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Research Advancement in Characterizing Land Functions of Brownfield

As a major space carrier, the re-structure of urban space is an inevitable process of social-economic development and renovation of urban functions. The brownfield redevelopment is the core conditions of restructure of industrial cities. In the process of brownfield redevelopment, the complication of land functions and its elaborate assessment is the key scientific foundation for high-efficiency planning of land reuse and realizing a sustainable restructure of regional social-economic environment. Traditional standard for land-use classification was based on the idea from above to below, stressed on unitary expression and suitable to the macro-and middle scale planning. For the micro-scale planning of brownfield movement, the more important is the environmental-economic coupled value of land, complication of land functional types and high accuracy management accounting so as to better reflect the land re-use value and serve the policy making for the sustainable development of brownfield.

Dr XUE Bing in the research group of Industrial Ecology, IAE and his team, Cooperated with Prof Bruce MITCHELL from Waterloo University, UK took Tiexi Old Industrial Area in Shenyang as core target, used 300 300m grid based on satellite remote sensing image, investigated 5206 buildings, theoretically developed 8 land use types and constructed a new coding system and then took 4 micro- scale cases including 2 residential areas and 2 industrial culture squares as object for the case study. The results show that the extended classification better indicates the functions of brownfield in reconstructed area, increases accuracy of land use classification, provides scientific base for the environment-economic integrated characterizing and accurate calculation in land re-use planning.

The results were published in Journal of Urban Planning and Development entitled as Extended Land-Use Coding System and Its Application in Urban Brownfield Redevelopment: Case Study of Tiexi District in Shenyang, China. The work was supported by NNSFC (41101126, 41471116) and National Science and Technology Support Program (2011BAJ06B01).



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