Multistop-based measurements of accessibility in a GTS environment

Abstract

The opportunities available at a demand location are usually measured as the costs of reaching a specified critical number of facilities from that location. This method does not however, account for multistop trips nor for differences in the diversity of supply at the level of individual facilities. In this paper we introduce an alternative measurement method that overcomes these shortcomings. In this method the probability of successfully visiting a specific facility is assumed to be a function of the diversity of supply provided. Trip routes are constructed that have an acceptable probability of success. Then, the expected costs of travelling the optimum route are determined as an indicator of spatial opportunities. The proposed method has been implemented in a GIS environment, using typical GIS data and GIS tools for spatial analysis and display. The results of a case study indicate that the new method, compared to current methods, may lead to different evaluations of the level of opportunities at demand locations.     

Geologically Constrained Probabilistic Mapping of Gold Potential, Baguio District, Philippines

Binary predictor patterns of geological features are integrated based on a probabilistic approach known as weights of evidence modeling to predict gold potential. In weights of evidence modeling, the log _e of the posterior odds of a mineral occurrence in a unit cell is obtained by adding a weight, W ⁺ or W ^– for presence of absence of a binary predictor pattern, to the log _e of the prior probability. The weights are calculated as log _e ratios of conditional probabilities. The contrast, C = W ⁺ – W ^–, provides a measure of the spatial association between the occurrences and the binary predictor patterns. Addition of weights of the input binary predictor patterns results in an integrated map of posterior probabilities representing gold potential. Combining the input binary predictor patterns assumes that they are conditionally independent from one another with respect to occurrences.     

基于神经网络的元胞自动机及模拟复杂土地利用系统

本文提出了基于神经网络的元胞自动机(CellularAutomata),并将其用来模拟复杂的土地利用系统及其演变。国际上已经有许多利用元胞自动机进行城市模拟的研究,但这些模型往往局限于模拟从非城市用地到城市用地的转变。模拟多种土地利用的动态系统比一般模拟城市演化要复杂得多,需要使用许多空间变量和参数,而确定模型的参数值和模型结构有很大困难。本文通过神经网络、元胞自动机和GIS相结合来进行土地利用的动态模拟,并利用多时相的遥感分类图像来训练神经网络,能十分方便地确定模型参数和模型结构,消除常规模拟方法所带来的弊端。     

Incorporating spatial association into statistical classifiers: local pattern-based prior tuning

ABSTRACT

This paper proposes a new classification method for spatial data by adjusting prior class probabilities according to local spatial patterns. First, the proposed method uses a classical statistical classifier to model training data. Second, the prior class probabilities are estimated according to the local spatial pattern and the classifier for each unseen object is adapted using the estimated prior probability. Finally, each unseen object is classified using its adapted classifier. Because the new method can be coupled with both generative and discriminant statistical classifiers, it performs generally more accurately than other methods for a variety of different spatial datasets. Experimental results show that this method has a lower prediction error than statistical classifiers that take no spatial information into account. Moreover, in the experiments, the new method also outperforms spatial auto-logistic regression and Markov random field-based methods when an appropriate estimate of local prior class distribution is used.     

改进的案例推理CA模型及土地覆盖变化模拟

对基于案例推理的元胞自动机模型(CBR-CA)进行改进,将各类别的宏观转移概率添加到目标函数中,体现各类别的转变特征,并增加时间权重来确定转移概率,实现时间尺度上的模拟;由于土地覆盖变化的多样性和空间结构的复杂性,利用Monte Carlo(M-C)法确定土地覆盖的最终转换类别。选择黄河源区为试验区,利用1977年、1985年土地覆盖数据建立原始案例库,模拟了该区域1995年、2000年和2006年的土地覆盖变化,模拟的各类别转换的数量精度与实际相吻合,各年份的总体误差分别为0.002%、0.012%和0.005%,空间位置精度总体在70%以上,并进行未来土地覆盖情景预测。该模型可用于多类别、长时间序列区域土地覆盖变化的模拟与预测。     

基于多智能体的城市人口分布模型

人口是城市发展中最为活跃的因素,快速增长的人口给城市安全、经济和生态环境带来了深远的影响,获取不同尺度的高精度人口空间分布信息对于城市安全管理、提高资源环境的综合管理能力具有非常重要的意义。针对常用的城市人口空间分布模拟方法存在的不足,构建了基于多智能体的城市人口分布模型,模型由影响要素、智能体、决策规则等组成。在两个不同尺度区域进行了模型应用实验,并以重力模型进行了对比分析。实验结果表明,与重力模型相比,此模型所模拟的结果具有更高的精度,且接近于实际的人口空间分布,为城市人口分布模拟提供了新的思路。     

Quantitative Prediction and Evaluation of Mineral Resources Based on GIS: A Case Study in Sanjiang Region,Southwestern China

Quantitative prediction and evaluation of mineral resources are one of the important topics of mathematical geology. On the basis of GIS technologies and weights of evidence modeling, MapGIS is integrated with GIS and mineral-resource prediction and evaluation. The final product is a predictor map of posterior probabilities of occurrence of the discrete event within a small unit cell. Predictor layers were created on a digital database that includes 1:200,000 scale geological, and geochemical, and geophysical maps, and remote-sensing images in study area. According to metallogenetic factors extractiont and weights of evidence modeling, there are four main metal ore belts in the study area: (1) the Batang belt; (2) the Lei Wuqi belt; (3) the Basu-Chayu belt; and (4) the Ganzi-Litang belt. The predictor map of posterior probabilities show that 29% of study area as zones with potential for porphyry copper, and 81% known mineral occurrences success rate is circled in the metallogenetic posterior probabilities map. The results demonstrate plausibility of weights-of-evidence modeling of mineral potential in large areas with small number of mineral prospects.     

Fuzzy Weights of Evidence Method and Its Application in Mineral Potential Mapping

This paper proposes a new approach of weights of evidence method based on fuzzy sets and fuzzy probabilities for mineral potential mapping. It can be considered as a generalization of the ordinary weights of evidence method, which is based on binary or ternary patterns of evidence and has been used in conjunction with geographic information systems for mineral potential mapping during the past few years. In the newly proposed method, instead of separating evidence into binary or ternary form, fuzzy sets containing more subjective genetic elements are created; fuzzy probabilities are defined to construct a model for calculating the posterior probability of a unit area containing mineral deposits on the basis of the fuzzy evidence for the unit area. The method can be treated as a hybrid method, which allows objective or subjective definition of a fuzzy membership function of evidence augmented by objective definition of fuzzy or conditional probabilities. Posterior probabilities calculated by this method would depend on existing data in a totally data-driven approach method, but depend partly on expert's knowledge when the hybrid method is used. A case study for demonstration purposes consists of application of the method to gold deposits in Meguma Terrane, Nova Scotia, Canada.     

基于粗集的知识发现与地理模拟——以深圳市土地利用变化为例

为了更有效地模拟地理现象的复杂演变过程,提出了用粗集理论来确定元胞自动机 (CA)不确定性转换规则的新方法。CA可以通过局部规则来有效地模拟许多地理现象的演变过程。但目前缺乏很好定义CA转换规则的方法。往往采用启发式的方法来定义CA的转换规则,这些转换规则是静态的,而且其参数值多是确定的。在反映诸如城市扩张、疾病扩散等不确定性复杂现象时,具有一定的局限性。利用粗集从GIS和遥感数据中发现知识,自动寻找CA的不确定性转换规则,基于粗集的CA在缩短建模时间的同时,能提取非确定性的转换规则,更好地反映复杂系统的特点。采用所提出的方法模拟了深圳市的城市发展过程,取得了比传统MCE方法更好的模拟效果。     

Geometric probability and GIS: some applications for the statistics of intersections

This paper identifies analytical and empirical methods for determining the probability that lines and areas intersect tiles in a regular tessellation. Such intersections are common in geographical information systems (GIS) applications. Knowledge of intersection probabilities is valuable in many instances, including estimating complexity and time required to process a distance or viewshed operation, developing optimal tiling schemes for national georeferencing systems, precalculating the number of map sheets a spatial feature may occupy, and identifying appropriate cell resolutions for vector-to-raster conversions. Buffon's Needle-type solutions from the field of geometric probability provide the framework for deriving probabilities for lines. Probabilities for simple areas like rectangles and circles are derived using geometric techniques and illustrated using hypothetical examples. Employing such probabilities in spatial analysis may yield more rigorous and theoretically informed results from GIS analysis, leading to better decisions and greater insight into spatial phenomena.     

CAD数据空间参考的判断与参数获取

地形图CAD数据是GIS应用与开发的重要数据源,而相应空间参考缺失的情况却并不鲜见。该文分析了CAD数据的特点,并指出在实际应用中对空间参考缺失的处理存在一些不科学的方法;针对我国及地方数字地形图坐标系建立的一般规律,提出了CAD数据空间参考判断及其参数获取的方法:以大地基准及地图投影已知(高斯-克吕格投影)为前提,通过对比实际地图坐标和标准地图坐标在数值上的差异,确定北伪偏移量和东伪偏移量这两个地图空间参考的重要参数;针对不同的CAD地形图数据,用不同的实例说明了该方法的具体实施过程。     

A probabilistic relaxation approach for matching road networks

Geospatial data matching is an important prerequisite for data integration, change detection and data updating. At present, crowdsourcing geospatial data are attracting considerable attention with its significant potential for timely and cost-effective updating of geospatial data and Geographical Information Science (GIS) applications. To integrate the available and up-to-date information of multi-source geospatial data, this article proposes a heuristic probabilistic relaxation road network matching method. The proposed method starts with an initial probabilistic matrix according to the dissimilarities in the shapes and then integrates the relative compatibility coefficient of neighbouring candidate pairs to iteratively update the initial probabilistic matrix until the probabilistic matrix is globally consistent. Finally, the initial 1:1 matching pairs are selected on the basis of probabilities that are calculated and refined on the basis of the structural similarity of the selected matching pairs. A process of matching is then implemented to find M:N matching pairs. Matching between OpenStreetMap network data and professional road network data shows that our method is independent of matching direction, successfully matches 1:0 (Null), 1:1 and M:N pairs, and achieves a robust matching precision of above 95%.     

Visualizing the spatial dynamics of student success

This study attempt to visualize the spatial patterns of selected academic attributes across college classroom space based on data from a map-embedded smart attendances and GIS visualizations. The academic attributes of 542 participants from Los Angeles Mission College (LAMC) in California were analyzed in a GIS platform. The spatial dynamics of student success revealed the distance decay effect on test scores, class participation, and class attendance. The visualization of class performance highlighted the spatial interdependence between seat location and academic attributes, which was validated by 145 sample students' perceived mental maps generated from the accompanying questionnaire survey. The replication of the visualization technique across different class sizes and courses could help educators identify seats for early intervention and micromanagement of classrooms.     

近25年来塔里木河流域区域经济空间关联及演化特征分析

以塔里木河流域为研究对象,借助Arcgis8.5及Geoda等软件平台,引入空间自相关模型,对塔里木河流域42县(市)1980-2005年近25年的区域经济空间关联类型、动态演化特征及动力机制进行研究,结果表明:(1)25年来塔里木河流域经济全局空间自相关系数增长了近1.7倍,总体呈现出空间正相关特征,且为波动上升的动态过程,在5%的显著性水平下,经济在空间上表现为显著的正相关性.(2)局部区域空间自相关特征显著,区域经济显著负相关的区域逐渐消失,正相关显著区域日趋加强,最终演化为低一低及高一高两种类型区在东北和西南集中分布格局,且差距不断增大,各类型区域面积消长在起始,震荡和稳定三个阶段呈现出不同特点.(3)区域经济增长的近邻效应不断增强,2004年低-低和高-高两种类型区域面积是1980的1.66倍,但经济空间集聚效应主要是由于低-低区域面积的迅速增加所致.(4)工业化初期阶段,矿产资源条件和区位因素及交通条件两大因素是促进区域经济空间集聚与演化的动力.文章最后探讨了流域经济空间关联特点及演化特征对区域经济集聚扩散过程、区域政策选择、空间开发模式及区域协调发展等问题的影响.     

Predicting landslides for risk analysis — Spatial models tested by a cross-validation technique

A landslide-hazard map is intended to show the location of future slope instability. Most spatial models of the hazard lack reliability tests of the procedures and predictions for estimating the probabilities of future landslides, thus precluding use of the maps for probabilistic risk analysis. To correct this deficiency we propose a systematic procedure comprising two analytical steps: “relative-hazard mapping” and “empirical probability estimation”. A mathematical model first generates a prediction map by dividing an area into “prediction” classes according to the relative likelihood of occurrence of future landslides, conditional by local geomorphic and topographic characteristics. The second stage estimates empirically the probability of landslide occurrence in each prediction class, by applying a cross-validation technique. Cross-validation, a “blind test” here using non-overlapping spatial or temporal subsets of mapped landslides, evaluates accuracy of the prediction and from the resulting statistics estimates occurrence probabilities of future landslides. This quantitative approach, exemplified by several experiments in an area near Lisbon, Portugal, can accommodate any subsequent analysis of landslide risk.     

GIS中的模糊形态运算

空间数据的不确定性是当前GIS领域的研究难点之一。为了描述空间数据的模糊性,把模糊集理论引入GIS,以加强GIS对模糊现象建模的能力,因而产生了模糊数据。但现有GIS缺乏对模糊数据分析和处理的能力。该文把模糊集理论引入数学形态学,提出能处理模糊数据的模糊形态运算,并给出模糊形态运算的隶属函数,使传统的数学形态学能够处理模糊数据且容易在计算机上实现。     

Extended weights of evidence modeling for the pseudo-estimation of metal grades

The weights of evidence modeling (WEM) for binary patterns is extended to take account of general categorical variables. The extension makes it possible to use the weights of evidence model in estimating the conditional probability distributions of metal grades. First, the target feature is converted into a set of binary target indicators. Second, the posterior probabilities are estimated for each of the target categories. Third, the estimates are combined to yield the posterior probability distribution of the target feature. Finally, the pseudometal estimates are derived from the probability distribution. The metal grade estimates are prefixed with pseudo, because the estimates are created from indirect evidence (explanatory variables). The pseudo-estimates provide a unique quantitative means to the delineation of exploration targets. This advantage reduces the ambiguities of target selection based solely on probability estimates. In order to use the generalized WEM, continuous geoscience attributes must be converted into categorical variables by means of optimal segmentation based on the target attribute of interest. The segmentation may be viewed as a process of defining evidence of the target feature. The extended weights of evidence model is demonstrated on a case study to select gold targets of Carlin type. The dataset used in the modeling includes apparent resistivity fields, soil geochemical samples, lithological and alteration information, and structural data.     

Geometric-based approach for integrating VGI POIs and road networks

Integrating heterogeneous spatial data is a crucial problem for geographical information systems (GIS) applications. Previous studies mainly focus on the matching of heterogeneous road networks or heterogeneous polygonal data sets. Few literatures attempt to approach the problem of integrating the point of interest (POI) from volunteered geographic information (VGI) and professional road networks from official mapping agencies. Hence, the article proposes an approach for integrating VGI POIs and professional road networks. The proposed method first generates a POI connectivity graph by mining the linear cluster patterns from POIs. Secondly, the matching nodes between the POI connectivity graph and the associated road network are fulfilled by probabilistic relaxation and refined by a vector median filtering (VMF). Finally, POIs are aligned to the road network by an affine transformation according to the matching nodes. Experiments demonstrate that the proposed method integrates both the POIs from VGI and the POIs from official mapping agencies with the associated road networks effectively and validly, providing a promising solution for enriching professional road networks by integrating VGI POIs.     

Combining indicator patterns in weights of evidence modeling for resource evaluation

The weights of evidence model for combining indicator patterns in mineral resource evaluation is briefly explained with emphasis on the effect of undiscovered deposits on the estimation of the weights and posterior probabilities. A group of six statistical tests is proposed for analyzing the interaction of two or three indicator patterns with the point pattern for mineral deposits. A distinction is made between statistics that depend on choice of unit cell size and those that are approximately or completely independent of it. Finally, weights of evidence are compared to regression coefficients obtained by means of the logistic model.     

Random encounters in probabilistic time geography

Probabilistic time geography considers the encounter of moving agents to be random; therefore, a quantitative time geography analysis must consider the actual encounter probability. The existing algorithm of encounter probability is oriented over a discrete space and is sensitive to the unit definition of a virtual grid; thus, it is not suitable for continuous space. For this reason, a new method is presented in this paper for the encounter of two moving agents in continuous space. When the encounters are less than a specified distance threshold apart, an encounter event occurs based on the probability of the product, which is calculated by their respective probability density functions over their respective potential location areas. This probability provides a quantitative basis for predicting the likelihood of two agents meeting, as well as the location of this meeting point. Finally, the validity of the proposed model is verified by an experiment, which uses tracking data to calculate the encounter probabilities of three zebras and analyse the distribution characteristics of these probabilities over time and space.