智能化专题地图表示方法选择的研究

首先阐述了专题地图表示方法选择的知识,包括十种常用表示方法的描述、影响表示方法选择的因素、表示方法选择之间的配合原则,提出了选择专题地图表示方法的新规则,总结了表示方法间搭配的可能性;接着介绍了知识工程中知识模型的基本概念,在此基础上,建立了专题地图表示方法选择的知识模型并利用关系数据库的理论与方法对其进行了模拟;最后基于WebService开发了试验系统并举例说明了问题。     

一种遥感影像目标的快速标记算法

遥感影像的分类方法在其研究中占有重要的地位。本文探讨了分类方法中的目标标记方法,比较分析了其原理及各自的优缺点,同时提出了一种快速标记方法。该方法引入了标记号等价结构体,消除了标记号冲突引起的标记差,提高了算法的执行效率,并在实验中验证了该方法的可行性。     

道路曲线放样方法的实验

对曲线放样的常见方法进行了比较分析,提出了改进方法,结合实例对自由设站极坐标法、DGPS-RTK法曲线测设方法进行了深入讨论,给出了相应的数据处理方法和实验方法,实验结果表明DGPS-RTK技术使曲线放样精度更高,实现更便捷。     

开采沉陷预报方法研究现状与展望

本文论述了建立开采沉陷模型的基本方法,介绍了现行地表移动预报方法,讨论了特殊地质采矿条件下开采沉陷的预报方法,最后指出了今后地表移动预报方法的发展方向。     

基于全站仪自由设站的高填方机场边坡变形监测方法

分析了高填方机场边坡变形监测传统方法的不足,创造性地提出了应用单台全站仪的自由设站变形监测方法,并提出了基于光束法平差的多测站观测值统一解算的数据处理方法,在实际工程中与GPS方法进行了比对,论证了该方法的正确性和优越性,为今后解决类似工程问题提供了成功的经验。     

高阻抗管线探测的方法概述

对高阻抗管线探测方法进行了概要总结,提出了多种探测方法,并对每种方法的基本原理、工作方法、优缺点等进行了阐述。     

测边后方交会在精密工程中的应用分析

本文通过对普通测设方法（极坐标法、直角坐标法等）的分析引出了测边后方交会的方法,并简要介绍了测边后方交会法的基本原理,推导了测边后方交会法的计算公式,评定了该方法的精度,论证了该方法在精密工程中的可行性,弥补了极坐标、直角坐标等普通测设方法在精密工程中的缺陷。     

星载宽幅SAR干涉数据处理研究

结合ScanSAR的工作原理和特点,提出了分条带处理的方法,分析了ScanSAR数据处理的关键,对比分析叠片式条带拼接和配准加权拼接两种方法,提出了改进的配准加权方法,并用实验证明了本文提出的分条带处理方法和改进的配准加权方法的可行性和可靠性,为ScanSAR干涉测量的进一步研究提供了科学参考。     

遥感影像分类中的空间尺度选择方法研究

提出了一种新的基于信息熵的空间尺度选择方法。该方法充分利用了遥感影像的多光谱信息。在这个方法中, 信息熵被用于评价影像类别可分性的定量标准; 另外影像的空间分布特征也被考虑。该方法与已有方法, 即基于局部方差的方法、基于变异函数(Variogram)的方法、基于离散度的方法, 进行了比较。TM和QuickBird两种影像被引入到评价中来。实验结果表明, 本方法能够准确地确定两种实验影像的最优分类精度所对应的空间尺度。QuickBird影像采用了面向对象的分类方法进行实验, 这表明本方法不仅适合于传统的分类方法, 同时也适用于面向对象的方法。通过比较分析表明, 本文方法明确优于已有各种方法。     

地理空间数据自动综合方法的研究现状与发展趋势

多年来人们已经报道了很多自动综合方法。这些方法确实解决了地理空间数据自动综合中的很多重要问题,但这些方法也有明显的缺陷和应用范围。本文对这些方法进行了研究,研究内容包括这些方法的分类、原理、优缺点和适用范围,并提出了今后自动综合方法的研究发展趋势。     

阿克苏河-塔里木河水系水质污染遥感监测与评价

 采用Landsat TM数据分析了阿克苏河—塔里木河断面水质污染状况,通过波段的DN值和常规监测数据建立能反映水质状况的 污染物监测模型。结果发现,将2000年常规监测数据代入模型后,与遥感数据的结果基本吻合| 重建阿克苏河—塔里木河的连续水体 污染变化曲线,得出污染物浓度随着远离上游而增加。     

地图符号及其本质的研究

本文探讨了制约地图符号设计的内在的基本规律,提出了地图符号的约定性原则和等价性原理。把作为地图符号的物质时象同传输过程中的地图符号区别开来,分析了地图符号的价值及价格,并对内涵地图符号和外延地图符号及其相互关系进行了研究,最后提出了新的地图符号分类原理。     

大地重力学的新进展

介绍了当前利用卫星探测地球重力场的技术及其实践,也就是目前采用的高轨卫星追踪低轨卫星技术(hl-SST)、低轨卫星追踪低轨卫星技术(ll-SST)、卫星重力梯度测定技术(SSG),及其相应的正在运行的CHAMP、GRACE、GOCE卫星和考虑发射的GRACEFollow-On卫星。运行的三颗卫星所提供的地球重力场信息不论在精度和分辨率方面都是大地重力学的一个重大进展。介绍了地形数据在构建地球重力场模型中的作用和美国SRTM对全球地形数据的测量。最后介绍了EGM2008与我国已有大陆重力值的比较,平均差值约为11mgal,与我国大陆现有的高程异常值的比较,平均差值为27cm左右。     

Landslide risk analysis between Giri and Tons Rivers in Himachal Himalaya (India)

The area around Sataun in the Sirmur district of Himachal Pradesh, India (falling between the rivers Giri and Tons; both tributaries of the Yamuna River) was studied for landslide vulnerability on behalf of the inhabitants. The study was made using extensive remote sensing data (satellite and airborne). It is well supported by field evidence, demographic and infrastructural details and aided by Geographic Information System (GIS) based techniques. Field observations testify that slope, aspect, geology, tectonic planes, drainage, and land use all influence landslides in the region. These parameters were taken into consideration using the statistical approach of landslide hazard zonation. Using the census data of 1991, vulnerability of the populace to the landslide hazard was accessed. As most of the infrastructure in the region is concentrated around population centres, population data alone was used for vulnerability studies.     

Behavior-based aggregation of land categories for temporal change analysis

Comparison between two time points of the same categorical variable for the same study extent can reveal changes among categories over time, such as transitions among land categories. If many categories exist, then analysis can be difficult to interpret. Category aggregation is the procedure that combines two or more categories to create a single broader category. Aggregation can simplify interpretation, and can also influence the sizes and types of changes. Some classifications have an a priori hierarchy to facilitate aggregation, but an a priori aggregation might make researchers blind to important category dynamics. We created an algorithm to aggregate categories in a sequence of steps based on the categories’ behaviors in terms of gross losses and gross gains. The behavior-based algorithm aggregates net gaining categories with net gaining categories and aggregates net losing categories with net losing categories, but never aggregates a net gaining category with a net losing category. The behavior-based algorithm at each step in the sequence maintains net change and maximizes swap change. We present a case study where data from 2001 and 2006 for 64 land categories indicate change on 17% of the study extent. The behavior-based algorithm produces a set of 10 categories that maintains nearly the original amount of change. In contrast, an a priori aggregation produces 10 categories while reducing the change to 9%. We offer a free computer program to perform the behavior-based aggregation.     

城市数字高程模型和数字正射影像建库系统架构

数字高程模型和数字正射影像是城市基础地理信息的核心载体.两者数据都是连续的地表模型数据.本论文旨在研究建立一个以这两种数据为主体的数据库集成管理系统,并能够提供基本的分析和应用功能,为城市的规划、建设、管理和社会各行业提供完善、优质和高效的地理空间数据服务.论文以宁波市两者数据的建库为例.首先介绍一些有关背景资料;然后详细研究了该系统的设计情况,包括设计的原则、技术路线,数据组织和功能规划;最后进行总结,分析了该系统架构设计的优缺点.     

关于社区详图编制与设计的探讨

地图是人们生活中不可或缺的一种工具,是国防建设的重要支持。专题图作为地图的一个大类,是以集中表现某种主题内容的地图。如今,根据不同的需要,专题图表现形式繁多。社区详图作为以社区为地图表现范围,以与社区相关信息为主题的专题图首次出现在杭州。本文从地图的分类出发,通过杭州市社区详图的编制等情况,进一步与大家共同探讨社区详图的编制与设计,以及社区详图在日常的生活中所发挥的作用及领域。     

利用DPS与RS技术生成DOM复合产品的试验研究

DPS具有几何精度高的特点，而RS具有信息量大、现势性强的优点，本文的目的是将两者的优点融合起来，形成DPS与RS的复合产品。研究了融合的理论基础，设计了融合的工艺流程，经过试验得出了令人满意的结果。     

Automatic representation and reconstruction of DBM from LiDAR data using Recursive Minimum Bounding Rectangle

Three-dimensional building models are important for various applications, such as disaster management and urban planning. The development of laser scanning sensor technologies has resulted in many different approaches for efficient building model generation using LiDAR data. Despite this effort, generation of these models lacks economical and reliable techniques that fully exploit the advantage of LiDAR data. Therefore, this research aims to develop a framework for fully-automated building model generation by integrating data-driven and model-driven methods using LiDAR datasets.The building model generation starts by employing LiDAR data for building detection and approximate boundary determination. The generated building boundaries are then integrated into a model-based processing strategy because LiDAR derived planes show irregular boundaries due to the nature of LiDAR point acquisition. The focus of the research is generating models for the buildings with right-angled-corners, which can be described with a collection of rectangles under the assumption that the majority of the buildings in urban areas belong to this category. Therefore, by applying the Minimum Bounding Rectangle (MBR) algorithm recursively, the LiDAR boundaries are decomposed into sets of rectangles for further processing. At the same time, the quality of the MBRs is examined to verify that the buildings, from which the boundaries are generated, are buildings with right-angled-corners. The parameters that define the model primitives are adjusted through a model-based boundary fitting procedure using LiDAR boundaries. The level of details in the final Digital Building Model is based on the number of recursions during the MBR processing, which in turn are determined by the LiDAR point density. The model-based boundary fitting improves the quality of the generated boundaries and as seen in experimental results, the quality depends on the average LiDAR point spacing. This research thus develops an approach which not only automates the building model generation, but also achieves the best accuracy of the model while utilizing only LiDAR data.     

A novel approach to optimize hierarchical vegetation mapping from hyper-temporal NDVI imagery,demonstrated at national level for Namibia

This paper presents a novel methodological approach to countrywide vegetation mapping. We used green vegetation biomass over the year as captured by coarse resolution hyper-temporal NDVI satellite-imagery, to generate vegetation mapping units at the biome, ecoregion and at the next lower hierarchical level for Namibia, excluding the Zambezi Region. Our method was based on a time series of 15 years of SPOT-VGT-MVC images each representing a specific 10-day period (dekad). The ISODATA unsupervised clustering technique was used to separately create 2–100 NDVI-cluster maps. The optimal number of temporal NDVI-clusters to represent the information on vegetation contained in the imagery was established by divergence separability statistics of all generated NDVI-clusters. The selected map consisted of legend of 81 cluster-specific temporal NDVI-profiles covering each a 15-year period of averaged NDVI data representing all pixels classified to that cluster. Then, by legend-entry using the dekad-medians of all 15 annual repeats, we produced generalized legend-entries without year-specific anomalies for each cluster. Subsequently, a hierarchical cluster analysis of these temporal NDVI-profiles was used to produce a dendrogram that generated grouping options for the 81 legend-entries. Maps with cluster-groups of 8 and 4 legend-entries resulted. The 81-cluster map and its 65 legend-entries vector version have no equivalent in published vegetation maps. The 8 cluster-group map broadly corresponds with published ecoregion level maps and the 4 cluster-group map with the published biome maps in their number of legend units. The published vegetation maps varied considerably from our NDVI-profile maps in the location of mapping unit boundaries. The agreement index between our map and published biome maps ranges from 70−93. For the ecoregion level, the agreement index is much lower, namely 51−75. Our methodological approach showed a considerably higher discretionary power for hierarchical levels and the number of vegetation mapping units than the approaches applied to previously published maps. We recommended an approach to transform our three hyper-temporal NDVI-profiles based legend-entries into more specific vegetation units. This might be accomplished by re-analysis of available, spatially-comprehensive plant species occurrence data.