Space-Time Analysis: Concepts, Quantitative Methods, and Future Directions

被引:52
作者
An, Li [1 ]
Tsou, Ming-Hsiang [1 ]
Crook, Stephen E. S. [1 ]
Chun, Yongwan [2 ]
Spitzberg, Brian [3 ]
Gawron, J. Mark [4 ]
Gupta, Dipak K. [5 ]
机构
[1] San Diego State Univ, Dept Geog, San Diego, CA 92182 USA
[2] Univ Texas Dallas, Sch Econ Polit & Policy Sci, Richardson, TX 75080 USA
[3] San Diego State Univ, Sch Commun, San Diego, CA 92182 USA
[4] San Diego State Univ, Dept Linguist, San Diego, CA 92182 USA
[5] San Diego State Univ, Dept Polit Sci, San Diego, CA 92182 USA
基金
美国国家科学基金会;
关键词
absolute versus relative space; review; simulation models; space-time analysis; statistical models; espacio absoluto vs; espacio relativo; modelos de simulacion; analisis espacio-tiempo; modelos estadisticos; LAND-COVER-CHANGE; COUPLED HUMAN; SPATIOTEMPORAL DATA; SEQUENCE ALIGNMENT; ACTIVITY PATTERNS; TEMPORAL ANALYSIS; SPATIAL MODEL; MOVEMENT; FRAMEWORK; DISEASE;
D O I
10.1080/00045608.2015.1064510
中图分类号
P9 [自然地理学]; K9 [地理];
学科分类号
0705 ; 070501 ;
摘要
Throughout most of human history, events and phenomena of interest have been characterized using space and time as their major characteristic dimensions, in either absolute or relative conceptualizations. Space-time analysis seeks to understand when and where (and sometimes why) things occur. In the context of several of the most recent and substantial advances in individual movement data analysis (time geography in particular) and spatial panel data analysis, we focus on quantitative space-time analytics. Based on more than 700 articles (from 1949 to 2013) we obtained through a key word search on the Web of Knowledge and through the authors' personal archives, this article provides a synthetic overview about the quantitative methodology for space-time analysis. Particularly, we highlight space-time pattern revelation (e.g., various clustering metrics, path comparison indexes, space-time tests), space-time statistical models (e.g., survival analysis, latent trajectory models), and simulation methods (e.g., cellular automaton, agent-based models) as well as their empirical applications in multiple disciplines. This article systematically presents the strengths and weaknesses of a set of prevalent methods used for space-time analysis and points to the major challenges, new opportunities, and future directions of space-time analysis. ????????????????,???????????????????,????????????????????????????(?????)???????????????(????????)???????????????????????,?????????????????????????????????????????????????(?1949 ?? 2013 ?),???????????,??????????????????????(????????????????????)???????(?????????????),??????(??????????????????),?????????????????????????????????????????,???????????????????,???????? Durante la mayor parte de la historia humana, la caracterizacion de eventos y fenomenos interesantes se ha basado en el espacio y el tiempo como sus principales dimensiones, tanto en absolutas como relativas conceptualizaciones. El analisis espacio-tiempo busca comprender cuando y donde (y algunas veces por que) ocurren las cosas. Dentro del contexto de varios de los mas recientes y sustanciales avances en el analisis de datos del movimiento individual (geografia del tiempo en particular) y analisis de datos del panel espacial, nosotros nos enfocamos en la analitica cuantitativa del espacio-tiempo. Este articulo entrega una vision de conjunto sintetica acerca de la metodologia cuantitativa para el analisis del espacio-tiempo, a partir de mas de 700 articulos (de 1949 a 2013) que obtuvimos por medio de una busqueda con palabras clave en la Web of Knowledge [Web del Conocimiento] y en los archivos personales de los autores. En particular, destacamos el patron de revelacion del espacio-tiempo (e.g., varias medidas de agrupamiento, indices de comparacion de rutas, pruebas de espacio-tiempo), modelos estadisticos de espacio-tiempo (e.g., analisis de supervivencia, modelos de trayectoria latente), y metodos de simulacion (e.g., automata celular, modelos basados en agente) lo mismo que sus aplicaciones empiricas en multiples disciplinas. Este articulo presenta sistematicamente las fortalezas y debilidades de un conjunto de metodos prevalentes usados para el analisis del espacio-tiempo y apunta a los principales retos, nuevas oportunidades y direcciones futuras del analisis espacio-tiempo.
引用
收藏
页码:891 / 914
页数:24
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