In the process of agricultural land consolidation, the land parcels are optimally redesigned and rearranged in such a way that the dimensions of the resulting parcels are proportional to agricultural criteria such as irrigation discharge, soil texture, and cropping pattern. Besides these criteria, spatial factors like slope, road accessibility, volume of earthwork, and geometrical factors such as size and shape of parcels are also included in the design process of agricultural land partitioning. In this study, a land partitioning model was proposed using a multi‐objective artificial bee colony algorithm (MOABC‐LP) taking into consideration the mentioned factors. Initially, a feasible dimension range of parcels in a block was calculated based on irrigation efficiency. Two partitioning layouts were defined according to the topography and geometry of blocks. The proposed method was applied to a real study area and the results suggest that the land partitioning plan obtained by the MOABC‐LP model, in comparison with a designer's plan, not only makes the shape and size of parcels more compatible with the topographical and agricultural conditions of each block, but also reduces their cut‐and‐fill ratio.
In conventional reallocation, farmers' preferences are used to determine the location of their new parcels in predetermined blocks. The most common conflict that can arise during this process is that demand may be high for some blocks. The manner of resolving such disputes, which deal directly with landowners' rights, can affect the success or failure of land consolidation projects. In this study, a novel model for land reallocation is proposed which is based on the principle that the initial situation of the landowner's parcels before land consolidation will be comparable with the new situation that includes all of his/her rights. For this, a spatial similarity‐based approach was proposed, taking into account geometric, ownership, physical, and locational criteria. Then, the agricultural land reallocation model (LR‐MOPSO) was developed using the multi‐objective particle swarm algorithm. Three objectives were defined: (1) simultaneous consideration of farmers' priority and spatial similarity criteria; (2) pooling of farmers' fragmented parcels; and (3) optimal placement of parcels within the block. The LR‐MOPSO model was applied to an Iranian case study and results were compared with a conventional approach. With this model decision‐makers in land consolidation projects will be able to redistribute parcels in a more transparent way, while dealing with landowners' rights.
One of the most complex issues of urban planning is informal settlement which is a multidimensional phenomenon with multiple indices. The spatial growth of informal settlements is affected by complex internal and external drivers. Combined use of GIS and agent based model as an approach of this research might be an adequate strategy for modeling these process. The purpose of this study is modeling informal settlement growth of the phenomenon on a cadastral scale in vector GIS, using land parcel agents and decision maker agents. Two scenarios were considered for defining the neighborhood effects and results of modeling were investigated and were evaluated for these scenarios. In this model decision maker agents as moving agents include people who are working in the downtown core and those who are working in industrial suburb areas.They search the surroundings to find suitable land for housing. Land parcel agents as immobilizing agents calculate their total suitability using spatial factor based on the preferences of decision maker agents. The proposed model was implemented on one of the informal settlements districts in the city of Kashan, Isfahan province, Iran. Evaluating results with actual data indicated that the proposed model was able to predict the informal settlements growth with 86% overall accuracy. This study indicated that although the developed neighboring numbers are important to develop a land parcel on cadastral scale, but developed neighborhood areas have a greater role than their numbers. The findings of this research also indicate that developed parcels located within the radius of 120 meters of a target land parcel have different effects on the development of target parcel proportional to their distances.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.