Categories are in flux,but their computational representations are fixed: That's a problem

As research advances, our conceptual understanding also changes. Computational approaches do little to recognize the evolution that occurs at the conceptual level during the research process. This can result in misunderstanding between knowledge producers and consumers and so inhibit the reusability of outcomes. In this article, we describe how changes at the conceptual level can be represented, along with related changes to data and methods, and how appropriate connections between these various artefacts can be maintained. To demonstrate these ideas, we show how categories used in remote sensing and land cover analysis change over time and how these changes are linked to various research activities. We present a new system (called AdvoCate) that augments typical GIS and remote sensing functionality with a conceptual model of categories that can undergo change, and that also captures the cause of conceptual change and its extent. We argue that concepts and categories should be represented explicitly and richly within GIS, because without this, we have a poor idea of what our modeled entities really mean, and by implication how they should be used appropriately. We demonstrate the usefulness of this deeper representation using examples of category evolution from a land cover mapping exercise.     

空间数据处理模型误差和不确定性分析

在GIS应用中,涉及到大量的模型应用,这些模型包括了利用GIS进行空间信息处理的大部分阶段中所用到的模型.模型处理以及分析结果往往是进行下一步应用的基础,因此模型处理结果的误差和不确定性制约了实际的GIS应用.影响空间数据处理模型的误差和不确定性的因素主要包括:定位和特征信息,制图,空间分析,空间数据库以及空间数据处理模型等所具有的误差和不确定性.主要分析了空间数据处理模型误差和不确定性的表达、来源以及分析方法.     

基于改进邻域均值的全色影像水域提取

利用传统邻域均值法对全色影像水域进行提取时,所提取的水域边界精确度严重依赖于搜索窗口的大小。本文通过分析水域灰度特征以及提取边界不精确的原因,对方法进行针对性的改进:依据邻域各像素点与种子点的灰度差值分别对其赋予不同的灰度值,以处理后的邻域均值作为特征进行水域提取。实验结果表明:基于改进的邻域均值方法对遥感影像水域有较好的提取结果,提取精度较之改进前有明显改善。     

用邻近索引来加快邻近关系处理的算法研究

针对数据量大、关系复杂情况下的空间邻近关系处理需要大量磁盘I/O的问题,本文提出了一种通过建立空间邻近索引来加快空间邻近关系处理速度的方法,给出了该索引建立、维护的方法以及用该索引实现邻近关系处理的过程。最后从理论上分析了使用和不使用邻近索引时邻近关系处理速度的差异,并用南京公交站点数据来验证,得出了一致的结论。在空间数据引擎的基础上使用邻近索引进行空间邻近关系处理的速度将大大提高。     

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.     

The Nature of Uncertainty in Historical Geographic Information

While the presence of uncertainty in the geometric and attribute aspects of geographic information is well known, it is also present in temporal information. In spatiotemporal GIS databases and other formal representations, uncertainty in all three aspects of geography (space, time, and theme) must often be modeled, but a good data model must first be based on a sound theoretical understanding of spatiotemporal uncertainty. The nature of both uncertainty inherent in a phenomenon (often termed indeterminacy) and uncertainty in assertions of that phenomenon can be better understood through the Uncertain Temporal Entity Model , which characterizes the cause, type, and form of uncertainties in the spatial, temporal, and attribute aspects of geographic information. These uncertainties are the result of complexities and problems in two processes: the process of conceptualization, by which humans make sense of an infinitely complex reality, and measurement, by which we create formal representations (e.g. GIS) of those conceptual models of reality. Based on this framework, the nature and form of uncertainty is remarkably consistent across various situations, and is approximately equivalent in the three aspects, which will enable consistent solutions for representation and processing of spatiotemporal data.     

Towards 3D lidar point cloud registration improvement using optimal neighborhood knowledge

Automatic 3D point cloud registration is a main issue in computer vision and remote sensing. One of the most commonly adopted solution is the well-known Iterative Closest Point (ICP) algorithm. This standard approach performs a fine registration of two overlapping point clouds by iteratively estimating the transformation parameters, assuming good a priori alignment is provided. A large body of literature has proposed many variations in order to improve each step of the process (namely selecting, matching, rejecting, weighting and minimizing). The aim of this paper is to demonstrate how the knowledge of the shape that best fits the local geometry of each 3D point neighborhood can improve the speed and the accuracy of each of these steps. First we present the geometrical features that form the basis of this work. These low-level attributes indeed describe the neighborhood shape around each 3D point. They allow to retrieve the optimal size to analyze the neighborhoods at various scales as well as the privileged local dimension (linear, planar, or volumetric). Several variations of each step of the ICP process are then proposed and analyzed by introducing these features. Such variants are compared on real datasets with the original algorithm in order to retrieve the most efficient algorithm for the whole process. Therefore, the method is successfully applied to various 3D lidar point clouds from airborne, terrestrial, and mobile mapping systems. Improvement for two ICP steps has been noted, and we conclude that our features may not be relevant for very dissimilar object samplings.     

Estimating the Effects of Map Error on Habitat Delineation for the California Spotted Owl in Southern California

The reliability of habitat maps that have been generated using Geographic Information Systems (GIS) and image processing of remotely sensed data can be overestimated. Habitat suitability and spatially explicit population viability models are often based on these products without explicit knowledge of the effects of these mapping errors on model results. While research has considered errors in population modeling assumptions, there is no standardized method for measuring the effects of inaccuracies resulting from errors in landscape classification. Using landscape‐scale maps of existing vegetation developed for the USDA Forest Service in southern California from Landsat Thematic Mapper satellite data and GIS modeling, we performed a sensitivity analysis to estimate how mapping errors in vegetation type, forest canopy cover, and tree crown size might affect delineation of suitable habitat for the California spotted owl (Strix occidentalis occidentalis). The resulting simulated uncertainty maps showed an increase in the estimated area of suitable habitat types. Further analysis measuring the fragmentation of the additional patches showed that they were too small to be useful as habitat areas.     

1∶100万数字地貌制图方法的实验——以昆明图幅(G-48)为例

数字地貌制图是地貌制图及其应用研究适应信息化发展的必然趋势。本文以昆明幅(G-48)地貌图为例,探讨在遥感与地理信息系统技术的支持下,中国1∶100万数字地貌制图的技术路线和方法,并结合昆明幅的具体地貌特征,重点分析数字地貌制图过程中的几个关键问题。分析结果表明:基于遥感与地理信息系统的数字地貌制图技术,不仅能提高地貌制图的效率,还能提高解译的质量和精度。     

Uncertainty Modeling in Buffer Operations Applied to Connectivity Analysis

In this paper we will study the potential connectivity of red squirrels in a fragmented landscape, using a buffer operation that takes into account the difficulty of moving through the landscape. The outcome of such an analysis is greatly influenced by the various sources of uncertainty that are introduced in the model. Two main sources of uncertainty can be identified: source layer uncertainty and model uncertainty. In this paper the propagation of source layer uncertainty resulting from a multivariate statistical classification of remotely sensed data is studied using Monte Carlo simulation, taking the spatial structure of uncertainty into account. Model uncertainty results from the adoption of deterministic model parameters regarding the dispersal capacity and the landscape effect, and is examined using fuzzy set theory. Comparing the outcome of error sensitized models to the observed dispersal activity of squirrels, demonstrates how modeling of uncertainty can help to explain the dispersal activity of red squirrels.     

空间数据处理模型误差和不确定性分析

在GIS应用中,涉及到大量的模型应用,这些模型包括了利用GIS进行空间信息处理的大部分阶段中所用到的模型。模型处理以及分析结果往往是进行下一步应用的基础,因此模型处理结果的误差和不确定性制约了实际的GIS应用。影响空间数据处理模型的误差和不确定性的因素主要包括:定位和特征信息,制图,空间分析,空间数据库以及空间数据处理模型等所具有的误差和不确定性。主要分析了空间数据处理模型误差和不确定性的表达、来源以及分析方法。     

自然邻域支持下的空间同位模式挖掘方法

空间同位模式指频繁发生在邻近空间位置的事件集合,此类模式对于深入理解不同空间要素间的交互关系具有重要意义。空间同位模式挖掘的一个核心内容是空间要素邻近关系构建,然而现有方法在空间要素分布不均匀时难以准确地描述要素间的邻近关系,容易导致挖掘结果的遗漏或误判。为此,本文提出了一种基于自然邻域的空间同位模式挖掘方法。首先从同位模式的产生机理分析入手,过滤同位模式挖掘中的干扰要素;进而,从距离邻近性、密度变化一致性和关系紧密性的原则出发,自适应地构建空间要素实例的自然邻近关系;最后,以自然邻域为基础,基于图的连通性从整体到局部发现多层次同位模式。试验分析与比较发现,本文方法能够有效发现空间要素分布不均匀情况下的同位模式,而且降低了人为设置邻域参数对挖掘结果的影响。     

现代地图学的最新进展与新世纪的展望

本文第一部分国际地图学的最新进展,阐述了专题制图进一步拓宽领域并向纵深发展;计算机制图已广泛应用于各类地图生产,多媒体电子地图集与互联网地图集迅速推广;地图学-遥感-地理信息系统相结合已形成一体化的研究技术体系;计算机制图-电子出版生产一体化,从根本上改变了地图设计与生产的传统工艺;地图学新概念与新理论的不断探索。第二部分分析了中国地图学与地图事业近30年的发展与成就,论述了测绘部门完成了全国大比例尺地形图的测制,完成1:100万与1:25万数字地形图制作.在完成一大批专题地图的同时,广泛开展区域与部门的综合制图,编制出版了一大批不同类型的高水平综合地图集;遥感制图、计算机制图与地理信息系统已达到世界先进水平。第三部分是对中国地图学新世纪的展望:①抓住数字地球的机遇,创建地学信息图谱;②专题与综合制图进一步向纵深发展;③地图学、遥感制图与地理信息系统一体化,形成完整的研究技术体系与生产体系,发展地球信息科学;④为适应市场经济与社会发展的需要,应进一步扩大地图应用领域与范围,增加地图新品种;⑤加强地图学、遥感制图与地理信息系统基础理论及其应用原理与方法的研究。     

Local Weighted Linear Combination

The article focuses on one of the most often used GIS‐based multicriteria analysis methods: the weighted linear combination (WLC). The WLC model has traditionally been used as a global approach based on the implicit assumption that its parameters do not vary as a function of geographical space. This assumption is often unrealistic in real‐world situations. The article proposes a new approach to GIS‐based multicriteria analysis. It develops a local form of the global WLC model. The range sensitivity principle is used as a central concept for developing the local WLC model. The principle postulates that the greater the range of criterion values is, the greater the weight assigned to that criterion should be. Consequently, the local criterion weight can be defined for each neighborhood within a study area as a function of the range of criterion values in a given neighborhood. The range of criterion values provides also the base for defining the local value function. The article presents the theory behind the local WLC modeling and illustrates an implementation of the model in a GIS environment.     

Combined object-based classification and manual interpretation–synergies for a quantitative assessment of parcels and biotopes

Recent technical advances in remote sensing data capture and spatial resolution lead to a widening gap between increasing data availability on the one hand and insufficient methodology for semi-automated image data processing and interpretation on the other hand. At the interface of GIS and remote sensing, object-based image analysis methodologies are one possible approach to close this gap. With this, methods from either side are integrated to use both the capabilities of information extraction from image data and the power to perform spatial analysis on derived polygon data. However, dealing with image objects from various sources and in different scales implies combining data with inconsistent boundaries. A landscape interpretation support tool (LIST) is introduced which seeks to investigate and quantify spatial relationships among image objects stemming from different sources by using the concept of spatial coincidence. Moreover, considering different categories of object fate, LIST enables a change categorization for each polygon of a time series of classifications. The application of LIST is illustrated by two case-studies, using Landsat TM and ETM as well as CIR aerial photographs: the first showing how the tool is used to perform object quantification and change analysis; the latter demonstrating how superior aggregation capabilities of the human brain can be combined with the fine spatial segmentation and classification. Possible fields of application are identified and limitations of the approach are discussed.     

基于SuperMap的公路工程地理信息平台研究

在研究公路交通地理信息系统（GIS—T）建设现状的基础上,提出了基于GIS组件SuperMap Objects的公路工程地理信息平台。从公路工程规划、设计、建设和管理过程中所涉及的各种数据和资料及现实需求出发,探讨了平台系统总体结构、数据库设计和系统功能设计,研究了系统开发中数据的组织与动态分段等关键技术。以广东省公路工程地理信息平台为实例,介绍了系统的功能和应用,实践了文中提出的技术和方法。     

论GIS的模糊不确定性及其表示

由于GIS在社会中的作用越来越大,研究其精度就格外重要,文章就GIS的模糊不确定性进行了研究:首先就人类对不确定性的认识进行了论述,接着简单介绍不确定性的相关概念,然后详细地阐述了GIS存在着模糊不确定性以及模糊不确定性的多种来源,接着,就空间实体中的模糊点、模糊线和模糊面用模糊理论进行表示,最后总结并提出了今后的研究方向。     

GIS图上地理区域空间不确定性的分析

区域是GIS空间分析的基本单元。它是环境科学、土壤科学等领域中广泛存在的一类地理实体。这类实体抽象概括为GIS中空间目标时不可避免地带有模糊性。利用模糊集这个强有力的数学工具，首先基于场模型提出了表达GIS中模糊区域目标的方法，分析了其空间不确定性。继而，建立了模糊区域的形态描述模式，即模糊区域边界、内部和外部，并指出了Cohn给出的定义中的不足。在此基础上，对Egenhofer提出的九元组进行了扩展，构建了适合于描述确定和模糊区域目标间拓扑空间关系的模型。