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العنوان
Adopting Landuse Optimization Models to Achieve Spatial Sustainability /
المؤلف
Abdelghany, Sarah Emadeldeen Mikaeil.
هيئة الاعداد
باحث / ساره عماد الدين توفيق مكيائيل عبدالغني
مشرف / هاني محمد عياد
hany.m.ayad@gmail.com
مشرف / انجي احمد الشريف
ingi.elcherif@star.alx.edu.eg
مناقش / دينا محمد علي سعدالله
dina_saadallah@hotmail.com
مناقش / مهاب عبدالمنعم عبدالعزيز رفاعي
الموضوع
Architecture.
تاريخ النشر
2024.
عدد الصفحات
195 p. :
اللغة
الإنجليزية
الدرجة
ماجستير
التخصص
الهندسة المعمارية
تاريخ الإجازة
1/1/2024
مكان الإجازة
جامعة الاسكندريه - كلية الهندسة - الهندسة المعمارية
الفهرس
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Abstract

As a result of the urban sprawl phenomenon, the world’s land-use patterns have been changing rapidly resulting in conflicted and competitive urban land-uses. Consequently, a wide range of inefficient land-use patterns are currently prevailing in urban settings. Among such patterns are low-density development, leapfrog fragmentation, edge development excessing inner city redevelopment, and single land-use patches. The negative implications of these patterns necessitate the enhancement of efficiency of land-use planning processes in order to support better sustainable development. However, the variety of land-use categories and the numerous constraints introduced in the land-use planning, wher bdecision-makersakers or stakeholders render land-use planning as a complex multi-objective optimization problem.This research investigates the use of multi-objective optimization models for land-use planning, in addition to an assessment of the potentials and challenges of their application in the context of Egypt. Considering the non-linear characteristics of spatial planning objectives, a meta-heuristic method; “Non-dominated Sorting Genetic Algorithm“ (NSGA-II) is applied to search for Pareto optimal land-use allocation alternatives. The algorithm addresses a variety of constraints and objectives besides providing a decision support tool to the land-use planning process. The research focuses on spatial sustainability as the fourth dimension of sustainability introduced by the New Urban Agenda (NUA). In this regard, the objectives of maximizing accessibility, urban compactness, and land-use suitability are considered. The research proposes an adaptation of the CoMOLA (Constrained Multi-objective Optimization of Land-use Allocation) model for improving the efficiency of land-use planning processes. Whereas minimum and maximum allowed total areas of land-use classes and transition rules defining the possible land use transformations are set as constraints. The objective functions are developed and implemented into a class of spatial planning problems in two case studies in Alexandria, Egypt, representing brownfield planning application and greenfield planning application. Variations of spatial unit numbers, population sizes, constraint handling methods and the importance of allocation objectives are investigated to pursue near-optimal land-use allocation scenarios and compared to the current state of land-use distribution. Additionally, the proposed model is utilized to evaluate development plans proposals. The results show that the proposed approach and modified CoMOLA tool exhibit good potential to support interactive land-use planning processes by searching over multiple plans for optimal sets of non-dominated plans according to preferred objectives. In this regard, the model resulted in 15 and 8 pareto solutions for each case study respectively. For the brownfield casestudy, the accessibility values improved more than the status quo within the range of 76.1% and 98.9%, while the urban compactness values persisted at an optimum value of 0.58. As for the greenfield casestudy, the pareto solutions were compared to a traditionally developed land-use development plan, where they depict superiority at urban accessibility with 100.27% and urban compactness with 10.017% The optimized results can provide the scientific basis for defining proper interventions for improving sustainability measures and spatial optimization of land-uses at Alexandrian neighborhood scale.