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Demetriou, D., See, L. 
ORCID: https://orcid.org/0000-0002-2665-7065, & Stillwell, J.
(2014).
Integrating GIS and genetic algorithms for automating land partitioning.
DOI:10.1117/12.2064520.
In: Proceedings of SPIE: Second International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2014), 7-10 April 2014.
Abstract
Land consolidation is considered to be the most effective land management planning approach for controlling land fragmentation and hence improving agricultural efficiency. Land partitioning is a basic process of land consolidation that involves the subdivision of land into smaller sub-spaces subject to a number of constraints. This paper explains the development of a module called LandParcelS (Land Parcelling System) that integrates geographical information systems and a genetic algorithm to automate the land partitioning process by designing and optimising land parcels in terms of their shape, size and value. This new module has been applied to two land blocks that are part of a larger case study area in Cyprus. Partitioning is carried out by guiding a Thiessen polygon process within ArcGIS and it is treated as a multiobjective problem. The results suggest that a step forward has been made in solving this complex spatial problem, although further research is needed to improve the algorithm. The contribution of this research extends land partitioning and space partitioning in general, since these approaches may have relevance to other spatial processes that involve single or multi-objective problems that could be solved in the future by spatial evolutionary algorithms.
| Item Type: | Conference or Workshop Item (UNSPECIFIED) |
|---|---|
| Research Programs: | Ecosystems Services and Management (ESM) |
| Bibliographic Reference: | In:; Proceedings of SPIE: Second International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2014); 7-10 April 2014, Paphos, Cyprus Vol.9929:08 |
| Depositing User: | IIASA Import |
| Date Deposited: | 15 Jan 2016 08:52 |
| Last Modified: | 27 Aug 2021 17:24 |
| URI: | https://pure.iiasa.ac.at/11237 |
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