Comparison of designed different land reallocation models in land consolidation: A case study in Konya/Turkey

Uyan, Mevlüt; Çay, Tayfun; İnceyol, Yaşar; Haklı, Hüseyin

doi:10.1016/j.compag.2014.11.022

Cited by 50 publications

(22 citation statements)

References 20 publications

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“…A GA-based model was compared with an SDSS-based model in a case study by Uyan, Cay, Inceyol, and Hakli (2015). The GA-based model was more successful than the SDSS-based model with respect to the number of parcels, the average parcel size, and the number of parcels per landowner.…”

Section: Intelligent Land-redistribution Methodsmentioning

confidence: 99%

“…Hence, it is necessary to determine an objective function that evaluates both criteria under equal circumstances to accurately perform the optimization technique. In their study, Inceyol 2014 based the objective function on these two criteria (Uyan, Cay, Inceyol, & Hakli, 2015).…”

Section: The Genetic Algorithmmentioning

confidence: 99%

“…Due to population growth, agriculture has become one of the most important sectors for people in recent years (Ertunc, Cay, & Hakli, ). Sustainable and successful land use/management in agriculture is increasingly needed day by day because of socio‐economic and physiographic conditions, problems of climate change, adaptation, and hunger (Uyan, Cay, Inceyol, & Hakli, ). To overcome these problems and to provide sustainable agricultural management, many studies have been proposed, such as Fang et al (), Gao, Xu, and Liang (), and Xu, Liang, and Gao ().…”

Section: Introductionmentioning

confidence: 99%

“…Inceyol () applied a GA to the land‐redistribution problem by considering landowners' preferences and the overflow and residual areas, and then compared the proposed method with the redistribution plan developed by experts for a real study area. A GA‐based model was compared with an SDSS‐based model in a case study by Uyan, Cay, Inceyol, and Hakli (). The GA‐based model was more successful than the SDSS‐based model with respect to the number of parcels, the average parcel size, and the number of parcels per landowner.…”

Section: Introductionmentioning

confidence: 99%

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Genetic algorithm supported by expert system to solve land redistribution problem

2018

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Land redistribution, a real‐world optimization problem, involves the distribution of land parcels in predetermined blocks based on the landowners' preferences. This process, measured in weeks or months, is usually performed manually by a technician with the support of computer software. Although various techniques have been developed in recent years to solve this complex problem, they all require improvement. This study aimed to develop a new technique and produce applicable redistribution plans using a genetic algorithm (GA) in combination with an expert system. Blocks of cadastral parcels were determined by a GA using a new objective function to consider the overflow and residual areas as well as the landowners' preferences. The expert system was employed to close (reduce to zero) the overflow or residual areas occurring after the GA distribution. To investigate the performance of the proposed method, the system was used on a real study area and the results were compared against those obtained for the same cadastral situation undertaken by a technician using a similar method from published literature. The experimental results showed that the method proposed in this study performed better than the other methods because it provided a successful and applicable redistribution plan for the study area in a much shorter time.

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Section: Intelligent Land-redistribution Methodsmentioning

confidence: 99%

Section: The Genetic Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Genetic algorithm supported by expert system to solve land redistribution problem

2018

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“…Geostatistics represents one of the most powerful procedures for producing contour maps for regionalised variables (Beliaeff & Cochard, 1995;Xu et al, 2005) and, thereby, indicates an appropriate method of prediction. Geostatistical results, using kriging techniques, are efficient when data for variables are distributed normally (Wu et al, 2014, Uyan et al, 2015. Interpolation is the process of estimating the value of parameters at unsampled points from a surrounding set of measurements (Burrough & McDonnell, 1998).…”

Section: Geostatistics and Spatial Interpolationmentioning

confidence: 99%

Arsenic-Safe Aquifers in Coastal Bangladesh: An Investigation With Ordinary Kriging Estimation

Hassan

Ahamed

2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Spatial point pattern is one of the most suitable methods for analysing groundwater arsenic concentrations. Groundwater arsenic poisoning in Bangladesh has been one of the biggest environmental health disasters in recent times. About 85 million people are exposed to arsenic more than 50μg/L in drinking water. The paper seeks to identify the existing suitable aquifers for arsenic-safe drinking water along with "spatial arsenic discontinuity" using GIS-based spatial geostatistical analysis in a small study site (12.69 km 2 ) in the coastal belt of southwest Bangladesh (Dhopakhali union of Bagerhat district). The relevant spatial data were collected with Geographical Positioning Systems (GPS), arsenic data with field testing kits, tubewell attributes with observation and questionnaire survey. Geostatistics with kriging methods can design water quality monitoring in different aquifers with hydrochemical evaluation by spatial mapping. The paper presents the interpolation of the regional estimates of arsenic data for spatial discontinuity mapping with Ordinary Kriging (OK) method that overcomes the areal bias problem for administrative boundary. This paper also demonstrates the suitability of isopleth maps that is easier to read than choropleth maps. The OK method investigated that around 80 percent of the study site are contaminated following the Bangladesh Drinking Water Standards (BDWS) of 50μg/L. The study identified a very few scattered "pockets" of arsenic-safe zone at the shallow aquifer.

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Comparing the performances of six nature-inspired algorithms on a real-world discrete optimization problem

2022

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Comparison of designed different land reallocation models in land consolidation: A case study in Konya/Turkey

Cited by 50 publications

References 20 publications

Genetic algorithm supported by expert system to solve land redistribution problem

Genetic algorithm supported by expert system to solve land redistribution problem

Arsenic-Safe Aquifers in Coastal Bangladesh: An Investigation With Ordinary Kriging Estimation

Comparing the performances of six nature-inspired algorithms on a real-world discrete optimization problem

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