확률선택모형에 의한 대구시의 토지이용변화에 대한 실증분석
An Empirical Anaysis of Land use Changes in Daegu Metropolitan City by Using Probabilistic Choice Model
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초록
As an essential part of integrated land use-transport models, prediction of land use changes and illumination of the many factors behind such change are always of interest to planners, policy makers, developers and others. Land use classifications are discrete, and spatial effects are fundamental. For these reasons, new specifications and computational methods are needed. The paper describes the computational methods used for model estimation and application, including likelihood simulation. Using a multinomial logit framework, this paper studies land use changes in Daegu metropolitan area, in 30m×30m pixels. In light of these challenges, this paper randomly samples 2,000 observations for 100 times and estimates a multinomial logit model via maximum likelihood estimation. Lagged variables are key to the model’'s specification and a series of neighborhood variables, computed for each cell in turn, control for population and local development. And uncertainties in predictions are quantified via an entropy statistic. Results indicate that neighborhood characteristics have strong effects on land use change: clustering is significant over space, but high residential densities can impede future development of non-residential land use.
Abstract
As an essential part of integrated land use-transport models, prediction of land use changes and illumination of the many factors behind such change are always of interest to planners, policy makers, developers and others. Land use classifications are discrete, and spatial effects are fundamental. For these reasons, new specifications and computational methods are needed. The paper describes the computational methods used for model estimation and application, including likelihood simulation. Using a multinomial logit framework, this paper studies land use changes in Daegu metropolitan area, in 30m×30m pixels. In light of these challenges, this paper randomly samples 2,000 observations for 100 times and estimates a multinomial logit model via maximum likelihood estimation. Lagged variables are key to the model’'s specification and a series of neighborhood variables, computed for each cell in turn, control for population and local development. And uncertainties in predictions are quantified via an entropy statistic. Results indicate that neighborhood characteristics have strong effects on land use change: clustering is significant over space, but high residential densities can impede future development of non-residential land use.
참고문헌 (23)
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