Soil quality and landscape metrics as driving factors in a multi-criteria GIS procedure for peri-urban land use planning

被引:34
作者
Borgogno-Mondino, E. [1 ]
Fabietti, G. [2 ]
Ajmone-Marsan, F. [1 ]
机构
[1] Univ Turin, DISAFA, I-10095 Turin, Italy
[2] ARPA Piemonte, I-10135 Turin, Italy
关键词
GIS; Multi Criteria Decision Analysis; Soil properties; Spatial indices; Urban landscape; Urban planning; URBAN; CONTAMINATION; FRAMEWORK; ELEMENTS; METALS;
D O I
10.1016/j.ufug.2015.07.004
中图分类号
Q94 [植物学];
学科分类号
071001 ;
摘要
Highly populated pen-urban areas are critical for urban sprawl, soil consumption and degradation, and, in general, loss of ecosystem services. In these areas, urban planning is usually based on a compromise among social, economic, political needs and geographic factors. Technicians cannot obviously intervene in political discussions, nor intercept social requirements; nevertheless, once a need has been recognized and a target identified, they can sustain politicians in their decisions concerning the way the new urban policy can be managed. Various territorial descriptors have been used to support planner's choices while programming urban expansion. In this context, ecosystem services potentially affected by urbanization represent an important unsolved issue, most probably for the general lack of reliable datasets for urban and pen-urban areas and for the scarce integration of the involved disciplines. In this paper a GIS-MCDA (Multi-Criteria Decision Analysis) approach is presented, aimed at generating synthetic maps useful for urban planners and authorities to make their decisions inclusive of territorial resources and environmental factors with special care about soil quality. The method was applied to a case study concerning the identification of the optimal location for a new leisure activity area in the pen-urban belt of the city of Torino (Italy). Landscape metrics, demographic data and soil chemical/physical properties - including contamination - obtained from extremely diverse sources, were jointly analysed. Some specific indices aggregating information were proposed and mapped using some advanced raster tools available in GIS. (C) 2015 Elsevier GmbH. All rights reserved.
引用
收藏
页码:743 / 750
页数:8
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