Demetris Demetriou

A new methodology for measuring land fragmentation

The presence of land fragmentation can indicate that an existing land tenure structure is problematic. It can be a major problem in many regions because it restricts rational agricultural development and reduces the opportunities for sustainable rural development although in some cases, it can prove beneficial and desirable for social and environmental reasons. Whilst policies to counter land fragmentation require reliable measurement of the situation, current fragmentation indices have significant weaknesses. In particular, they ignore critical spatial variables such as the shape of parcels as well as non-spatial variables such as ownership type and the existence or absence of road access for each land parcel. Furthermore, there is no flexibility for users to select the variables that they think appropriate for inclusion in the fragmentation index, and no variable weighting mechanism is available. The aim of this paper is to introduce a new ‘global land fragmentation index’ that combines a multi-attribute decision-making method with a geographic information system. When applied to a case study area in Cyprus, the new index outperforms the existing indices in terms of reliability as it is comprehensive, flexible, problem specific and knowledge-based. The methodology can be easily applied to assess the quality of any existing system for which evaluation criteria can be defined with values ranging from the worst to best conditions.

A Parcel Shape Index for Use in Land Consolidation Planning

Area shape analysis has been a subject of focus for research in geography and other disciplines for many years. However, existing area shape indices present significant weaknesses for the analysis of land parcels in an agricultural context as they do not measure shape in an appropriate, reliable or explicit manner. This article presents a new parcel shape index (PSI) which integrates six geometric parameters through multi-attribute decision-making, combined with value functions for parameter standardization. The superior performance of the new PSI in relation to three existing indices is demonstrated through a case study area in Cyprus. The methodology can be applied in other contexts aimed at assessing the quality of a particular shape compared to an optimum.

A spatial genetic algorithm for automating land partitioning

Land fragmentation is a widespread situation which may often hinder agricultural development. 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 is a part of an integrated planning and decision support system called LACONISS (LAndCONsolidation Integrated Support System) which has been developed to assist land consolidation planning in Cyprus. LandParcelS automates the land partitioning process by designing and optimising land parcels in terms of their shape, size and value. The methodology integrates geographical information systems and a genetic algorithm that has been applied to two land blocks that are part of a larger case study area in Cyprus. Partitioning is treated as either a single or multi-objective problem for various optimisation cases. 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. This approach may have relevance to other spatial planning tasks that involve single or multi-objective optimisation problems, especially those dealing with space partitioning.

An Integrated Planning and Decision Support System (IPDSS) for Land Consolidation: Theoretical Framework and Application of the Land-Redistribution Modules

This paper introduces a new planning support system currently under development for land consolidation in Cyprus called LACONISS (LAnd CONsolidation Integrated Support System). The systems structural framework is outlined and the core land redistribution sub-system called LandSpaCES (Land Spatial Consolidation Expert System) is exemplified using a case study. Model evaluation indicates that the results provide a close fit to those derived by independent human experts. Alternative solutions are generated under different evaluation scenarios and sensitivity analysis is used to examine the weights and performance scores of the criteria involved in the process.

LandSpaCES: A Spatial Expert System for Land Consolidation

Land fragmentation is a major issue in many rural areas around the world, preventing rational agricultural production and sustainable rural development. Traditionally, land consolidation has been the primary land management approach for solving this problem. Land reallocation is recognised as the most important, complex, and time-consuming process of land consolidation. It is split into two components: land redistribution and land partitioning. In this paper, we outline a land redistribution model called LandSpaCES (Land Spatial Consolidation Expert System) which is the central module of LACONISS, a LAnd CONsolidation Integrated Support System for planning and decision making. LandSpaCES integrates GIS with an expert system (ES) and is able to generate alternative land redistributions under different scenarios. Two key system concepts are utilised: ‘No-Inference Engine Theory (NIET),’ which differentiates Land- SpaCES from conventional ES development and a parcel priority index (PPI), which constitutes the basic measure that defines the redistribution of land in terms of location. The module has been applied to a case study area in Cyprus and the results compare very favourably against an independent solution derived previously by human experts.

A GIS-based shape index for land parcels

Shape analysis is of interest in many fields of spatial science and planning including land management in rural areas. In particular, evaluating the shape of existing land parcels is critical when implementing rural development schemes such as land consolidation. However, existing land parcel shape indices have major deficiencies: completely different shapes of parcels may have the same index value or similar parcel shapes may have different index scores. Thus, there is a clear requirement for a more accurate and reliable measurement method. This paper therefore presents a new parcel shape index (PSI) which integrates a geographical information system (GIS) with a multi-attribute decision-making (MADM) method. It involves the amalgamated outcome of six geometric measures represented by value functions involving a mathematical representation of judgements by experts that compare each geometric measure with that of an optimum parcel shape defined for land consolidation projects. The optimum shape has a PSI value of 1 while the worst shape has a value close to 0. The shape measures used in the model include length of sides, acute angles, reflex angles, boundary points, compactness and regularity. The paper uses data for two case study areas in Cyprus to demonstrate the superiority of the new PSI over three existing shape indices employed in other studies. The methodology utilized here can be implemented in other disciplines dealing with the assessment of objects that can be compared to an optimum.

A spatially based artificial neural network mass valuation model for land consolidation

Land consolidation, which aims to promote sustainable development of rural areas, involves the reorganization of space through land reallocation, both in terms of ownership and land parcel boundaries. Land reallocation, which is the core part of such schemes, is based on land values because each landowner is entitled to receive a property with approximately the same land value after land consolidation. Therefore, land value, which in the case of Cyprus is the market value, is a critical parameter, and hence it should be reliable, accurate, and fairly valued. However, the conventional land valuation process has some weaknesses. It is carried out manually and empirically by a five-member Land Valuation Committee, which visits every unique parcel in the consolidated area to assign a market value. As a result, it is time consuming and hence costly. Moreover, the outcomes can be inconsistent across valuators for whom, in the case of such a mass appraisal procedure, it is hard to analytically calculate the scores for a series of land valuation factors and compare all of these for hundreds of land parcels using a manual process. A solution to these shortcomings is the use of automated valuation models. In this context, this paper presents the development, implementation, and evaluation of an artificial neural network automated valuation model combined with a geographical information system applied in a land consolidation case study area in Cyprus. The model has been tested for quality assurance based on international standards. The evaluation showed that a sample of 15% of the selected land parcel values provided by the Land Valuation Committee is adequate for appraising the land values of all parcels in the land consolidation area with a high or acceptable accuracy, reliability, and consistency. Consequently, the automated valuation model is highly efficient compared to the conventional land valuation method since it may reduce time and resources used by up to 80%. Although the new process is based partly on the Land Valuation Committee sample, which inherently carries inconsistencies, it is systematic, analytical, and standardized, hence enhancing transparency. The comparison of artificial neural networks with similar linear and nonlinear models applied to the same case study area showed that it is capable of producing better results than the former and similar outcomes to the latter.

LACONISS: A Planning Support System for Land Consolidation

Land consolidation is considered as the most effective land management planning approach for solving the land fragmentation problem in rural areas and more broadly to assist the implementation of regional and urban planning. This chapter focuses on a planning support system for land consolidation in rural areas called Land CONsolidation Integrated Support System for planning and decision making (LACONISS) that integrates GIS, artificial intelligence techniques and multi-criteria decision methods. The system involves four modules: the Land Fragmentation System (LandFragmentS) module measures existing land fragmentation in an agricultural context; the Land Spatial Consolidation Expert System (LandSpaCES) Design module produces alternative land redistribution plans; the LandSpaCES Evaluation module assesses these plans based on a set of criteria; and the Land Parcelling System (LandParcelS) module produces the final land partitioning plan. The final output is the land reallocation plan. The whole system has been applied to a case study area in Cyprus and this reveals that land fragmentation can be reliably measured, that alternative land reallocation plans can be produced that can successfully emulate planners’ reasoning, that the most beneficial plan for various combinations of criteria and weights can be identified and that the subdivision process can be automated satisfactorily although further improvements are needed. The contribution of LACONISS is relevant to both rural and urban sustainable development since it supports and automates the land reallocation (or land readjustment) process which is the principal component of any land consolidation project whether rural or urban. Eventually, LACONISS may constitute the foundations for developing a generic system that could be applied in any country that implements land consolidation projects.

Integrating GIS and genetic algorithms for automating land partitioning

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.

A discussion for integrating INSPIRE with volunteered geographic information (VGI) and the vision for a global spatial-based platform

INSPIRE is the EU’s authoritative Spatial Data Infrastructure (SDI) in which each Member State provides access to their spatial data across a wide spectrum of data themes to support policy making. In contrast, Volunteered Geographic Information (VGI) is one type of user-generated geographic information where volunteers use the web and mobile devices to create, assemble and disseminate spatial information. There are similarities and differences between SDIs and VGI initiatives, as well as advantages and disadvantages. Thus, the integration of these two data sources will enhance what is offered to end users to facilitate decision makers and the wider community regarding solving complex spatial problems, managing emergency situations and getting useful information for peoples’ daily activities. Although some efforts towards this direction have been arisen, several key issues need to be considered and resolved. Further to this integration, the vision is the development of a global integrated GIS platform, which extends the capabilities of a typical data-hub by embedding on-line spatial and non-spatial applications, to deliver both static and dynamic outputs to support planning and decision making. In this context, this paper discusses the challenges of integrating INSPIRE with VGI and outlines a generic framework towards creating a global integrated web-based GIS platform. The tremendous high speed evolution of the Web and Geospatial technologies suggest that this “super” global Geo-system is not far away.