اولويت‌بندي و تعيين كاربري هاي مستعد تغيير در پلاك هاي شهري با استفاده از تصميم‌گيري چندمعياره فازي

Ranking and Determining Change-Prone Urban Land-Uses by Fuzzy Multi-Criteria Decision Analysis

بررسي تناسب كاربري­ هاي موجود و اولويت­­ بندي كاربري­ها­ براي پلاك­هاي شهري با توجه به مشخصات كالبدي آن­ها در ارتباط با ساير كاربري­هاي مجاور، منجر به مديريت بهينه در محيط شهري خواهد شد. ازاين‌رو، هدف اصلي اين تحقيق، ارائه مدلي براي ارزيابي و اولويت­بندي كاربري­ اراضي شهري بر اساس معيارهاي تعريف‌شده است. در اين مدل با توجه به تقريبي بودن نظر كارشناسان در تعيين مقادير معيارهاي ارزيابي شهري، براي برآورد كلي مقادير اين معيارها از محاسبات فازي استفاده گرديده است. اولويت­ بندي كاربري­ها براي هر يك از پلاك­هاي شهري نيز با توجه به فازي بودن مقادير معيارها، با استفاده از روش TOPSIS-فازي صورت گرفته است تا اولويت­هاي تخصيص كاربري براي هر يك از پلاك­ها تعيين گردد. درنهايت بر اساس اولويت­ بندي­هاي انجام‌گرفته كاربري­هاي مستعد تغيير مي­توانند شناسايي گردند. توسط مدل پيشنهادي، اولويت كاربري­هاي موجود در شهر با توجه به خصوصيات فيزيكي و كالبدي زمين براي هر كاربري مشخص شده و تصميم ­گيرنده در مراحل تصميم ­گيري براي تغيير كاربري­ها مي­تواند اولويت كاربري مناسب را براي قطعات مختلف ملاحظه نمايد. اين مدل با استفاده از داده­هاي مكاني ناحيه يك منطقه 7 تهران مورد پياده ­سازي و ارزيابي قرار گرفت. رتبه­بندي كاربري‍هاي شهري براي پلاك­هاي موجود در منطقه­ ي موردمطالعه نشان داد كه 77.2 درصد كاربري­هاي موجود داراي اولويت اول براي پلاك­هاي خود هستند. درنتيجه 22.8 درصد پلاك­هاي شهري در منطقه موردمطالعه، كاربري با اولويت اول را به خود اختصاص نداده ­اند و كاربري اين پلاك­ها، مي­توانند مستعد تغيير باشند. نتايج به‌دست‌آمده علاوه بر پلاك­هاي شهري با كاربري مستعد تغيير، اولويت­هاي تخصيص كاربري براي هر يك از اين پلاك­ها را نيز مشخص نموده است.

Urban land-use allocation is a complicated problem due to diversity in land-uses, a large number of parcels and different stakeholders with various and conflicting interests. A variety of studies presents many criteria in this regard. Different methods have been proposed for the optimal allocation of urban land-uses. The outputs of these methods are near optimum layouts that offer a suitable land-use for every land unit. However, because of some limitations such as disagreement of stockholders by a specific land-use or the high cost of land-use conversion to a certain land-use, it is not possible for planners to propose desirable land-uses for all parcels and as a result, have to use next priorities of the land-uses. Thus, prioritizing land-uses for parcels along with optimal land-use allocation could be essential in urban land-uses planning. Furthermore, due to the approximate nature of land-use evaluation criteria, using fuzzy calculations can be more compatible with the urban land-uses allocation models. Therefore, in this study, a parcel-level urban land-use prioritization model based on fuzzy calculation is presented. In the proposed model, at first evaluation criteria are estimated by fuzzy calculations for each parcel. Urban land-use evaluation criteria include neighborhood effects (i.e. compatibility, dependency, and proximity), physical suitability, and per capita. Compatibility and dependency factors depend on the different service level of each land-use. Each land-use is defined in three service level of local, district and regional and different radius of effect is considered according to these service levels. Furthermore, suitability criterion is calculated according to the characteristics and physical properties of land units for each land-use as a fuzzy number. Per-capita criterion is calculated as per capita violation in a fuzzy manner and is considered in land-use prioritization. After fuzzy calculations of criteria, the importance of each criterion must be determined. To determine the importance of each criterion in proposed model, the weight of criteria is estimated by subjective and objective weighting approaches. Expert knowledge is used for estimating subjective weights, and Shannon's entropy method applied for determining objective weights. The Fuzzy TOPSIS[1] technique is used to prioritize land-uses for each parcel. In fuzzy TOPSIS, after normalization and applying weights to each criterion, positive and negative ideal points are calculated based on the best and worst values of criteria. Finally, with calculating the distance of each land-use as alternatives from worst and best ideal points, land-uses will be ranked for each parcel. This procedure is repeated for all parcels in the study area, and therefore, all land-uses are ranked for all parcels. The proposed model was implemented on spatial data of region 7, district 1 of Tehran. Ranking urban land-uses for parcels in the study area showed that 77.2 percent of current land-uses have the first priority for their own parcels. It came that 22.8 percent of parcels in the study area were not allocated the first priority of land-use, and the land-use of these parcels can be susceptible to change. In the land-uses of the study area, in terms of susceptibility to changes, residential units have the best situation, and industrial units have worst situation. As a future research, based on proposed model, different scenarios can be proposed for optimal allocation of urban land-uses by taking into account stockholders' preferences. For modeling the stakeholders' preferences, approaches such as multi-agent systems and game theory can be used.