A GEP-based spatial decision support system for multisite land use allocation

Eldrandaly, Khalid A.

doi:10.1016/j.asoc.2009.07.014

Cited by 42 publications

(23 citation statements)

References 11 publications

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“…Land conversion in these plans occurs only to improve compactness. Compactness is one of the most important objectives considered in most related studies [17,26,27,[31][32][33][34][35][36][37], but landslide risk also needs to be reduced to some extent, because land use conversion is very costly. We have obtained 100 non-dominated plans of various weight combinations, but the range of plans that can actually be selected is narrow.…”

Section: Discussionmentioning

confidence: 99%

Multi-Objective Land-Use Allocation Considering Landslide Risk under Climate Change: Case Study in Pyeongchang-gun, Korea

et al. 2017

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Abstract:Extreme landslides triggered by rainfall in hilly regions frequently lead to serious damage, including casualties and property loss. The frequency of landslide occurrences may increase under climate change, due to the increasing variability of precipitation. Developing urban areas outside landslide risk zones is the most effective method of reducing or preventing damage; however, planning in real life is a complex and nonlinear problem. For such multi-objective problems, genetic algorithms may be the most appropriate optimization tools. Therefore, in this study, we suggest a comprehensive land-use allocation plan using the Non-dominated Sorting Genetic Algorithm II to overcome multi-objective problems, including the minimization of landslide risk, minimization of change, and maximization of compactness. Our study area is Pyeongchang-gun, the host city of the 2018 Winter Olympics in Korea, where high development pressure has resulted in urban sprawl into the hazard zone where a large-scale landslide occurred in 2006. We obtain 100 Pareto plans that are better than the actual land use data for at least one objective, with five plans that explain the trade-offs between meeting the first and second objectives. The results can be used by decision makers for better urban planning and for climate change-related spatial adaptation.

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Section: Discussionmentioning

confidence: 99%

Multi-Objective Land-Use Allocation Considering Landslide Risk under Climate Change: Case Study in Pyeongchang-gun, Korea

et al. 2017

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“…The criteria considered for optimization were related to some spatial patterns and non-pattern objectives. The knowledge-based Pareto algorithm showed better performances compared to the classical algorithm (Duh and Brown 2007), Eldrandaly (2010) proposed the use of Gene Expression Programming for solving the Multisite Land Use Allocation Problem. He considered a fictive case study to illustrate his proposed approach.…”

Section: Studies Using Other Metaheuristicsmentioning

confidence: 99%

“…Two criteria were taken into account, namely the minimization of the development costs and the maximization of the compactness of the land uses. He considered also the coverage of three land use types as predefined, i.e., as constraints (Eldrandaly 2010).…”

Section: Studies Using Other Metaheuristicsmentioning

confidence: 99%

Metaheuristics for agricultural land use optimization. A review

Memmah

Lescourret

Yao

et al. 2015

Agron. Sustain. Dev.

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Agricultural landscapes presently cover about 46 % of earth terrestrial surface. This cultivated area is decreasing, whereas the global food demand is projected to increase up to 70 % in 2050. The intensification of agriculture is not a solution to this food issue because intensive agriculture has often resulted in pollution and loss of biodiversity. On the other hand, mechanistic models with optimization algorithms can be used to design alternative land uses for sustainable agriculture. Here, we present a review of metaheuristics for land use optimization reported in 50 articles including 38 case studies carried out in 16 countries. Our main conclusions are: 1) the success of metaheuristics is problem-dependent. In general, metaheuristics enable search to escape from local optima and find a good global approximation solution.2) The choice of a given metaheuristic for solving a given problem seems to be driven by its historical use in a research team and by its popularity outside the metaheuristics research community, rather than by the characteristics of the problems to be solved and by the latest results from the metaheuristics research community. 3) Stakeholders of land use are increasingly involved at different levels of the land use optimization procedure and multi-actors decision-making methods are necessary to find trade-offs between their competing interests. 4) A future challenge is the use of parallelization techniques along with the hybridization of different metaheuristics or of metaheuristics with other optimization methods.

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“…Thus in recent years the importance has been shown of these techniques and tools, and of the interdisciplinary and multidimensional focuses found at the heart of the development of SDSS, especially in environmental assessment or conservation and territorial planning (e.g. [62][63][64]). …”

Section: Spatial Decision Support Systems For Planning and Integratedmentioning

confidence: 99%

Territorial Planning for Coastal Zones in Chile: The Need for Geographical-Environmental and Natural Risk Indicators for Spatial Decision Support Systems

Peña‒Cortés¹,

Rozas-Vásquez²,

Rebolledo³

et al. 2013

IJG

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Coastal zones are very dynamic and fragile environments, constituting a landscape ever more heterogeneous, fragmented and with increasing levels of complexity due to the changing relationship between man and nature. Integrated coastal zone management therefore requires detailed knowledge of the system and its components, based-to a large extent-on technical and scientific information. However, the information generated must be in line with the political requirements necessary for decision-making and planning. Thus the use of indicators to give a simplified view of the many components of the territory, and at the same time to provide important information about patterns or trends, becomes a tool of the utmost importance. These indicators can be understood as measurable characteristics of the environment, which facilitate comprehension of the processes occurring at different scales and serve as a reference to inform the population and support decision-making. The aim of the present note is to demonstrate briefly the need to develop geographical-environmental and natural risk indicators to facilitate comprehension of the dynamic of spatial and temporal landscape patterns, particularly in coastal environments. This approach offers an historical summary of the natural, socio-economic and political processes which currently make up the territory, and which without doubt will continue to influence it in the future. At the same time, it is proposed that information should be integrated on the basis of this framework with a view to generating spatial decision support systems in a context of planning and integrated management of the coastal zones of Chile.

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A GEP-based spatial decision support system for multisite land use allocation

Cited by 42 publications

References 11 publications

Multi-Objective Land-Use Allocation Considering Landslide Risk under Climate Change: Case Study in Pyeongchang-gun, Korea

Multi-Objective Land-Use Allocation Considering Landslide Risk under Climate Change: Case Study in Pyeongchang-gun, Korea

Metaheuristics for agricultural land use optimization. A review

Territorial Planning for Coastal Zones in Chile: The Need for Geographical-Environmental and Natural Risk Indicators for Spatial Decision Support Systems

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