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Paper Information

Journal:   REMOTE SENSING & GIS   WINTER 2010 , Volume 1 , Number 4; Page(s) 21 To 40.
 
Paper: 

DEVELOPING A GIS-BASED MODEL FOR REGIONAL LAND USE PLANNING (CASE STUDY AREA: BORKHAR AND MAYMEH TOWNSHIPS)

 
 
Author(s):  KARIMI M.*, MESGARI M.S., SHARIFI M.A.
 
* NO. 1346, VALI ASR ST., FACULTY OF GEODESY AND GEOMATICS, K.N. TOOSI UNIV. OF TECHNOLOGY, TEHRAN, IRAN
 
Abstract: 

Major development activities in a region usually take place on the basis of a regional land use plan. The dynamic interactions of socio-economic and environmental factors in both space and time aspects are main reasons for complexity of regional land use planning. The main goal of this research is to develop a new GIS-based model for the allocation of various land use types at the regional level. The model is based on the comparison of land suitability (calculated in large scale) and land demand (evaluated in small scale). In different parts of the model, computational intelligece, multi-criteria decision making methods, regression analysis and GIS functions are used. Important driving factors in land suitability model are ecological capability, neighborhood effect, accessibility and zoning regulations. In this research, proper factor maps for these driving factors were generated and integrated using multiplicative weighted average. To generate ecological capability maps, the Makhdoum!s ecological capability model, which is widely applied in Iran, was implemented using a Fuzzy Inference System (FIS). The fuzzy maps of soil texture, soil depth, slope, climate, elevation, erosion and geology were considered as inputs to the FIS. Neighborhood effect maps were produced based on cellular automat concept. The neighborhood effect for each cell was estimated based on the agglomerated spatial externalities of its neighboring cells, located in its influence region. The spatial externalities of land use types over distance were defined using land values, spatial metrics and expert knowledge. Accessibility was calculated using weighted average of the accessibility to infrastructures and major activity centers. Accessibility to relevant infrastructures (road networks, electricity transmission lines, gas pipelines and water canals) was modeled on the basis of Euclidean distance.
Accessibility to major activity centers (population and industry centers) was determined using the gravity model. To estimate the land demands in the years of 2016 and 2021, the land use changes occured during the past two decades were used, in a stocastic regression model. Beside land suitability and land demand, land use conversion rules and policies are also needed to be considered in land use allocation process. Finally, in an inventive procedure, the demanded land use types were allocated, shut that the arrangement of land use types in the entire area was optimised. The developed model was implemented using the data of Borkhar & Maymeh townships, in Esfahan province, Iran. Considering 2004 as the base year, the result of the model is the allocation of urban residential, rural residential, industry and agriculture land use types for the years of 2016 and 2021, based on both agglomerated policies, as well as non-agglomerated ones.The developed methodology can be used by planners and decision makers when studying and proposing future land use plans. In this research, two conditions were assumed to limit the scope of the work. First, only the increases of land demands were modeled. Second, only the general land use types were considered. As the continuation of this research, both the decreases in the land demand and and the more detailed land use types can be considered.

 
Keyword(s): LAND SUITABILITY, LAND DEMAND, LAND USE ALLOCATION, PLANNING, COMPUTATIONAL INTELLIGECE METHODS
 
References: 
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