Spatial Analysis and Fuzzy Relation Equations

Martino, Ferdinando Di; Sessa, Salvatore

doi:10.1155/2011/429498

Cited by 12 publications

(14 citation statements)

References 16 publications

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“…Di Martino and Sessa (2011a) implement the Universal Algorithm in a GIS-based framework to solve urban planning problems. They apply the Universal Algorithm on a study area; the SFRE (1) is constructed deriving the symptoms from a set of known r measurable facts (the input variables i 1 ,…, i r ).…”

Section: Introductionmentioning

confidence: 99%

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A GIS-based framework using fuzzy relation equation system solutions in urban planning

Cardone

Martino

2022

J Ambient Intell Human Comput

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Several fuzzy decision models are proposed in literature to solve urban planning problems. In this research we present a novel GIS-based framework to solve decision problems in urban planning based on a System of Fuzzy Relation Equations in which the unknowns represent characteristics affecting observable facts constituting the input variables. Aim of this research is to partition the urban study area into subzones, each of which identifies a sub-area of the study area within which the set of analyzed characteristics are homogeneous. The study area is initially decomposed in atomic urban areas called microzones; for each microzone are calculated the greatest and lowest solutions of a System of Fuzzy Relation Equations by using the Universal solution Algorithm and are calculated and fuzzified the values of the output variables. Spatially adjoining microzones with same output variables are dissolved forming homogeneous urban areas with reference to the problem analyzed, called Urban Contexts. For each output variable a thematic map is constructed; in addition, a thematic map of its reliability is created. This framework is tested on a study area given by the district of Ponticelli in the municipality of Naples (Italy); comparison tests performed with respect to a previous GIS-based framework based on a System of Fuzzy Relation Equations show that our method provides a more detailed knowledge of the characteristics of the urban study area with reference to the problem dealt with.

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Section: Introductionmentioning

confidence: 99%

“…In Di Martino and Sessa (2011a) the authors apply this method to evaluate a set of urban features in each the district of the eastern area of the municipality of Naples (Italy). In addition, a reliability of the results obtained in each district is calculated.…”

Section: Introductionmentioning

confidence: 99%

A GIS-based framework using fuzzy relation equation system solutions in urban planning

Cardone

Martino

2022

J Ambient Intell Human Comput

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“…In Reference [13], a simulated annealing method is applied to partition an area of study into homogeneous zones based on socio-economic characteristics. In Reference [14], a partition of the urban system in census zones is performed in order to study the spatial distribution of socio-economic characteristics. In Reference [15], a multi-objective approach is applied in order to partition the municipalities of the region of Parana in Brazil into microregions; this approach maximizes population homogeneity and the medical procedure used in any microregion and minimizes inter-microregion traveling.…”

Section: Introductionmentioning

confidence: 99%

A New Geospatial Model Integrating a Fuzzy Rule-Based System in a GIS Platform to Partition a Complex Urban System in Homogeneous Urban Contexts

Cardone

Martino

2018

Geosciences

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Here, we present a new unsupervised method aimed at obtaining a partition of a complex urban system in homogenous urban areas, called urban contexts. Our model integrates spatial analysis processes and a fuzzy rule-based system applied to manage the knowledge of domain experts; it is implemented using a GIS platform. The area of study is initially partitioned in microzones, homogeneous portions of the urban system, which are the atomic reference elements for the census data. With the contribution of domain experts, we identify the physical, morphological, environmental, and socio-economic indicators needed to identify synthetic characteristics of urban contexts and create the fuzzy rule set necessary for determining the type of urban context. We implement the set of spatial analysis processes required to calculate the indicators for the microzones and apply a Mamdani fuzzy rule system to classify the microzones. Finally, the partition of the area of study in urban contexts is obtained by dissolving continuous microzones belonging to the same type of urban context. Tests are performed on the Municipality of Pozzuoli (Naples, Italy); the reliability of the out model is measured by comparing the results with the ones obtained through a detailed analysis.

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“…In [3] a simulated annealing method is applied to partition an area of study in homogeneous zones based on socioeconomic characteristics. In [6] a partition of the urban system in census zones is performed in order to study the spatial distribution of socioeconomic characteristics. In [1] a multiobjective approach is applied in order to partition into microregions the municipalities of the region of Parana in Brazil; this approach maximize the population homogeneity and the medical procedure used in any microregion and minimize inter-microregion traveling.…”

Section: Introductionmentioning

confidence: 99%

A New Fuzzy Rule-based Model to Partition a Complex Urban System in Homogeneous Urban Contexts

Martino¹,

Cardone²

2018

Preprint

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We present a new unsupervised method aimed to obtain a partition of a complex urban system in homogenous urban areas, called urban contexts. The area of study is initially partitioned in microzones, homogeneous portion of the urban system, that are the atomic reference elements for the census data. With the contribution of domain experts, we identify the physical, morphological, environmental and socio-economic indicators need to identify synthetic characteristics of urban contexts and create the fuzzy rule set necessary to determine the type of urban context. We implement the set of spatial analysis processes necessary to calculate the indicators for microzone and apply a Mamdani fuzzy rule system to classify the microzones. Finally, the partition of the area of study in urban contexts is obtained by dissolving continuous microzones belonging to the same type of urban context. Tests are performed on the Municipality of Pozzuoli (Naples - Italy); the reliability of out model is measured by comparing the results with the ones obtained by detailed analysis.

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Spatial Analysis and Fuzzy Relation Equations

Cited by 12 publications

References 16 publications

A GIS-based framework using fuzzy relation equation system solutions in urban planning

A GIS-based framework using fuzzy relation equation system solutions in urban planning

A New Geospatial Model Integrating a Fuzzy Rule-Based System in a GIS Platform to Partition a Complex Urban System in Homogeneous Urban Contexts

A New Fuzzy Rule-based Model to Partition a Complex Urban System in Homogeneous Urban Contexts

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