Abstract

Urban land-use allocation is a complicated problem due to the variety of land-uses, a large number of parcels, and different stakeholders with diverse and conflicting interests. Various approaches and techniques have been proposed for the optimization of urban land-use allocation. The outputs of these approaches are almost optimum plans that suggest a unique, appropriate land-use for every land unit. However, because of some restrictions, such stakeholder opposition to a specific land-use or the high cost of land-use change, it is not possible for planners to propose a desirable land-use for each parcel. As a result, planners have to identify other priorities of the land-uses. Thus, ranking land-uses for parcels along with optimal land-use allocation could be advantageous in urban land-use planning. In this paper, a parcel-level model is presented for ranking and allocating urban land-uses. The proposed model benefits from the capabilities of geographic information systems (GIS), fuzzy calculations, and Multi-Criteria Decision-Making (MCDM) methods (fuzzy TOPSIS), intends to improve the capabilities of existing urban land-use planning support systems. In this model, as a first step, using fuzzy calculations and spatial analysis capabilities of GIS, quantitative and qualitative evaluation criteria are estimated based on physical characteristics of the parcels and their neighborhoods. In the second step, through the fuzzy TOPSIS method, urban land-uses are ranked for each of the urban land units. In the third step, using the proposed land-use allocation process and genetic algorithm, the efficiency of the model is evaluated in urban land-use optimal allocation. The proposed model is tested on spatial data of region 7, district 1 of Tehran. The implementation results demonstrate that, in the study area, the land-use of 77.2% of the parcels have first priority. As such, the land-use of 22.8% of the parcels do not have first priority, and are prone to change.

Highlights

  • Urban land-use planning (ULUP), as the main core of urban planning, allocates various land-use types to the different land units and causes the urban activities to become more organized based on the requirements of urban society [1]

  • CV = ∑ PCVi i=1 where m indicates the number of land-use types, and PCVi is per capita violation of the land-use i, which is calculated by Equation (14)

  • Due to using previously-defined constraints, such as constraints related to the parcel area and access types, the land-use layouts are in accordance with reality, and each of the land-uses is allocated in their appropriate parcels and street types

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Summary

Introduction

Urban land-use planning (ULUP), as the main core of urban planning, allocates various land-use types to the different land units and causes the urban activities to become more organized based on the requirements of urban society [1]. The first approach is dealing with multi-criteria evaluation (MCE), and the second one involves applying spatial optimization methods to support spatial decision-making In the former approach, an overall suitability map for a land-use, or a special facility, is estimated by combining MCE and spatial analysis operations. According to the above-mentioned studies, many attempts have been made to present effective models for ULUP to achieve the optimal land-use plans Among these models, there are some models to rank different sites according to their suitability for a specific land-use or facility [13,28,29], but to the best of our knowledge, there is not much work on the urban land-use allocation model with the ability to rank all urban land-use types for each parcel.

Fuzzy Numbers and Arithmetic Operations
Compatibility
Dependency
Compactness
Suitability
Per Capita Demand
Ranking Urban Land-Uses for Each Parcel
Allocating Land-Uses to Urban Parcels
Constraints
Constraint related to urban land-uses per capita
Parameters Setting
Results of Urban Land-Use Allocation
Full Text
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