地形图数字化数据的纠正与平差

本文从分析地形图上采集ＧＩＳ数据的误差来源入手，提出了消除ＧＩＳ输入数据的系统误差的纠正与平差方法，并且对深圳市蛇口工业区的１：１０００地形图数据进行了部分试验，探讨了地理单元划分，解析点的点位分布以及解析点数目对数据纠正精度的影响。     

地形图数字化数据的纠正与平差

本文从分析地形图上采集ＧＩＳ数据的误差来源入手，提出了消除ＧＩＳ输入数据的系统误差的纠正与平差方法，并且对深圳市蛇口工业区的１∶１０００地形图数据进行了部分试验，探讨了地理单元划分、解析点的点位分布以及解析点数目对数据纠正精度的影响。     

GIS空间数据误差分析

本文阐述ＧＩＳ空间数据的特性,指出系统误差一般也是不可避免的;给出了衡量精度的指标及不确定度;举ＧＩＳ实例说明空间分析中统计估计和假设检验方法。     

浅析GIS空间数据的误差来源及处理方法

ＧＩＳ空间数据质量的好坏是ＧＩＳ可靠性,实用性,效益性的关键,本文根据ＧＩＳ数据的流程系统地分析了ＧＩＳ空间数据的误差类型,来源,并且探讨了改善ＧＩＳ数据精度的方法。     

浅析GIS空间数据的误差来源及处理方法

ＧＩＳ空间数据质量的好坏是ＧＩＳ可靠性、实用性、效益性的关键,本文根据ＧＩＳ数据的流程系统地分析了ＧＩＳ空间数据的数据类型、来源,并且探讨了改善ＧＩＳ数据精度的方法。     

GIS数据采集中的坐标变换模型应用

数据采集是ＧＩＳ应用中的一项重要的基础上,本文分析屯仿真变换和相似变换模型在ＧＩＳ图像配准,数字化结果坐标校正和ＣＡＤ数据转入等数据采集过程中的应用;并特别提出了在不直接提供坐标变换功能的ＧＩＳ软件环境下,利用仿射变换模型对数字化结果实现坐标变换的方法。     

异构地理信息处理环境互操作的Internet GIS方法

提出了异构地理信息处理环境互操作的Ｉｎｔｅｒｎｅｔ ＧＩＳ方法和基于互操作性的Ｉｎｔｅｒｎｅｔ ＧＩＳ构造模型,即分布式超图模型,阐述了其具体实现过程,并以自主开发的Ｉｎｔｅｒｎｅｔ ＧＩＳＧｅｏＳｕｒｆ为例验证了此方法。     

面向对象的GIS结构设计

本文提出了一种以地理实体为中心加空间数据结构模型－面向对象的ＧＩＳ结构模型。在此基础上，讨论了利用规范关系存贮ＧＩＳ中的各种基本数据，以及用ＮＦ２（Ｎｏｎ－ＦｉｒｓｔＮｏｒｍａｌ－Ｆｏｒｍ）的嵌套结构描述和构造面向对象的几何数据，从而实现了面向对象的ＧＩＳ结构设计与管理，提高了ＧＩＳ系统的生命力，简化了系统的开发进程。     

GIS系统集成的模型基础

为满足各行各业的不同要求，ＧＩＳ与其它系统的集成已成为一个引人注目的问题，一般说，系统的集成就是要融合各组成部分的优点以满足用户的特殊要求。ＧＩＳ系统集成研究的一个重要方面就是模型基础，因为各系统所用的模型不同，如ＧＩＳ模型中缺少环境模型所必需的时——空结构，ＧＩＳ系统一般用“面向特征的模型”，遥感数据处理一般用“域模型”，而这些建模方法在整个系统的数据处理、数据表示和数据分析中是十分重要的，它对于认识那些由特殊模型引起的特殊问题也是十分有用的，因此本文以３级模式（外模式、概念模式和内模式）描述了ＧＩＳ和其它系统，这种方法使各种集成问题归于各组成部分的相应模式。     

矿区GIS信息（数据）编码的设计

从矿区ＧＩＳ信息的特点入手,提出了矿区ＧＩＳ信息（数据）分类和编码的原则和方法,并用信息论的方法确定了编码长度,最后给出了矿区ＧＩＳ信息（数据）编码的初步设计和部分编码。     

GIS中数字化数据误差的分布检验与处理

对GIS中手工地图数字化中的数据误差进行了系统分析和各种分布检验,认为数字化数据误差可能服从p≈1.6的p-范分布。在此基础上,探讨了数字化数据误差处理的p-范平差,并与最小二乘平差进行了比较。     

基于时空尺度的线位统一不确定性模型

在GIS矢量数据中,线对象在建模过程中存在的建模误差是必然的,并且成为不确定性内容中的重要组成部分,而现有的线位不确定性模型则往往将其忽略,本文充分考虑建模误差,采用误差传播律,对附有建模误差的二维折线不确定性模型进行估计,其中,e带模型、g带模型是其中的一个特例,即当且仅当建模误差为零时,便是e带模型、g带模型.     

双因子抗差贝叶斯估计及其在GIS数据采集质量控制中的应用

在对GIS扫描数字化过程中,所采集的数据里经常含有系统误差和异常误差。在纠正这些误差的过程中,应同时考虑控制点坐标和数字化坐标的先验协因数。文中以数字化的系统误差拟合模型为例,提出双因子抗差贝叶斯估计误差拟合方法,并分别就控制点含有粗差、数字化点含有粗差和两者均含有粗差3种情况建立相应的模型,实例验证了其抗差效果。     

A measure of average error variance of line features

This article presents a new development in measuring the positional error of line features in Geographic Information Systems (GIS), in the form of a new measure for estimating the average error variance of line features, including line segment, polyline, polygon, and curved lines. This average error measure is represented in the form of a covariance matrix derived by an analytical approach. Corresponding error indicators are derived from this matrix. The error of line features mainly results from two factors: (1) an error propagated from the original component points of line features and (2) a model error of interpolation between these points. In this study, a method of average error estimation has been derived regarding the first type error of line features that are interpolated by either linear or cubic interpolation methods. The main contribution of the research is the provision of an error measure to assess the quality of spatial data in application settings. The proposed error models for estimating average error variance of line features in a GIS are illustrated by both simulated and practical experiments. The results show that the line accuracy from a linear interpolation is better than a line interpolated using a cubic model.     

GIS中宗地面积的平差模型与方案探讨

首先给出了面积平差的基本原理和数学模型,并提出了面积平差处理的3种方案,并对这3种方案进行了实际计算和分析。     

A Review and Evaluation of Uncertainty Classification and the Error‐Band Geometry Model

Advances in computer technologies have improved the quality of maps, making map comparison and analysis easier, but uncertainty and error still exist in GIS when overlaying geographic data with multiple or unknown confidence levels. The goals of this research are to review current geospatial uncertainty literature, present the Error‐Band Geometry Model (EBGM) for classifying the size and shape of spatial confidence intervals for vector GIS data, and to analyze the interpretability of the model by looking at how people use metadata to classify the uncertainty of geographic objects. The results from this research are positive and provide important insight into how people interpret maps and geographic data. They suggest that uncertainty is more easily interpreted for well defined point data and GPS data. When data is poorly defined, people are unable to determine an approach to model uncertainty and generate error‐bands. There is potential for using the EBGM to aid in the development of a GIS tool that can help individuals parameterize and model spatial confidence intervals, but more research is needed to refine the process by which people use the decision tree. A series of guiding questions or an “uncertainty wizard” tool that helps one select an uncertainty modeling approach might improve the way people apply this model to real‐world applications.     

GIS叠置后同名点元不确定性的严密估计

基于最小二乘估计理论,建立了更加合理的GIS多层叠置同名点元的不确定性估计模型,改善了叠置点的精度.得出的单位权方差估计公式,理论上符合在一个平差系统中,其母体单位权方差应具有唯一性的要求.从理论和实例两方面验证了当同层内观测数据精度相同时,经多层叠置后各点精度均相同的结论.     

GIS叠置后同名点元不确定性的严密估计

基于最小二乘估计理论,建立了更加合理的GIS多层叠置同名点元的不确定性估计模型,改善了叠置点的精度。得出的单位权方差估计公式,理论上符合在一个平差系统中,其母体单位权方差应具有唯一性的要求。从理论和实例两方面验证了当同层内观测数据精度相同时,经多层叠置后各点精度均相同的结论。     

A Conceptual Framework for Uncertainty Investigation in Map‐based Land Cover Change Modelling

Uncertainty research represents a research stream of high interest within the community of geographical information science. Its elements, terminology and typology are still under strong discussion and adopted methods for analysis are currently under intensive development. This paper presents a conceptual framework for systematic investigation of uncertainty which occurs in applications of land cover change modelling in Geographical Information Systems (GIS) based on historical map data. Historical, in this context, means the map is old enough to allow identification of changes in landscape elements of interest, such as vegetation. To date such analyses are rarely conducted or not satisfactorily carried out, despite the fact that historical map data represent a potentially rich information source. The general validity and practicability of the framework for related applications is demonstrated with reference to one example in which forest cover change in Switzerland is investigated. The conceptual model consists of three domains in which main potential sources of uncertainty are systematically exposed. Existing links between data quality research and uncertainty are investigated to access the complex nature of uncertainty and to characterise the most suitable concepts for analysis. In accordance with these concepts appropriate methods and procedures are suggested to assess uncertainty in each domain. One domain is the production‐oriented amount of uncertainty which is inherent in the historical map. Vagueness and ambiguity represent suitable concepts for analysis. Transformation‐oriented uncertainty as the second domain occurs owing to editing and processing of digital data. Thereby, the suitable concept of uncertainty is error. The third domain is the application‐oriented uncertainty which occurs in comparing semantically different data. This domain relates to multi‐temporal discord which assumes the assessment of ‘equi‐temporal’ ambiguity and is thus connected to the production‐oriented domain. The framework provides an estimation of the overall amount of uncertainty. This can be linked to subsequent assessment of ‘fitness for use’. Thus the model provides a practicable and systematic approach to access the complex nature of uncertainty in the scope of land cover change modelling.     

GIS中地籍宗地面积的方差分量估计

探讨在地籍宗地数字化的面积处理问题中,把已知面积数据和数字化坐标同时作为观测值的面积处理方法.采用方差分量估计,解决已知面积数据参与平差时的权的确定.通过实例分析,认为采用条件平差方差分量估计方法来对宗地面积处理,能够更加合理地调整已有面积与由数字化坐标得到的面积值之间的差异.