Identification and Location of a Transitional Zone between an Urban and a Rural Area Using Fuzzy Set Theory, CLC, and HRL Data

Author:

Biłozor AndrzejORCID,Czyża SzymonORCID,Bajerowski TomaszORCID

Abstract

Changes in land use, which accompany the development of towns, generate a transitional zone on the border between areas of urban and rural use, which—due to its complex (unspecified, fuzzy) land use—cannot be identified either as a rural or an urban area. In order to prevent the unplanned development, it should go according to plan, in line with the spatial order principles, making a coherent whole, taking into account all functional, socio-economic, cultural, as well as aesthetic factors and requirements. This paper describes studies and analyses of the fuzzy set theory applicability in studies of land use in areas around towns. The main aim of the study was to present the methodology, which employs fuzzy logic to identify and locate a transitional zone between rural and urban areas. This study dealt with the transitional zone at the junction of the urban and rural area and its parameters, which affect the type of land use. The attributes of the transitional zone were defined based on an analysis of current land use methods in areas under direct urbanisation pressure. The study was conducted in the city of Olsztyn (Poland) and on its outskirts, directly exposed to the impact of the developing city, with an area of 202.4 km2, within an 8-km radius of the city centre. The study determined the impact of individual forms of land use on the development of urban or rural use. The degree of each type of use—urban or rural—allowed for developing a fuzzy town and country model, identifying the urban investment border and its spatial dispersion, as well as identifying and locating the transitional zone between urban and rural areas. Moreover, land cover models based on the Corine land cover (CLC) data as well as high-resolution layers (HRL) impervious and canopy data were developed. The borders of urban investment determined on the basis of the fuzzy set theory assumptions, CLC, and HRL data were also identified and verified.

Publisher

MDPI AG

Subject

Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development

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