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1.
Mining Association Rules in Spatio-Temporal Data: An Analysis of Urban Socioeconomic and Land Cover Change 总被引：8，自引：0，他引：8
This research demonstrates the application of association rule mining to spatio‐temporal data. Association rule mining seeks to discover associations among transactions encoded in a database. An association rule takes the form A→B where A (the antecedent) and B (the consequent) are sets of predicates. A spatio‐temporal association rule occurs when there is a spatio‐temporal relationship in the antecedent or consequent of the rule. As a case study, association rule mining is used to explore the spatial and temporal relationships among a set of variables that characterize socioeconomic and land cover change in the Denver, Colorado, USA region from 1970–1990. Geographic Information Systems (GIS)‐based data pre‐processing is used to integrate diverse data sets, extract spatio‐temporal relationships, classify numeric data into ordinal categories, and encode spatio‐temporal relationship data in tabular format for use by conventional (non‐spatio‐temporal) association rule mining software. Multiple level association rule mining is supported by the development of a hierarchical classification scheme (concept hierarchy) for each variable. Further research in spatio‐temporal association rule mining should address issues of data integration, data classification, the representation and calculation of spatial relationships, and strategies for finding ‘interesting’ rules. 相似文献
2.
The effects of spatial autoregressive dependencies on inference in ordinary least squares: a geometric approach 总被引：1，自引：1，他引：0
There is a common belief that the presence of residual spatial autocorrelation in ordinary least squares (OLS) regression
leads to inflated significance levels in beta coefficients and, in particular, inflated levels relative to the more efficient
spatial error model (SEM). However, our simulations show that this is not always the case. Hence, the purpose of this paper
is to examine this question from a geometric viewpoint. The key idea is to characterize the OLS test statistic in terms of
angle cosines and examine the geometric implications of this characterization. Our first result is to show that if the explanatory
variables in the regression exhibit no spatial autocorrelation, then the distribution of test statistics for individual beta
coefficients in OLS is independent of any spatial autocorrelation in the error term. Hence, inferences about betas exhibit all the optimality properties of
the classic uncorrelated error case. However, a second more important series of results show that if spatial autocorrelation
is present in both the dependent and explanatory variables, then the conventional wisdom is correct. In particular, even when
an explanatory variable is statistically independent of the dependent variable, such joint spatial dependencies tend to produce
“spurious correlation” that results in over-rejection of the null hypothesis. The underlying geometric nature of this problem
is clarified by illustrative examples. The paper concludes with a brief discussion of some possible remedies for this problem. 相似文献
3.
Developing a bivariate spatial association measure: An integration of Pearson's r and Moran's I 总被引：1，自引：0，他引：1
Sang-Il Lee 《Journal of Geographical Systems》2001,3(4):369-385
This research is concerned with developing a bivariate spatial association measure or spatial correlation coefficient, which
is intended to capture spatial association among observations in terms of their point-to-point relationships across two spatial
patterns. The need for parameterization of the bivariate spatial dependence is precipitated by the realization that aspatial bivariate association measures, such as Pearson's correlation coefficient,
do not recognize spatial distributional aspects of data sets. This study devises an L statistic by integrating Pearson's r as an aspatial bivariate association measure and Moran's I as a univariate spatial association measure. The concept of a spatial smoothing scalar (SSS) plays a pivotal role in this task.
Received: 07 November 2000 / Accepted: 02 August 2001 相似文献
4.
This paper presents the first application of spatially correlated neutral models to the detection of changes in mortality rates across space and time using the local Morans I statistic. Sequential Gaussian simulation is used to generate realizations of the spatial distribution of mortality rates under increasingly stringent conditions: 1) reproduction of the sample histogram, 2) reproduction of the pattern of spatial autocorrelation modeled from the data, 3) incorporation of regional background obtained by geostatistical smoothing of observed mortality rates, and 4) incorporation of smooth regional background observed at a prior time interval. The simulated neutral models are then processed using two new spatio-temporal variants of the Morans I statistic, which allow one to identify significant changes in mortality rates above and beyond past spatial patterns. Last, the results are displayed using an original classification of clusters/outliers tailored to the space-time nature of the data. Using this new methodology the space-time distribution of cervix cancer mortality rates recorded over all US State Economic Areas (SEA) is explored for 9 time periods of 5 years each. Incorporation of spatial autocorrelation leads to fewer significant SEA units than obtained under the traditional assumption of spatial independence, confirming earlier claims that Type I errors may increase when tests using the assumption of independence are applied to spatially correlated data. Integration of regional background into the neutral models yields substantially different spatial clusters and outliers, highlighting local patterns which were blurred when local Morans I was applied under the null hypothesis of constant risk.This research was funded by grants R01 CA92669 and 1R43CA105819-01 from the National Cancer Institute and R43CA92807 under the Innovation in Biomedical Information Science and Technology Initiative at the National Institute of Health. The views stated in this publication are those of the authors and do not necessarily represent the official views of the NCI. The authors also thank three anonymous reviewers for their comments that helped improve the presentation of the methodology. 相似文献
5.
Charles Otunga John Odindi Onisimo Mutanga Clement Adjorlolo Jacobus Botha 《国际地球制图》2018,33(5):489-504
The spatial distribution of different C3 and C4 grass species in tropical montane areas is commonly influenced by a number of factors that include site-specific topography. Hence, the distribution of these grasses across topographic gradients can vary significantly. In this study, we investigate the influence of topographic factors (elevation, slope and aspect) on the spatial distribution of Festuca grass species in a commonage area, comprising agro-biodiversity conservation land use. Integration of the topographic variables using GIS and binary logistic regression (LR) modelling showed that C3, Festuca grass species distribution can be predicted or mapped with an accuracy of 80% in the landscape under study. The study contributes to understanding the spatial distribution of C3 grass species and provides valuable information for designing and optimizing rangeland conservation in the subtropical montane landscapes. 相似文献
6.
ABSTRACTThe spatial distance (gap) between map symbols can have a great impact on their discriminability, however, there is little empirical evidence to establish spatial and attribute thresholds. In this paper, we examine the effect of the spatial gap in discriminability of color hue and value, that is, we conducted an online study to obtain performance metrics; then an eye-tracking study to understand participants’ strategies and cognitive processes. Participants completed two experimental tasks (compare two areas and decide if their color is the same; and compare three areas and rank them from the lightest to the darkest). The color distances and the spatial distances were strictly controlled for the compared areas. Our analyses confirmed that, overall, increasing the gap between colors has a consistent negative impact on the ability to differentiate them with both sequential and qualitative schemes. Furthermore, we observed that sequential schemes require larger color distances than qualitative schemes for discriminability. Finally, our results suggested that for qualitative colors, the largest tested color distance ?E00 = 10 yields considerably higher levels of accuracy in color discrimination (even when the spatial gap between the two colors is large), thus we recommend ?E00 = 10 to practicing cartographers and other information visualization designers. 相似文献
7.
8.
Identifying local spatial association in flow data 总被引：5，自引：1，他引：4
In this paper we develop a spatial association statistic for flow data by generalizing the statistic of Getis-Ord, G
i (and G
i
*). This local measure of spatial association, G
ij, is associated with each origin-destination pair. We define spatial weight matrices with different metrics in flow space.
These spatial weight matrices focus on different aspects of local spatial association. We also define measures which control
for generation or attraction nonstationarity. The measures are implemented to examine the spatial association of residuals
from two different models. Using the permutation approach, significance bounds are computed for each statistic. In contrast
to the G
i statistic, the normal approximation is often appropriate, but the statistics are still correlated. Small sample properties
are also briefly discussed.
Received: 18 February 1998/Accepted: 29 September 1998 相似文献
9.
10.
This article reports on an empirical study of the trends and patterns of research activities in Geographic Information Science (GIScience) during the years 1997–2007. The GIScience research priorities identified by the University Consortium of Geographic Information Science (UCGIS) were used as guidelines to examine the 985 research articles published in six well‐recognized academic journals. Latent Semantic Analysis (LSA) was employed to investigate the association among the different GIScience research themes. The spatial and temporal patterns of the association between the publications and the different GIScience themes were examined to show the development of GIScience research during the study period. Furthermore, correlation analyses between the publications were conducted following the LSA results to reveal GIScience research networks, including the networks of the published articles and those formed by the research places. In this article, we applied an approach that was developed within information science to depict what GIS research activities were conducted when and where and how they connect to each other through sharing common research themes. The related findings pave the way for future efforts to describe the paradigm of GIScience as well as the pattern of GIScience research. 相似文献
11.
This study analyses the relationship between fire incidence and some environmental factors, exploring the spatial non-stationarity
of the phenomenon in sub-Saharan Africa. Geographically weighted regression (GWR) was used to study the above relationship.
Environment covariates comprise land cover, anthropogenic and climatic variables. GWR was compared to ordinary least squares,
and the hypothesis that GWR represents no improvement over the global model was tested. Local regression coefficients were
mapped, interpreted and related with fire incidence. GWR revealed local patterns in parameter estimates and also reduced the
spatial autocorrelation of model residuals. All the covariates were non-stationary and in terms of goodness of fit, the model
replicates the data very well (R
2 = 87%). Vegetation has the most significant relationship with fire incidence, with climate variables being more important
than anthropogenic variables in explaining variability of the response. Some coefficient estimates exhibit locally different
signs, which would have gone undetected by a global approach. This study provides an improved understanding of spatial fire–environment
relationships and shows that GWR is a valuable complement to global spatial analysis methods. When studying fire regimes,
effects of spatial non-stationarity need to be incorporated in vegetation-fire modules to have better estimates of burned
areas and to improve continental estimates of biomass burning and atmospheric emissions derived from vegetation fires. 相似文献
12.
提出了一类无穷多种称为准熵的新的独立性度量 ,它们用严格凸函数对原变量经分布函数变换再量化后得到的变量的联合概率的均匀性进行度量 ,并提出了基于准熵的盲分离算法 ,可分离任意连续分布的信号 ,包括峭度为零的信号。通过与前人算法的对比试验 ,证实了基于准熵的算法的优越性 相似文献
13.
14.
Yukio Sadahiro 《Journal of Geographical Systems》1999,1(2):107-136
This paper develops statistical methods for analyzing the distribution of spatial objects—points, convex polygons, and line
segments—in relation to a surface. We propose statistics for measuring the relationship between the distribution of these
objects and a surface and derive their expectations and variances under the null hypothesis that the objects are independently
and randomly distributed. The statistics are approximately distributed according to the normal distribution under the null
hypothesis, which enables us to test the significance of the spatial relationships statistically. Using the proposed methods,
we empirically analyze the distribution of convenience stores in relation to the distribution of population in a suburb of
Osaka, Japan. Some empirical findings are shown. 相似文献
15.
A Spatial Entropy-Based Decision Tree for Classification of Geographical Information 总被引：1，自引：0，他引：1
A decision tree is a classification algorithm that automatically derives a hierarchy of partition rules with respect to a target attribute of a large dataset. However, spatial autocorrelation makes conventional decision trees underperform for geographical datasets as the spatial distribution is not taken into account. The research presented in this paper introduces the concept of a spatial decision tree based on a spatial diversity coefficient that measures the spatial entropy of a geo‐referenced dataset. The principle of this solution is to take into account the spatial autocorrelation phenomena in the classification process, within a notion of spatial entropy that extends the conventional notion of entropy. Such a spatial entropy‐based decision tree integrates the spatial autocorrelation component and generates a classification process adapted to geographical data. A case study oriented to the classification of an agriculture dataset in China illustrates the potential of the proposed approach. 相似文献
16.
GONGJianya DUDaosheng LIDajun GUANYunlan 《地球空间信息科学学报》2003,6(2):20-24
Positional error of line segments is usually described byusing “g-band”,however,its band width is in relation to the confidence level choice.In fact,given different confidence levels,a series of concentric bands can be obtained.To overcome the effect of confidence level on the error indicator,by introducing the union entropy theory,we propose an entropy error ellipse index of point,then extend it to line segment and polygon.and establish an entropy error band of line segment and an entropy error do-nut of polygon.The research shows that the entropy error index can be determined uniquely and is not influenced by confidence level,and that they are suitable for positional uncertainty of planar geometry features. 相似文献
17.
ABSTRACTTree species distribution mapping using remotely sensed data has long been an important research area. However, previous studies have rarely established a comprehensive and efficient classification procedure to obtain an accurate result. This study proposes a hierarchical classification procedure with optimized node variables and thresholds to classify tree species based on high spatial resolution satellite imagery. A classification tree structure consisting of parent and leaf nodes was designed based on user experience and visual interpretation. Spectral, textural, and topographic variables were extracted based on pre-segmented images. The random forest algorithm was used to select variables by ranking the impact of all variables. An iterating approach was used to optimize variables and thresholds in each loop by comprehensively considering the test accuracy and selected variables. The threshold range for each selected variable was determined by a statistical method considering the mean and standard deviation for two subnode types at each parent node. Classification of tree species was implemented using the optimized variables and thresholds. The results show that (1) the proposed procedure can accurately map the tree species distribution, with an overall accuracy of over 86% for both training and test stages; (2) critical variables for each class can be identified using this proposed procedure, and optimal variables of most tree plantation nodes are spectra related; (3) the overall forest classification accuracy using the proposed method is more accurate than that using the random forest (RF) and classification and regression tree (CART). The proposed approach provides results with 3.21% and 7.56% higher overall land cover classification accuracy and 4.68% and 10.28% higher overall forest classification accuracy than RF and CART, respectively. 相似文献
18.
This paper systematically investigates spatially autocorrelated patterns and the behaviour of their associated test statistic
Moran's I in three bounded regular tessellations. These regular tessellations consist of triangles, squares, and hexagons, each of
increasing size (n=64; 256; 1024). These tesselations can be downloaded at http://geo-www.sbs.ohio-state.edu/faculty/tiefelsdorf/regspastruc/
in several GIS formats. The selection of squares is particularly motivated by their use in raster based GIS and remote sensing.
In contrast, because of topological correspondences, the hexagons serve as excellent proxy tessellations for empirical maps
in vector based GIS. For all three tessellations, the distributional characteristics and the feasibility of the normal approximation
are examined for global Moran's I, Moran's I
(k) associated with higher order spatial lags, and local Moran's I
i. A set of eigenvectors can be generated for each tessellation and their spatial patterns can be mapped. These eigenvectors
can be used as proxy variables to overcome spatial autocorrelation in regression models. The particularities and similarities
in the spatial patterns of these eigenvectors are discussed. The results indicate that [i] the normal approximation for Moran's
I is not always feasible; [ii] the three tessellations induce different distributional characteristics of Moran's I, and [iii] different spatial patterns of eigenvectors are associated with the three tessellations.
Received: 2 July 1999 / Accepted: 9 November 1999 相似文献
19.
Geocoding systems typically use more than one geographic reference dataset to improve match rates and spatial accuracy, resulting in multiple candidate geocodes from which the single “best” result must be selected. Little scientific evidence exists for formalizing this selection process or comparing one strategy to another, leading to the approach used in existing systems which we term the hierarchy‐based criterion: place the available reference data layers into qualitative, static, and in many cases, arbitrary hierarchies and attempt a match in each layer, in order. The first non‐ambiguous match with suitable confidence is selected and returned as output. This approach assumes global relationships of relative accuracy between reference data layers, ignoring local variations that could be exploited to return more precise geocodes. We propose a formalization of the selection criteria and present three alternative strategies which we term the uncertainty‐, gravitationally‐, and topologically‐based strategies. The performance of each method is evaluated against two ground truth datasets of nationwide GPS points to determine any resulting spatial improvements. We find that any of the three new methods improves on current practice in the majority of cases. The gravitationally‐ and topologically‐based approaches offer improvement over a simple uncertainty‐based approach in cases with specific characteristics. 相似文献
20.
Yukio Hagiwara 《Journal of Geodesy》1976,50(2):131-135
In this paper, a new formula for evaluating the truncation coefficientQ
n
is derived from recurrence relations of Legendre polynomials. The present formula has been conveniently processed by an electronic
computer, providing the value ofQ
n
up to a degreen=49 which are exactly equal to those of Paul (1973). 相似文献