遥感影像制图综合的智能化研究

本文以人工智能为基础,用计算机模拟一般制图人员对遥感图像进行制图综合的过程,用框架的知识表示方法建立了一个实验性的知识库,并设计了一个推理机。对蒙古人民共和国乌布苏淖尔地区的ＴＭ分类图进行了实验,取得了较好的效果。     

地面沉降时空形变场的构建方法研究

由于离散分布的精密水准测量数据只能对点状沉降信息进行监测分析,描述特定时间点的静态空间趋势,无法表达区域性地面沉降整体时空变化.该文提出一种地面沉降时空形变场的构建方法,在多项式拟合法构建形变场的基础上考虑时间项,通过探索地面沉降量与坐标、时间的关系,对区域地面形变的整体效果进行拟合,构建地面沉降时空形变场.该方法顾及...     

高精度住房空置率的地理空间影响因素定量研究

为揭示住房空置率对地理空间因素的依赖性,本文首先以50 m×50 m格网为基本单位,通过建模等方式计算格网尺度的住房空置率、自然因子、社会因子,然后对研究区进行不同级别的划分和相关性分析,最后采用地理探测器法对自然因子的影响机制进行进一步研究。结果表明：①研究区住房空置率与所选地理空间因子均呈显著性相关,植被占比对住房空置率的影响程度最大,其他自然因子的影响程度普遍偏小;②由于非建成区尚处于快速发展阶段,有较大的发展潜力,因此非建成区对于社会因子和自然因子的依赖程度均大于建成区;③各街道的住房空置率受坡度的影响程度普遍小于其他自然因子,各因子两两之间的交互作用对住房空置率的解释力具有显著增强的效果。本文为小区域住房空置率的影响因素剖析提供了参考。     

Experimental Analysis of Various Types of Road Intersections for Interchange Detection

Road interchanges are a major pattern type in road networks. Recognition of road interchanges benefits automated road network generalization, car navigation and traffic flow analysis. This study first investigated several existing approaches to automatically detecting interchanges in a road network, and determined that the recognition of characteristic road intersections is essential for the effective detection of interchanges. Several experiments were carried out to investigate nine types of road intersections for interchange detection and to analyze characteristic ones. Furthermore, an approach to the detection of both intersections and segments of interchanges was proposed and validated. The road networks across different scales were tested and results show that: (1) the T‐shaped and Cross‐shaped junctions are very common in road networks, but they are not the most characteristic ones for interchange detection; (2) the y‐shaped, Y‐shaped types, X‐shaped, Fork‐shaped and Multi‐leg may be the characteristic types for interchange detection; (3) the proposed approach to detecting interchanges is effective, and most of the intersections and segments of interchanges can be detected. In addition, taking multiple characteristic types into consideration for interchange detection is suggested.     

Comparative Study of Approaches to Delineating Built‐Up Areas Using Road Network Data

Delineated built‐up areas may be used for applications such as navigation, database enrichment and the identification of urban sprawl. As more road network data have become available, many studies have considered using road network data to delineate built‐up areas. This study investigated the three existing approaches to delineating built‐up areas on a map: the grid‐based approach, kernel density analysis and an approach based on street blocks. These approaches are evaluated and compared from three angles. First, two measures were proposed to quantitatively evaluate the land area of the delineated built‐up areas; second, a questionnaire was designed to visually compare the representations of the delineated built‐up areas; and, third, the time complexity of using each approach was tested. The three approaches were applied to different sets of road network data for New Zealand; data from buildings and residential areas were used as benchmarks. The results showed that: (1) in a quantitative assessment, both the grid‐based approach and kernel density analysis can usually detect more built‐up areas than the approach based on street blocks; (2) on visual inspection, most of the students who completed the questionnaire performed the representations using the approach based on street blocks; and (3) in time complexity, the approach based on street blocks always takes the least time.     

融合像素—多尺度区域特征的高分辨率遥感影像分类算法

针对基于像素多特征的高分辨率遥感影像分类算法的"胡椒盐"现象和面向对象影像分析方法的"平滑地物细节"现象,提出了一种融合像素特征和多尺度区域特征的高分辨率遥感影像分类算法。(1)首先采用均值漂移算法对原始影像进行初始过分割,然后对初始过分割结果进行多尺度的区域合并,形成多尺度分割结果。根据多尺度区域合并RMI指数变化和分割尺度对分类精度的影响,确定最优分割尺度。(2)融合光谱特征、像元形状指数PSI(Pixel Shape Index)、初始尺度和最优尺度区域特征,并对多类型特征进行归一化,最后结合支持向量机(SVM)进行分类。实验结果表明该算法既能有效减少基于像素多特征的高分辨率遥感影像分类算法的"胡椒盐"现象,又能保持地物对象的完整性和地物细节信息,提高易混淆类别(如阴影和街道,裸地和草地)的分类精度。     

星地多源数据的区域土壤有机质数字制图

土壤有机质(SOM)是全球碳循环、土壤养分的重要组成部分,精确估算土壤有机质含量具有重要意义。本文以中国东北—华北平原为研究区,收集了1078个土壤样本,以遥感数据(MODIS,TRMM和STRM数据)与土壤地面光谱数据为预测因子,运用基于树形结构的数据挖掘技术构建土壤有机质-环境预测因子模型进行数字土壤制图。通过不同建模样本数建模精度比较,选择300个样本数时的模型为最优模型。建模结果表明土壤光谱和气候因子是研究区SOM变异的主控因子,生物因子次之,而地形因子影响最小。预测结果经检验,RMSE为7.25,R2为0.69,RPD为1.53制图结果与基于第二次全国土壤普查数据的土壤有机质地图具有相似的分布规律,呈现SOM自东北向西南递减的趋势。通过比较分析发现,经过20年左右的土地开发与利用,研究区低SOM和高SOM含量土壤面积减少,而中等SOM含量土壤面积增加。     

一种适用于电离层层析成像的TV-MART算法

针对电离层电子密度重构问题,提出了一种综合利用总变差最小化(toalvariation,TV)与乘法代数重构算法(multiplicativealgebraicreconstructiontechnique,MART)的电离层层析成像算法。该算法对反演模型的参数施加总变差约束,以提高反演过程的稳定性和结果的精确性。通过模拟数据和实测数据对模型的重构结果进行验证,结果表明,相对于乘法代数重构算法,该算法能够有效地提高电离层电子密度的重构精度。     

贵州省国土资源执法监察监管系统建设与应用

针对贵州省山地居多、生态环境脆弱、交通通讯不发达,人力资金相对不足等现状,研究建设了在线、离线相结合,内业、外业相协同,"省、市、县、乡"四级一体化应用,涵盖"线索发现、问题分析、外业核查、立案查处"全流程的国土资源执法监察监管系统。系统突破了高效、高精度、多模式的国土资源执法监察监管的系列关键技术方法,建立了国土资源监察监管系统与"一张图"平台一体化集成应用的新模式,已经部署应用到贵州省国土资源执法局和9个市州国土局和若干区县国土局。实践表明系统可以节省大量的国土资源执法人力、物力和时间,有效提升贵州省国土资源执法监察监管的效率和水平。     

电网GIS全过程管理及数据获取技术研究

针对电网GIS数据的及时性维护、低压及营销用户设备的数据获取存在的较大需求,通过对电网GIS在不同环节、不同业务部门的数据管理需求及维护流程的研究,提出了一套安全、规范、高效的电网GIS数据全过程管理体系,探讨了移动终端安全通信及自动采集过程中涉及的关键技术。该研究成果有利于保证电网GIS数据的整体性、完整性、准确性和及时性,能够推动平台及各业务系统的实用化,推进了智能电网的信息化建设。