Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Employment Distribution and Land-Use Structure in the Metropolitan Area of Columbus, Ohio
AbstractLand-use structure variables derived from landscape ecology theory are introduced into traditional employment density models based on the distance to the major central business district in the monocentric framework or on distances to multiple employment centers in the polycentric framework. Four groups of land use indexes related to size, complexity, diversity, and neighborhood are computed for the Columbus, Ohio, metropolitan area. Models are first constructed for each of its seven counties separately and then combined to form a complete metropolitan-level model. The spatial error model (SEM) is used to account for the spatial autocorrelation that characterizes the data. The results show that distances to both Columbus and county central business districts (CBDs) are strong employment density determinants but also show that land-use structure, measured by the dominance index and the mean edge contrast index, is an important employment density factor. The predictive capability of the model is validated by estimating it over six counties and using it to estimate the density pattern in the omitted county.
Employment Distribution and Land-Use Structure in the Metropolitan Area of Columbus, Ohio
AbstractLand-use structure variables derived from landscape ecology theory are introduced into traditional employment density models based on the distance to the major central business district in the monocentric framework or on distances to multiple employment centers in the polycentric framework. Four groups of land use indexes related to size, complexity, diversity, and neighborhood are computed for the Columbus, Ohio, metropolitan area. Models are first constructed for each of its seven counties separately and then combined to form a complete metropolitan-level model. The spatial error model (SEM) is used to account for the spatial autocorrelation that characterizes the data. The results show that distances to both Columbus and county central business districts (CBDs) are strong employment density determinants but also show that land-use structure, measured by the dominance index and the mean edge contrast index, is an important employment density factor. The predictive capability of the model is validated by estimating it over six counties and using it to estimate the density pattern in the omitted county.
Employment Distribution and Land-Use Structure in the Metropolitan Area of Columbus, Ohio
Lu, Jia (Autor:in) / Guldmann, Jean-Michel
2015
Aufsatz (Zeitschrift)
Englisch
Employment Distribution and Land-Use Structure in the Metropolitan Area of Columbus, Ohio
| British Library Online Contents | 2015