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A New Combined Assessment of Mixed Uncertainty in Spatial Models: Conceptualization and Implementation 
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下载免费PDF全文 Uncertainty quantification is not often performed in spatial modeling applications, especially when there is a mixture of probabilistic and non‐probabilistic uncertainties. Furthermore, the effect of positional uncertainty is often not assessed, despite its relevance to geographical applications. Although there has been much work in investigating the aforementioned types of uncertainty in isolation, combined approaches have not been much researched. This has resulted in a lack of tools for conducting mixed uncertainty analyses that include positional uncertainty. This research addresses the issue by first presenting a new, flexible, simulation‐oriented conceptualization of positional uncertainty in geographic objects called F‐Objects. F‐Objects accommodates various representations of uncertainty, while remaining conceptually simple. Second, a new Python‐based framework is introduced, termed Wiggly and capable of conducting mixed uncertainty propagation using fuzzy Monte Carlo simulation (FMCS). FMCS combines both traditional Monte Carlo with fuzzy analysis in a so‐called hybrid approach. F‐Objects is implemented within the Wiggly framework, resulting in a tool capable of considering any combination of: (1) probabilistic variables; (2) fuzzy variables; and (3) positional uncertainty of objects (probabilistic/fuzzy). Finally, a realistic GIS‐based groundwater contamination problem demonstrates how F‐Objects and Wiggly can be used to assess the effect of positional uncertainty. 相似文献
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Anderson Chaves Carniel Pedro Vinícius Almeida Borges de Venâncio Markus Schneider 《Transactions in GIS》2023,27(3):900-927
Spatial libraries are core components in many geographic information systems, spatial database systems, and spatial data science projects. These libraries provide the implementation of spatial type systems that include spatial data types and a large diversity of geometric operations. Their focus relies on handling crisp spatial objects, which are characterized by an exact location and a precisely defined extent, shape, and boundary in space. However, there is an increasing interest in analyzing spatial phenomena characterized by fuzzy spatial objects, which have inexact locations, vague boundaries, and/or blurred interiors. Unfortunately, available spatial libraries do not provide support for fuzzy spatial objects. In this article, we describe the R package named fsr, which is based on the Spatial Plateau Algebra and is publicly available at https://cran.r-project.org/package=fsr . Our tool provides methods for building fuzzy spatial objects as spatial plateau objects and conducting exploratory spatial data analysis by using fuzzy spatial operations. 相似文献
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八方向模糊不均匀划分及参考点位误差所致不确定性分析 总被引：1，自引：0，他引：1
方向概念的模糊性和空间数据固有的不确定性导致了方向关系的复杂性,在空间关系描述和推理研究中需要考虑空间数据的不确定性和方向概念的模糊性。在四方向模型中各方向片是等角划分;在八方向模型中4个主要方向片各占60°,4个次要方向片各占30°。利用区间二型模糊集理论建立了顾及参考点点位误差的八方向模糊不均匀划分模型,基于区间二型模糊集讨论了方向主隶属度成员函数和隶属度的不确定性。对比分析了八方向模糊不均匀划分模型与锥形模型的区别,讨论了具有点位误差的参考点与线和多边形的方向关系计算过程,通过两个实例分析了该模型的特点和点与多边形方向关系的确定方法。 相似文献
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位置不确定性与属性不确定性的场模型 总被引：23，自引：2，他引：21
不确定性是自地理信息系统发展与应用以来一个引起关注的课题。位置不确定性与属性不确定常常不加区分地被看作是可以单个讨论的问题。本文将借助场的概念和模型使二者得以统一的描述和分析;对于明确定义的离散目标,二者虽然可分别讨论,但却在数学上有着联合的基础;对于非明确定义的地理现象,二者以连续体的形式而存在,位置不确定性可以作为属性不确定性的空间映射而提取出来。 相似文献
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Fuzziness is an internal property of spatial objects.How to model fuzziness of a spatial object is a main task of next generation GIS.This paper proposes basic fuzzy spatial object types based on fuzzy topology.These object types are the natural extension of current nonfuzzy spatial object types.A fuzzy cell complex structure is defined for modeling fuzzy regions,lines and points.Furthermore,fuzzy topological relations between these fuzzy spatial objects are formalized based on the 9intersection approach.This model can be implemented for GIS applications due to its scientific theory basis. 相似文献
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随着对GIS中的空间对象模型和自然地理特征表达的研究深入,模糊空间对象被提出。针对模糊空间对象表达的特点,提出了一种基于模糊神经网络的模糊空间对象生成方法。该方法将模糊技术与神经网络相结合,利用神经网络的学习能力调整模糊隶属函数和模糊规则,使系统具备自适应的特性。实验表明,这种基于模糊神经网络的生成模糊空间对象的方法比传统方法大大的提高了成果的精度。 相似文献
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随着对GIS中的空间对象模型和自然地理特征表达的研究深入,模糊空间对象被提出。针对模糊空间对象表达的特点,提出了一种基于模糊神经网络的模糊空间对象生成方法。该方法将模糊技术与神经网络相结合,利用神经网络的学习能力调整模糊隶属函数和模糊规则,使系统具备自适应的特性。实验表明,这种基于模糊神经网络的生成模糊空间对象的方法比传统方法大大的提高了成果的精度。 相似文献
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A framework of region-based spatial relations for non-overlapping features and its application in object based image analysis 总被引：2，自引：0，他引：2
Yu Liu Qinghua Guo Maggi Kelly 《ISPRS Journal of Photogrammetry and Remote Sensing》2008,63(4):461-475
Object based image analysis (OBIA) is an approach increasingly used in classifying high spatial resolution remote sensing images. Object based image classifiers first segment an image into objects (or image segments), and then classify these objects based on their attributes and spatial relations. Numerous algorithms exist for the first step of the OBIA process, i.e. image segmentation. However, less research has been conducted on the object classification part of OBIA, in particular the spatial relations between objects that are commonly used to construct rules for classifying image objects and refining classification results. In this paper, we establish a context where objects are areal (not points or lines) and non-overlapping (we call this “single-valued” space), and propose a framework of binary spatial relations between segmented objects to aid in object classification. In this framework, scale-dependent “line-like objects” and “point-like objects” are identified from areal objects based on their shapes. Generally, disjoint and meet are the only two possible topological relations between two non-overlapping areal objects. However, a number of quasi- topological relations can be defined when the shapes of the objects involved are considered. Some of these relations are fuzzy and thus quantitatively defined. In addition, we define the concepts of line-like objects (e.g. roads) and point-like objects (e.g. wells), and develop the relations between two line-like objects or two point-like objects. For completeness, cardinal direction relations and distance relations are also introduced in the proposed context. Finally, we implement the framework to extract roads and moving vehicles from an aerial photo. The promising results suggest that our methods can be a valuable tool in defining rules for object based image analysis. 相似文献
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Alireza Chehreghan 《国际地球制图》2017,32(5):471-487
Similarity between the objects has close association with the geometrical structure and details of the objects. Therefore, in this study, a framework was presented based on the geometric criteria, the fuzzy Membership Functions (MF) and human spatial cognition. To increase the efficiency of MF and for the problem to get closer to reality, 1 K, 2 K, 5 K, 10 K, 25 K, 50 K, and 100 K data were used in this framework. The results showed that the degree of spatial similarity is specific to the objects themselves and their geometric structure. No linear or non-linear relationship could be found between scale changes and degree of spatial similarity of the objects, because the geometry of any object independently affects its degree of similarity to other objects in different scales and sources. 相似文献
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面向图层处理单元的GIS数据模型、数据处理模式已不再适应大规模海量空间数据组织、处理以及网络分发的需要。文章提出以空间要素基元处理取代传统的面向图层处理的模式,并在对象-关系数据库(ORDBMS)统一框架下构筑、组织、存储、处理空间数据,最终形成基于ORDBMS的GIS应用。 相似文献
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Sanaz Salati Frank J.A. van Ruitenbeek Freek D. van der Meer Majid Hashemi Tangestani Harald van der Werff 《International Journal of Applied Earth Observation and Geoinformation》2011
Lithological boundaries provide information useful for activities such as mineral and hydrocarbon exploration, water resource surveys, and natural hazard evaluation. Automated detection of lithological boundaries reduces bias inherent in expert interpretation of boundaries and thus improves the reliability of lithological mapping. The Rotation Variant Template Matching (RTM) algorithm was applied to ASTER imagery to detect pre-defined lithological boundaries. Templates incorporating the mineral combinations gypsum–calcite and calcite–illite were designed to detect boundaries between evaporites, marly limestone, and sandstone. The RTM algorithm successfully detected lithological boundaries by rotating the templates over the ASTER imagery. The accuracy of the detected boundaries was spatially assessed using fuzzy set theory. Boundaries from a published geological map and boundaries interpreted from a stereo pair of aerial photos by five experts were used as references for assessing the accuracy. A confidence region unifying spatial errors was defined for the geological map and stereo-pair interpretation to provide boundary zones from these references. The correspondence between detected boundaries and the boundary zones of the aerial photo was better than between detected boundaries and boundary zones of the geological map. 相似文献
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对GIS中空间数据不确定性研究中存在的问题进行思考后提出了5点建议。主要包括:1)要区分GIS中确定性目标和不确定性目标;2)要区分用离散点逼近曲线/曲面的逼近误差和离散点自身量测误差及其传播;3)要研究GIS中的几何不确定性,更要重视研究属性和时态不确定性;4)要研究空间数据质量,更要研究空间信息服务的质量;5)空间数据不确定性研究要努力向实际应用转化。 相似文献
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From fields to objects: A review of geographic boundary analysis 总被引：12，自引：0，他引：12
Geographic boundary analysis is a relatively new approach unfamiliar to many spatial analysts. It is best viewed as a technique
for defining objects – geographic boundaries – on spatial fields, and for evaluating the statistical significance of characteristics
of those boundary objects. This is accomplished using null spatial models representative of the spatial processes expected
in the absence of boundary-generating phenomena. Close ties to the object-field dialectic eminently suit boundary analysis
to GIS data. The majority of existing spatial methods are field-based in that they describe, estimate, or predict how attributes
(variables defining the field) vary through geographic space. Such methods are appropriate for field representations but not
object representations. As the object-field paradigm gains currency in geographic information science, appropriate techniques
for the statistical analysis of objects are required. The methods reviewed in this paper are a promising foundation. Geographic
boundary analysis is clearly a valuable addition to the spatial statistical toolbox.? This paper presents the philosophy of,
and motivations for geographic boundary analysis. It defines commonly used statistics for quantifying boundaries and their
characteristics, as well as simulation procedures for evaluating their significance. We review applications of these techniques,
with the objective of making this promising approach accessible to the GIS-spatial analysis community. We also describe the
implementation of these methods within geographic boundary analysis software: GEM.
Received: 22 March 1999 / Accepted: 7 September 1999 相似文献
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Kimfung Liu Wenzhong Shi 《International Journal of Applied Earth Observation and Geoinformation》2009
This paper presents a study on the modeling of fuzzy topological relations between uncertain objects in Geographic Information Systems (GIS). Based on the recently developed concept of computational fuzzy topological space, topological relations between simple fuzzy spatial objects are modeled. The fuzzy spatial objects here cover simple fuzzy region, simple fuzzy line segment and fuzzy point. To compute the topological relations between the simple spatial objects, intersection concepts and integration methods are applied and a computational 9-intersection model are proposed and developed. There are different types of intersection, and we have proposed different integration methods for computation in different cases. For example, surface integration method is applied to the case of the fuzzy region-to-fuzzy region relation, while the line integration method is used in the case of fuzzy line segment-to-fuzzy line segment relation. Moreover, this study has discovered that there are (a) sixteen topological relations between simple fuzzy region to line segment; (b) forty-six topological relations between simple fuzzy line segments; (c) three topological relations between simple fuzzy region to fuzzy point; and (d) three topological relations between simple fuzzy line segment to fuzzy point. 相似文献
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ZHANG Jingxiong Roger P.Kirby 《地球空间信息科学学报》2000,3(2):26-34
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This article combines stereology with image mining. Image mining identifies and models objects from a series of remote sensing images and communicates this information to stakeholders. Stereology is the science of deriving properties of objects from lower dimensional features. This article first applies stereology to quantify properties of crisp objects on single images. Next it addresses the development of an object in space and time. Finally, it quantifies uncertainty of fuzzy objects. The article is illustrated with a case study from Cambodia, where flooding regularly occurs along the Mekong River. Nine Landsat images have been mined to assess the size of the flooding in space and time. Areal estimates obtained with stereology from single images show a high precision. Estimates of a space–time volume of the size of flooding in space and time include uncertainty estimates that could be ascribed to atmospheric distortion and limited resolution. Finally stereology is applied to estimate the effects on area estimates of fuzzified boundaries. All information can be transferred to stakeholders, e.g. to quantify the size of a disaster. The article concludes that stereology successfully and concisely quantifies phenomena and their uncertainties in a remote sensing image mining context. 相似文献