Article
DEVELOPMENT AND STATISTICAL VALIDATION OF A SIMPLIFIED LOGISTIC LAND USE CHANGE MODEL
DOI: 10.7708/ijtte.2016.6(4).03
6 / 4 / 390-405 Pages
Author(s)
Tahmina Khan - Civil and Environmental Engineering Department, the University of Alabama in Huntsville, USA -
Abstract
Landscapes are dynamic, and the driving forces towards the societal change are related to the population growth and the lifestyle becoming increasingly urban and more mobile. The efforts to understand patterns and driving forces of urban growth or expansion have been analyzed in previous and recent studies. There is no doubt that the demand for urban land and the pressure for sustainable development will increase in any Metropolitan Area in the near future. In this study, land use change models were derived with and without variables related to urban sprawl and compared based on their statistical significance. The main goal of this paper is to propose a simplified logistic model, tested in Huntsville, AL that can highlight the probability of land use change by Traffic Analysis Zone (TAZ). Validation approach demonstrates the applications of measures of discrimination and calibration for a logistic regression model. This study can help to improve the understanding of patterns and determinants of urban growth and land expansion in Huntsville, AL. The model can be very useful to forecast the future probability of land use change and can be a substantial input in planning and decision-making process.
Number of downloads: 1156
Keywords:
land use change model;
logistic regression;
statistical validation;
probability of land use change;
traffic analysis zone;
References:
Antrop, M. 2005. Why landscapes of the past are important for the future, Landscape and urban planning, 70(1): 21-34.
Clay, M.J.; White, W.L.; Holley, P. 2011. Data Development for Implementing an Integrated Land Use and Transportation Forecasting Modeling in a Medium-Sized MPO. In Proceedings of Transportation Research Board 90th Annual Meeting.
COCH. 2015. 2015 State of the Economy-The Chamber of Commerce of Huntsville/Madison County. Available from internet: http://www.huntsvillealabamausa.com/.
DEM. 2015. Digital Elevation Model. AlabamaView. Accessed December 10, 2015. Available from internet: http://www.alabamaview.org/DEM.php.
ESRI. 2004. ESRI Data & Maps-ArcGIS 9 Media Kit. Redlands, CA: ESRI.
Ewing, R.; Hamidi, S. 2014. Measuring urban sprawl and validating sprawl measures. Available from internet: https://gis.cancer.gov/tools/urban-sprawl/sprawl-report-short.pdf .
Giancristofaro, R.A.; Salmaso, L. 2007. Model performance analysis and model validation in logistic regression, Statistica, 63(2): 375-396.
Han, J.; Hayashi, Y.; Cao, X.; Imura, H. 2009. Application of an integrated system dynamics and cellular automata model for urban growth assessment: A case study of Shanghai, China, Landscape and Urban Planning, 91(3): 133-141.
LED. 2015. Longitudinal Employer-Household Dynamics. Local Employment Dynamics. Accessed December 10, 2015. Available from internet: http://lehd.ces.census.gov/data/.
Luo, J.;Wei, Y.D. 2009. Modeling spatial variations of urban growth patterns in Chinese cities: the case of Nanjing, Landscape and Urban Planning, 91(2): 51-64.
MathWorks. 2015. MATLAB and Statistics Toolbox Release 2015a. The MathWorks, Inc.Massachusetts, United States.
Minitab. 2015. Minitab Statistical Software, Release 17. Available from internet: https://www.minitab.com/en-us/.
MRLC. 2016. National Land Cover Database. Multi-Resolution Land Characteristics (MRLC) Consortium. Available from internet: http://www.mrlc.gov/finddata.php.
Mukherjee, A.B.; Pate, N.; Krishna, A.P. 2014. Development of heterogeneity index for assessment of relationship between land use pattern and traffic congestion, International Journal for Traffic & Transport Engineering, 4(4): 397-414.
Rana, S.; Midi, H.; Sarkar, S.K. 2010. Validation and performance analysis of binary logistic regression model. In Proceedings of the WSEAS International Conference on Environmental, Medicine and Health Sciences, 51-55.
Rao, A.M.; Rao, K.R. 2012. Measuring urban traffic congestion-a review, International Journal for Traffic and Transport Engineering, 2(4): 286-305.
Schneeberger, N.; Bürgi, M.; Hersperger, A.M.; Ewald, K.C. 2007. Driving forces and rates of landscape change as a promising combination for landscape change research-An application on the northern fringe of the Swiss Alps, Land Use Policy, 24(2): 349-361.
USCB. 2010. Tiger/Line Shapefiles. United States Census Bureau. Available from internet: https://www.census.gov/geo/maps-data/data/tiger-line.html.
Zhao, L.; Peng, Z-R. 2010. An Integrated Bi-Level Model to Explore the Interaction between Land Use Allocation and Transportation, Transportation Research Record: Journal of the Transportation Research Board, 2176(2010): 14-25.
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