using the mined relationships. Prediction of soil property values at each location is made by combining the similarities of the soil at that location to different soil types and the representative soil property values of these soil types. The new approach was applied in the Raffelson Watershed and Pleasant Valley in the Driftless Area of Wisconsin, United States to map soil A horizon texture (in both areas) and depth to soil C horizon (in Pleasant Valley). The property maps from the dmSoil approach capture the spatial gradation and details of soil properties better than those from the linking method. The new approach also shows consistent accuracy improvement at validation points. In addition to the improved performances, the inputs for the dmSoil approach are easy to prepare, and the approach itself is simple to deploy. It provides an effective way to derive better soil property information from soil category maps for hydrological modelling. Copyright © 2014 John Wiley & Sons, Ltd.     

广西近海灾害地质因素及声学反射特征

利用高分辨率地球物理资料及相关历史资料,对北部湾北部的广西近海灾害地质因素进行了地质地球物理解译,识别出海底沙波、海底沙脊、塌陷洼地、冲刷沟槽、浅层气、残积砂体、地层间断、埋藏丘、埋藏古河道等多种灾害地质因素.根据它们出现的频率、规模及声学特征可知:浅层气和埋藏古河道是广西近海最为发育的灾害地质因素,其对海洋工程的施工与建设有较大的危害性.     

鲜水河断裂带炉霍县卡扎村大探槽古地震研究

本文测定分析了特殊地区的两种不同饱和状态的干压实土体在不同等级荷栽作用下产生的沉陷量，探讨了施荷时间对沉陷量的影响从而提示了两种干压实土体在荷载作用下沉陷量变化规律，并分析研究了这两种干压实土体的最大压缩模量与饱和度的关系。这一研究成果对干旱特殊地区的公路设计施工具有一定的参考价值。     

全球海平面变化研究新进展

综述了近10年来海平面变化研究的主要成果,分析了影响海平面变化的主要因素,探讨了海平面变化研究中存在的一些问题。结果表明：①近10年全球平均海平面上升幅度大约为2.5~3.84 mm/a,热膨胀是引起海平面上升的主因;②海平面变化具有时空分布差异——西太平洋和东印度洋地区上升最快,其值高出全球平均值的10倍以上;大西洋与太平洋30~40°N地区季节变化最明显;③将海平面季节高值时段与北半球热带气旋出现时间进行对比,发现每年8~10月份,在20~50°N的西北太平洋与北大西洋沿岸地区出现海平面最高值与热带气旋相叠加的全球危险海岸带,该地带包括中国大陆东部、日本沿海地区、美国东部海岸带、墨西哥湾地区和加勒比海地区。     

交通地理信息系统中的时空动态分段模型研究

动态分段技术是交通地理信息系统(GIS-T)中一项重要的线性要素动态显示与分析技术,该文提出了一种时空动态分段模型,使动态分段系统的组成成分融入时态因素,并将属性的时态信息作为属性信息表的字段存储,通过时态地理信息系统技术完成物理段的时态变化。利用统一建模语言(UML)的类图设计方式开发了物理模型,描述了时空动态分段模型中对象之间的关系,并定义了必要的属性和操作;同时基于线性参照系统(LRS)表达空间实体的方法,概括了模型中所涉及到的主要拓扑关系。实验表明,时空动态分段模型弥补其他模型将时空参考分为时间参考和空间参考所产生的不足,而且更明确地将多重属性和物理实体有机结合起来。     

SVG在热带气旋信息图形化中的应用

介绍了SVG技术显示地图信息的优点以及使用MICAPS的地图数据做矢量地图的方法,提出用SVG图像进行热带气旋信息图形矢量化服务的技术方案,认为使用SVG技术开展气象信息图形矢量化服务的研发工作,可以大大提高气象预报信息产品的可视化程度与数据信息共享,以及结构化的信息交换能力。     

中国东海海平面长期变化与趋势研究

From the analyses of the satellite altimeter Maps of Sea Level Anomaly(MSLA) data, tidal gauge sea level data and historical sea level data, this paper investigates the long-term sea level variability in the East China Sea(ECS).Based on the correlation analysis, we calculate the correlation coefficient between tidal gauge and the closest MSLA grid point, then generate the map of correlation coefficient of the entire ECS. The results show that the satellite altimeter MSLA data is effective to observe coastal sea level variability. An important finding is that from map of correlation coefficient we can identify the Kuroshio. The existence of Kuroshio decreases the correlation between coastal and the Pacific sea level. Kurishio likes a barrier or a wall, which blocks the effect of the Pacific and the global change. Moreover, coastal sea level in the ECS is mainly associated with local systems rather than global change. In order to calculate the long-term sea level variability trend, the empirical mode decomposition(EMD) method is applied to derive the trend on each MSLA grid point in the entire ECS. According to the 2-D distribution of the trend and rising rate, the sea level on the right side of the axis of Kuroshio rise faster than in its left side. This result supports the barrier effect of Kuroshio in the ECS. For the entire ECS, the average sea level rose 45.0 mm between 1993 and 2010, with a rising rate of(2.5±0.4) mm/a which is slower than global average.The relatively slower sea level rising rate further proves that sea level rise in the ECS has less response to global change due to its own local system effect.