Applying the Fuzzy AHP and Multi-Objective Land Allocation method for Land use planning Case study: Sari city, Iran

Interaction between various land uses is necessary for sustaniable development. This paper presents the fuzzy-AHP and Multi-Objective Land Allocation (MOLA) methods in a Geospatial Information-based System (GIS) to allocate suitable lands for both agriculture and industry towns area. Sari city in North of Iran was considered as the case study. A Landsat8 image, acquired at 2014 with the pixel size of 30 meter was used. This image was classified based on Anderson level 1 with Maximum Likelihood classification. Factors concidered to allocate optimal areas for industry townss were included: 1) Elevation, 2) Slope, 3) Distance from main roads, 4) Distance from the exterior urban boundary, 5) Distance from not-built areas, 6) Distance from forests, 7) Distance from rivers, 8) Distance from agriculture areas, 9) Distance from the airport, and finally 10) Distance from power stations. Moreover, factors to allocate optimal areas for agriculture area were: 1) Elevation, 2) Slope, 3) Distance from main roads, 4) Distance from rivers, 5) Distance from the urban, and 6) Distance from Forests. Comments of 30 numbers of experts in the field of land use were requested for weighting the proposed fuzzy-AHP method. After providing weights of the factors, the fuzzy- AHP method was developded by the Weighted Overlay Analysis to allocate suitable areas. As a result, the most important factors with the highest weights achieved by the proposed fuzzy-AHP method for industry towns areas were: elevation parameters and proximity to not-built areas, and also for agriculture areas were: proximity to water resources and elevation factors. Allocated areas by the proposed fuzzy-AHP method were compaired with outcomes of the proposed MOLA and the common areas between these methods were concidered as the suitable areas for either agriculture areas or industrial towns.

کلیدواژه ها:

Fuzzy-AHP ، Multi-objective Land Allocation ، Geospatial Information System ، Maximum Likelihood Classification ، Land use