BAYSIAN INFERENCE FOR ORDERED RESPONSE DATA WITH A DYNAMIC SPATIAL‐ORDERED PROBIT MODEL

ABSTRACT Many databases involve ordered discrete responses in a temporal and spatial context, including, for example, land development intensity levels, vehicle ownership, and pavement conditions. An appreciation of such behaviors requires rigorous statistical methods, recognizing spatial effects and dynamic processes. This study develops a dynamic spatial‐ordered probit (DSOP) model in order to capture patterns of spatial and temporal autocorrelation in ordered categorical response data. This model is estimated in a Bayesian framework using Gibbs sampling and data augmentation, in order to generate all autocorrelated latent variables. It incorporates spatial effects in an ordered probit model by allowing for interregional spatial interactions and heteroskedasticity, along with random effects across regions or any clusters of observational units. The model assumes an autoregressive, AR(1), process across latent response values, thereby recognizing time‐series dynamics in panel data sets. The model code and estimation approach is tested on simulated data sets, in order to reproduce known parameter values and provide insights into estimation performance, yielding much more accurate estimates than standard, nonspatial techniques. The proposed and tested DSOP model is felt to be a significant contribution to the field of spatial econometrics, where binary applications (for discrete response data) have been seen as the cutting edge. The Bayesian framework and Gibbs sampling techniques used here permit such complexity, in world of two‐dimensional autocorrelation.     

城市系统演化的复杂性研究

城市演化是由复杂多样的动力和主体推动的,受全球、国家和地方尺度的多重影响,表现出复杂的演化规律和特征。笔者认为城市系统演化模式与过程的研究需要发展一个基于复杂性理论的跨学科的分析框架。本文首先提出一个城市系统演化的概念模型,然后运用层次理论分析了城市系统演化的复杂相互作用,论述了城市系统演化的组成异质性、时空复杂性、决策复杂性等复杂性表征,最后讨论了城市系统演化的各种复杂规律。     

Spatial-Domain Chaos in Landscapes

It has been speculated that deterministic chaos may be responsible for the spatial complexity commonly observed in biophysical landscapes. However, deterministic chaos is a temporally defined concept and has been rigorously investigated only in the temporal domain. It is shown here, using a simple hillslope regolith cover model as an example, that temporal chaos in the presence of even minor spatial anisotropy will result in a spatially chaotic pattern. It is also shown that behavior of spatially chaotic landscape systems can be deduced, at least in theory, from spatial patterns of a single landscape component or variable. Because stochastic complexity is likely to exist in landscapes in addition to any deterministic complexity, detecting and analyzing chaotic behavior in landscapes is difficult. Progress in efforts to examine chaos in the spatial domain and to isolate deterministic and stochastic complexity may be the key to developing a theory of landscape evolution that can reconcile the simultaneous presence of apparently random, irregular variability and orderly, regular patterns.     

The fractal geometry of ancient Maya settlement

Ancient Maya settlement patterns exhibit fractal geometry both within communities and across regions. Fractals are self-similar sets of fractional dimension. In this paper, we show how Maya settlement patterns are logically and statistically self-similar. We demonstrate how to measure the fractal dimensions (or Hausdorff–Besicovitch dimensions) of several data sets. We describe nonlinear dynamical processes, such as chaotic and self-organized critical systems, that generate fractal patterns. As an illustration, we show that the fractal dimensions calculated for some Maya settlement patterns are similar to those produced by warfare, supporting recent claims that warfare is a significant factor in Maya settlement patterning.     

基于齐夫法则的江苏省旅游收入规模结构变化研究

借用齐夫法则研究了江苏省近10年的旅游收入规模结构变化,并与差异度变化加以对比。结果显示无论是国内旅游收入还是国际旅游收入,规模分布均基本遵循齐夫定律,与差异度变化趋势也相一致;无标度区范围均呈扩大趋势,规模结构逐步得到优化。但两者也有不同点:(1)前者从局部单分形演变为几乎覆盖全域的单分形,而后者则从局部单分形→几乎覆盖全域的单分形→局部单分形→双分形;(2)前者是先呈帕雷托模式后呈不规则的帕雷托模式,而后者则是前几年呈不规则的帕雷托模式,后几年标度区一呈对数正态分布模式,标度区二呈不规则的帕雷托模式;(3)前者的规模变差是先扩大后缩小,而后者则是前几年规模变差略有波动,后几年两个标度区之间的差距稍有扩大,但各标度区内部的规模变差却呈缩小趋势。齐夫法则可为分析旅游收入规模结构变化提供新的定量方法。     

Guanaco (Lama guanicoe) isotopic ecology in southern South America: spatial and temporal tendencies, and archaeological implications

We synthesize and discuss available isotopic data on Holocene guanaco samples from southern South America, extending from Tierra del Fuego Island to northern Patagonia and the Pampean region. We evaluate temporal and spatial tendencies on the basis of 91 samples (mainly based on δ¹³C_collagen values), presenting implications for paleodietary research in archaeology. We conclude that there are no strong correlations with latitude in the macro-spatial scale, while there is a set of interesting patterns at smaller regional scales. These patterns lead us to evaluate the role of ecologic and topographic variables (e.g. canopy effect, variations in altitude, ecotones) in structuring isotopic variability. Finally, on the basis of the present analysis we suggest a number of hypotheses and perspectives for the use of stable isotopes as geographic tracers of guanaco distribution in the past, and specific implications for the paleodietary study of human samples.     

Quantifying Animal Trajectories Using Spatial Aggregation and Sequence Analysis: A Case Study of Differentiating Trajectories of Multiple Species

The increasing availability of telemetry data with high spatial and temporal resolution promises to greatly advance scientific understandings of the movement patterns of individual organisms across space and time. The amount of data provided by such methods, however, can be challenging to analyze and interpret. In this study, we present a new approach for analyzing animal movements that aggregates telemetry locations into spatial clusters and extracts the information from sequences formed by individuals passing through these spatial clusters. We applied this integrated approach of spatial aggregation and sequence analysis to quantify and compare trajectories of cattle (Bos taurus), mule deer (Odocoileus hemionus), and elk (Cervus elaphus) tracked by automated telemetry at the Starkey Experimental Forest and Range in northeastern Oregon, USA. Our approach effectively differentiated movement patterns of the three species. It provides a useful mean of quantifying movement patterns of species in a landscape.     

经济发展与住宅市场异速增长时空格局及其形成机理——以长三角地区为例

住宅具有重要的社会稳定功能,其市场发展状况与经济增长关系是实现城市更高质量发展和畅通国内大循环的关键。本文以GDP表征经济发展,住宅价格和租金表征住宅市场发展状况,利用空间变差函数、异速增长模型和增强回归树模型探究2008—2018年长三角地区三者的时空格局及演化机理。研究表明：(1)长三角地区城市经济规模、住宅价格和住宅租金空间格局具有较强的稳定性,呈现出“一极多核”形态。(2)在纵向和横向异速上,经济规模—住宅价格、经济规模—住宅租金均以负异速增长为主,前者异速增长系数多高于后者。(3)在影响三者异速增长的因素中,科技发展水平、财政投入水平、城市人口规模、设施供给水平、产业发展水平和城乡收入差距是经济规模与住宅市场异速增长的主导因素;经济、人口、社会和行政等因素影响的差异性,在预期因素的催化下,使经济规模—住宅价格异速增长高于经济规模—住宅租金。     

A Geographic Network Automata Approach for Modeling Dynamic Ecological Systems

Landscape connectivity networks are composed of nodes representing georeferenced habitat patches that link together based on a species’ maximum dispersal distance. These static representations cannot capture the complexity in species dispersal where the network of habitat patch nodes changes structure over time as a function of local dispersal dynamics. Therefore, the objective of this study is to integrate geographic information, complexity, and network science to propose a novel Geographic Network Automata (GNA) modeling approach for the simulation of dynamic spatial ecological networks. The proposed GNA modeling approach is applied to the emerald ash borer (EAB) forest insect infestation using geospatial data sets from Michigan, U.S.A. and simulates the evolution of the EAB spatiotemporal dispersal network structures across a large regional scale. The GNA model calibration and sensitivity analysis are performed. The simulated spatial network structures are quantified using graph theory measures. Results indicate that the spatial distribution of habitat patch nodes across the landscape in combination with EAB dispersal processes generate a highly connected small-world dispersal network that is robust to node removal. The presented GNA model framework is general and flexible so that different types of geospatial phenomena can be modeled, providing valuable insights for management and decision-making.     

An Initial Analysis of River Discharge and Rainfall in Coastal New South Wales,Australia Using Wavelet Transforms

In many coastal catchments of south eastern New South Wales, Australia, changes in river morphology are a response to human impact superimposed on spatial and temporal patterns of variability in precipitation and discharge. Understanding, and preferably quantifying, spatial and temporal patterns of hydrologic variability are essential to understanding natural changes, and to separate these from artificial changes in river systems. Prediction and management of water resources are also dependent upon this understanding. We assess the variability in precipitation and discharge using the wavelet transform which projects the time series of data into a three dimensional surface of frequency, amplitude and time. The analysis reveals that changes across time often reflect changes in individual seasons and may be linked to changes in particular seasonal atmospheric circulation systems. Strong perturbations in the analysis of one catchment are consistent with documented, geomorphically‐effective, flooding sequences. The characteristics of the series in the transformed data reveal interesting differences at certain times and scales which may be a reflection of changes in larger scale atmospheric processes.     

Spatial Analysis in Physical Geography and the Challenge of Deterministic Uncertainty

The application of complex and nonlinear dynamical systems (NDS) theory in physical geography and geosciences has proceeded through several stages, and has recently entered a phase where field-testable hypotheses and historical or mechanistic explanations are being generated. However, there are some fundamental challenges. It seems clear that chaos and dynamical self-organization are present, and may be common in earth surface systems, and that these phenomena have spatial manifestations in the landscape. However, NDS theory and methods have been formulated primarily in the temporal domain and are typically ill-suited to real-world spatial data. Spatial analytical methods are not generally capable of distinguishing deterministic complexity and uncertainty from noise. Thus, the detection of the signals of complex deterministic dynamics in real landscapes and spatial data is a major challenge. Entropy-based methods of spatial analysis can be directly linked to nonlinear dynamics, and are at present the best available method to approach this problem. However, there is evidence in the spatial analysis literature suggesting that development of techniques to detect deterministic uncertainty is possible. Pending such a break-through, three general approaches are described, based on spatial analysis of chronosequences, the characteriziation of changes in spatial structure over time, and the spatial-domain testing of specific hypotheses relevant to deterministic uncertainty. Current trends generally suggest a shift in mathematical modeling and spatial analysis in physical geography away from traditional determinism toward approaches that incorporate locational, historical, and scale contingency.     

Spatiotemporal Modeling of Correlated Small‐Area Outcomes: Analyzing the Shared and Type‐Specific Patterns of Crime and Disorder

This research applies a Bayesian multivariate modeling approach to analyze the spatiotemporal patterns of physical disorder, social disorder, property crime, and violent crime at the small‐area scale. Despite crime and disorder exhibiting similar spatiotemporal patterns, as hypothesized by broken windows and collective efficacy theories, past studies often analyze a single outcome and overlook the correlation structures between multiple crime and disorder types. Accounting for five covariates, the best‐fitting model partitions the residual risk of each crime and disorder type into one spatial shared component, one temporal shared component, and type‐specific spatial, temporal, and space–time components. The shared components capture the underlying spatial pattern and time trend common to all types of crime and disorder. Results show that population size, residential mobility, and the central business district are positively associated with all outcomes. The spatial shared component is found to explain the largest proportion of residual variability for all types of crime and disorder. Spatiotemporal hotspots of crime and disorder are examined to contextualize broken windows theory. Applications of multivariate spatiotemporal modeling with shared components to ecological crime theories and crime prevention policy are discussed.     

不同尺度乡村聚落景观的空间集聚性分形特征及影响因素分析——以江苏省镇江市为例

为分析乡村聚落景观空间结构的分形特征,以GIS为平台、土地调查数据为主要数据源,通过集聚维数,分别在县域、镇域和村域三个尺度上,分析了聚落体系空间集聚性的分形特征及其影响因素。结果表明:乡村聚落景观在空间结构上具有比较明显的分形特征;空间集聚性存在不同尺度分形特征的差异,同时丹阳市的镇和中心村的集聚性则明显小于句容市;不同尺度聚落集聚性出现明显的尺度特征,即中心村 > 镇 > 县城;地形是影响乡村聚落景观空间集聚性分形特征,表现为腹地内坡度越大,集聚性越强;交通网络的完善降低了乡村聚落对空间直线距离的依赖性。     

中心城区金融服务业空间集聚过程与格局研究——以潍坊市奎文区为例

近年来金融服务业发展成为我国经济与地理领域学者关注的新热点。本文通过GIS空间分析和电信黄页统计模拟,对潍坊市中心城区奎文区金融服务业的集聚现状、空间演变趋势进行了实证研究,重点探讨了金融服务业集聚格局的形成过程及演变机制。结论指出:金融服务业空间高度集聚于中心城区CBD内(单核心),集聚主要受城市等级规模和政策推动的影响;较之非银行业(保险业、证券业和其他金融活动),银行业时空演变规律性更强,但总体都呈现"轴向扩散"、"楼宇主导"态势;演变过程和城市主导发展方向、城市功能转型相契合,空间表现为由非均衡向相对均衡发展的格局过渡。     

Adaptation,interaction and urgency: a complex evolutionary economic geography approach to leisure

Local and regional governments in western European peripheral areas aim to spur leisure-led regional development. We explore planning for leisure by applying an evolutionary economic geography (EEG) approach from a complexity perspective. We identify conditions which enable and constrain leisure development and its effects on the region as a whole. This means combining the local level of individual adaptations with the institutional setting and with the regional scale. We examine the Dutch province of Fryslân and explore by means of case study analysis how current leisure development processes can be explained in a complex evolutionary manner. We explore economic novelty as a result of individual adaptations; how such adaptations through interactions create emerging spatial patterns; how these spatial patterns form self-organizing new types of order; and the way this process is dependent on previous paths whilst also creating new pathways. Our findings show that although development is dependent on individual adaptations often stemming from a few actors, for such adaptations to have an effect on the region requires a connectivity between actors and a sense of urgency amongst those actors. Using a complex EEG approach allows us to explain leisure-led regional development as the product of these conditions. This can help planners deal with the complexity and unpredictability of this process, focusing not on a desired end goal as such, but on creating the conditions in which a more autonomous development can take place.     

A probabilistic framework for assessing spatio-temporal point patterns in the archaeological record

The assessment of spatial patterns in archaeology is hampered by a number of constraints, one of the most serious of which is the intrinsic temporal uncertainty associated with most of the archaeological record. Different types of chronological definition or different degrees of temporal knowledge will suggest different kinds of spatial pattern, ultimately obscuring and restricting our interpretation of the background process, especially in cases where we are seeking a diachronic perspective. This paper addresses these problems by adopting both a probabilistic approach and a more standardised framework for diachronic analysis. First, we define the notion of temporal uncertainty and explore its analytical consequences. Second, we consider two methods by which it might be formally quantified, emphasising (a) the advantages of probability-weighted spatial analysis and (b) the comparison of alternative spatio-temporal patterns via Monte-Carlo simulation. Finally, we apply these methods to a case study that considers the distribution of Middle to Late Jomon (ca.5000–3000 BP) pithouses recorded in the Chiba New Town area of Japan.     

The Potential of Tree Rings in Eucalyptus pauciflora for Climatological and Hydrological Reconstruction

We investigate the causes of variability in a tree‐ring chronology comprising data from Eucalyptus pauciflora Sieb. Ex. Spreng. at the alpine treeline on the Kosciuszko Plateau in New South Wales, Australia. Following verification of crossdating in a subset of the available data, we found that ring width correlates significantly with net radiation, precipitation and mean minimum and maximum air temperature during the preceding winter and spring of the growing season. Our results for spring are consistent with the impact of climate on tree growth in alpine woodlands reported in previous studies. Analyses of snow‐depth data revealed negative correlations with ring width throughout winter and spring. Our results indicate that low temperature and high precipitation during winter negatively affect the growth of E. pauciflora by prolonging spring snow cover. Ring width also correlates significantly with an index of soil dryness and flow in rivers with their headwaters in the Kosciuszko plateau. Given the apparent sensitivity of our chronology to climate and snow conditions, our results suggest that tree‐ring chronologies comprising data from E. pauciflora at the alpine treeline have potential for climatological and hydrological reconstruction in southeast Australia.     

The Broken Past: Fractals in Archaeology

Many archaeological patterns are fractal. Fractal analysis, therefore, has much to contribute to archaeology. This article offers an introduction to fractal analysis for archaeologists. We explain what fractals are, describe the essential methods of fractal analysis, and present archaeological examples. Some examples have been published previously, while others are presented here for the first time. We also explain the connection between fractal geometry and nonlinear dynamical systems. Fractals are the geometry of complex nonlinear systems. Therefore, fractal analysis is an indispensable method in our efforts to understand nonlinearities in past cultural dynamics.     

ECONOMIC DEVELOPMENT TRENDS IN THE USSR, 1970-1988: PART I (PRODUCTION AND PRODUCTIVITY)

The first of two articles devoted to spatial and temporal trends in economic development and levels of living within the USSR focuses on changes in the pattern of absolute and per capita economic output—national income produced and gross value of industrial output (at the republic and economic regional level, respectively). It then investigates the question of whether divergence or convergence has occurred among republics and economic regions in terms of these indicators. Finally, it assesses patterns of change in labor and capital productivity across Soviet republics.     

基于微博大数据的西安国内游客日内时间分布模式研究

移动互联网的迅速发展与大数据时代的到来为研究不同尺度的游客时间行为提供了可能。本文以西安为案例地,基于游客生成的大规模微博签到数据研究国内游客的日内时间分布模式。研究表明:1国内游客与日常用户的分时签到规律存在明显的差异;2游客在重要旅游节点的日内时间分布模式可分为"多峰波动型"、"日间活跃型"和"夜间活跃型";3客流的时间分布模式与空间特征具有较强的对应关系;4空间与活动的叠加是形成游客时间分布模式的重要作用机制。