This work is part of an investigation into the contemporary dynamics of development and modernization in the southern and far southern coastal areas of Chile, specifically the shoreline of the northern part of the Aysen Region. The objective is to propose a theoretical-conceptual reflection to enable ethnographic data to be framed as a problem and interpreted as a function of a political reading which - why not say so? - could transform the world of the southern and far southern coastal zone. The central argument of the text is hypothetical: the dilemmas of development, in the current circumstances of the coasts of the Aysen Region, are susceptible of resolution (at least up to a point) from a conscious, reflexive change of perspective on culture as the word is understood in anthropology. Este trabajo se enmarca en una investigación sobre las dinámicas contemporáneas del desarrollo y la modernización en las costas sur-australes de Chile, específicamente en el litoral norte de la región de Aisén. A partir de un conjunto de datos etnográficos se propone una reflexión teórico-conceptual que permita problematizar e interpretar esos datos en función de una lectura política y, por qué no decirlo, transformadora del mundo costero sur-austral. El argumento central del texto tiene carácter hipotético: las encrucijadas del desarrollo, en las actuales coyunturas de las costas aiseninas, son susceptibles de ser resueltas (al menos hasta cierto punto) a partir de un giro reflexivo y consciente sobre eso que en antropología llamamos cultura

A Barrat

A Goetz

AJ Tatem

Andres J. Garcia

Andrew J. Tatem

D Balcan

D Smith

DL Bryan

E Kenah

E Taaffe

F Simini

H Yang

IML Rvachev LA, Jr

J Brownstein

J Brueckner

J Nystuen

J Parker

J Wang

JC Crotts

K Button

L A. Rvachev

M Bell

M Brons

M Irwin

M Marazzo

M Newman

M O’Kelly

MA Johansson

ME O’Kelly

MJ Kuby

P Adey

P Upham

PJ Taylor

R Guimerà

RF Grais

S Collinson

ST Stoddard

T Grosche

TAB Snijders

TH Grubesic

Timothy J. Fik

Tobias Preis

Xiao Wu

Z Huang

Z-J Liu

Zhuojie Huang

PubMed

<div><p>The expanding global air network provides rapid and wide-reaching connections accelerating both domestic and international travel. To understand human movement patterns on the network and their socioeconomic, environmental and epidemiological implications, information on passenger flow is required. However, comprehensive data on global passenger flow remain difficult and expensive to obtain, prompting researchers to rely on scheduled flight seat capacity data or simple models of flow. This study describes the construction of an open-access modeled passenger flow matrix for all airports with a host city-population of more than 100,000 and within two transfers of air travel from various publicly available air travel datasets. Data on network characteristics, city population, and local area GDP amongst others are utilized as covariates in a spatial interaction framework to predict the air transportation flows between airports. Training datasets based on information from various transportation organizations in the United States, Canada and the European Union were assembled. A log-linear model controlling the random effects on origin, destination and the airport hierarchy was then built to predict passenger flows on the network, and compared to the results produced using previously published models. Validation analyses showed that the model presented here produced improved predictive power and accuracy compared to previously published models, yielding the highest successful prediction rate at the global scale. Based on this model, passenger flows between 1,491 airports on 644,406 unique routes were estimated in the prediction dataset. The airport node characteristics and estimated passenger flows are freely available as part of the Vector-Borne Disease Airline Importation Risk (VBD-Air) project at: <a href="http://www.vbd-air.com/data" target="_blank">www.vbd-air.com/data</a>.</p></div

Zhuojie Huang (412883)

Xiao Wu (158273)

Andres J. Garcia (105101)

Timothy J. Fik (412884)

Andrew J. Tatem (82578)

FigShare

An Open-Access Modeled Passenger Flow Matrix for the Global Air Network in 2010

The expanding global air network provides rapid and wide-reaching connections accelerating both domestic and international travel. To understand human movement patterns on the network and their socioeconomic, environmental and epidemiological implications, information on passenger flow is required. However, comprehensive data on global passenger flow remain difficult and expensive to obtain, prompting researchers to rely on scheduled flight seat capacity data or simple models of flow. This study describes the construction of an open-access modeled passenger flow matrix for all airports with a host city-population of more than 100,000 and within two transfers of air travel from various publicly available air travel datasets. Data on network characteristics, city population, and local area GDP amongst others are utilized as covariates in a spatial interaction framework to predict the air transportation flows between airports. Training datasets based on information from various transportation organizations in the United States, Canada and the European Union were assembled. A log-linear model controlling the random effects on origin, destination and the airport hierarchy was then built to predict passenger flows on the network, and compared to the results produced using previously published models. Validation analyses showed that the model presented here produced improved predictive power and accuracy compared to previously published models, yielding the highest successful prediction rate at the global scale. Based on this model, passenger flows between 1,491 airports on 644,406 unique routes were estimated in the prediction dataset. The airport node characteristics and estimated passenger flows are freely available as part of the Vector-Borne Disease Airline Importation Risk (VBD-Air) project at: www.vbd-air.com/data

Andres J Garcia

Timothy J Fik

Andrew J Tatem

Directory of Open Access Journals

PLoS ONE

An open-access modeled passenger flow matrix for the global air network in 2010.

The expanding global air network provides rapid and wide-reaching connections accelerating both domestic and international travel. To understand human movement patterns on the network and their socioeconomic, environmental and epidemiological implications, information on passenger flow is required. However, comprehensive data on global passenger flow remain difficult and expensive to obtain, prompting researchers to rely on scheduled flight seat capacity data or simple models of flow. This study describes the construction of an open-access modeled passenger flow matrix for all airports with a host city-population of more than 100,000 and within two transfers of air travel from various publicly available air travel datasets. Data on network characteristics, city population, and local area GDP amongst others are utilized as covariates in a spatial interaction framework to predict the air transportation flows between airports. Training datasets based on information from various transportation organizations in the United States, Canada and the European Union were assembled. A log-linear model controlling the random effects on origin, destination and the airport hierarchy was then built to predict passenger flows on the network, and compared to the results produced using previously published models. Validation analyses showed that the model presented here produced improved predictive power and accuracy compared to previously published models, yielding the highest successful prediction rate at the global scale. Based on this model, passenger flows between 1,491 airports on 644,406 unique routes were estimated in the prediction dataset. The airport node characteristics and estimated passenger flows are freely available as part of the Vector-Borne Disease Airline Importation Risk (VBD-Air) project (see link below)

Preis, Tobias

Huang, Zhuojie

Wu, Xiao

Garcia, Andres J.

Fik, Timothy J.

Tatem, Andrew J.

Southampton (e-Prints Soton)

An open-access modeled passenger flow matrix for the global air network in 2010

Crossref

http://dx.doi.org/10.1371/journal.pone.0064317