Prediction of Land-Use Change along the Urban Rail Transit Based on Markov Model

Article Preview

Abstract:

Urban rail transit will have a direct impact on the land use types and structure. This paper mainly focused on Wuhan rail transit line 1, Using 2002、2010 Wuhan local remote sensing image, based on RS and GIS techniques, the transfer matrix of land use around the orbit is achieved by analyzing the land use data in two different periods before and after the urban rail system run, and then based on the markov model to quantitatively forecast the change of land use types between 2013 and 2018. The results showed that, Wuhan rail transit increased the strength of the development and the degree of land use along it, accelerated the mutual transformation between the land use types, changed the land use structure and land cover types along it, in which the construction lands and roads were mainly come from cultivated lands and green lands.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

894-898

Citation:

Online since:

May 2014

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] Pielke R A. Land use and climate change. SCIENCE, 2005, 310(5754): 1625-1626.

DOI: 10.1126/science.1120529

Google Scholar

[2] Schaldach R, Alcamo J, Koch J, Kolking C, Lapola D M, Schungel J, Priess J A. An integrated approach to modelling land-use change on continental and global scales. Environmental Modelling & Software, 2011, 26: 1041-1051.

DOI: 10.1016/j.envsoft.2011.02.013

Google Scholar

[3] Li Yan et al. Research on Worldwide Land Use and Land Cover Change[J]. Anhui Agricultural Science Bulletin, 2012, (7).

Google Scholar

[4] ZHOU Xian fang. Research on the Temporal and Spatial Dynamic Simulation of Urban Land Use in Karst Area Based on CLUE-S Model[J]. Journal of Anhui Agricultural Sciences, 2011, (34).

Google Scholar

[5] Thielen D R, San Jos, J J. Assessment of land use changes on woody cover and landscape fragmentation in the Orinoco savannas using fractal distributions. Ecological Indicators, 2008, 8(3): 224-238.

DOI: 10.1016/j.ecolind.2007.01.009

Google Scholar

[6] Kamusoko C, Aniya M. Hybrid classification of Landsat data and GIS for land use/cover change analysis of the Bindura district, Zimbabwe. International Journal of Remote Sensing, 2009, 30(1): 97-115.

DOI: 10.1080/01431160802244268

Google Scholar

[7] KASPER. K, FALLOWA, VELDK, AMPVA, et al. A method and application of multi2scale validation in spatial land use models[J]. Agric Ecosyst Environ, 2001, 85: 223-238.

Google Scholar

[8] Wu CR, Du XC, et al. Research of land value-added mechanism along the urban rail transit [J]. Road Traffic & Safety, 2008, 8(8).

Google Scholar

[9] Li L, Tang ZX, Zhang QJ. Research of coordinated development strategy between the urban rail transit and land use along[J]. Heilongjiang traffic science and technology, 2011(6): 289-290.

Google Scholar

[10] Gao J. Integration and application of urban rail transit and land use. Study of urban rail transit, 2008,(8): 17-19.

Google Scholar

[11] Wu Q, Li HQ, Wang RS, et al. Monitoring and predicting land use change in Beijing using remote sensing and GIS. Landscape and Urban Planning, 2006, 78: 322-333.

DOI: 10.1016/j.landurbplan.2005.10.002

Google Scholar

[12] Lin FC, Zeng ZC. Influence of Shanghai Rail Transit Line 1 on city spatial diffusion[J]. Stydy of urban rail transit, 2008, 9(7): 1537-1543.

Google Scholar

[13] Zhang HL, Jiang JJ, Xie XP, et al. Study on the change of landscape dynamics of Weihe basin based on GIS and Markov model[J]. Resources and environment in arid region, 2005, 19(7): 119-124.

Google Scholar

[14] Hou XY, Chang B, Yu XF. Research on land use change in Hexi Corridor Based on CA - Markov model[J]. Journal of agricultural engineering, 2004, 20(5): 286-291.

Google Scholar

[15] Zheng CC, Wang XZ, Zhu L, Mou KL. Analysis of spatial and temporal changes of county land use based on RS and GIS[J]. Anhui Agricultural Sciences, 2008, (17).

Google Scholar

[16] Xiao X, Huang HT, Wu HJ, Pu LJ, Zhu M, Xu XS. Prediction of land use change in Suzhou based on Markov model. Jiangxi Journal of Agricultural Sciences, 2008, 20(11): 134-136.

Google Scholar